effect of problem solving teaching method

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Front Psychol

The problem-solving method: Efficacy for learning and motivation in the field of physical education

Ghaith ezeddine.

1 High Institute of Sport and Physical Education of Sfax, University of Sfax, Sfax, Tunisia

Nafaa Souissi

2 Research Unit of the National Sports Observatory (ONS), Tunis, Tunisia

Liwa Masmoudi

3 Research Laboratory: Education, Motricity, Sport and Health, EM2S, LR19JS01, University of Sfax, Sfax, Tunisia

Khaled Trabelsi

4 Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy

Cain C. T. Clark

5 Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom

Nicola Luigi Bragazzi

6 Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, ON, Canada

Maher Mrayah

7 High Institute of Sport and Physical Education of Ksar Saîd, University Manouba, UMA, Manouba, Tunisia

Associated Data

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

In pursuit of quality teaching and learning, teachers seek the best method to provide their students with a positive educational atmosphere and the most appropriate learning conditions.

The purpose of this study is to compare the effects of the problem-solving method vs. the traditional method on motivation and learning during physical education courses.

Fifty-three students ( M age 15 ± 0.1 years), in their 1st year of the Tunisian secondary education system, voluntarily participated in this study, and randomly assigned to a control or experimental group. Participants in the control group were taught using the traditional methods, whereas participants in the experimental group were taught using the problem-solving method. Both groups took part in a 10-hour experiment over 5 weeks. To measure students' situational motivation, a questionnaire was used to evaluate intrinsic motivation, identified regulation, external regulation, and amotivation during the first (T0) and the last sessions (T2). Additionally, the degree of students' learning was determined via video analyses, recorded at T0, the fifth (T1), and T2.

Motivational dimensions, including identified regulation and intrinsic motivation, were significantly greater (all p < 0.001) in the experimental vs. the control group. The students' motor engagement in learning situations, during which the learner, despite a degree of difficulty performs the motor activity with sufficient success, increased only in the experimental group ( p < 0.001). The waiting time in the experimental group decreased significantly at T1 and T2 vs. T0 (all p < 0.001), with lower values recorded in the experimental vs. the control group at the three-time points (all p < 0.001).

Conclusions

The problem-solving method is an efficient strategy for motor skills and performance enhancement, as well as motivation development during physical education courses.

1. Introduction

The education of children is a sensitive and poignant subject, where the wellbeing of the child in the school environment is a key issue (Ergül and Kargin, 2014 ). For this, numerous research has sought to find solutions to the problems of the traditional method, which focuses on the teacher as an instructor, giver of knowledge, arbiter of truth, and ultimate evaluator of learning (Ergül and Kargin, 2014 ; Cunningham and Sood, 2018 ). From this perspective, a teachers' job is to present students with a designated body of knowledge in a predetermined order (Arvind and Kusum, 2017 ). For them, learners are seen as people with “knowledge gaps” that need to be filled with information. In this method, teaching is conceived as the act of transmitting knowledge from point A (responsible for the teacher) to point B (responsible for the students; Arvind and Kusum, 2017 ). According to Novak ( 2010 ), in the traditional method, the teacher is the one who provokes the learning.

The traditional method focuses on lecture-based teaching as the center of instruction, emphasizing delivery of program and concept (Johnson, 2010 ; Ilkiw et al., 2017 ; Dickinson et al., 2018 ). The student listens and takes notes, passively accepts and receives from the teacher undifferentiated and identical knowledge (Bi et al., 2019 ). Course content and delivery are considered most important, and learners acquire knowledge through exercise and practice (Johnson et al., 1998 ). In the traditional method, academic achievement is seen as the ability of students to demonstrate, replicate, or convey this designated body of knowledge to the teacher. It is based on a transmissive model, the teacher contenting themselves with exchanging and transmitting information to the learner. Here, only the “knowledge” and “teacher” poles of the pedagogical triangle are solicited. The teacher teaches the students, who play the role of the spectator. They receive information without participating in its creation (Perrenoud, 2003 ). For this, researchers invented a new student-centered method with effects on improving students' graphic interpretation skills and conceptual understanding of kinematic motion represent an area of contemporary interest (Tebabal and Kahssay, 2011 ). Indeed, in order to facilitate the process of knowledge transfer, teachers should use appropriate methods targeted to specific objectives of the school curricula.

For instance, it has been emphasized that the effectiveness of any educational process as a whole relies on the crucial role of using a well-designed pedagogical (teaching and/or learning) strategy (Kolesnikova, 2016 ).

Alternate to a traditional method of teaching, Ergül and Kargin ( 2014 ), proposed the problem-solving method, which represents one of the most common student-centered learning strategies. Indeed, this method allows students to participate in the learning environment, giving them the responsibility for their own acquisition of knowledge, as well as the opportunity for the understanding and structuring of diverse information.

For Cunningham and Sood ( 2018 ), the problem-solving method may be considered a fundamental tool for the acquisition of new knowledge, notably learning transfer. Moreover, the problem-solving method is purportedly efficient for the development of manual skills and experiential learning (Ergül and Kargin, 2014 ), as well as the optimization of thinking ability. Additionally, the problem-solving method allows learners to participate in the learning environment, while giving them responsibility for their learning and making them understand and structure the information (Pohan et al., 2020 ). In this context, Ali ( 2019 ) reported that, when faced with an obstacle, the student will have to invoke his/her knowledge and use his/her abilities to “break the deadlock.” He/she will therefore make the most of his/her potential, but also share and exchange with his/her colleagues (Ali, 2019 ). Throughout the process, the student will learn new concepts and skills. The role of the teacher is paramount at the beginning of the activity, since activities will be created based on problematic situations according to the subject and the program. However, on the day of the activity, it does not have the main role, and the teacher will guide learners in difficulty and will allow them to manage themselves most of the time (Ali, 2019 ).

The problem-solving method encourages group discussion and teamwork (Fidan and Tuncel, 2019 ). Additionally, in this pedagogical approach, the role of the teacher is a facilitator of learning, and they take on a much more interactive and less rebarbative role (Garrett, 2008 ).

For the teaching method to be effective, teaching should consist of an ongoing process of making desirable changes among learners using appropriate methods (Ayeni, 2011 ; Norboev, 2021 ). To bring about positive changes in students, the methods used by teachers should be the best for the subject to be taught (Adunola et al., 2012 ). Further, suggests that teaching methods work effectively, especially if they meet the needs of learners since each learner interprets and answers questions in a unique way. Improving problem-solving skills is a primary educational goal, as is the ability to use reasoning. To acquire this skill, students must solve problems to learn mathematics and problem-solving (Hu, 2010 ); this encourages the students to actively participate and contribute to the activities suggested by the teacher. Without sufficient motivation, learning goals can no longer be optimally achieved, although learners may have exceptional abilities. The method of teaching employed by the teachers is decisive to achieve motivational consequences in physical education students (Leo et al., 2022 ). Pérez-Jorge et al. ( 2021 ) posited that given we now live in a technological society in which children are used to receiving a large amount of stimuli, gaining and maintaining their attention and keeping them motivated at school becomes a challenge for teachers.

Fenouillet ( 2012 ) stated that academic motivation is linked to resources and methods that improve attention for school learning. Furthermore, Rolland ( 2009 ) and Bessa et al. ( 2021 ) reported a link between a learner's motivational dynamics and classroom activities. The models of learning situations, where the student is the main actor, directly refers to active teaching methods, and that there is a strong link between motivation and active teaching (Rossa et al., 2021 ). In the same context, previous reports assert that the motivation of students in physical education is an important factor since the intra-individual motivation toward this discipline is recognized as a major determinant of physical activity for students (Standage et al., 2012 ; Luo, 2019 ; Leo et al., 2022 ). Further, extensive research on the effectiveness of teaching methods shows that the quality of teaching often influences the performance of learners (Norboev, 2021 ). Ayeni ( 2011 ) reported that education is a process that allows students to make changes desirable to achieve specific results. Thus, the consistency of teaching methods with student needs and learning influences student achievement. This has led several researchers to explore the impact of different teaching strategies, ranging from traditional methods to active learning techniques that can be used such as the problem-solving method (Skinner, 1985 ; Darling-Hammond et al., 2020 ).

In the context of innovation, Blázquez ( 2016 ) emphasizes the importance of adopting active methods and implementing them as the main element promoting the development of skills, motivation and active participation. Pedagogical models are part of the active methods which, together with model-based practice, replace traditional teaching (Hastie and Casey, 2014 ; Casey et al., 2021 ). Thus, many studies have identified pedagogical models as the most effective way to place students at the center of the teaching-learning process (Metzler, 2017 ), making it possible to assess the impact of physical education on learning students (Casey, 2014 ; Rivera-Pérez et al., 2020 ; Manninen and Campbell, 2021 ). Since each model is designed to focus on a specific program objective, each model has limitations when implemented in isolation (Bunker and Thorpe, 1982 ; Rivera-Pérez et al., 2020 ). Therefore, focusing on developing students' social and emotional skills and capacities could help them avoid failure in physical education (Ang and Penney, 2013 ). Thus, the current emergence of new pedagogical models goes with their hybridization with different methods, which is a wave of combinations proposed today as an innovative pedagogical strategy. The incorporation of this type of method in the current education system is becoming increasingly important because it gives students a greater role, participation, autonomy and self-regulation, and above all it improves their motivation (Puigarnau et al., 2016 ). The teaching model of personal and social responsibility, for example, is closely related to the sports education model because both share certain approaches to responsibility (Siedentop et al., 2011 ). One of the first studies to use these two models together was Rugby (Gordon and Doyle, 2015 ), which found significant improvements in student behavior. Also, the recent study by Menendez and Fernandez-Rio ( 2017 ) on educational kickboxing.

Previous studies have indicated that hybridization can increase play, problem solving performance and motor skills (Menendez and Fernandez-Rio, 2017 ; Ward et al., 2021 ) and generate positive psychosocial consequences, such as pleasure, intention to be physically active and responsibility (Dyson and Grineski, 2001 ; Menendez and Fernandez-Rio, 2017 ).

But despite all these research results, the picture remains unclear, and it remains unknown which method is more effective in improving students' learning and motivation. Given the lack of published evidence on this topic, the aim of this study was to compare the effects of problem-solving vs. the traditional method on students' motivation and learning.

We hypothesized would that the problem-solving method would be more effective in improving students' motivation and learning better than the traditional method.

2. Materials and method

2.1. participants.

Fifty-three students, aged 15–16 ( M age 15 ± 0.1 years), in their 1st year of the Tunisian secondary education system, voluntarily participated in this study. All participants were randomly chosen. Repeating students, those who practice handball activity in civil/competitive/amateur clubs or in the high school sports association, and students who were absent, even for one session, were excluded. The first class consisted of 30 students (16 boys and 14 girls), who represented the experimental group and followed basic courses on a learning method by solving problems. The second class consisted of 23 students (10 boys and 13 girls), who represented the control group and followed the traditional teaching method. The total duration was spread over 5 weeks, or two sessions per week and each session lasted 50 min.

University research ethics board approval (CPPSUD: 0295/2021) was obtained before recruiting participants who were subsequently informed of the nature, objective, methodology, and constraints. Teacher, school director, parental/guardian, and child informed consent was obtained prior to participation in the study.

2.2. Procedure

Before the start of the experiment, the participants were familiarized with the equipment and the experimental protocol in order to ensure a good learning climate. For this and to mitigate the impact of the observer and the cameras on the students, the two researchers were involved prior to the data collection in a week of familiarization by making test recordings with the classes concerned.

An approach of a teaching cycle consisting of 10 sessions spread over 5 weeks, amounting to two sessions per week. Physical education classes were held in the morning from 8 a.m. to 9 a.m., with a single goal for each session that lasted 50 min. The cyclic programs were produced by the teacher responsible for carrying out the experiment with 18 years of service. To do this, the students had the same lessons with the same objectives, only pedagogy that differs: the experimental group worked using problem-solving pedagogy, while the control group was confronted with traditional pedagogy. The sessions took place in a handball field 40 m long and 20 m wide. Examples of training sessions using the problem-solving pedagogy and the traditional pedagogy are presented in Table 1 . In addition, a motivation questionnaire, the Situational Motivation Scale (SIMS; Guay et al., 2000 ), was administered to learners at the end of the session (i.e., in the beginning, and end of the cycle). Each student answered the questions alone and according to their own ideas. This questionnaire was taken in a classroom to prevent students from acting abnormally during the study. It lasted for a maximum of 10 min.

Example of activities for the different sessions.

Two diametrically opposed cameras were installed so to film all the movements and behaviors of each student and teacher during the three sessions [(i) test at the start of the cycle (T0), (ii) in the middle of the cycle (T1), and (iii) test at the end of the cycle (T2)]. These sessions had the same content and each consisted of four phases: the getting started, the warm-up, the work up (which consisted of three situations: first, the work was goes up the ball to two to score in the goal following a shot. Second, the same principle as the previous situation but in the presence of a defender. Finally, third, a match 7 ≠ 7), and the cooling down These recordings were analyzed using a Learning Time Analysis System grid (LTAS; Brunelle et al., 1988 ). This made it possible to measure individual learning by coding observable variables of the behavior of learners in a learning situation.

2.3. Data collection and analysis

2.3.1. the motivation questionnaire.

In this study, in order to measure the situational motivation of students, the situational motivation scale (SIMS; Guay et al., 2000 ), which used. This questionnaire assesses intrinsic motivation, identified regulation, external regulation and amotivation. SIMS has demonstrated good reliability and factor validity in the context of physical education in adolescents (Lonsdale et al., 2011 ). The participants received exact instructions from the researchers in accordance with written instructions on how to conduct the data collection. Participants completed the SIMS anonymously at the start of a physical education class. All students had the opportunity to write down their answers without being observed and to ask questions if anything was unclear. To minimize the tendency to give socially desirable answers, they were asked to answer as honestly as possible, with the confidence that the teacher would not be able to read their answers and that their grades would not be affected by how they responded. The SIMS questionnaire was filled at T0 and T2. This scale is made up of 16 items divided into four dimensions: intrinsic motivation, identified regulation, external regulation and amotivation. Each item is rated on a 7-point Likert scale ranging from 1 (which is the weakest factor) “not at all” to 7 (which is the strongest factor) “exactly matches.”

• In order to assess the internal consistency of the scales, a Cronbach alpha test was conducted (Cronbach, 1951 ). The internal consistency of the scales was acceptable with reliability coefficients ranging from 0.719 to 0.87. The coefficient of reliability was 0.8.
• In the present study, Cronbach's alphas were: intrinsic motivation = 0.790; regulation identified = 0.870; external regulation = 0.749; and amotivation = 0.719.

2.3.2. Camcorders

The audio-visual data collection was conducted using two Sony camcorders (Model; Handcam 4K) with a wireless microphone with a DJ transmitter-receiver (VHF 10HL F4 Micro HF) with a range of 80 m (Maddeh et al., 2020 ). The collection took place over a period of 5 weeks, with three captures for each class (three sessions of 50 min for each at T0, T1, and T2). Two researchers were trained in the procedures and video capture techniques. The cameras were positioned diagonally, in order to film all the behavior of the students and teacher on the set.

2.3.3. The Learning Time Analysis System (LTAS)

To measure the degree of student learning, the analysis of videos recorded using the LTAS grid by Brunelle et al. ( 1988 ) was used, at T0, T1, and T2. This observation system with predetermined categories uses the technique of observation by small intervals (i.e., 6 s) and allows to measure individual learning by coding observable variables of their behaviors when they have been in a learning situation. This grid also permits the specification of the quantity and quality with which the participants engaged in the requested work and was graded, broadly, on two characteristics: the type of situation offered to the group by the teacher and the behavior of the target participant. The situation offered to the group was subdivided into three parts: preparatory situations; knowledge development situations, and motor development situations.

The observations and coding of behaviors are carried out “at intervals.” This technique is used extensively in research on behavior analysis. The coder observes the teaching situation and a particular student during each interval (Brunelle et al., 1988 ). It then makes a decision concerning the characteristic of the observed behavior. The 6-s observation interval is followed by a coding interval of 6 s too. A cassette tape recorder is used to regulate the observation and recording intervals. It is recorded for this purpose with the indices “observe” and “code” at the start of each 6-s period. During each coding unit, the observer answered the following questions: What is the type of situation in which the class group finds itself? If the class group is in a learning situation proper, in what form of commitment does the observed student find himself? The abbreviations representing the various categories of behavior have been entered in the spaces which correspond to them. The coder was asked to enter a hyphen instead of the abbreviation when the same categories of behavior follow one another in consecutive intervals (Brunelle et al., 1988 ).

During the preparatory period, the following behaviors were identified and analyzed:

• - Deviant behavior: The student adopts a behavior incompatible with a listening attitude or with the smooth running of the preparatory situations.
• - Waiting time: The student is waiting without listening or observing.
• - Organized during: The student is involved in a complementary activity that does not represent a contribution to learning (e.g., regaining his place in a line, fetching a ball that has just left the field, replacing a piece of equipment).

During the motor development situations, the following behaviors were identified and analyzed:

• - Motor engagement 1: The participant performs the motor activity with such easy that it can be inferred that their actions have little chance to engage in a learning process.
• - Motor engagement 2: The participant-despite a certain degree of difficulty, performs the motor activity with sufficient success, which makes it possible to infer that they are in the process of learning.
• - Motor engagement 3: The participant performs the motor activity with such difficulty that their efforts have very little chance of being part of a learning process.

2.4. Statistical analysis

Statistical tests were performed using statistical software 26.0 for windows (SPSS, Inc, Chicago, IL, USA). Data are presented in text and tables as means ± standard deviations and in figures as means and standard errors. Once the normal distribution of data was confirmed by the Shapiro-Wilk W -test, parametric tests were performed. Analysis of the results was performed using a mixed 2-way analysis of variance (ANOVA): Groups × Time with repeated measures.

• For the learning parameters, the ANOVA took the following form: 2 Groups (Control Group vs. Experimental Group) × 3 Times (T0, T1, and T2).
• For the dimensions of motivation, the ANOVA took the following form: 2 Groups (Control Group vs. Experimental Group) × 2 Time (T0 vs. T2).

In instances where the ANOVA showed a significant effect, a Bonferroni post-hoc test was applied in order to compare the experimental data in pairs, otherwise by an independent or paired Student's T -test. Effect sizes were calculated as partial eta-squared η p 2 to estimate the meaningfulness of significant findings, where η p 2 values of 0.01, 0.06, and 0.13 represent small, moderate, and large effect sizes, respectively (Lakens, 2013 ). All observed differences were considered statistically significant for a probability threshold lower than p < 0.05.

Table 2 shows the results of learning variables during the preparatory and the development learning periods at T0, T1, and T2, in the control group and the experimental group.

Comparison of learning variables using two teaching methods in physical education.

* Significantly different from control group at p <0.05.

# Significantly different from T0 at p <0.05.

$ Significantly different from T1 at p <0.05.

For motor engagement 1 (ME1), the time devoted to this variable is equal zero for the three measurement times (T0, T1, and T2).

The analysis of variance of two factors with repeated measures showed a significant effect of group, learning, and group learning interaction for the deviant behavior. The post-hoc test revealed significantly less frequent deviant behaviors in the experimental than in the control group at T0, T1, and T2 (all p < 0.001). Additionally, the deviant behavior decreased significantly at T1 and T2 compared to T0 for both groups (all p < 0.001).

For appropriate engagement, there were no significant group effect, a significant learning effect, and a significant group learning interaction effect. The post-hoc test revealed that compared to T0, Appropriate engagement recorded at T1 and T2 increased significantly ( p = 0.032; p = 0.031, respectively) in the experimental group, whilst it decreased significantly in the control group ( p < 0.001). Additionally, Appropriate engagement was higher in the experimental vs. control group at T1 and T2 (all p < 0.001).

For waiting time, a significant interaction in terms of group effect, learning, and group learning was found. The post-hoc test revealed that waiting time was higher at T1 and T2 vs. T0 (all p < 0.001) in the control group. In addition, waiting time in the experimental group decreased significantly at T1 and T2 vs. T0 (all p < 0.001), with higher values recorded at T2 vs. T1 ( p = 0.025). Additionally, lower values were recorded in the experimental group vs. the control group at the three-time points (all p < 0.001).

For Motor engagement 2, a significant group, learning, and group-learning interaction effect was noted. The post-hoc test revealed that Motor engagement 2 increased significantly in both groups at T1 ( p < 0.0001) and T2 ( p < 0.0001) vs. T0 ( p = 0.045), with significantly higher values recorded in the experimental group at T1 and T2.

Regarding Motor engagement 3, a non-significant group effect was reported. Contrariwise, a significant learning effect and group learning interaction was reported ( Table 1 ). The post-hoc test revealed a significant decrease in the control group and the experimental group at T1 ( p = 0.294) at T2 ( p = 0.294) vs. T0 ( p = 0.0543). In addition, a non-significant difference between the two groups was found.

A significant group and learning effect was noted for the organized during, and a non-significant group learning interaction. For organized during, the paired Student T -test showed a significant decrease in the control group and the experimental group (all p < 0.001). The independent Student T -test revealed a non-significant difference between groups at the three-time points.

Results of the motivational dimensions in the control group and the experimental group recorded at T0 and T2 are presented in Table 3 .

Comparison of the four motivational dimensions in two teaching methods in physical education.

For intrinsic motivation, a significant group effect and group learning interaction and also a non-significant learning effect was found. The post-hoc test indicated that the intrinsic motivation decreased significantly in the control group ( p = 0.029), whilst it increased in the experimental group ( p = 0.04). Additionally, the intrinsic motivation of the experimental group was higher at T0 ( p = 0.026) and T2 ( p < 0.001) compared to that of the control group.

For the identified regulation, a significant group effect, a non-significant learning effect and group learning interaction were reported. The paired Student's T -test revealed that from T0 to T1, the identified motivation increased significantly only in the experimental group ( p = 0.022), while it remained unchanged in the control group. The independent Student's T -test revealed that the identified regulation recorded in the experimental group at T0 ( p = 0.012) and T2 ( p < 0.001) was higher compared to that of the control group.

The external regulation presents a significant group effect. In addition, a non-significant learning effect and group learning interaction were reported. The paired Student's T -test showed that the external regulation decreased significantly in the experimental group ( p = 0.038), whereas it remained unchanged in the control group. Further, the independent Student's T -test revealed that the external regulation recorded at T2 was higher in the control group vs. the experimental group ( p < 0.001).

Relating to amotivation, results showed a significant group effect. Furthermore, a non-significant learning effect and group learning interaction were reported. The paired Student's T -test showed that, from T0 to T2, amotivation decreased significantly in the experimental group ( p = 0.011) and did not change in the control group. The independent Student T -test revealed that amotivation recorded at T2 was lower in the experimental compared to the control group ( p = 0.002).

4. Discussion

The main purpose of this study was to compare the effects of the problem-solving vs. traditional method on motivation and learning during physical education courses. The results revealed that the problem-solving method is more effective than the traditional method in increasing students' motivation and improving their learning. Moreover, the results showed that mean wait times and deviant behaviors decreased using the problem-solving method. Interestingly, the average time spent on appropriate engagement increased using the problem-solving method compared to the traditional method. When using the traditional method, the average wait times increased and, as a result, the time spent on appropriate engagement decreased. Then, following the decrease in deviant behaviors and waiting times, an increase in the time spent warming up was evident (i.e., appropriate engagement). Indeed, there was an improvement in engagement time using the problem-solving method and a decrease using the traditional method. On the other hand, there was a decrease in motor engagement 3 in favor of motor engagement 2. Indeed, it has been shown that the problem-solving method has been used in the learning process and allows for its improvement (Docktor et al., 2015 ). In addition, it could also produce better quality solutions and has higher scores on conceptual and problem-solving measures. It is also a good method for the learning process to enhance students' academic performance (Docktor et al., 2015 ; Ali, 2019 ). In contrast, the traditional method limits the ability of teachers to reach and engage all students (Cook and Artino, 2016 ). Furthermore, it produces passive learning with an understanding of basic knowledge which is characterized by its weakness (Goldstein, 2016 ). Taken together, it appears that the problem-solving method promotes and improves learning more than the traditional method.

It should be acknowledged that other factors, such as motivation, could influence learning. In this context, our results showed that the method of problem-solving could improve the motivation of the learners. This motivation includes several variables that change depending on the situation, namely the intrinsic motivation that pushes the learner to engage in an activity for the interest and pleasure linked to the practice of the latter (Komarraju et al., 2009 ; Guiffrida et al., 2013 ; Chedru, 2015 ). The student, therefore, likes to learn through problem-solving and neglects that of the traditional method. These results are concordant with others (Deci and Ryan, 1985 ; Chedru, 2015 ; Ryan and Deci, 2020 ). Regarding the three forms of extrinsic motivation: first, extrinsic motivation by an identified regulation which manifests itself in a high degree of self-determination where the learner engages in the activity because it is important for him (Deci and Ryan, 1985 ; Chedru, 2015 ). This explains the significant difference between the two groups. Then, the motivation by external regulation which is characterized by a low degree of self-determination such as the behavior of the learner is manipulated by external circumstances such as obtaining rewards or the removal of sanctions (Deci and Ryan, 1985 ; Chedru, 2015 ). For this, the means of this variable decreased for the experimental group which is intrinsically motivated. He does not need any reward to work and is not afraid of punishment because he is self-confident. Third, amotivation is at the opposite end of the self-determination continuum. Unmotivated students are the most likely to feel negative emotions (Ratelle et al., 2007 ; David, 2010 ), to have low self-esteem (Deci and Ryan, 1995 ), and who attempts to abandon their studies (Vallerand et al., 1997 ; Blanchard et al., 2005 ). So, more students are motivated by external regulation or demotivated, less interest they show and less effort they make, and more likely they are to fail (Grolnick et al., 1991 ; Miserandino, 1996 ; Guay et al., 2000 ; Blanchard et al., 2005 ).

It is worth noting that there is a close link between motivation and learning (Bessa et al., 2021 ; Rossa et al., 2021 ). Indeed, when the learner's motivation is high, so will his learning. However, all this depends on the method used (Norboev, 2021 ). For example, the method of problem-solving increase motivation more than the traditional method, as evidenced by several researchers (Parish and Treasure, 2003 ; Artino and Stephens, 2009 ; Kim and Frick, 2011 ; Lemos and Veríssimo, 2014 ).

Given the effectiveness of the problem-solving method in improving students' learning and motivation, it should be used during physical education teaching. This could be achieved through the organization of comprehensive training programs, seminars, and workshops for teachers so to master and subsequently be able to use the problem-solving method during physical education lessons.

Despite its novelty, the present study suffers from a few limitations that should be acknowledged. First, a future study, consisting of a group taught using the mixed method would preferable so to better elucidate the true impact of this teaching and learning method. Second, no gender and/or age group comparisons were performed. This issue should be addressed in future investigations. Finally, the number of participants is limited. This may be due to working in a secondary school where the number of students in a class is limited to 30 students. Additionally, the number of participants fell to 53 after excluding certain students (exempted, absent for a session, exercising in civil clubs or member of the school association). Therefore, to account for classes of finite size, a cluster-based trial would be beneficial in the future. Moreover, future studies investigating the effect of the active method in reducing some behaviors (e.g., disruptive behaviors) and for the improvement of pupils' attention are warranted.

5. Conclusion

There was an improvement in student learning in favor of the problem-solving method. Additionally, we found that the motivation of learners who were taught using the problem-solving method was better than that of learners who were educated by the traditional method.

Data availability statement

Ethics statement.

University Research Ethics Board approval was obtained before recruiting participants who were subsequently informed of the nature, objective, methodology, and constraints. Teacher, school director, parental/guardian, and child informed consent was obtained prior to participation in the study. In addition, exclusion criteria included; the practice of handball activity in civil/competitive/amateur clubs or in the high school sports association. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Acknowledgments

Special thanks for all students and physical education teaching staff from the 15 November 1955 Secondary School, who generously shared their time, experience, and materials for the proposes of this study.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer MJ declared a shared affiliation, with no collaboration, with the authors GE, NS, LM, and KT to the handling editor at the time of review.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

• Adunola O., Ed B., Adeniran A. (2012). The Impact of Teachers' Teaching Methods on the Academic Performance of Primary School Pupils . Ogun: Ego Booster Books. [ Google Scholar ]
• Ali S. S. (2019). Problem based learning: A student-centered approach . Engl. Lang. Teach . 12 , 73. 10.5539/elt.v12n5p73 [ CrossRef ] [ Google Scholar ]
• Ang S. C., Penney D. (2013). Promoting social and emotional learning outcomes in physical education: Insights from a school-based research project in Singapore . Asia-Pac. J. Health Sport Phys. Educ . 4 , 267–286. 10.1080/18377122.2013.836768 [ CrossRef ] [ Google Scholar ]
• Artino A. R., Stephens J. M. (2009). Academic motivation and self-regulation: A comparative analysis of undergraduate and graduate students learning online . Internet. High. Educ. 12 , 146–151. 10.1016/j.iheduc.2009.02.001 [ CrossRef ] [ Google Scholar ]
• Arvind K., Kusum G. (2017). Teaching approaches, methods and strategy . Sch. Res. J. Interdiscip. Stud. 4 , 6692–6697. 10.21922/srjis.v4i36.10014 [ CrossRef ] [ Google Scholar ]
• Ayeni A. J. (2011). Teachers' professional development and quality assurance in Nigerian secondary schools . World J. Educ. 1 , 143. 10.5430/wje.v1n2p143 [ CrossRef ] [ Google Scholar ]
• Bessa C., Hastie P., Rosado A., Mesquita I. (2021). Sport education and traditional teaching: Influence on students' empowerment and self-confidence in high school physical education classes . Sustainability 13 , 578. 10.3390/su13020578 [ CrossRef ] [ Google Scholar ]
• Bi M., Zhao Z., Yang J., Wang Y. (2019). Comparison of case-based learning and traditional method in teaching postgraduate students of medical oncology . Med. Teach . 4 , 1124–1128. 10.1080/0142159X.2019.1617414 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Blanchard C., Pelletier L., Otis N., Sharp E. (2005). Role of self-determination and academic ability in predicting school absences and intention to drop out . J. Educ. Sci. 30 , 105–123. 10.7202/011772ar [ CrossRef ] [ Google Scholar ]
• Blázquez D. (2016). Métodos de enseñanza en Educación Física . Enfoques innovadores para la enseñanza de competencias . Barcelona: Inde Publisher. [ Google Scholar ]
• Brunelle J., Drouin D., Godbout P., Tousignant M. (1988). Supervision of physical activity intervention. Montreal, Canada: G. Morin, Dl . Open J. Soc. Sci. 8. [ Google Scholar ]
• Bunker D., Thorpe R. (1982). A model for the teaching of games in secondary schools . Bull. Phys. Educ . 18 , 5–8. [ Google Scholar ]
• Casey A. (2014). Models-based practice: Great white hope or white elephant? Phys. Educ. Sport Pedagog. 19 , 18–34. 10.1080/17408989.2012.726977 [ CrossRef ] [ Google Scholar ]
• Casey A., MacPhail A., Larsson H., Quennerstedt M. (2021). Between hope and happening: Problematizing the M and the P in models-based practice . Phys. Educ. Sport Pedagog. 26 , 111–122. 10.1080/17408989.2020.1789576 [ CrossRef ] [ Google Scholar ]
• Chedru M. (2015). Impact of motivation and learning styles on the academic performance of engineering students . J. Educ. Sci. 41 , 457–482. 10.7202/1035313ar [ CrossRef ] [ Google Scholar ]
• Cook D. A., Artino A. R. (2016). Motivation to learn: An overview of contemporary theories . J. Med. Educ . 50 , 997–1014. 10.1111/medu.13074 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cronbach L. J. (1951). Coefficient alpha and the internal structure of tests . Psychometrika. J. 16 , 297–334. 10.1007/BF02310555 [ CrossRef ] [ Google Scholar ]
• Cunningham J., Sood K. (2018). How effective are working memory training interventions at improving maths in schools: a study into the efficacy of working memory training in children aged 9 and 10 in a junior school? . Education 46 , 174–187. 10.1080/03004279.2016.1210192 [ CrossRef ] [ Google Scholar ]
• Darling-Hammond L., Flook L., Cook-Harvey C., Barron B., Osher D. (2020). Implications for educational practice of the science of learning and development . Appl. Dev. Sci. 24 , 97–140. 10.1080/10888691.2018.1537791 [ CrossRef ] [ Google Scholar ]
• David A. (2010). Examining the relationship of personality and burnout in college students: The role of academic motivation . E. M. E. Rev. 1 , 90–104. [ Google Scholar ]
• Deci E., Ryan R. (1985). Intrinsic motivation and self-determination in human behavior . Perspect. Soc. Psychol . 2271 , 7. 10.1007/978-1-4899-2271-7 [ CrossRef ] [ Google Scholar ]
• Deci E. L., Ryan R. M. (1995). “Human autonomy,” in Efficacy, Agency, and Self-Esteem (Boston, MA: Springer; ). [ Google Scholar ]
• Dickinson B. L., Lackey W., Sheakley M., Miller L., Jevert S., Shattuck B. (2018). Involving a real patient in the design and implementation of case-based learning to engage learners . Adv. Physiol. Educ. 42 , 118–122. 10.1152/advan.00174.2017 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Docktor J. L., Strand N. E., Mestre J. P., Ross B. H. (2015). Conceptual problem solving in high school . Phys. Rev. ST Phys. Educ. Res. 11 , 20106. 10.1103/PhysRevSTPER.11.020106 [ CrossRef ] [ Google Scholar ]
• Dyson B., Grineski S. (2001). Using cooperative learning structures in physical education . J. Phys. Educ. Recreat. Dance. 72 , 28–31. 10.1080/07303084.2001.10605831 [ CrossRef ] [ Google Scholar ]
• Ergül N. R., Kargin E. K. (2014). The effect of project based learning on students' science success . Procedia. Soc. Behav. Sci. 136 , 537–541. 10.1016/j.sbspro.2014.05.371 [ CrossRef ] [ Google Scholar ]
• Fenouillet F. (2012). Les théories de la motivation . Psycho Sup : Dunod. [ Google Scholar ]
• Fidan M., Tuncel M. (2019). Integrating augmented reality into problem based learning: The effects on learning achievement and attitude in physics education . Comput. Educ . 142 , 103635. 10.1016/j.compedu.2019.103635 [ CrossRef ] [ Google Scholar ]
• Garrett T. (2008). Student-centered and teacher-centered classroom management: A case study of three elementary teachers . J. Classr. Interact. 43 , 34–47. [ Google Scholar ]
• Goldstein O. A. (2016). Project-based learning approach to teaching physics for pre-service elementary school teacher education students. Bevins S, éditeur . Cogent. Educ. 3 , 1200833. 10.1080/2331186X.2016.1200833 [ CrossRef ] [ Google Scholar ]
• Gordon B., Doyle S. (2015). Teaching personal and social responsibility and transfer of learning: Opportunities and challenges for teachers and coaches . J. Teach. Phys. Educ. 34 , 152–161. 10.1123/jtpe.2013-0184 [ CrossRef ] [ Google Scholar ]
• Grolnick W. S., Ryan R. M., Deci E. L. (1991). Inner resources for school achievement: Motivational mediators of children's perceptions of their parents . J. Educ. Psychol . 83 , 508–517. 10.1037/0022-0663.83.4.508 [ CrossRef ] [ Google Scholar ]
• Guay F., Vallerand R. J., Blanchard C. (2000). On the assessment of situational intrinsic and extrinsic motivation: The Situational Motivation Scale (SIMS) . Motiv. Emot . 24 , 175–213. 10.1023/A:1005614228250 [ CrossRef ] [ Google Scholar ]
• Guiffrida D., Lynch M., Wall A., Abel D. (2013). Do reasons for attending college affect academic outcomes? A test of a motivational model from a self-determination theory perspective . J. Coll. Stud. Dev. 54 , 121–139. 10.1353/csd.2013.0019 [ CrossRef ] [ Google Scholar ]
• Hastie P. A., Casey A. (2014). Fidelity in models-based practice research in sport pedagogy: A guide for future investigations . J. Teach. Phys. Educ . 33 , 422–431. 10.1123/jtpe.2013-0141 [ CrossRef ] [ Google Scholar ]
• Hu W. (2010). Creative scientific problem finding and its developmental trend . Creat. Res. J. 22 , 46–52. 10.1080/10400410903579551 [ CrossRef ] [ Google Scholar ]
• Ilkiw J. E., Nelson R. W., Watson J. L., Conley A. J., Raybould H. E., Chigerwe M., et al.. (2017). Curricular revision and reform: The process, what was important, and lessons learned . J. Vet. Med. Educ . 44 , 480–489. 10.3138/jvme.0316-068R [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Johnson A. P. (2010). Making Connections in Elementary and Middle School Social Studies. 2nd Edn. London: SAGE. [ Google Scholar ]
• Johnson D. W., Johnson R. T., Smith K. A. (1998). Active Learning: Cooperation in the College Classroom. 2nd Edn. Edina, MN: Interaction Press. [ Google Scholar ]
• Kim K. J., Frick T. (2011). Changes in student motivation during online learning . J. Educ. Comput. 44 , 23. 10.2190/EC.44.1.a [ CrossRef ] [ Google Scholar ]
• Kolesnikova I. (2016). Combined teaching method: An experimental study . World J. Educ. 6 , 51–59. 10.5430/wje.v6n6p51 [ CrossRef ] [ Google Scholar ]
• Komarraju M., Karau S. J., Schmeck R. R. (2009). Role of the Big Five personality traits in predicting college students' academic motivation and achievement . Learn. Individ. Differ. 19 , 47–52. 10.1016/j.lindif.2008.07.001 [ CrossRef ] [ Google Scholar ]
• Lakens D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t -tests and ANOVAs . Front. Psychol . 4 , 863. 10.3389/fpsyg.2013.00863 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lemos M. S., Veríssimo L. (2014). The relationships between intrinsic motivation, extrinsic motivation, and achievement, along elementary school . Procedia. Soc. Behav. Sci . 112 , 930–938. 10.1016/j.sbspro.2014.01.1251 [ CrossRef ] [ Google Scholar ]
• Leo M. F., Mouratidis A., Pulido J. J., López-Gajardo M. A., Sánchez-Oliva D. (2022). Perceived teachers' behavior and students' engagement in physical education: the mediating role of basic psychological needs and self-determined motivation . Phys. Educ. Sport Pedagogy. 27 , 59–76. 10.1080/17408989.2020.1850667 [ CrossRef ] [ Google Scholar ]
• Lonsdale C., Sabiston C., Taylor I., Ntoumanis N. (2011). Measuring student motivation for physical education: Examining the psychometric properties of the Perceived Locus of Causality Questionnaire and the Situational Motivation Scale . Psychol. Sport. Exerc . 12 , 284–292. 10.1016/j.psychsport.2010.11.003 [ CrossRef ] [ Google Scholar ]
• Luo Y. J. (2019). The influence of problem-based learning on learning effectiveness in students' of varying learning abilities within physical education . Innov. Educ. Teach. Int. 56 , 3–13. 10.1080/14703297.2017.1389288 [ CrossRef ] [ Google Scholar ]
• Maddeh T., Amamou S., Desbiens J., françois Souissi N. (2020). The management of disruptive behavior of secondary school students by Tunisian trainee teachers in physical education: Effects of a training program in the prevention and management of indiscipline . J. Educ. Fac . 4 , 323–344. 10.34056/aujef.674931 [ CrossRef ] [ Google Scholar ]
• Manninen M., Campbell S. (2021). The effect of the sport education model on basic needs, intrinsic motivation and prosocial attitudes: A systematic review and multilevel meta-Analysis . Eur. Phys. Educ. Rev . 28 , 76–99. 10.1177/1356336X211017938 [ CrossRef ] [ Google Scholar ]
• Menendez J. I., Fernandez-Rio J. (2017). Hybridising sport education and teaching for personal and social responsibility to include students with disabilities . Eur. J. Spec. Needs Educ. 32 , 508–524 10.1080/08856257.2016.1267943 [ CrossRef ] [ Google Scholar ]
• Metzler M. (2017). Instructional Models in Physical Education . London: Routledge. [ Google Scholar ]
• Miserandino M. (1996). Children who do well in school: Individual differences in perceived competence and autonomy in above-average children . J. Educ. Psychol . 88 , 203–214. 10.1037/0022-0663.88.2.203 [ CrossRef ] [ Google Scholar ]
• Norboev N. N. (2021). Theoretical aspects of the influence of motivation on increasing the efficiency of physical education . Curr. Res. J. Pedagog . 2 , 247–252. 10.37547/pedagogics-crjp-02-10-44 [ CrossRef ] [ Google Scholar ]
• Novak D. J. (2010). Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations . J. E-Learn. Knowl. Soc . 6 , 21–30. 10.20368/1971-8829/441 [ CrossRef ] [ Google Scholar ]
• Parish L. E., Treasure D. C. (2003). Physical activity and situational motivation in physical education: Influence of the motivational climate and perceived ability . Res. Q. Exerc. Sport. 74 , 173. 10.1080/02701367.2003.10609079 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Pérez-Jorge D., González-Dorta D., Del Carmen Rodríguez-Jiménez D., Fariña-Hernández L. (2021). Problem-solving teacher training, the effect of the ProyectaMates Programme in Tenerife . International Educ . 49 , 777–7791. 10.1080/03004279.2020.1786427 [ CrossRef ] [ Google Scholar ]
• Perrenoud P. (2003). Qu'est-ce qu'apprendre . Enfances Psy . 4 , 9–17. 10.3917/ep.024.0009 [ CrossRef ] [ Google Scholar ]
• Pohan A., Asmin A., Menanti A. (2020). The effect of problem based learning and learning motivation of mathematical problem solving skills of class 5 students at SDN 0407 Mondang . BirLE . 3 , 531–539. 10.33258/birle.v3i1.850 [ CrossRef ] [ Google Scholar ]
• Puigarnau S., Camerino O., Castañer M., Prat Q., Anguera M. T. (2016). El apoyo a la autonomía en practicantes de centros deportivos y de fitness para aumentar su motivación . Rev. Int. de Cienc. del deporte. 43 , 48–64. 10.5232/ricyde2016.04303 [ CrossRef ] [ Google Scholar ]
• Ratelle C. F., Guay F., Vallerand R. J., Larose S., Senécal C. (2007). Autonomous, controlled, and amotivated types of academic motivation: A person-oriented analysis . J. Educ. Psychol. 99 , 734–746. 10.1037/0022-0663.99.4.734 [ CrossRef ] [ Google Scholar ]
• Rivera-Pérez S., Fernandez-Rio J., Gallego D. I. (2020). Effects of an 8-week cooperative learning intervention on physical education students' task and self-approach goals, and Emotional Intelligence . Int. J. Environ. Res. Public Health . 18 , 61. 10.3390/ijerph18010061 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rolland V. (2009). Motivation in the School Context . 5th Edn . Belguim: De Boeck Superior, 218. [ Google Scholar ]
• Rossa R., Maulidiah R. H., Aryni Y. (2021). The effect of problem solving technique and motivation toward students' writing skills . J. Pena. Edukasi. 8 , 43–54. 10.54314/jpe.v8i1.654 [ CrossRef ] [ Google Scholar ]
• Ryan R., Deci E. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions . Contemp. Educ. Psychol . 61 , 101860. 10.1016/j.cedpsych.2020.101860 [ CrossRef ] [ Google Scholar ]
• Siedentop D., Hastie P. A., Van Der Mars H. (2011). Complete Guide to Sport Education, 2nd Edn. Champaign, IL: Human Kinetics. [ Google Scholar ]
• Skinner B. F. (1985). Cognitive science and behaviourism . Br. J. Psychol. 76 , 291–301. 10.1111/j.2044-8295.1985.tb01953.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Standage M., Gillison F. B., Ntoumanis N., Treasure D. C. (2012). Predicting students' physical activity and health-related well-being: a prospective cross-domain investigation of motivation across school physical education and exercise settings . J. Sport. Exerc. Psychol . 34 , 37–60. 10.1123/jsep.34.1.37 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tebabal A., Kahssay G. (2011). The effects of student-centered approach in improving students' graphical interpretation skills and conceptual understanding of kinematical motion . Lat. Am. J. Phys. Educ. 5 , 9. [ Google Scholar ]
• Vallerand R. J., Fbrtier M. S., Guay F. (1997). Self-determination and persistence in a real-life setting toward a motivational model of high school dropout . J. Pers. Soc. Psychol. 2 , 1161–1176. 10.1037/0022-3514.72.5.1161 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ward P., Mitchell M. F., van der Mars H., Lawson H. A. (2021). Chapter 3: PK+12 School physical education: conditions, lessons learned, and future directions . J. Teach. Phys. Educ. 40 , 363–371. 10.1123/jtpe.2020-0241 [ CrossRef ] [ Google Scholar ]

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Review Article
• Open access
• Published: 11 January 2023

The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature

• Enwei Xu   ORCID: orcid.org/0000-0001-6424-8169 1 ,
• Wei Wang 1 &
• Qingxia Wang 1  

Humanities and Social Sciences Communications volume  10 , Article number:  16 ( 2023 ) Cite this article

16k Accesses

16 Citations

3 Altmetric

Metrics details

• Science, technology and society

Collaborative problem-solving has been widely embraced in the classroom instruction of critical thinking, which is regarded as the core of curriculum reform based on key competencies in the field of education as well as a key competence for learners in the 21st century. However, the effectiveness of collaborative problem-solving in promoting students’ critical thinking remains uncertain. This current research presents the major findings of a meta-analysis of 36 pieces of the literature revealed in worldwide educational periodicals during the 21st century to identify the effectiveness of collaborative problem-solving in promoting students’ critical thinking and to determine, based on evidence, whether and to what extent collaborative problem solving can result in a rise or decrease in critical thinking. The findings show that (1) collaborative problem solving is an effective teaching approach to foster students’ critical thinking, with a significant overall effect size (ES = 0.82, z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]); (2) in respect to the dimensions of critical thinking, collaborative problem solving can significantly and successfully enhance students’ attitudinal tendencies (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI[0.87, 1.47]); nevertheless, it falls short in terms of improving students’ cognitive skills, having only an upper-middle impact (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI[0.58, 0.82]); and (3) the teaching type (chi 2  = 7.20, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), and learning scaffold (chi 2  = 9.03, P  < 0.01) all have an impact on critical thinking, and they can be viewed as important moderating factors that affect how critical thinking develops. On the basis of these results, recommendations are made for further study and instruction to better support students’ critical thinking in the context of collaborative problem-solving.

Similar content being viewed by others

Fostering twenty-first century skills among primary school students through math project-based learning

A meta-analysis to gauge the impact of pedagogies employed in mixed-ability high school biology classrooms

A guide to critical thinking: implications for dental education

Introduction.

Although critical thinking has a long history in research, the concept of critical thinking, which is regarded as an essential competence for learners in the 21st century, has recently attracted more attention from researchers and teaching practitioners (National Research Council, 2012 ). Critical thinking should be the core of curriculum reform based on key competencies in the field of education (Peng and Deng, 2017 ) because students with critical thinking can not only understand the meaning of knowledge but also effectively solve practical problems in real life even after knowledge is forgotten (Kek and Huijser, 2011 ). The definition of critical thinking is not universal (Ennis, 1989 ; Castle, 2009 ; Niu et al., 2013 ). In general, the definition of critical thinking is a self-aware and self-regulated thought process (Facione, 1990 ; Niu et al., 2013 ). It refers to the cognitive skills needed to interpret, analyze, synthesize, reason, and evaluate information as well as the attitudinal tendency to apply these abilities (Halpern, 2001 ). The view that critical thinking can be taught and learned through curriculum teaching has been widely supported by many researchers (e.g., Kuncel, 2011 ; Leng and Lu, 2020 ), leading to educators’ efforts to foster it among students. In the field of teaching practice, there are three types of courses for teaching critical thinking (Ennis, 1989 ). The first is an independent curriculum in which critical thinking is taught and cultivated without involving the knowledge of specific disciplines; the second is an integrated curriculum in which critical thinking is integrated into the teaching of other disciplines as a clear teaching goal; and the third is a mixed curriculum in which critical thinking is taught in parallel to the teaching of other disciplines for mixed teaching training. Furthermore, numerous measuring tools have been developed by researchers and educators to measure critical thinking in the context of teaching practice. These include standardized measurement tools, such as WGCTA, CCTST, CCTT, and CCTDI, which have been verified by repeated experiments and are considered effective and reliable by international scholars (Facione and Facione, 1992 ). In short, descriptions of critical thinking, including its two dimensions of attitudinal tendency and cognitive skills, different types of teaching courses, and standardized measurement tools provide a complex normative framework for understanding, teaching, and evaluating critical thinking.

Cultivating critical thinking in curriculum teaching can start with a problem, and one of the most popular critical thinking instructional approaches is problem-based learning (Liu et al., 2020 ). Duch et al. ( 2001 ) noted that problem-based learning in group collaboration is progressive active learning, which can improve students’ critical thinking and problem-solving skills. Collaborative problem-solving is the organic integration of collaborative learning and problem-based learning, which takes learners as the center of the learning process and uses problems with poor structure in real-world situations as the starting point for the learning process (Liang et al., 2017 ). Students learn the knowledge needed to solve problems in a collaborative group, reach a consensus on problems in the field, and form solutions through social cooperation methods, such as dialogue, interpretation, questioning, debate, negotiation, and reflection, thus promoting the development of learners’ domain knowledge and critical thinking (Cindy, 2004 ; Liang et al., 2017 ).

Collaborative problem-solving has been widely used in the teaching practice of critical thinking, and several studies have attempted to conduct a systematic review and meta-analysis of the empirical literature on critical thinking from various perspectives. However, little attention has been paid to the impact of collaborative problem-solving on critical thinking. Therefore, the best approach for developing and enhancing critical thinking throughout collaborative problem-solving is to examine how to implement critical thinking instruction; however, this issue is still unexplored, which means that many teachers are incapable of better instructing critical thinking (Leng and Lu, 2020 ; Niu et al., 2013 ). For example, Huber ( 2016 ) provided the meta-analysis findings of 71 publications on gaining critical thinking over various time frames in college with the aim of determining whether critical thinking was truly teachable. These authors found that learners significantly improve their critical thinking while in college and that critical thinking differs with factors such as teaching strategies, intervention duration, subject area, and teaching type. The usefulness of collaborative problem-solving in fostering students’ critical thinking, however, was not determined by this study, nor did it reveal whether there existed significant variations among the different elements. A meta-analysis of 31 pieces of educational literature was conducted by Liu et al. ( 2020 ) to assess the impact of problem-solving on college students’ critical thinking. These authors found that problem-solving could promote the development of critical thinking among college students and proposed establishing a reasonable group structure for problem-solving in a follow-up study to improve students’ critical thinking. Additionally, previous empirical studies have reached inconclusive and even contradictory conclusions about whether and to what extent collaborative problem-solving increases or decreases critical thinking levels. As an illustration, Yang et al. ( 2008 ) carried out an experiment on the integrated curriculum teaching of college students based on a web bulletin board with the goal of fostering participants’ critical thinking in the context of collaborative problem-solving. These authors’ research revealed that through sharing, debating, examining, and reflecting on various experiences and ideas, collaborative problem-solving can considerably enhance students’ critical thinking in real-life problem situations. In contrast, collaborative problem-solving had a positive impact on learners’ interaction and could improve learning interest and motivation but could not significantly improve students’ critical thinking when compared to traditional classroom teaching, according to research by Naber and Wyatt ( 2014 ) and Sendag and Odabasi ( 2009 ) on undergraduate and high school students, respectively.

The above studies show that there is inconsistency regarding the effectiveness of collaborative problem-solving in promoting students’ critical thinking. Therefore, it is essential to conduct a thorough and trustworthy review to detect and decide whether and to what degree collaborative problem-solving can result in a rise or decrease in critical thinking. Meta-analysis is a quantitative analysis approach that is utilized to examine quantitative data from various separate studies that are all focused on the same research topic. This approach characterizes the effectiveness of its impact by averaging the effect sizes of numerous qualitative studies in an effort to reduce the uncertainty brought on by independent research and produce more conclusive findings (Lipsey and Wilson, 2001 ).

This paper used a meta-analytic approach and carried out a meta-analysis to examine the effectiveness of collaborative problem-solving in promoting students’ critical thinking in order to make a contribution to both research and practice. The following research questions were addressed by this meta-analysis:

What is the overall effect size of collaborative problem-solving in promoting students’ critical thinking and its impact on the two dimensions of critical thinking (i.e., attitudinal tendency and cognitive skills)?

How are the disparities between the study conclusions impacted by various moderating variables if the impacts of various experimental designs in the included studies are heterogeneous?

This research followed the strict procedures (e.g., database searching, identification, screening, eligibility, merging, duplicate removal, and analysis of included studies) of Cooper’s ( 2010 ) proposed meta-analysis approach for examining quantitative data from various separate studies that are all focused on the same research topic. The relevant empirical research that appeared in worldwide educational periodicals within the 21st century was subjected to this meta-analysis using Rev-Man 5.4. The consistency of the data extracted separately by two researchers was tested using Cohen’s kappa coefficient, and a publication bias test and a heterogeneity test were run on the sample data to ascertain the quality of this meta-analysis.

Data sources and search strategies

There were three stages to the data collection process for this meta-analysis, as shown in Fig. 1 , which shows the number of articles included and eliminated during the selection process based on the statement and study eligibility criteria.

This flowchart shows the number of records identified, included and excluded in the article.

First, the databases used to systematically search for relevant articles were the journal papers of the Web of Science Core Collection and the Chinese Core source journal, as well as the Chinese Social Science Citation Index (CSSCI) source journal papers included in CNKI. These databases were selected because they are credible platforms that are sources of scholarly and peer-reviewed information with advanced search tools and contain literature relevant to the subject of our topic from reliable researchers and experts. The search string with the Boolean operator used in the Web of Science was “TS = (((“critical thinking” or “ct” and “pretest” or “posttest”) or (“critical thinking” or “ct” and “control group” or “quasi experiment” or “experiment”)) and (“collaboration” or “collaborative learning” or “CSCL”) and (“problem solving” or “problem-based learning” or “PBL”))”. The research area was “Education Educational Research”, and the search period was “January 1, 2000, to December 30, 2021”. A total of 412 papers were obtained. The search string with the Boolean operator used in the CNKI was “SU = (‘critical thinking’*‘collaboration’ + ‘critical thinking’*‘collaborative learning’ + ‘critical thinking’*‘CSCL’ + ‘critical thinking’*‘problem solving’ + ‘critical thinking’*‘problem-based learning’ + ‘critical thinking’*‘PBL’ + ‘critical thinking’*‘problem oriented’) AND FT = (‘experiment’ + ‘quasi experiment’ + ‘pretest’ + ‘posttest’ + ‘empirical study’)” (translated into Chinese when searching). A total of 56 studies were found throughout the search period of “January 2000 to December 2021”. From the databases, all duplicates and retractions were eliminated before exporting the references into Endnote, a program for managing bibliographic references. In all, 466 studies were found.

Second, the studies that matched the inclusion and exclusion criteria for the meta-analysis were chosen by two researchers after they had reviewed the abstracts and titles of the gathered articles, yielding a total of 126 studies.

Third, two researchers thoroughly reviewed each included article’s whole text in accordance with the inclusion and exclusion criteria. Meanwhile, a snowball search was performed using the references and citations of the included articles to ensure complete coverage of the articles. Ultimately, 36 articles were kept.

Two researchers worked together to carry out this entire process, and a consensus rate of almost 94.7% was reached after discussion and negotiation to clarify any emerging differences.

Eligibility criteria

Since not all the retrieved studies matched the criteria for this meta-analysis, eligibility criteria for both inclusion and exclusion were developed as follows:

The publication language of the included studies was limited to English and Chinese, and the full text could be obtained. Articles that did not meet the publication language and articles not published between 2000 and 2021 were excluded.

The research design of the included studies must be empirical and quantitative studies that can assess the effect of collaborative problem-solving on the development of critical thinking. Articles that could not identify the causal mechanisms by which collaborative problem-solving affects critical thinking, such as review articles and theoretical articles, were excluded.

The research method of the included studies must feature a randomized control experiment or a quasi-experiment, or a natural experiment, which have a higher degree of internal validity with strong experimental designs and can all plausibly provide evidence that critical thinking and collaborative problem-solving are causally related. Articles with non-experimental research methods, such as purely correlational or observational studies, were excluded.

The participants of the included studies were only students in school, including K-12 students and college students. Articles in which the participants were non-school students, such as social workers or adult learners, were excluded.

The research results of the included studies must mention definite signs that may be utilized to gauge critical thinking’s impact (e.g., sample size, mean value, or standard deviation). Articles that lacked specific measurement indicators for critical thinking and could not calculate the effect size were excluded.

Data coding design

In order to perform a meta-analysis, it is necessary to collect the most important information from the articles, codify that information’s properties, and convert descriptive data into quantitative data. Therefore, this study designed a data coding template (see Table 1 ). Ultimately, 16 coding fields were retained.

The designed data-coding template consisted of three pieces of information. Basic information about the papers was included in the descriptive information: the publishing year, author, serial number, and title of the paper.

The variable information for the experimental design had three variables: the independent variable (instruction method), the dependent variable (critical thinking), and the moderating variable (learning stage, teaching type, intervention duration, learning scaffold, group size, measuring tool, and subject area). Depending on the topic of this study, the intervention strategy, as the independent variable, was coded into collaborative and non-collaborative problem-solving. The dependent variable, critical thinking, was coded as a cognitive skill and an attitudinal tendency. And seven moderating variables were created by grouping and combining the experimental design variables discovered within the 36 studies (see Table 1 ), where learning stages were encoded as higher education, high school, middle school, and primary school or lower; teaching types were encoded as mixed courses, integrated courses, and independent courses; intervention durations were encoded as 0–1 weeks, 1–4 weeks, 4–12 weeks, and more than 12 weeks; group sizes were encoded as 2–3 persons, 4–6 persons, 7–10 persons, and more than 10 persons; learning scaffolds were encoded as teacher-supported learning scaffold, technique-supported learning scaffold, and resource-supported learning scaffold; measuring tools were encoded as standardized measurement tools (e.g., WGCTA, CCTT, CCTST, and CCTDI) and self-adapting measurement tools (e.g., modified or made by researchers); and subject areas were encoded according to the specific subjects used in the 36 included studies.

The data information contained three metrics for measuring critical thinking: sample size, average value, and standard deviation. It is vital to remember that studies with various experimental designs frequently adopt various formulas to determine the effect size. And this paper used Morris’ proposed standardized mean difference (SMD) calculation formula ( 2008 , p. 369; see Supplementary Table S3 ).

Procedure for extracting and coding data

According to the data coding template (see Table 1 ), the 36 papers’ information was retrieved by two researchers, who then entered them into Excel (see Supplementary Table S1 ). The results of each study were extracted separately in the data extraction procedure if an article contained numerous studies on critical thinking, or if a study assessed different critical thinking dimensions. For instance, Tiwari et al. ( 2010 ) used four time points, which were viewed as numerous different studies, to examine the outcomes of critical thinking, and Chen ( 2013 ) included the two outcome variables of attitudinal tendency and cognitive skills, which were regarded as two studies. After discussion and negotiation during data extraction, the two researchers’ consistency test coefficients were roughly 93.27%. Supplementary Table S2 details the key characteristics of the 36 included articles with 79 effect quantities, including descriptive information (e.g., the publishing year, author, serial number, and title of the paper), variable information (e.g., independent variables, dependent variables, and moderating variables), and data information (e.g., mean values, standard deviations, and sample size). Following that, testing for publication bias and heterogeneity was done on the sample data using the Rev-Man 5.4 software, and then the test results were used to conduct a meta-analysis.

Publication bias test

When the sample of studies included in a meta-analysis does not accurately reflect the general status of research on the relevant subject, publication bias is said to be exhibited in this research. The reliability and accuracy of the meta-analysis may be impacted by publication bias. Due to this, the meta-analysis needs to check the sample data for publication bias (Stewart et al., 2006 ). A popular method to check for publication bias is the funnel plot; and it is unlikely that there will be publishing bias when the data are equally dispersed on either side of the average effect size and targeted within the higher region. The data are equally dispersed within the higher portion of the efficient zone, consistent with the funnel plot connected with this analysis (see Fig. 2 ), indicating that publication bias is unlikely in this situation.

This funnel plot shows the result of publication bias of 79 effect quantities across 36 studies.

Heterogeneity test

To select the appropriate effect models for the meta-analysis, one might use the results of a heterogeneity test on the data effect sizes. In a meta-analysis, it is common practice to gauge the degree of data heterogeneity using the I 2 value, and I 2  ≥ 50% is typically understood to denote medium-high heterogeneity, which calls for the adoption of a random effect model; if not, a fixed effect model ought to be applied (Lipsey and Wilson, 2001 ). The findings of the heterogeneity test in this paper (see Table 2 ) revealed that I 2 was 86% and displayed significant heterogeneity ( P  < 0.01). To ensure accuracy and reliability, the overall effect size ought to be calculated utilizing the random effect model.

The analysis of the overall effect size

This meta-analysis utilized a random effect model to examine 79 effect quantities from 36 studies after eliminating heterogeneity. In accordance with Cohen’s criterion (Cohen, 1992 ), it is abundantly clear from the analysis results, which are shown in the forest plot of the overall effect (see Fig. 3 ), that the cumulative impact size of cooperative problem-solving is 0.82, which is statistically significant ( z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]), and can encourage learners to practice critical thinking.

This forest plot shows the analysis result of the overall effect size across 36 studies.

In addition, this study examined two distinct dimensions of critical thinking to better understand the precise contributions that collaborative problem-solving makes to the growth of critical thinking. The findings (see Table 3 ) indicate that collaborative problem-solving improves cognitive skills (ES = 0.70) and attitudinal tendency (ES = 1.17), with significant intergroup differences (chi 2  = 7.95, P  < 0.01). Although collaborative problem-solving improves both dimensions of critical thinking, it is essential to point out that the improvements in students’ attitudinal tendency are much more pronounced and have a significant comprehensive effect (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI [0.87, 1.47]), whereas gains in learners’ cognitive skill are slightly improved and are just above average. (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI [0.58, 0.82]).

The analysis of moderator effect size

The whole forest plot’s 79 effect quantities underwent a two-tailed test, which revealed significant heterogeneity ( I 2  = 86%, z  = 12.78, P  < 0.01), indicating differences between various effect sizes that may have been influenced by moderating factors other than sampling error. Therefore, exploring possible moderating factors that might produce considerable heterogeneity was done using subgroup analysis, such as the learning stage, learning scaffold, teaching type, group size, duration of the intervention, measuring tool, and the subject area included in the 36 experimental designs, in order to further explore the key factors that influence critical thinking. The findings (see Table 4 ) indicate that various moderating factors have advantageous effects on critical thinking. In this situation, the subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), learning scaffold (chi 2  = 9.03, P  < 0.01), and teaching type (chi 2  = 7.20, P  < 0.05) are all significant moderators that can be applied to support the cultivation of critical thinking. However, since the learning stage and the measuring tools did not significantly differ among intergroup (chi 2  = 3.15, P  = 0.21 > 0.05, and chi 2  = 0.08, P  = 0.78 > 0.05), we are unable to explain why these two factors are crucial in supporting the cultivation of critical thinking in the context of collaborative problem-solving. These are the precise outcomes, as follows:

Various learning stages influenced critical thinking positively, without significant intergroup differences (chi 2  = 3.15, P  = 0.21 > 0.05). High school was first on the list of effect sizes (ES = 1.36, P  < 0.01), then higher education (ES = 0.78, P  < 0.01), and middle school (ES = 0.73, P  < 0.01). These results show that, despite the learning stage’s beneficial influence on cultivating learners’ critical thinking, we are unable to explain why it is essential for cultivating critical thinking in the context of collaborative problem-solving.

Different teaching types had varying degrees of positive impact on critical thinking, with significant intergroup differences (chi 2  = 7.20, P  < 0.05). The effect size was ranked as follows: mixed courses (ES = 1.34, P  < 0.01), integrated courses (ES = 0.81, P  < 0.01), and independent courses (ES = 0.27, P  < 0.01). These results indicate that the most effective approach to cultivate critical thinking utilizing collaborative problem solving is through the teaching type of mixed courses.

Various intervention durations significantly improved critical thinking, and there were significant intergroup differences (chi 2  = 12.18, P  < 0.01). The effect sizes related to this variable showed a tendency to increase with longer intervention durations. The improvement in critical thinking reached a significant level (ES = 0.85, P  < 0.01) after more than 12 weeks of training. These findings indicate that the intervention duration and critical thinking’s impact are positively correlated, with a longer intervention duration having a greater effect.

Different learning scaffolds influenced critical thinking positively, with significant intergroup differences (chi 2  = 9.03, P  < 0.01). The resource-supported learning scaffold (ES = 0.69, P  < 0.01) acquired a medium-to-higher level of impact, the technique-supported learning scaffold (ES = 0.63, P  < 0.01) also attained a medium-to-higher level of impact, and the teacher-supported learning scaffold (ES = 0.92, P  < 0.01) displayed a high level of significant impact. These results show that the learning scaffold with teacher support has the greatest impact on cultivating critical thinking.

Various group sizes influenced critical thinking positively, and the intergroup differences were statistically significant (chi 2  = 8.77, P  < 0.05). Critical thinking showed a general declining trend with increasing group size. The overall effect size of 2–3 people in this situation was the biggest (ES = 0.99, P  < 0.01), and when the group size was greater than 7 people, the improvement in critical thinking was at the lower-middle level (ES < 0.5, P  < 0.01). These results show that the impact on critical thinking is positively connected with group size, and as group size grows, so does the overall impact.

Various measuring tools influenced critical thinking positively, with significant intergroup differences (chi 2  = 0.08, P  = 0.78 > 0.05). In this situation, the self-adapting measurement tools obtained an upper-medium level of effect (ES = 0.78), whereas the complete effect size of the standardized measurement tools was the largest, achieving a significant level of effect (ES = 0.84, P  < 0.01). These results show that, despite the beneficial influence of the measuring tool on cultivating critical thinking, we are unable to explain why it is crucial in fostering the growth of critical thinking by utilizing the approach of collaborative problem-solving.

Different subject areas had a greater impact on critical thinking, and the intergroup differences were statistically significant (chi 2  = 13.36, P  < 0.05). Mathematics had the greatest overall impact, achieving a significant level of effect (ES = 1.68, P  < 0.01), followed by science (ES = 1.25, P  < 0.01) and medical science (ES = 0.87, P  < 0.01), both of which also achieved a significant level of effect. Programming technology was the least effective (ES = 0.39, P  < 0.01), only having a medium-low degree of effect compared to education (ES = 0.72, P  < 0.01) and other fields (such as language, art, and social sciences) (ES = 0.58, P  < 0.01). These results suggest that scientific fields (e.g., mathematics, science) may be the most effective subject areas for cultivating critical thinking utilizing the approach of collaborative problem-solving.

The effectiveness of collaborative problem solving with regard to teaching critical thinking

According to this meta-analysis, using collaborative problem-solving as an intervention strategy in critical thinking teaching has a considerable amount of impact on cultivating learners’ critical thinking as a whole and has a favorable promotional effect on the two dimensions of critical thinking. According to certain studies, collaborative problem solving, the most frequently used critical thinking teaching strategy in curriculum instruction can considerably enhance students’ critical thinking (e.g., Liang et al., 2017 ; Liu et al., 2020 ; Cindy, 2004 ). This meta-analysis provides convergent data support for the above research views. Thus, the findings of this meta-analysis not only effectively address the first research query regarding the overall effect of cultivating critical thinking and its impact on the two dimensions of critical thinking (i.e., attitudinal tendency and cognitive skills) utilizing the approach of collaborative problem-solving, but also enhance our confidence in cultivating critical thinking by using collaborative problem-solving intervention approach in the context of classroom teaching.

Furthermore, the associated improvements in attitudinal tendency are much stronger, but the corresponding improvements in cognitive skill are only marginally better. According to certain studies, cognitive skill differs from the attitudinal tendency in classroom instruction; the cultivation and development of the former as a key ability is a process of gradual accumulation, while the latter as an attitude is affected by the context of the teaching situation (e.g., a novel and exciting teaching approach, challenging and rewarding tasks) (Halpern, 2001 ; Wei and Hong, 2022 ). Collaborative problem-solving as a teaching approach is exciting and interesting, as well as rewarding and challenging; because it takes the learners as the focus and examines problems with poor structure in real situations, and it can inspire students to fully realize their potential for problem-solving, which will significantly improve their attitudinal tendency toward solving problems (Liu et al., 2020 ). Similar to how collaborative problem-solving influences attitudinal tendency, attitudinal tendency impacts cognitive skill when attempting to solve a problem (Liu et al., 2020 ; Zhang et al., 2022 ), and stronger attitudinal tendencies are associated with improved learning achievement and cognitive ability in students (Sison, 2008 ; Zhang et al., 2022 ). It can be seen that the two specific dimensions of critical thinking as well as critical thinking as a whole are affected by collaborative problem-solving, and this study illuminates the nuanced links between cognitive skills and attitudinal tendencies with regard to these two dimensions of critical thinking. To fully develop students’ capacity for critical thinking, future empirical research should pay closer attention to cognitive skills.

The moderating effects of collaborative problem solving with regard to teaching critical thinking

In order to further explore the key factors that influence critical thinking, exploring possible moderating effects that might produce considerable heterogeneity was done using subgroup analysis. The findings show that the moderating factors, such as the teaching type, learning stage, group size, learning scaffold, duration of the intervention, measuring tool, and the subject area included in the 36 experimental designs, could all support the cultivation of collaborative problem-solving in critical thinking. Among them, the effect size differences between the learning stage and measuring tool are not significant, which does not explain why these two factors are crucial in supporting the cultivation of critical thinking utilizing the approach of collaborative problem-solving.

In terms of the learning stage, various learning stages influenced critical thinking positively without significant intergroup differences, indicating that we are unable to explain why it is crucial in fostering the growth of critical thinking.

Although high education accounts for 70.89% of all empirical studies performed by researchers, high school may be the appropriate learning stage to foster students’ critical thinking by utilizing the approach of collaborative problem-solving since it has the largest overall effect size. This phenomenon may be related to student’s cognitive development, which needs to be further studied in follow-up research.

With regard to teaching type, mixed course teaching may be the best teaching method to cultivate students’ critical thinking. Relevant studies have shown that in the actual teaching process if students are trained in thinking methods alone, the methods they learn are isolated and divorced from subject knowledge, which is not conducive to their transfer of thinking methods; therefore, if students’ thinking is trained only in subject teaching without systematic method training, it is challenging to apply to real-world circumstances (Ruggiero, 2012 ; Hu and Liu, 2015 ). Teaching critical thinking as mixed course teaching in parallel to other subject teachings can achieve the best effect on learners’ critical thinking, and explicit critical thinking instruction is more effective than less explicit critical thinking instruction (Bensley and Spero, 2014 ).

In terms of the intervention duration, with longer intervention times, the overall effect size shows an upward tendency. Thus, the intervention duration and critical thinking’s impact are positively correlated. Critical thinking, as a key competency for students in the 21st century, is difficult to get a meaningful improvement in a brief intervention duration. Instead, it could be developed over a lengthy period of time through consistent teaching and the progressive accumulation of knowledge (Halpern, 2001 ; Hu and Liu, 2015 ). Therefore, future empirical studies ought to take these restrictions into account throughout a longer period of critical thinking instruction.

With regard to group size, a group size of 2–3 persons has the highest effect size, and the comprehensive effect size decreases with increasing group size in general. This outcome is in line with some research findings; as an example, a group composed of two to four members is most appropriate for collaborative learning (Schellens and Valcke, 2006 ). However, the meta-analysis results also indicate that once the group size exceeds 7 people, small groups cannot produce better interaction and performance than large groups. This may be because the learning scaffolds of technique support, resource support, and teacher support improve the frequency and effectiveness of interaction among group members, and a collaborative group with more members may increase the diversity of views, which is helpful to cultivate critical thinking utilizing the approach of collaborative problem-solving.

With regard to the learning scaffold, the three different kinds of learning scaffolds can all enhance critical thinking. Among them, the teacher-supported learning scaffold has the largest overall effect size, demonstrating the interdependence of effective learning scaffolds and collaborative problem-solving. This outcome is in line with some research findings; as an example, a successful strategy is to encourage learners to collaborate, come up with solutions, and develop critical thinking skills by using learning scaffolds (Reiser, 2004 ; Xu et al., 2022 ); learning scaffolds can lower task complexity and unpleasant feelings while also enticing students to engage in learning activities (Wood et al., 2006 ); learning scaffolds are designed to assist students in using learning approaches more successfully to adapt the collaborative problem-solving process, and the teacher-supported learning scaffolds have the greatest influence on critical thinking in this process because they are more targeted, informative, and timely (Xu et al., 2022 ).

With respect to the measuring tool, despite the fact that standardized measurement tools (such as the WGCTA, CCTT, and CCTST) have been acknowledged as trustworthy and effective by worldwide experts, only 54.43% of the research included in this meta-analysis adopted them for assessment, and the results indicated no intergroup differences. These results suggest that not all teaching circumstances are appropriate for measuring critical thinking using standardized measurement tools. “The measuring tools for measuring thinking ability have limits in assessing learners in educational situations and should be adapted appropriately to accurately assess the changes in learners’ critical thinking.”, according to Simpson and Courtney ( 2002 , p. 91). As a result, in order to more fully and precisely gauge how learners’ critical thinking has evolved, we must properly modify standardized measuring tools based on collaborative problem-solving learning contexts.

With regard to the subject area, the comprehensive effect size of science departments (e.g., mathematics, science, medical science) is larger than that of language arts and social sciences. Some recent international education reforms have noted that critical thinking is a basic part of scientific literacy. Students with scientific literacy can prove the rationality of their judgment according to accurate evidence and reasonable standards when they face challenges or poorly structured problems (Kyndt et al., 2013 ), which makes critical thinking crucial for developing scientific understanding and applying this understanding to practical problem solving for problems related to science, technology, and society (Yore et al., 2007 ).

Suggestions for critical thinking teaching

Other than those stated in the discussion above, the following suggestions are offered for critical thinking instruction utilizing the approach of collaborative problem-solving.

First, teachers should put a special emphasis on the two core elements, which are collaboration and problem-solving, to design real problems based on collaborative situations. This meta-analysis provides evidence to support the view that collaborative problem-solving has a strong synergistic effect on promoting students’ critical thinking. Asking questions about real situations and allowing learners to take part in critical discussions on real problems during class instruction are key ways to teach critical thinking rather than simply reading speculative articles without practice (Mulnix, 2012 ). Furthermore, the improvement of students’ critical thinking is realized through cognitive conflict with other learners in the problem situation (Yang et al., 2008 ). Consequently, it is essential for teachers to put a special emphasis on the two core elements, which are collaboration and problem-solving, and design real problems and encourage students to discuss, negotiate, and argue based on collaborative problem-solving situations.

Second, teachers should design and implement mixed courses to cultivate learners’ critical thinking, utilizing the approach of collaborative problem-solving. Critical thinking can be taught through curriculum instruction (Kuncel, 2011 ; Leng and Lu, 2020 ), with the goal of cultivating learners’ critical thinking for flexible transfer and application in real problem-solving situations. This meta-analysis shows that mixed course teaching has a highly substantial impact on the cultivation and promotion of learners’ critical thinking. Therefore, teachers should design and implement mixed course teaching with real collaborative problem-solving situations in combination with the knowledge content of specific disciplines in conventional teaching, teach methods and strategies of critical thinking based on poorly structured problems to help students master critical thinking, and provide practical activities in which students can interact with each other to develop knowledge construction and critical thinking utilizing the approach of collaborative problem-solving.

Third, teachers should be more trained in critical thinking, particularly preservice teachers, and they also should be conscious of the ways in which teachers’ support for learning scaffolds can promote critical thinking. The learning scaffold supported by teachers had the greatest impact on learners’ critical thinking, in addition to being more directive, targeted, and timely (Wood et al., 2006 ). Critical thinking can only be effectively taught when teachers recognize the significance of critical thinking for students’ growth and use the proper approaches while designing instructional activities (Forawi, 2016 ). Therefore, with the intention of enabling teachers to create learning scaffolds to cultivate learners’ critical thinking utilizing the approach of collaborative problem solving, it is essential to concentrate on the teacher-supported learning scaffolds and enhance the instruction for teaching critical thinking to teachers, especially preservice teachers.

Implications and limitations

There are certain limitations in this meta-analysis, but future research can correct them. First, the search languages were restricted to English and Chinese, so it is possible that pertinent studies that were written in other languages were overlooked, resulting in an inadequate number of articles for review. Second, these data provided by the included studies are partially missing, such as whether teachers were trained in the theory and practice of critical thinking, the average age and gender of learners, and the differences in critical thinking among learners of various ages and genders. Third, as is typical for review articles, more studies were released while this meta-analysis was being done; therefore, it had a time limit. With the development of relevant research, future studies focusing on these issues are highly relevant and needed.

Conclusions

The subject of the magnitude of collaborative problem-solving’s impact on fostering students’ critical thinking, which received scant attention from other studies, was successfully addressed by this study. The question of the effectiveness of collaborative problem-solving in promoting students’ critical thinking was addressed in this study, which addressed a topic that had gotten little attention in earlier research. The following conclusions can be made:

Regarding the results obtained, collaborative problem solving is an effective teaching approach to foster learners’ critical thinking, with a significant overall effect size (ES = 0.82, z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]). With respect to the dimensions of critical thinking, collaborative problem-solving can significantly and effectively improve students’ attitudinal tendency, and the comprehensive effect is significant (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI [0.87, 1.47]); nevertheless, it falls short in terms of improving students’ cognitive skills, having only an upper-middle impact (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI [0.58, 0.82]).

As demonstrated by both the results and the discussion, there are varying degrees of beneficial effects on students’ critical thinking from all seven moderating factors, which were found across 36 studies. In this context, the teaching type (chi 2  = 7.20, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), and learning scaffold (chi 2  = 9.03, P  < 0.01) all have a positive impact on critical thinking, and they can be viewed as important moderating factors that affect how critical thinking develops. Since the learning stage (chi 2  = 3.15, P  = 0.21 > 0.05) and measuring tools (chi 2  = 0.08, P  = 0.78 > 0.05) did not demonstrate any significant intergroup differences, we are unable to explain why these two factors are crucial in supporting the cultivation of critical thinking in the context of collaborative problem-solving.

Data availability

All data generated or analyzed during this study are included within the article and its supplementary information files, and the supplementary information files are available in the Dataverse repository: https://doi.org/10.7910/DVN/IPFJO6 .

Bensley DA, Spero RA (2014) Improving critical thinking skills and meta-cognitive monitoring through direct infusion. Think Skills Creat 12:55–68. https://doi.org/10.1016/j.tsc.2014.02.001

Article   Google Scholar  

Castle A (2009) Defining and assessing critical thinking skills for student radiographers. Radiography 15(1):70–76. https://doi.org/10.1016/j.radi.2007.10.007

Chen XD (2013) An empirical study on the influence of PBL teaching model on critical thinking ability of non-English majors. J PLA Foreign Lang College 36 (04):68–72

Google Scholar  

Cohen A (1992) Antecedents of organizational commitment across occupational groups: a meta-analysis. J Organ Behav. https://doi.org/10.1002/job.4030130602

Cooper H (2010) Research synthesis and meta-analysis: a step-by-step approach, 4th edn. Sage, London, England

Cindy HS (2004) Problem-based learning: what and how do students learn? Educ Psychol Rev 51(1):31–39

Duch BJ, Gron SD, Allen DE (2001) The power of problem-based learning: a practical “how to” for teaching undergraduate courses in any discipline. Stylus Educ Sci 2:190–198

Ennis RH (1989) Critical thinking and subject specificity: clarification and needed research. Educ Res 18(3):4–10. https://doi.org/10.3102/0013189x018003004

Facione PA (1990) Critical thinking: a statement of expert consensus for purposes of educational assessment and instruction. Research findings and recommendations. Eric document reproduction service. https://eric.ed.gov/?id=ed315423

Facione PA, Facione NC (1992) The California Critical Thinking Dispositions Inventory (CCTDI) and the CCTDI test manual. California Academic Press, Millbrae, CA

Forawi SA (2016) Standard-based science education and critical thinking. Think Skills Creat 20:52–62. https://doi.org/10.1016/j.tsc.2016.02.005

Halpern DF (2001) Assessing the effectiveness of critical thinking instruction. J Gen Educ 50(4):270–286. https://doi.org/10.2307/27797889

Hu WP, Liu J (2015) Cultivation of pupils’ thinking ability: a five-year follow-up study. Psychol Behav Res 13(05):648–654. https://doi.org/10.3969/j.issn.1672-0628.2015.05.010

Huber K (2016) Does college teach critical thinking? A meta-analysis. Rev Educ Res 86(2):431–468. https://doi.org/10.3102/0034654315605917

Kek MYCA, Huijser H (2011) The power of problem-based learning in developing critical thinking skills: preparing students for tomorrow’s digital futures in today’s classrooms. High Educ Res Dev 30(3):329–341. https://doi.org/10.1080/07294360.2010.501074

Kuncel NR (2011) Measurement and meaning of critical thinking (Research report for the NRC 21st Century Skills Workshop). National Research Council, Washington, DC

Kyndt E, Raes E, Lismont B, Timmers F, Cascallar E, Dochy F (2013) A meta-analysis of the effects of face-to-face cooperative learning. Do recent studies falsify or verify earlier findings? Educ Res Rev 10(2):133–149. https://doi.org/10.1016/j.edurev.2013.02.002

Leng J, Lu XX (2020) Is critical thinking really teachable?—A meta-analysis based on 79 experimental or quasi experimental studies. Open Educ Res 26(06):110–118. https://doi.org/10.13966/j.cnki.kfjyyj.2020.06.011

Liang YZ, Zhu K, Zhao CL (2017) An empirical study on the depth of interaction promoted by collaborative problem solving learning activities. J E-educ Res 38(10):87–92. https://doi.org/10.13811/j.cnki.eer.2017.10.014

Lipsey M, Wilson D (2001) Practical meta-analysis. International Educational and Professional, London, pp. 92–160

Liu Z, Wu W, Jiang Q (2020) A study on the influence of problem based learning on college students’ critical thinking-based on a meta-analysis of 31 studies. Explor High Educ 03:43–49

Morris SB (2008) Estimating effect sizes from pretest-posttest-control group designs. Organ Res Methods 11(2):364–386. https://doi.org/10.1177/1094428106291059

Article   ADS   Google Scholar  

Mulnix JW (2012) Thinking critically about critical thinking. Educ Philos Theory 44(5):464–479. https://doi.org/10.1111/j.1469-5812.2010.00673.x

Naber J, Wyatt TH (2014) The effect of reflective writing interventions on the critical thinking skills and dispositions of baccalaureate nursing students. Nurse Educ Today 34(1):67–72. https://doi.org/10.1016/j.nedt.2013.04.002

National Research Council (2012) Education for life and work: developing transferable knowledge and skills in the 21st century. The National Academies Press, Washington, DC

Niu L, Behar HLS, Garvan CW (2013) Do instructional interventions influence college students’ critical thinking skills? A meta-analysis. Educ Res Rev 9(12):114–128. https://doi.org/10.1016/j.edurev.2012.12.002

Peng ZM, Deng L (2017) Towards the core of education reform: cultivating critical thinking skills as the core of skills in the 21st century. Res Educ Dev 24:57–63. https://doi.org/10.14121/j.cnki.1008-3855.2017.24.011

Reiser BJ (2004) Scaffolding complex learning: the mechanisms of structuring and problematizing student work. J Learn Sci 13(3):273–304. https://doi.org/10.1207/s15327809jls1303_2

Ruggiero VR (2012) The art of thinking: a guide to critical and creative thought, 4th edn. Harper Collins College Publishers, New York

Schellens T, Valcke M (2006) Fostering knowledge construction in university students through asynchronous discussion groups. Comput Educ 46(4):349–370. https://doi.org/10.1016/j.compedu.2004.07.010

Sendag S, Odabasi HF (2009) Effects of an online problem based learning course on content knowledge acquisition and critical thinking skills. Comput Educ 53(1):132–141. https://doi.org/10.1016/j.compedu.2009.01.008

Sison R (2008) Investigating Pair Programming in a Software Engineering Course in an Asian Setting. 2008 15th Asia-Pacific Software Engineering Conference, pp. 325–331. https://doi.org/10.1109/APSEC.2008.61

Simpson E, Courtney M (2002) Critical thinking in nursing education: literature review. Mary Courtney 8(2):89–98

Stewart L, Tierney J, Burdett S (2006) Do systematic reviews based on individual patient data offer a means of circumventing biases associated with trial publications? Publication bias in meta-analysis. John Wiley and Sons Inc, New York, pp. 261–286

Tiwari A, Lai P, So M, Yuen K (2010) A comparison of the effects of problem-based learning and lecturing on the development of students’ critical thinking. Med Educ 40(6):547–554. https://doi.org/10.1111/j.1365-2929.2006.02481.x

Wood D, Bruner JS, Ross G (2006) The role of tutoring in problem solving. J Child Psychol Psychiatry 17(2):89–100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x

Wei T, Hong S (2022) The meaning and realization of teachable critical thinking. Educ Theory Practice 10:51–57

Xu EW, Wang W, Wang QX (2022) A meta-analysis of the effectiveness of programming teaching in promoting K-12 students’ computational thinking. Educ Inf Technol. https://doi.org/10.1007/s10639-022-11445-2

Yang YC, Newby T, Bill R (2008) Facilitating interactions through structured web-based bulletin boards: a quasi-experimental study on promoting learners’ critical thinking skills. Comput Educ 50(4):1572–1585. https://doi.org/10.1016/j.compedu.2007.04.006

Yore LD, Pimm D, Tuan HL (2007) The literacy component of mathematical and scientific literacy. Int J Sci Math Educ 5(4):559–589. https://doi.org/10.1007/s10763-007-9089-4

Zhang T, Zhang S, Gao QQ, Wang JH (2022) Research on the development of learners’ critical thinking in online peer review. Audio Visual Educ Res 6:53–60. https://doi.org/10.13811/j.cnki.eer.2022.06.08

Download references

Acknowledgements

This research was supported by the graduate scientific research and innovation project of Xinjiang Uygur Autonomous Region named “Research on in-depth learning of high school information technology courses for the cultivation of computing thinking” (No. XJ2022G190) and the independent innovation fund project for doctoral students of the College of Educational Science of Xinjiang Normal University named “Research on project-based teaching of high school information technology courses from the perspective of discipline core literacy” (No. XJNUJKYA2003).

Author information

Authors and affiliations.

College of Educational Science, Xinjiang Normal University, 830017, Urumqi, Xinjiang, China

Enwei Xu, Wei Wang & Qingxia Wang

You can also search for this author in PubMed   Google Scholar

Corresponding authors

Correspondence to Enwei Xu or Wei Wang .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

Informed consent

Additional information.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary tables, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Xu, E., Wang, W. & Wang, Q. The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature. Humanit Soc Sci Commun 10 , 16 (2023). https://doi.org/10.1057/s41599-023-01508-1

Download citation

Received : 07 August 2022

Accepted : 04 January 2023

Published : 11 January 2023

DOI : https://doi.org/10.1057/s41599-023-01508-1

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Impacts of online collaborative learning on students’ intercultural communication apprehension and intercultural communicative competence.

• Hoa Thi Hoang Chau
• Hung Phu Bui
• Quynh Thi Huong Dinh

Education and Information Technologies (2024)

Exploring the effects of digital technology on deep learning: a meta-analysis

Sustainable electricity generation and farm-grid utilization from photovoltaic aquaculture: a bibliometric analysis.

• A. A. Amusa
• M. Alhassan

International Journal of Environmental Science and Technology (2024)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Center for Teaching

Teaching problem solving.

Print Version

Tips and Techniques

Expert vs. novice problem solvers, communicate.

• Have students  identify specific problems, difficulties, or confusions . Don’t waste time working through problems that students already understand.
• If students are unable to articulate their concerns, determine where they are having trouble by  asking them to identify the specific concepts or principles associated with the problem.
• In a one-on-one tutoring session, ask the student to  work his/her problem out loud . This slows down the thinking process, making it more accurate and allowing you to access understanding.
• When working with larger groups you can ask students to provide a written “two-column solution.” Have students write up their solution to a problem by putting all their calculations in one column and all of their reasoning (in complete sentences) in the other column. This helps them to think critically about their own problem solving and helps you to more easily identify where they may be having problems. Two-Column Solution (Math) Two-Column Solution (Physics)

Encourage Independence

• Model the problem solving process rather than just giving students the answer. As you work through the problem, consider how a novice might struggle with the concepts and make your thinking clear
• Have students work through problems on their own. Ask directing questions or give helpful suggestions, but  provide only minimal assistance and only when needed to overcome obstacles.
• Don’t fear  group work ! Students can frequently help each other, and talking about a problem helps them think more critically about the steps needed to solve the problem. Additionally, group work helps students realize that problems often have multiple solution strategies, some that might be more effective than others

Be sensitive

• Frequently, when working problems, students are unsure of themselves. This lack of confidence may hamper their learning. It is important to recognize this when students come to us for help, and to give each student some feeling of mastery. Do this by providing  positive reinforcement to let students know when they have mastered a new concept or skill.

Encourage Thoroughness and Patience

• Try to communicate that  the process is more important than the answer so that the student learns that it is OK to not have an instant solution. This is learned through your acceptance of his/her pace of doing things, through your refusal to let anxiety pressure you into giving the right answer, and through your example of problem solving through a step-by step process.

Experts (teachers) in a particular field are often so fluent in solving problems from that field that they can find it difficult to articulate the problem solving principles and strategies they use to novices (students) in their field because these principles and strategies are second nature to the expert. To teach students problem solving skills,  a teacher should be aware of principles and strategies of good problem solving in his or her discipline .

The mathematician George Polya captured the problem solving principles and strategies he used in his discipline in the book  How to Solve It: A New Aspect of Mathematical Method (Princeton University Press, 1957). The book includes  a summary of Polya’s problem solving heuristic as well as advice on the teaching of problem solving.

Teaching Guides

• Online Course Development Resources
• Principles & Frameworks
• Pedagogies & Strategies
• Reflecting & Assessing
• Challenges & Opportunities
• Populations & Contexts

Quick Links

• Services for Departments and Schools
• Examples of Online Instructional Modules

ORIGINAL RESEARCH article

The problem-solving method: efficacy for learning and motivation in the field of physical education.

• 1 High Institute of Sport and Physical Education of Sfax, University of Sfax, Sfax, Tunisia
• 2 Research Unit of the National Sports Observatory (ONS), Tunis, Tunisia
• 3 Research Laboratory: Education, Motricity, Sport and Health, EM2S, LR19JS01, University of Sfax, Sfax, Tunisia
• 4 Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
• 5 Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom
• 6 Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, ON, Canada
• 7 High Institute of Sport and Physical Education of Ksar Saîd, University Manouba, UMA, Manouba, Tunisia

Background: In pursuit of quality teaching and learning, teachers seek the best method to provide their students with a positive educational atmosphere and the most appropriate learning conditions.

Objectives: The purpose of this study is to compare the effects of the problem-solving method vs. the traditional method on motivation and learning during physical education courses.

Methods: Fifty-three students ( M age 15 ± 0.1 years), in their 1st year of the Tunisian secondary education system, voluntarily participated in this study, and randomly assigned to a control or experimental group. Participants in the control group were taught using the traditional methods, whereas participants in the experimental group were taught using the problem-solving method. Both groups took part in a 10-hour experiment over 5 weeks. To measure students' situational motivation, a questionnaire was used to evaluate intrinsic motivation, identified regulation, external regulation, and amotivation during the first (T0) and the last sessions (T2). Additionally, the degree of students' learning was determined via video analyses, recorded at T0, the fifth (T1), and T2.

Results: Motivational dimensions, including identified regulation and intrinsic motivation, were significantly greater (all p < 0.001) in the experimental vs. the control group. The students' motor engagement in learning situations, during which the learner, despite a degree of difficulty performs the motor activity with sufficient success, increased only in the experimental group ( p < 0.001). The waiting time in the experimental group decreased significantly at T1 and T2 vs. T0 (all p < 0.001), with lower values recorded in the experimental vs. the control group at the three-time points (all p < 0.001).

Conclusions: The problem-solving method is an efficient strategy for motor skills and performance enhancement, as well as motivation development during physical education courses.

1. Introduction

The education of children is a sensitive and poignant subject, where the wellbeing of the child in the school environment is a key issue ( Ergül and Kargin, 2014 ). For this, numerous research has sought to find solutions to the problems of the traditional method, which focuses on the teacher as an instructor, giver of knowledge, arbiter of truth, and ultimate evaluator of learning ( Ergül and Kargin, 2014 ; Cunningham and Sood, 2018 ). From this perspective, a teachers' job is to present students with a designated body of knowledge in a predetermined order ( Arvind and Kusum, 2017 ). For them, learners are seen as people with “knowledge gaps” that need to be filled with information. In this method, teaching is conceived as the act of transmitting knowledge from point A (responsible for the teacher) to point B (responsible for the students; Arvind and Kusum, 2017 ). According to Novak (2010) , in the traditional method, the teacher is the one who provokes the learning.

The traditional method focuses on lecture-based teaching as the center of instruction, emphasizing delivery of program and concept ( Johnson, 2010 ; Ilkiw et al., 2017 ; Dickinson et al., 2018 ). The student listens and takes notes, passively accepts and receives from the teacher undifferentiated and identical knowledge ( Bi et al., 2019 ). Course content and delivery are considered most important, and learners acquire knowledge through exercise and practice ( Johnson et al., 1998 ). In the traditional method, academic achievement is seen as the ability of students to demonstrate, replicate, or convey this designated body of knowledge to the teacher. It is based on a transmissive model, the teacher contenting themselves with exchanging and transmitting information to the learner. Here, only the “knowledge” and “teacher” poles of the pedagogical triangle are solicited. The teacher teaches the students, who play the role of the spectator. They receive information without participating in its creation ( Perrenoud, 2003 ). For this, researchers invented a new student-centered method with effects on improving students' graphic interpretation skills and conceptual understanding of kinematic motion represent an area of contemporary interest ( Tebabal and Kahssay, 2011 ). Indeed, in order to facilitate the process of knowledge transfer, teachers should use appropriate methods targeted to specific objectives of the school curricula.

For instance, it has been emphasized that the effectiveness of any educational process as a whole relies on the crucial role of using a well-designed pedagogical (teaching and/or learning) strategy ( Kolesnikova, 2016 ).

Alternate to a traditional method of teaching, Ergül and Kargin (2014 ), proposed the problem-solving method, which represents one of the most common student-centered learning strategies. Indeed, this method allows students to participate in the learning environment, giving them the responsibility for their own acquisition of knowledge, as well as the opportunity for the understanding and structuring of diverse information.

For Cunningham and Sood (2018) , the problem-solving method may be considered a fundamental tool for the acquisition of new knowledge, notably learning transfer. Moreover, the problem-solving method is purportedly efficient for the development of manual skills and experiential learning ( Ergül and Kargin, 2014 ), as well as the optimization of thinking ability. Additionally, the problem-solving method allows learners to participate in the learning environment, while giving them responsibility for their learning and making them understand and structure the information ( Pohan et al., 2020 ). In this context, Ali (2019) reported that, when faced with an obstacle, the student will have to invoke his/her knowledge and use his/her abilities to “break the deadlock.” He/she will therefore make the most of his/her potential, but also share and exchange with his/her colleagues ( Ali, 2019 ). Throughout the process, the student will learn new concepts and skills. The role of the teacher is paramount at the beginning of the activity, since activities will be created based on problematic situations according to the subject and the program. However, on the day of the activity, it does not have the main role, and the teacher will guide learners in difficulty and will allow them to manage themselves most of the time ( Ali, 2019 ).

The problem-solving method encourages group discussion and teamwork ( Fidan and Tuncel, 2019 ). Additionally, in this pedagogical approach, the role of the teacher is a facilitator of learning, and they take on a much more interactive and less rebarbative role ( Garrett, 2008 ).

For the teaching method to be effective, teaching should consist of an ongoing process of making desirable changes among learners using appropriate methods ( Ayeni, 2011 ; Norboev, 2021 ). To bring about positive changes in students, the methods used by teachers should be the best for the subject to be taught ( Adunola et al., 2012 ). Further, suggests that teaching methods work effectively, especially if they meet the needs of learners since each learner interprets and answers questions in a unique way. Improving problem-solving skills is a primary educational goal, as is the ability to use reasoning. To acquire this skill, students must solve problems to learn mathematics and problem-solving ( Hu, 2010 ); this encourages the students to actively participate and contribute to the activities suggested by the teacher. Without sufficient motivation, learning goals can no longer be optimally achieved, although learners may have exceptional abilities. The method of teaching employed by the teachers is decisive to achieve motivational consequences in physical education students ( Leo et al., 2022 ). Pérez-Jorge et al. (2021 ) posited that given we now live in a technological society in which children are used to receiving a large amount of stimuli, gaining and maintaining their attention and keeping them motivated at school becomes a challenge for teachers.

Fenouillet (2012) stated that academic motivation is linked to resources and methods that improve attention for school learning. Furthermore, Rolland (2009) and Bessa et al. (2021) reported a link between a learner's motivational dynamics and classroom activities. The models of learning situations, where the student is the main actor, directly refers to active teaching methods, and that there is a strong link between motivation and active teaching ( Rossa et al., 2021 ). In the same context, previous reports assert that the motivation of students in physical education is an important factor since the intra-individual motivation toward this discipline is recognized as a major determinant of physical activity for students ( Standage et al., 2012 ; Luo, 2019 ; Leo et al., 2022 ). Further, extensive research on the effectiveness of teaching methods shows that the quality of teaching often influences the performance of learners ( Norboev, 2021 ). Ayeni (2011) reported that education is a process that allows students to make changes desirable to achieve specific results. Thus, the consistency of teaching methods with student needs and learning influences student achievement. This has led several researchers to explore the impact of different teaching strategies, ranging from traditional methods to active learning techniques that can be used such as the problem-solving method ( Skinner, 1985 ; Darling-Hammond et al., 2020 ).

In the context of innovation, Blázquez (2016 ) emphasizes the importance of adopting active methods and implementing them as the main element promoting the development of skills, motivation and active participation. Pedagogical models are part of the active methods which, together with model-based practice, replace traditional teaching ( Hastie and Casey, 2014 ; Casey et al., 2021 ). Thus, many studies have identified pedagogical models as the most effective way to place students at the center of the teaching-learning process ( Metzler, 2017 ), making it possible to assess the impact of physical education on learning students ( Casey, 2014 ; Rivera-Pérez et al., 2020 ; Manninen and Campbell, 2021 ). Since each model is designed to focus on a specific program objective, each model has limitations when implemented in isolation ( Bunker and Thorpe, 1982 ; Rivera-Pérez et al., 2020 ). Therefore, focusing on developing students' social and emotional skills and capacities could help them avoid failure in physical education ( Ang and Penney, 2013 ). Thus, the current emergence of new pedagogical models goes with their hybridization with different methods, which is a wave of combinations proposed today as an innovative pedagogical strategy. The incorporation of this type of method in the current education system is becoming increasingly important because it gives students a greater role, participation, autonomy and self-regulation, and above all it improves their motivation ( Puigarnau et al., 2016 ). The teaching model of personal and social responsibility, for example, is closely related to the sports education model because both share certain approaches to responsibility ( Siedentop et al., 2011 ). One of the first studies to use these two models together was Rugby ( Gordon and Doyle, 2015 ), which found significant improvements in student behavior. Also, the recent study by Menendez and Fernandez-Rio (2017) on educational kickboxing.

Previous studies have indicated that hybridization can increase play, problem solving performance and motor skills ( Menendez and Fernandez-Rio, 2017 ; Ward et al., 2021 ) and generate positive psychosocial consequences, such as pleasure, intention to be physically active and responsibility ( Dyson and Grineski, 2001 ; Menendez and Fernandez-Rio, 2017 ).

But despite all these research results, the picture remains unclear, and it remains unknown which method is more effective in improving students' learning and motivation. Given the lack of published evidence on this topic, the aim of this study was to compare the effects of problem-solving vs. the traditional method on students' motivation and learning.

We hypothesized would that the problem-solving method would be more effective in improving students' motivation and learning better than the traditional method.

2. Materials and method

2.1. participants.

Fifty-three students, aged 15–16 ( M age 15 ± 0.1 years), in their 1st year of the Tunisian secondary education system, voluntarily participated in this study. All participants were randomly chosen. Repeating students, those who practice handball activity in civil/competitive/amateur clubs or in the high school sports association, and students who were absent, even for one session, were excluded. The first class consisted of 30 students (16 boys and 14 girls), who represented the experimental group and followed basic courses on a learning method by solving problems. The second class consisted of 23 students (10 boys and 13 girls), who represented the control group and followed the traditional teaching method. The total duration was spread over 5 weeks, or two sessions per week and each session lasted 50 min.

University research ethics board approval (CPPSUD: 0295/2021) was obtained before recruiting participants who were subsequently informed of the nature, objective, methodology, and constraints. Teacher, school director, parental/guardian, and child informed consent was obtained prior to participation in the study.

2.2. Procedure

Before the start of the experiment, the participants were familiarized with the equipment and the experimental protocol in order to ensure a good learning climate. For this and to mitigate the impact of the observer and the cameras on the students, the two researchers were involved prior to the data collection in a week of familiarization by making test recordings with the classes concerned.

An approach of a teaching cycle consisting of 10 sessions spread over 5 weeks, amounting to two sessions per week. Physical education classes were held in the morning from 8 a.m. to 9 a.m., with a single goal for each session that lasted 50 min. The cyclic programs were produced by the teacher responsible for carrying out the experiment with 18 years of service. To do this, the students had the same lessons with the same objectives, only pedagogy that differs: the experimental group worked using problem-solving pedagogy, while the control group was confronted with traditional pedagogy. The sessions took place in a handball field 40 m long and 20 m wide. Examples of training sessions using the problem-solving pedagogy and the traditional pedagogy are presented in Table 1 . In addition, a motivation questionnaire, the Situational Motivation Scale (SIMS; Guay et al., 2000 ), was administered to learners at the end of the session (i.e., in the beginning, and end of the cycle). Each student answered the questions alone and according to their own ideas. This questionnaire was taken in a classroom to prevent students from acting abnormally during the study. It lasted for a maximum of 10 min.

Table 1 . Example of activities for the different sessions.

Two diametrically opposed cameras were installed so to film all the movements and behaviors of each student and teacher during the three sessions [(i) test at the start of the cycle (T0), (ii) in the middle of the cycle (T1), and (iii) test at the end of the cycle (T2)]. These sessions had the same content and each consisted of four phases: the getting started, the warm-up, the work up (which consisted of three situations: first, the work was goes up the ball to two to score in the goal following a shot. Second, the same principle as the previous situation but in the presence of a defender. Finally, third, a match 7 ≠ 7), and the cooling down These recordings were analyzed using a Learning Time Analysis System grid (LTAS; Brunelle et al., 1988 ). This made it possible to measure individual learning by coding observable variables of the behavior of learners in a learning situation.

2.3. Data collection and analysis

2.3.1. the motivation questionnaire.

In this study, in order to measure the situational motivation of students, the situational motivation scale (SIMS; Guay et al., 2000 ), which used. This questionnaire assesses intrinsic motivation, identified regulation, external regulation and amotivation. SIMS has demonstrated good reliability and factor validity in the context of physical education in adolescents ( Lonsdale et al., 2011 ). The participants received exact instructions from the researchers in accordance with written instructions on how to conduct the data collection. Participants completed the SIMS anonymously at the start of a physical education class. All students had the opportunity to write down their answers without being observed and to ask questions if anything was unclear. To minimize the tendency to give socially desirable answers, they were asked to answer as honestly as possible, with the confidence that the teacher would not be able to read their answers and that their grades would not be affected by how they responded. The SIMS questionnaire was filled at T0 and T2. This scale is made up of 16 items divided into four dimensions: intrinsic motivation, identified regulation, external regulation and amotivation. Each item is rated on a 7-point Likert scale ranging from 1 (which is the weakest factor) “not at all” to 7 (which is the strongest factor) “exactly matches.”

In order to assess the internal consistency of the scales, a Cronbach alpha test was conducted ( Cronbach, 1951 ). The internal consistency of the scales was acceptable with reliability coefficients ranging from 0.719 to 0.87. The coefficient of reliability was 0.8.

In the present study, Cronbach's alphas were: intrinsic motivation = 0.790; regulation identified = 0.870; external regulation = 0.749; and amotivation = 0.719.

2.3.2. Camcorders

The audio-visual data collection was conducted using two Sony camcorders (Model; Handcam 4K) with a wireless microphone with a DJ transmitter-receiver (VHF 10HL F4 Micro HF) with a range of 80 m ( Maddeh et al., 2020 ). The collection took place over a period of 5 weeks, with three captures for each class (three sessions of 50 min for each at T0, T1, and T2). Two researchers were trained in the procedures and video capture techniques. The cameras were positioned diagonally, in order to film all the behavior of the students and teacher on the set.

2.3.3. The Learning Time Analysis System (LTAS)

To measure the degree of student learning, the analysis of videos recorded using the LTAS grid by Brunelle et al. (1988) was used, at T0, T1, and T2. This observation system with predetermined categories uses the technique of observation by small intervals (i.e., 6 s) and allows to measure individual learning by coding observable variables of their behaviors when they have been in a learning situation. This grid also permits the specification of the quantity and quality with which the participants engaged in the requested work and was graded, broadly, on two characteristics: the type of situation offered to the group by the teacher and the behavior of the target participant. The situation offered to the group was subdivided into three parts: preparatory situations; knowledge development situations, and motor development situations.

The observations and coding of behaviors are carried out “at intervals.” This technique is used extensively in research on behavior analysis. The coder observes the teaching situation and a particular student during each interval ( Brunelle et al., 1988 ). It then makes a decision concerning the characteristic of the observed behavior. The 6-s observation interval is followed by a coding interval of 6 s too. A cassette tape recorder is used to regulate the observation and recording intervals. It is recorded for this purpose with the indices “observe” and “code” at the start of each 6-s period. During each coding unit, the observer answered the following questions: What is the type of situation in which the class group finds itself? If the class group is in a learning situation proper, in what form of commitment does the observed student find himself? The abbreviations representing the various categories of behavior have been entered in the spaces which correspond to them. The coder was asked to enter a hyphen instead of the abbreviation when the same categories of behavior follow one another in consecutive intervals ( Brunelle et al., 1988 ).

During the preparatory period, the following behaviors were identified and analyzed:

- Deviant behavior: The student adopts a behavior incompatible with a listening attitude or with the smooth running of the preparatory situations.

- Waiting time: The student is waiting without listening or observing.

- Organized during: The student is involved in a complementary activity that does not represent a contribution to learning (e.g., regaining his place in a line, fetching a ball that has just left the field, replacing a piece of equipment).

During the motor development situations, the following behaviors were identified and analyzed:

- Motor engagement 1: The participant performs the motor activity with such easy that it can be inferred that their actions have little chance to engage in a learning process.

- Motor engagement 2: The participant-despite a certain degree of difficulty, performs the motor activity with sufficient success, which makes it possible to infer that they are in the process of learning.

- Motor engagement 3: The participant performs the motor activity with such difficulty that their efforts have very little chance of being part of a learning process.

2.4. Statistical analysis

Statistical tests were performed using statistical software 26.0 for windows (SPSS, Inc, Chicago, IL, USA). Data are presented in text and tables as means ± standard deviations and in figures as means and standard errors. Once the normal distribution of data was confirmed by the Shapiro-Wilk W -test, parametric tests were performed. Analysis of the results was performed using a mixed 2-way analysis of variance (ANOVA): Groups × Time with repeated measures.

For the learning parameters, the ANOVA took the following form: 2 Groups (Control Group vs. Experimental Group) × 3 Times (T0, T1, and T2).

For the dimensions of motivation, the ANOVA took the following form: 2 Groups (Control Group vs. Experimental Group) × 2 Time (T0 vs. T2).

In instances where the ANOVA showed a significant effect, a Bonferroni post-hoc test was applied in order to compare the experimental data in pairs, otherwise by an independent or paired Student's T -test. Effect sizes were calculated as partial eta-squared η p 2 to estimate the meaningfulness of significant findings, where η p 2 values of 0.01, 0.06, and 0.13 represent small, moderate, and large effect sizes, respectively ( Lakens, 2013 ). All observed differences were considered statistically significant for a probability threshold lower than p < 0.05.

Table 2 shows the results of learning variables during the preparatory and the development learning periods at T0, T1, and T2, in the control group and the experimental group.

Table 2 . Comparison of learning variables using two teaching methods in physical education.

The analysis of variance of two factors with repeated measures showed a significant effect of group, learning, and group learning interaction for the deviant behavior. The post-hoc test revealed significantly less frequent deviant behaviors in the experimental than in the control group at T0, T1, and T2 (all p < 0.001). Additionally, the deviant behavior decreased significantly at T1 and T2 compared to T0 for both groups (all p < 0.001).

For appropriate engagement, there were no significant group effect, a significant learning effect, and a significant group learning interaction effect. The post-hoc test revealed that compared to T0, Appropriate engagement recorded at T1 and T2 increased significantly ( p = 0.032; p = 0.031, respectively) in the experimental group, whilst it decreased significantly in the control group ( p < 0.001). Additionally, Appropriate engagement was higher in the experimental vs. control group at T1 and T2 (all p < 0.001).

For waiting time, a significant interaction in terms of group effect, learning, and group learning was found. The post-hoc test revealed that waiting time was higher at T1 and T2 vs. T0 (all p < 0.001) in the control group. In addition, waiting time in the experimental group decreased significantly at T1 and T2 vs. T0 (all p < 0.001), with higher values recorded at T2 vs. T1 ( p = 0.025). Additionally, lower values were recorded in the experimental group vs. the control group at the three-time points (all p < 0.001).

For Motor engagement 2, a significant group, learning, and group-learning interaction effect was noted. The post-hoc test revealed that Motor engagement 2 increased significantly in both groups at T1 ( p < 0.0001) and T2 ( p < 0.0001) vs. T0 ( p = 0.045), with significantly higher values recorded in the experimental group at T1 and T2.

Regarding Motor engagement 3, a non-significant group effect was reported. Contrariwise, a significant learning effect and group learning interaction was reported ( Table 1 ). The post-hoc test revealed a significant decrease in the control group and the experimental group at T1 ( p = 0.294) at T2 ( p = 0.294) vs. T0 ( p = 0.0543). In addition, a non-significant difference between the two groups was found.

A significant group and learning effect was noted for the organized during, and a non-significant group learning interaction. For organized during, the paired Student T -test showed a significant decrease in the control group and the experimental group (all p < 0.001). The independent Student T -test revealed a non-significant difference between groups at the three-time points.

Results of the motivational dimensions in the control group and the experimental group recorded at T0 and T2 are presented in Table 3 .

Table 3 . Comparison of the four motivational dimensions in two teaching methods in physical education.

For intrinsic motivation, a significant group effect and group learning interaction and also a non-significant learning effect was found. The post-hoc test indicated that the intrinsic motivation decreased significantly in the control group ( p = 0.029), whilst it increased in the experimental group ( p = 0.04). Additionally, the intrinsic motivation of the experimental group was higher at T0 ( p = 0.026) and T2 ( p < 0.001) compared to that of the control group.

For the identified regulation, a significant group effect, a non-significant learning effect and group learning interaction were reported. The paired Student's T -test revealed that from T0 to T1, the identified motivation increased significantly only in the experimental group ( p = 0.022), while it remained unchanged in the control group. The independent Student's T -test revealed that the identified regulation recorded in the experimental group at T0 ( p = 0.012) and T2 ( p < 0.001) was higher compared to that of the control group.

The external regulation presents a significant group effect. In addition, a non-significant learning effect and group learning interaction were reported. The paired Student's T -test showed that the external regulation decreased significantly in the experimental group ( p = 0.038), whereas it remained unchanged in the control group. Further, the independent Student's T -test revealed that the external regulation recorded at T2 was higher in the control group vs. the experimental group ( p < 0.001).

Relating to amotivation, results showed a significant group effect. Furthermore, a non-significant learning effect and group learning interaction were reported. The paired Student's T -test showed that, from T0 to T2, amotivation decreased significantly in the experimental group ( p = 0.011) and did not change in the control group. The independent Student T -test revealed that amotivation recorded at T2 was lower in the experimental compared to the control group ( p = 0.002).

4. Discussion

The main purpose of this study was to compare the effects of the problem-solving vs. traditional method on motivation and learning during physical education courses. The results revealed that the problem-solving method is more effective than the traditional method in increasing students' motivation and improving their learning. Moreover, the results showed that mean wait times and deviant behaviors decreased using the problem-solving method. Interestingly, the average time spent on appropriate engagement increased using the problem-solving method compared to the traditional method. When using the traditional method, the average wait times increased and, as a result, the time spent on appropriate engagement decreased. Then, following the decrease in deviant behaviors and waiting times, an increase in the time spent warming up was evident (i.e., appropriate engagement). Indeed, there was an improvement in engagement time using the problem-solving method and a decrease using the traditional method. On the other hand, there was a decrease in motor engagement 3 in favor of motor engagement 2. Indeed, it has been shown that the problem-solving method has been used in the learning process and allows for its improvement ( Docktor et al., 2015 ). In addition, it could also produce better quality solutions and has higher scores on conceptual and problem-solving measures. It is also a good method for the learning process to enhance students' academic performance ( Docktor et al., 2015 ; Ali, 2019 ). In contrast, the traditional method limits the ability of teachers to reach and engage all students ( Cook and Artino, 2016 ). Furthermore, it produces passive learning with an understanding of basic knowledge which is characterized by its weakness ( Goldstein, 2016 ). Taken together, it appears that the problem-solving method promotes and improves learning more than the traditional method.

It should be acknowledged that other factors, such as motivation, could influence learning. In this context, our results showed that the method of problem-solving could improve the motivation of the learners. This motivation includes several variables that change depending on the situation, namely the intrinsic motivation that pushes the learner to engage in an activity for the interest and pleasure linked to the practice of the latter ( Komarraju et al., 2009 ; Guiffrida et al., 2013 ; Chedru, 2015 ). The student, therefore, likes to learn through problem-solving and neglects that of the traditional method. These results are concordant with others ( Deci and Ryan, 1985 ; Chedru, 2015 ; Ryan and Deci, 2020 ). Regarding the three forms of extrinsic motivation: first, extrinsic motivation by an identified regulation which manifests itself in a high degree of self-determination where the learner engages in the activity because it is important for him ( Deci and Ryan, 1985 ; Chedru, 2015 ). This explains the significant difference between the two groups. Then, the motivation by external regulation which is characterized by a low degree of self-determination such as the behavior of the learner is manipulated by external circumstances such as obtaining rewards or the removal of sanctions ( Deci and Ryan, 1985 ; Chedru, 2015 ). For this, the means of this variable decreased for the experimental group which is intrinsically motivated. He does not need any reward to work and is not afraid of punishment because he is self-confident. Third, amotivation is at the opposite end of the self-determination continuum. Unmotivated students are the most likely to feel negative emotions ( Ratelle et al., 2007 ; David, 2010 ), to have low self-esteem ( Deci and Ryan, 1995 ), and who attempts to abandon their studies ( Vallerand et al., 1997 ; Blanchard et al., 2005 ). So, more students are motivated by external regulation or demotivated, less interest they show and less effort they make, and more likely they are to fail ( Grolnick et al., 1991 ; Miserandino, 1996 ; Guay et al., 2000 ; Blanchard et al., 2005 ).

It is worth noting that there is a close link between motivation and learning ( Bessa et al., 2021 ; Rossa et al., 2021 ). Indeed, when the learner's motivation is high, so will his learning. However, all this depends on the method used ( Norboev, 2021 ). For example, the method of problem-solving increase motivation more than the traditional method, as evidenced by several researchers ( Parish and Treasure, 2003 ; Artino and Stephens, 2009 ; Kim and Frick, 2011 ; Lemos and Veríssimo, 2014 ).

Given the effectiveness of the problem-solving method in improving students' learning and motivation, it should be used during physical education teaching. This could be achieved through the organization of comprehensive training programs, seminars, and workshops for teachers so to master and subsequently be able to use the problem-solving method during physical education lessons.

Despite its novelty, the present study suffers from a few limitations that should be acknowledged. First, a future study, consisting of a group taught using the mixed method would preferable so to better elucidate the true impact of this teaching and learning method. Second, no gender and/or age group comparisons were performed. This issue should be addressed in future investigations. Finally, the number of participants is limited. This may be due to working in a secondary school where the number of students in a class is limited to 30 students. Additionally, the number of participants fell to 53 after excluding certain students (exempted, absent for a session, exercising in civil clubs or member of the school association). Therefore, to account for classes of finite size, a cluster-based trial would be beneficial in the future. Moreover, future studies investigating the effect of the active method in reducing some behaviors (e.g., disruptive behaviors) and for the improvement of pupils' attention are warranted.

5. Conclusion

There was an improvement in student learning in favor of the problem-solving method. Additionally, we found that the motivation of learners who were taught using the problem-solving method was better than that of learners who were educated by the traditional method.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

University Research Ethics Board approval was obtained before recruiting participants who were subsequently informed of the nature, objective, methodology, and constraints. Teacher, school director, parental/guardian, and child informed consent was obtained prior to participation in the study. In addition, exclusion criteria included; the practice of handball activity in civil/competitive/amateur clubs or in the high school sports association. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Acknowledgments

Special thanks for all students and physical education teaching staff from the 15 November 1955 Secondary School, who generously shared their time, experience, and materials for the proposes of this study.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer MJ declared a shared affiliation, with no collaboration, with the authors GE, NS, LM, and KT to the handling editor at the time of review.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Adunola, O., Ed, B., and Adeniran, A. (2012). The Impact of Teachers' Teaching Methods on the Academic Performance of Primary School Pupils . Ogun: Ego Booster Books.

Google Scholar

Ali, S. S. (2019). Problem based learning: A student-centered approach. Engl. Lang. Teach . 12, 73. doi: 10.5539/elt.v12n5p73

CrossRef Full Text | Google Scholar

Ang, S. C., and Penney, D. (2013). Promoting social and emotional learning outcomes in physical education: Insights from a school-based research project in Singapore. Asia-Pac. J. Health Sport Phys. Educ . 4, 267–286. doi: 10.1080/18377122.2013.836768

Artino, A. R., and Stephens, J. M. (2009). Academic motivation and self-regulation: A comparative analysis of undergraduate and graduate students learning online. Internet. High. Educ. 12, 146–151. doi: 10.1016/j.iheduc.2009.02.001

Arvind, K., and Kusum, G. (2017). Teaching approaches, methods and strategy. Sch. Res. J. Interdiscip. Stud. 4, 6692–6697. doi: 10.21922/srjis.v4i36.10014

Ayeni, A. J. (2011). Teachers' professional development and quality assurance in Nigerian secondary schools. World J. Educ. 1, 143. doi: 10.5430/wje.v1n2p143

Bessa, C., Hastie, P., Rosado, A., and Mesquita, I. (2021). Sport education and traditional teaching: Influence on students' empowerment and self-confidence in high school physical education classes. Sustainability 13, 578. doi: 10.3390/su13020578

Bi, M., Zhao, Z., Yang, J., and Wang, Y. (2019). Comparison of case-based learning and traditional method in teaching postgraduate students of medical oncology. Med. Teach . 4, 1124–1128. doi: 10.1080/0142159X.2019.1617414

PubMed Abstract | CrossRef Full Text | Google Scholar

Blanchard, C., Pelletier, L., Otis, N., and Sharp, E. (2005). Role of self-determination and academic ability in predicting school absences and intention to drop out. J. Educ. Sci. 30, 105–123. doi: 10.7202/011772ar

Blázquez, D. (2016).Métodos de enseñanza en Educación Física. Enfoques innovadores para la enseñanza de competencias . Barcelona: Inde Publisher.

Brunelle, J., Drouin, D., Godbout, P., and Tousignant, M. (1988). Supervision of physical activity intervention. Montreal, Canada: G. Morin, Dl. Open J. Soc. Sci. 8.

Bunker, D., and Thorpe, R. (1982). A model for the teaching of games in secondary schools. Bull. Phys. Educ . 18, 5–8.

Casey, A. (2014). Models-based practice: Great white hope or white elephant? Phys. Educ. Sport Pedagog. 19, 18–34. doi: 10.1080/17408989.2012.726977

Casey, A., MacPhail, A., Larsson, H., and Quennerstedt, M. (2021). Between hope and happening: Problematizing the M and the P in models-based practice. Phys. Educ. Sport Pedagog. 26, 111–122. doi: 10.1080/17408989.2020.1789576

Chedru, M. (2015). Impact of motivation and learning styles on the academic performance of engineering students. J. Educ. Sci. 41, 457–482. doi: 10.7202/1035313ar

Cook, D. A., and Artino, A. R. (2016). Motivation to learn: An overview of contemporary theories. J. Med. Educ . 50, 997–1014. doi: 10.1111/medu.13074

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika. J. 16, 297–334. doi: 10.1007/BF02310555

Cunningham, J., and Sood, K. (2018). How effective are working memory training interventions at improving maths in schools: a study into the efficacy of working memory training in children aged 9 and 10 in a junior school?. Education 46, 174–187. doi: 10.1080/03004279.2016.1210192

Darling-Hammond, L., Flook, L., Cook-Harvey, C., Barron, B., and Osher, D. (2020). Implications for educational practice of the science of learning and development. Appl. Dev. Sci. 24, 97–140. doi: 10.1080/10888691.2018.1537791

David, A. (2010). Examining the relationship of personality and burnout in college students: The role of academic motivation. E. M. E. Rev. 1, 90–104.

Deci, E., and Ryan, R. (1985). Intrinsic motivation and self-determination in human behavior. Perspect. Soc. Psychol . 2271, 7. doi: 10.1007/978-1-4899-2271-7

Deci, E. L., and Ryan, R. M. (1995). “Human autonomy,” in Efficacy, Agency, and Self-Esteem (Boston, MA: Springer).

Dickinson, B. L., Lackey, W., Sheakley, M., Miller, L., Jevert, S., and Shattuck, B. (2018). Involving a real patient in the design and implementation of case-based learning to engage learners. Adv. Physiol. Educ. 42, 118–122. doi: 10.1152/advan.00174.2017

Docktor, J. L., Strand, N. E., Mestre, J. P., and Ross, B. H. (2015). Conceptual problem solving in high school. Phys. Rev. ST Phys. Educ. Res. 11, 20106. doi: 10.1103/PhysRevSTPER.11.020106

Dyson, B., and Grineski, S. (2001). Using cooperative learning structures in physical education. J. Phys. Educ. Recreat. Dance. 72, 28–31. doi: 10.1080/07303084.2001.10605831

Ergül, N. R., and Kargin, E. K. (2014). The effect of project based learning on students' science success. Procedia. Soc. Behav. Sci. 136, 537–541. doi: 10.1016/j.sbspro.2014.05.371

Fenouillet, F. (2012). Les théories de la motivation . Psycho Sup : Dunod.

Fidan, M., and Tuncel, M. (2019). Integrating augmented reality into problem based learning: The effects on learning achievement and attitude in physics education. Comput. Educ .142, 103635. doi: 10.1016/j.compedu.2019.103635

Garrett, T. (2008). Student-centered and teacher-centered classroom management: A case study of three elementary teachers. J. Classr. Interact. 43, 34–47.

Goldstein, O. A. (2016). Project-based learning approach to teaching physics for pre-service elementary school teacher education students. Bevins S, éditeur. Cogent. Educ. 3, 1200833. doi: 10.1080/2331186X.2016.1200833

Gordon, B., and Doyle, S. (2015). Teaching personal and social responsibility and transfer of learning: Opportunities and challenges for teachers and coaches. J. Teach. Phys. Educ. 34, 152–161. doi: 10.1123/jtpe.2013-0184

Grolnick, W. S., Ryan, R. M., and Deci, E. L. (1991). Inner resources for school achievement: Motivational mediators of children's perceptions of their parents. J. Educ. Psychol . 83, 508–517. doi: 10.1037/0022-0663.83.4.508

Guay, F., Vallerand, R. J., and Blanchard, C. (2000). On the assessment of situational intrinsic and extrinsic motivation: The Situational Motivation Scale (SIMS). Motiv. Emot . 24, 175–213. doi: 10.1023/A:1005614228250

Guiffrida, D., Lynch, M., Wall, A., and Abel, D. (2013). Do reasons for attending college affect academic outcomes? A test of a motivational model from a self-determination theory perspective. J. Coll. Stud. Dev. 54, 121–139. doi: 10.1353/csd.2013.0019

Hastie, P. A., and Casey, A. (2014). Fidelity in models-based practice research in sport pedagogy: A guide for future investigations. J. Teach. Phys. Educ . 33, 422–431. doi: 10.1123/jtpe.2013-0141

Hu, W. (2010). Creative scientific problem finding and its developmental trend. Creat. Res. J. 22, 46–52. doi: 10.1080/10400410903579551

Ilkiw, J. E., Nelson, R. W., Watson, J. L., Conley, A. J., Raybould, H. E., Chigerwe, M., et al. (2017). Curricular revision and reform: The process, what was important, and lessons learned. J. Vet. Med. Educ . 44, 480–489. doi: 10.3138/jvme.0316-068R

Johnson, A. P. (2010). Making Connections in Elementary and Middle School Social Studies. 2nd Edn. London: SAGE.

Johnson, D. W., Johnson, R. T., and Smith, K. A. (1998). Active Learning: Cooperation in the College Classroom. 2nd Edn. Edina, MN: Interaction Press.

Kim, K. J., and Frick, T. (2011). Changes in student motivation during online learning. J. Educ. Comput. 44, 23. doi: 10.2190/EC.44.1.a

Kolesnikova, I. (2016). Combined teaching method: An experimental study. World J. Educ. 6, 51–59. doi: 10.5430/wje.v6n6p51

Komarraju, M., Karau, S. J., and Schmeck, R. R. (2009). Role of the Big Five personality traits in predicting college students' academic motivation and achievement. Learn. Individ. Differ. 19, 47–52. doi: 10.1016/j.lindif.2008.07.001

Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t -tests and ANOVAs. Front. Psychol . 4, 863. doi: 10.3389/fpsyg.2013.00863

Lemos, M. S., and Veríssimo, L. (2014). The relationships between intrinsic motivation, extrinsic motivation, and achievement, along elementary school. Procedia. Soc. Behav. Sci . 112, 930–938. doi: 10.1016/j.sbspro.2014.01.1251

Leo, M. F., Mouratidis, A., Pulido, J. J., López-Gajardo, M. A., and Sánchez-Oliva, D. (2022). Perceived teachers' behavior and students' engagement in physical education: the mediating role of basic psychological needs and self-determined motivation. Phys. Educ. Sport Pedagogy. 27, 59–76. doi: 10.1080/17408989.2020.1850667

Lonsdale, C., Sabiston, C., Taylor, I., and Ntoumanis, N. (2011). Measuring student motivation for physical education: Examining the psychometric properties of the Perceived Locus of Causality Questionnaire and the Situational Motivation Scale. Psychol. Sport. Exerc . 12, 284–292. doi: 10.1016/j.psychsport.2010.11.003

Luo, Y. J. (2019). The influence of problem-based learning on learning effectiveness in students' of varying learning abilities within physical education. Innov. Educ. Teach. Int. 56, 3–13. doi: 10.1080/14703297.2017.1389288

Maddeh, T., Amamou, S., Desbiens, J., and françois Souissi, N. (2020). The management of disruptive behavior of secondary school students by Tunisian trainee teachers in physical education: Effects of a training program in the prevention and management of indiscipline. J. Educ. Fac . 4, 323–344. doi: 10.34056/aujef.674931

Manninen, M., and Campbell, S. (2021). The effect of the sport education model on basic needs, intrinsic motivation and prosocial attitudes: A systematic review and multilevel meta-Analysis. Eur. Phys. Educ. Rev . 28, 76–99. doi: 10.1177/1356336X211017938

Menendez, J. I., and Fernandez-Rio, J. (2017). Hybridising sport education and teaching for personal and social responsibility to include students with disabilities. Eur. J. Spec. Needs Educ. 32, 508–524 doi: 10.1080/08856257.2016.1267943

Metzler, M. (2017). Instructional Models in Physical Education . London: Routledge.

Miserandino, M. (1996). Children who do well in school: Individual differences in perceived competence and autonomy in above-average children. J. Educ. Psychol . 88, 203–214. doi: 10.1037/0022-0663.88.2.203

Norboev, N. N. (2021). Theoretical aspects of the influence of motivation on increasing the efficiency of physical education. Curr. Res. J. Pedagog . 2, 247–252. doi: 10.37547/pedagogics-crjp-02-10-44

Novak, D. J. (2010). Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations. J. E-Learn. Knowl. Soc . 6, 21–30. doi: 10.20368/1971-8829/441

Parish, L. E., and Treasure, D. C. (2003). Physical activity and situational motivation in physical education: Influence of the motivational climate and perceived ability. Res. Q. Exerc. Sport. 74, 173. doi: 10.1080/02701367.2003.10609079

Pérez-Jorge, D., González-Dorta, D., Del Carmen Rodríguez-Jiménez, D., and Fariña-Hernández, L. (2021). Problem-solving teacher training, the effect of the ProyectaMates Programme in Tenerife. International Educ . 49, 777–7791. doi: 10.1080/03004279.2020.1786427

Perrenoud, P. (2003). Qu'est-ce qu'apprendre. Enfances Psy . 4, 9–17. doi: 10.3917/ep.024.0009

Pohan, A., Asmin, A., and Menanti, A. (2020). The effect of problem based learning and learning motivation of mathematical problem solving skills of class 5 students at SDN 0407 Mondang. BirLE . 3, 531–539. doi: 10.33258/birle.v3i1.850

Puigarnau, S., Camerino, O., Castañer, M., Prat, Q., and Anguera, M. T. (2016). El apoyo a la autonomía en practicantes de centros deportivos y de fitness para aumentar su motivación. Rev. Int. de Cienc. del deporte. 43, 48–64. doi: 10.5232/ricyde2016.04303

Ratelle, C. F., Guay, F., Vallerand, R. J., Larose, S., and Senécal, C. (2007). Autonomous, controlled, and amotivated types of academic motivation: A person-oriented analysis. J. Educ. Psychol. 99, 734–746. doi: 10.1037/0022-0663.99.4.734

Rivera-Pérez, S., Fernandez-Rio, J., and Gallego, D. I. (2020). Effects of an 8-week cooperative learning intervention on physical education students' task and self-approach goals, and Emotional Intelligence. Int. J. Environ. Res. Public Health . 18, 61. doi: 10.3390/ijerph18010061

Rolland, V. (2009). Motivation in the School Context . 5th Edn . Belguim: De Boeck Superior, 218.

Rossa, R., Maulidiah, R. H., and Aryni, Y. (2021). The effect of problem solving technique and motivation toward students' writing skills. J. Pena. Edukasi. 8, 43–54. doi: 10.54314/jpe.v8i1.654

Ryan, R., and Deci, E. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemp. Educ. Psychol . 61, 101860. doi: 10.1016/j.cedpsych.2020.101860

Siedentop, D., Hastie, P. A., and Van Der Mars, H. (2011). Complete Guide to Sport Education, 2nd Edn. Champaign, IL: Human Kinetics.

Skinner, B. F. (1985). Cognitive science and behaviourism. Br. J. Psychol. 76, 291–301. doi: 10.1111/j.2044-8295.1985.tb01953.x

Standage, M., Gillison, F. B., Ntoumanis, N., and Treasure, D. C. (2012). Predicting students' physical activity and health-related well-being: a prospective cross-domain investigation of motivation across school physical education and exercise settings. J. Sport. Exerc. Psychol . 34, 37–60. doi: 10.1123/jsep.34.1.37

Tebabal, A., and Kahssay, G. (2011). The effects of student-centered approach in improving students' graphical interpretation skills and conceptual understanding of kinematical motion. Lat. Am. J. Phys. Educ. 5, 9.

Vallerand, R. J., Fbrtier, M. S., and Guay, F. (1997). Self-determination and persistence in a real-life setting toward a motivational model of high school dropout. J. Pers. Soc. Psychol. 2, 1161–1176. doi: 10.1037/0022-3514.72.5.1161

Ward, P., Mitchell, M. F., van der Mars, H., and Lawson, H. A. (2021). Chapter 3: PK+12 School physical education: conditions, lessons learned, and future directions. J. Teach. Phys. Educ. 40, 363–371. doi: 10.1123/jtpe.2020-0241

Keywords: problem-solving method, traditional method, motivation, learning, students

Citation: Ezeddine G, Souissi N, Masmoudi L, Trabelsi K, Puce L, Clark CCT, Bragazzi NL and Mrayah M (2023) The problem-solving method: Efficacy for learning and motivation in the field of physical education. Front. Psychol. 13:1041252. doi: 10.3389/fpsyg.2022.1041252

Received: 10 September 2022; Accepted: 15 December 2022; Published: 25 January 2023.

Reviewed by:

Copyright © 2023 Ezeddine, Souissi, Masmoudi, Trabelsi, Puce, Clark, Bragazzi and Mrayah. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Teaching Problem-Solving Skills

Many instructors design opportunities for students to solve “problems”. But are their students solving true problems or merely participating in practice exercises? The former stresses critical thinking and decision­ making skills whereas the latter requires only the application of previously learned procedures.

Problem solving is often broadly defined as "the ability to understand the environment, identify complex problems, review related information to develop, evaluate strategies and implement solutions to build the desired outcome" (Fissore, C. et al, 2021). True problem solving is the process of applying a method – not known in advance – to a problem that is subject to a specific set of conditions and that the problem solver has not seen before, in order to obtain a satisfactory solution.

Below you will find some basic principles for teaching problem solving and one model to implement in your classroom teaching.

Principles for teaching problem solving

• Model a useful problem-solving method . Problem solving can be difficult and sometimes tedious. Show students how to be patient and persistent, and how to follow a structured method, such as Woods’ model described below. Articulate your method as you use it so students see the connections.
• Teach within a specific context . Teach problem-solving skills in the context in which they will be used by students (e.g., mole fraction calculations in a chemistry course). Use real-life problems in explanations, examples, and exams. Do not teach problem solving as an independent, abstract skill.
• Help students understand the problem . In order to solve problems, students need to define the end goal. This step is crucial to successful learning of problem-solving skills. If you succeed at helping students answer the questions “what?” and “why?”, finding the answer to “how?” will be easier.
• Take enough time . When planning a lecture/tutorial, budget enough time for: understanding the problem and defining the goal (both individually and as a class); dealing with questions from you and your students; making, finding, and fixing mistakes; and solving entire problems in a single session.
• Ask questions and make suggestions . Ask students to predict “what would happen if …” or explain why something happened. This will help them to develop analytical and deductive thinking skills. Also, ask questions and make suggestions about strategies to encourage students to reflect on the problem-solving strategies that they use.
• Link errors to misconceptions . Use errors as evidence of misconceptions, not carelessness or random guessing. Make an effort to isolate the misconception and correct it, then teach students to do this by themselves. We can all learn from mistakes.

Woods’ problem-solving model

Define the problem.

• The system . Have students identify the system under study (e.g., a metal bridge subject to certain forces) by interpreting the information provided in the problem statement. Drawing a diagram is a great way to do this.
• Known(s) and concepts . List what is known about the problem, and identify the knowledge needed to understand (and eventually) solve it.
• Unknown(s) . Once you have a list of knowns, identifying the unknown(s) becomes simpler. One unknown is generally the answer to the problem, but there may be other unknowns. Be sure that students understand what they are expected to find.
• Units and symbols . One key aspect in problem solving is teaching students how to select, interpret, and use units and symbols. Emphasize the use of units whenever applicable. Develop a habit of using appropriate units and symbols yourself at all times.
• Constraints . All problems have some stated or implied constraints. Teach students to look for the words "only", "must", "neglect", or "assume" to help identify the constraints.
• Criteria for success . Help students consider, from the beginning, what a logical type of answer would be. What characteristics will it possess? For example, a quantitative problem will require an answer in some form of numerical units (e.g., $/kg product, square cm, etc.) while an optimization problem requires an answer in the form of either a numerical maximum or minimum.

Think about it

• “Let it simmer”.  Use this stage to ponder the problem. Ideally, students will develop a mental image of the problem at hand during this stage.
• Identify specific pieces of knowledge . Students need to determine by themselves the required background knowledge from illustrations, examples and problems covered in the course.
• Collect information . Encourage students to collect pertinent information such as conversion factors, constants, and tables needed to solve the problem.

Plan a solution

• Consider possible strategies . Often, the type of solution will be determined by the type of problem. Some common problem-solving strategies are: compute; simplify; use an equation; make a model, diagram, table, or chart; or work backwards.
• Choose the best strategy . Help students to choose the best strategy by reminding them again what they are required to find or calculate.

Carry out the plan

• Be patient . Most problems are not solved quickly or on the first attempt. In other cases, executing the solution may be the easiest step.
• Be persistent . If a plan does not work immediately, do not let students get discouraged. Encourage them to try a different strategy and keep trying.

Encourage students to reflect. Once a solution has been reached, students should ask themselves the following questions:

• Does the answer make sense?
• Does it fit with the criteria established in step 1?
• Did I answer the question(s)?
• What did I learn by doing this?
• Could I have done the problem another way?

If you would like support applying these tips to your own teaching, CTE staff members are here to help.  View the  CTE Support  page to find the most relevant staff member to contact. 

• Fissore, C., Marchisio, M., Roman, F., & Sacchet, M. (2021). Development of problem solving skills with Maple in higher education. In: Corless, R.M., Gerhard, J., Kotsireas, I.S. (eds) Maple in Mathematics Education and Research. MC 2020. Communications in Computer and Information Science, vol 1414. Springer, Cham. https://doi.org/10.1007/978-3-030-81698-8_15
• Foshay, R., & Kirkley, J. (1998). Principles for Teaching Problem Solving. TRO Learning Inc., Edina MN.  (PDF) Principles for Teaching Problem Solving (researchgate.net)
• Hayes, J.R. (1989). The Complete Problem Solver. 2nd Edition. Hillsdale, NJ: Lawrence Erlbaum Associates.
• Woods, D.R., Wright, J.D., Hoffman, T.W., Swartman, R.K., Doig, I.D. (1975). Teaching Problem solving Skills.
• Engineering Education. Vol 1, No. 1. p. 238. Washington, DC: The American Society for Engineering Education.

Catalog search

Teaching tip categories.

• Assessment and feedback
• Blended Learning and Educational Technologies
• Career Development
• Course Design
• Course Implementation
• Inclusive Teaching and Learning
• Learning activities
• Support for Student Learning
• Support for TAs
• Learning activities ,

What is the most effective way to teach problem solving? A commentary on productive failure as a method of teaching

• Published: 04 May 2012
• Volume 40 , pages 731–735, ( 2012 )

Cite this article

• Allan Collins 1 , 2  

1669 Accesses

8 Citations

1 Altmetric

Explore all metrics

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Jacobson, M. J., Thompson, K., Kennedy-Clark, S. & Hu, C. (2011) Failure and success in sequencing of model - based learning activities. Paper presented at the American Educational Research Association Annual Meeting, New Orleans.

Kapur, M. (2008). Productive failure. Cognition and Instruction, 26 (3), 379–424.

Article   Google Scholar  

Kapur, M. (2009). Productive failure in mathematical problem solving. Instructional Science, 38 (6), 523–550.

Kapur, M. (2010). A further study of productive failure in mathematical problem solving: Unpacking the design components. Instructional Science, 39 (4), 561–579.

Kapur, M. (2012). Productive failure in learning the concept of variance. Instructional Science . doi: 10.1007/s11251-012-9209-6 .

Google Scholar  

Kapur, M., & Bielaczyc, K. (2012). Designing for productive failure. Journal of the Learning Sciences, 21 (1), 45–83.

Koedinger, K. R., Aleven, V., Roll, I., & Baker, R. S. J. D. (2009). In vivo experiments on whether supporting metacognition in intelligent tutoring systems yields robust learning. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 383–412). New York: Routledge.

Roll, I., Holmes, N. G., Day, J., & Bonn, D. (2012). Evaluating metacognitive scaffolding in guided invention activities. Instructional Science . doi: 10.1007/s11251-012-9208-7 .

Salden, R. J. C. M., Koedinger, K. R., Renkl, A., Aleven, V., & McLaren, B. M. (2010). Accounting for beneficial effects of worked examples in tutored problem solving. Educational Psychology Review, 22 (4), 379–392.

Schoenfeld, A. J. (1985). Mathematical problem solving . New York: Academic Press.

Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition and Instruction, 16 (4), 475–522.

Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for future learning: The hidden efficiency of encouraging original student production in statistics instruction. Cognition and Instruction, 22 (2), 129–184.

Stigler, J. & Hiebert, J. (2009) The teaching gap: Best ideas from the world’s teachers for improving education in the classroom (paperback edition) . New York: Free Press.

Vygotsky, L. S. (1978). Mind in society. In M. Cole, V. John-Steiner, S. Scribner & E. Souberman (Eds.), The development of higher psychological processes. Cambridge: Harvard University Press.

Westermann, K., & Rummel, N. (2012). Delaying instruction: evidence from a study in a university relearning setting. Instructional Science . doi: 10.1007/s11251-012-9207-8 .

White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition and Instruction, 16 (1), 3–118.

Wiedmann, M., Leach, R. C., Rummel, N., & Wiley, J. (2012). Does group composition affect learning by invention? Instructional Science . doi: 10.1007/s11251-012-9204-y .

Download references

Author information

Authors and affiliations.

School of Education and Social Policy, Northwestern University, Evanston, IL, 60208, USA

Allan Collins

135 Cedar St., Lexington, MA, 02421, USA

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Allan Collins .

Rights and permissions

Reprints and permissions

About this article

Collins, A. What is the most effective way to teach problem solving? A commentary on productive failure as a method of teaching. Instr Sci 40 , 731–735 (2012). https://doi.org/10.1007/s11251-012-9234-5

Download citation

Received : 05 April 2012

Accepted : 10 April 2012

Published : 04 May 2012

Issue Date : July 2012

DOI : https://doi.org/10.1007/s11251-012-9234-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Generation Phase
• Direct Instruction
• Productive Failure
• Invention Phase
• Canonical Solution
• Find a journal
• Publish with us
• Track your research

Center for Teaching Innovation

Resource library.

• Establishing Community Agreements and Classroom Norms
• Sample group work rubric
• Problem-Based Learning Clearinghouse of Activities, University of Delaware

Problem-Based Learning

Problem-based learning  (PBL) is a student-centered approach in which students learn about a subject by working in groups to solve an open-ended problem. This problem is what drives the motivation and the learning. 

Why Use Problem-Based Learning?

Nilson (2010) lists the following learning outcomes that are associated with PBL. A well-designed PBL project provides students with the opportunity to develop skills related to:

• Working in teams.
• Managing projects and holding leadership roles.
• Oral and written communication.
• Self-awareness and evaluation of group processes.
• Working independently.
• Critical thinking and analysis.
• Explaining concepts.
• Self-directed learning.
• Applying course content to real-world examples.
• Researching and information literacy.
• Problem solving across disciplines.

Considerations for Using Problem-Based Learning

Rather than teaching relevant material and subsequently having students apply the knowledge to solve problems, the problem is presented first. PBL assignments can be short, or they can be more involved and take a whole semester. PBL is often group-oriented, so it is beneficial to set aside classroom time to prepare students to   work in groups  and to allow them to engage in their PBL project.

Students generally must:

• Examine and define the problem.
• Explore what they already know about underlying issues related to it.
• Determine what they need to learn and where they can acquire the information and tools necessary to solve the problem.
• Evaluate possible ways to solve the problem.
• Solve the problem.
• Report on their findings.

Getting Started with Problem-Based Learning

• Articulate the learning outcomes of the project. What do you want students to know or be able to do as a result of participating in the assignment?
• Create the problem. Ideally, this will be a real-world situation that resembles something students may encounter in their future careers or lives. Cases are often the basis of PBL activities. Previously developed PBL activities can be found online through the University of Delaware’s PBL Clearinghouse of Activities .
• Establish ground rules at the beginning to prepare students to work effectively in groups.
• Introduce students to group processes and do some warm up exercises to allow them to practice assessing both their own work and that of their peers.
• Consider having students take on different roles or divide up the work up amongst themselves. Alternatively, the project might require students to assume various perspectives, such as those of government officials, local business owners, etc.
• Establish how you will evaluate and assess the assignment. Consider making the self and peer assessments a part of the assignment grade.

Nilson, L. B. (2010).  Teaching at its best: A research-based resource for college instructors  (2nd ed.).  San Francisco, CA: Jossey-Bass. 

Problem-Solving Method in Teaching

The problem-solving method is a highly effective teaching strategy that is designed to help students develop critical thinking skills and problem-solving abilities . It involves providing students with real-world problems and challenges that require them to apply their knowledge, skills, and creativity to find solutions. This method encourages active learning, promotes collaboration, and allows students to take ownership of their learning.

Table of Contents

Definition of problem-solving method.

Problem-solving is a process of identifying, analyzing, and resolving problems. The problem-solving method in teaching involves providing students with real-world problems that they must solve through collaboration and critical thinking. This method encourages students to apply their knowledge and creativity to develop solutions that are effective and practical.

Meaning of Problem-Solving Method

The meaning and Definition of problem-solving are given by different Scholars. These are-

Woodworth and Marquis(1948) : Problem-solving behavior occurs in novel or difficult situations in which a solution is not obtainable by the habitual methods of applying concepts and principles derived from past experience in very similar situations.

Skinner (1968): Problem-solving is a process of overcoming difficulties that appear to interfere with the attainment of a goal. It is the procedure of making adjustments in spite of interference

Benefits of Problem-Solving Method

The problem-solving method has several benefits for both students and teachers. These benefits include:

• Encourages active learning: The problem-solving method encourages students to actively participate in their own learning by engaging them in real-world problems that require critical thinking and collaboration
• Promotes collaboration: Problem-solving requires students to work together to find solutions. This promotes teamwork, communication, and cooperation.
• Builds critical thinking skills: The problem-solving method helps students develop critical thinking skills by providing them with opportunities to analyze and evaluate problems
• Increases motivation: When students are engaged in solving real-world problems, they are more motivated to learn and apply their knowledge.
• Enhances creativity: The problem-solving method encourages students to be creative in finding solutions to problems.

Steps in Problem-Solving Method

The problem-solving method involves several steps that teachers can use to guide their students. These steps include

• Identifying the problem: The first step in problem-solving is identifying the problem that needs to be solved. Teachers can present students with a real-world problem or challenge that requires critical thinking and collaboration.
• Analyzing the problem: Once the problem is identified, students should analyze it to determine its scope and underlying causes.
• Generating solutions: After analyzing the problem, students should generate possible solutions. This step requires creativity and critical thinking.
• Evaluating solutions: The next step is to evaluate each solution based on its effectiveness and practicality
• Selecting the best solution: The final step is to select the best solution and implement it.

Verification of the concluded solution or Hypothesis

The solution arrived at or the conclusion drawn must be further verified by utilizing it in solving various other likewise problems. In case, the derived solution helps in solving these problems, then and only then if one is free to agree with his finding regarding the solution. The verified solution may then become a useful product of his problem-solving behavior that can be utilized in solving further problems. The above steps can be utilized in solving various problems thereby fostering creative thinking ability in an individual.

The problem-solving method is an effective teaching strategy that promotes critical thinking, creativity, and collaboration. It provides students with real-world problems that require them to apply their knowledge and skills to find solutions. By using the problem-solving method, teachers can help their students develop the skills they need to succeed in school and in life.

• Jonassen, D. (2011). Learning to solve problems: A handbook for designing problem-solving learning environments. Routledge.
• Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235-266.
• Mergendoller, J. R., Maxwell, N. L., & Bellisimo, Y. (2006). The effectiveness of problem-based instruction: A comparative study of instructional methods and student characteristics. Interdisciplinary Journal of Problem-based Learning, 1(2), 49-69.
• Richey, R. C., Klein, J. D., & Tracey, M. W. (2011). The instructional design knowledge base: Theory, research, and practice. Routledge.
• Savery, J. R., & Duffy, T. M. (2001). Problem-based learning: An instructional model and its constructivist framework. CRLT Technical Report No. 16-01, University of Michigan. Wojcikowski, J. (2013). Solving real-world problems through problem-based learning. College Teaching, 61(4), 153-156

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Effects of Problem-Solving Teaching Strategy on Secondary School Students’ Academic Achievement in Physics

2020, European Modern Studies Journal

Related Papers

Global Journal of Guidance and Counseling in Schools: Current Perspectives

This study investigated the effects of problem-solving teaching method on elementary school students' physics achievement at elementary school. In this investigation an experimental research procedure was used. Along with this, a sample of sixty students was drawn from a total of three hundred seventy-eight students using lottery method of sampling technique. Physics achievement test (pre-test and post-test) covering the unit ''Introduction to Electronics'' was used as measuring instrument. Then, based on the pre-test scores, mixed ability groups such as fifteen high and fifteen low scoring 30 students each were assigned as experimental (13Fand17M) and control(15 and15M) groups using lottery method of sampling technique Students in the experimental group were taught using problem solving teaching method while those in the control group were instructed with lecture teaching method. The post-test constructed by the writer in the sample unit taught was administrated to both groups immediately after the treatment was over. Finally, the results of the study revealed that problem-solving teaching method was more effective in teaching physics as compared with lecture method at elementary school level.

Australian Journal of Basic and Applied Sciences

JAMIU OLUWADAMILARE AMUSA

This research work examined the relationship among teachers' abilities, students' learning styles and students' achievement in physics. A total of one hundred and fifty (150) randomly selected senior secondary school 11 (SS11) physics students and ten (10) physics teachers from five (5) selected schools in Lagos Mainland Local government area of Lagos State served as the subjects of this study. The simple survey design was adopted for this study. Data were gathered with the research instruments which included a learning style questionnaire administered to the selected students and a questionnaire on teachers' expertise which was administered to the selected teachers. Data was analyzed using simple regression analysis, statistical package for social science (SPSS) such as mean, percentage, t-test and analysis of variance (ANOVA). The outcome of the findings from the study include the following 1. The relationship between teachers' problem solving abilities and students academic achievement in physics is positive and significant 2. The relationship between students' learning styles and their academic achievement in physics is positive and significant. 3. The main and combined effect of teachers' problem solving abilities, students' learning styles on students' academic performance in physics are positive and significant. Based on these findings, it was concluded that teachers' problem solving abilities and students' learning styles have significant effects on the students' achievement in physics.

IJSRP Journal

“Mathematics is the language of Physics”. This is the actual scenario of how Physics has to be taught by the teacher and be learned by the students through using formula, equations and analysis. The study aimed to determine the effect of the structured problem solving strategy on performance in Physics among students who are enrolled in the University of Rizal System. There were 152 students taking up Physics I (General Physics) in the first semester of the SY 2013-2014 utilized in the study. The respondents were forty one (41) BT Drafting, forty (40) BT HRM, thirty nine (39) BT Electrical and thirty two (32) Biomedical Technician Coursestudents. Two experimental and two controlled groups were given pretest and posttest during the mid-term period covering concepts on Momentum, Work, Power and Energy together with simple machine. Specifically, the study attempted to answer questions on how do performance of the students in Physics compared when grouped according to the course and which method is more effective in teaching Physics, conventional or structured problem solving process. Dependent t-test was used to determine the significant difference on the performance in pretest and posttest of the experimental and controlled groups with respect to their courses, likewise, F-value was used to determine the significant difference on the level of performance in both groups after exposures to two different strategies.

Gamze Sezgin Selçuk

This study has investigated the effects of problem solving instruction on physics achievement, problem-solving performance and strategy use in an introductory physics course at university level. In this study, pretest-posttest and quasi-experimental design with nonequivalent control group was used. Two groups of student teachers (n=74) participated in this study. During the 8-week study, one group received the strategy instruction while the other group acted as control. Data of the study were collected by Physics Achievement Test (PAT), Problem-Solving Performance Test (PSPT) and Problem-Solving Strategies Scale (PSSS). Findings of the study indicate that strategy instruction was effective on physics achievement, problem-solving performance, and strategy use. The implications of these results for physics instruction are discussed.

Ambrose Mbia

The purpose of this study was to experimentally determine the effect of innovative method of teaching on the academic performance of senior secondary school physics students in Akamkpa Local Government Area of Cross River State, putting into consideration variables such as peer tutoring, problem-based learning, discovery learning and cooperative methods. Four research questions were articulated and four hypotheses were formulated to guide the study. The study employed a quasi-experimental research design. The population for the study was 6,203 senior secondary two (SSII) students in 19 secondary schools in Akamkpa Local Government Area for the 2016/2017 session. Out of 19 secondary schools, purposive random sampling technique was employed to select six schools. In each of the school selected, an intact class of the students were used. One hundred and twenty (120) students in the six intact classes constitute the sample for the study. The instrument for data collection was a 50-item ...

Procedia - Social and Behavioral Sciences

Gumisirizah Nicholus

Enabling students to learn smoothly at an early stage of learning is a paramount effort that African education should takeoff. This study established the effect of problem-based learning (PBL) on students' learning achievement. The participants were selected from form-2 of lower secondary schools in Sheema District, Western Uganda. Participants were randomly assigned to the treatment class with PBL instruction and the control class with content-based learning (CBL). A quantitative approach and a quasi-experimental design were used. Thus, the pretest-posttest non-equivalent quasi-experimental design was applied. A learning achievement test in simple machines was used as a data collection tool. The test was validated by experts and piloted with a split-half reliability (r = 0.87). Data was analysed in MS Excel and SPSS. A repeated measures

carljames beltran

European Scientific Journal ESJ

The study assessed instructional strategies employed by Physics teachers and students academic achievement in Secondary schools in Rivers State. The study in specific terms, assessed the instructional strategies employed by physics teachers, determine the level of use of instructional strategies in the teaching of Physics and determine the difference in the academic achievement of those taught with frequently used instructional strategies in Rivers State. The population of the study consisted of all practicing Physics teachers and students in Rivers State. The sample size of the study was 28 Physics teaachers selected from 18 science teaching schools in Rivers State and 140 science students from 4 schools whose teachers indicated usage of any of the frequently used instructional strategies. A structured questionnaire and Physic Achievement Test (PAT) was used to collect data from Physics teachers and students respectively. Frequency, Mean and standard deviation was used to analyze the gathered data, while z-test was used to test hypotheses at 0.05 level of significance. In the study, among the traditional instructional strategies, it was found that lecture method, demonstration method, laboratory method and problem solving method of teaching are the most frequently used strategies employed by Physics teachers in Rivers State. However, when the students who were taught Physic by these most frequently used strategies were tested, it was found that students who were frequently taught Physics with demonstration method achieved more that those taught with lecture method. Similarly, students taught with problem solving methods achieved more than those who were frequently taught with laboratory strategy. It was recommended that Physics teachers should employ instructional strategies that will actively engage students in the lesson.

Journal of Education and Practice

Kodjo Donkor Taale

RELATED PAPERS

Dusan Schreiber

Journal of Citrus Pathology

ghjtftgd ghhtrf

Journal of Visual Communication and Image Representation

Ángel Carmona Poyato

Kapil Katyal

Journal of Manufacturing and Materials Processing

Mochamad Zakki Fahmi

Earthquake Engineering &amp; Structural Dynamics

Jeen-Shang Lin

Camosun学位证 卡莫森学院毕业证

Journal of Economic Theory

ROGERS AKINSOKEJI

Roger Pyddoke

Infrared Physics &amp; Technology

Ljiljana Puskar

Tetrahedron

Hafeez Ur Rehman

Philosophical Transactions of the Royal Society B

Robert G K Donald

Joaquim Domingues

Biophysical Journal

John Lindsay

OUC学位证 奥肯那根学院毕业证

Michelle Budig

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Effects of different geriatric nursing teaching methods on nursing students’ knowledge and attitude: Systematic review and network meta-analysis

Contributed equally to this work with: Yifen Cheng, Shuqin Sun

Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft

Current address: The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui Province, China

Affiliation Department of Orthopedics, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, Anhui, China

Roles Conceptualization, Data curation, Formal analysis, Methodology, Resources, Supervision, Writing – original draft

Current address: Anhui University of Chinese Medicine, Hefei, Anhui Province, China

Affiliation School of Nursing, Anhui University of Traditional Chinese Medicine, Hefei, Anhui, China

Roles Data curation, Writing – original draft

Roles Conceptualization, Funding acquisition, Resources, Supervision, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Endocrinology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, Anhui, China

Roles Investigation, Visualization

Current address: Chuxiong Medical College, Chuxiong, Yunnan Province, China

Affiliation School of Nursing, Chuxiong Medical College, Chuxiong, Yunnan, China

Roles Resources, Supervision

Roles Data curation, Validation

• Yifen Cheng, 
• Shuqin Sun, 
• Yu Hu, 
• Jing Wang, 
• Wenzhen Chen, 
• Yukuan Miao, 

• Published: May 31, 2024
• https://doi.org/10.1371/journal.pone.0300618
• Reader Comments

The purpose of this study was to evaluate the effect of different teaching methods of geriatric nursing on the mastery of geriatric knowledge among nursing students and their attitude toward the elderly.

Relevant randomized controlled trials (RCTs) and quasi-experimental studies on teaching methods to improve nursing students’ knowledge and attitude were systematically retrieved in electronic databases. The time scale of retrieval spans from the database establishment to January 2024, and the database consists of PubMed, the Cochrane Library, Web of Science, Embase, China National Knowledge Infrastructure Database (CNKI), China Biological literature database (CBM), Wanfang Database and VIP Database. Network meta-analysis was performed by Stata 16.0 software.

Thirty-nine studies involving 5310 nursing students met our inclusion criteria, and a total of 6 teaching methods were analyzed. According to the surface under the cumulative ranking (SUCRA) ranking, problem-based learning (PBL) was most effective in enhancing the knowledge mastery of geriatric nursing, while simulation-based learning (SBL) demonstrated the best application effect in improving nursing students’ attitude toward the elderly. When considering both knowledge acquisition and attitude improvement simultaneously, service learning combined with traditional teaching method (SL+TTM) was found to exhibit the most optimal effectiveness.

Educators in geriatric nursing education should prioritize the adoption of PBL, SBL and SL + TTM to enhance nursing students’ knowledge and attitude.

Protocol registry

PROSPERO ( CRD42023442001 ).

Citation: Cheng Y, Sun S, Hu Y, Wang J, Chen W, Miao Y, et al. (2024) Effects of different geriatric nursing teaching methods on nursing students’ knowledge and attitude: Systematic review and network meta-analysis. PLoS ONE 19(5): e0300618. https://doi.org/10.1371/journal.pone.0300618

Editor: César Leal-Costa, Murcia University, Spain, SPAIN

Received: December 4, 2023; Accepted: March 3, 2024; Published: May 31, 2024

Copyright: © 2024 Cheng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: We acknowledge the support received from the Quality Engineering Project of Anhui Provincial Department of Education [grant number 2022xskc056] for our research. The funders had a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

With the global elderly population continuously increasing, China has become the country with the largest middle-aged and elderly population. The result of the seventh national census showed that the number of individuals aged 60 and above in China reached 264.0188 million in 2020, accounting for 18.70% of the total population, and the process of population aging was on the rise [ 1 ]. By the end of 2019, the prevalence of chronic diseases among individuals aged 60 and above in China had reached 69.13% [ 2 ], signaling a huge demand for elderly care professionals. Nursing students constitute a pivotal cohort in the provision of nursing services for elderly patients. Their mastery of geriatric knowledge and attitude toward the elderly will directly shape the extent to which caregivers’ willingness to provide elderly care [ 3 ] and their vocational preferences [ 4 ]. The positive attitude among nursing students toward the elderly has the potential to enhance the quality of geriatric care. Adopting a negative attitude, however, can lead to substantial adverse ramifications, exacerbating societal issues including discrimination and instances of elder mistreatment [ 5 ]. Research findings indicate that most nursing students lack knowledge in geriatric nursing, hold age-discriminatory attitude, and still need improvement [ 6 ]. Geriatric nursing education plays a vital role in shaping nursing students’ perceptions of aging, and the instructional design of geriatric nursing courses can enhance nursing students’ knowledge and positive attitude toward the elderly [ 7 , 8 ].

Traditional teaching methods (TTM) involve instructors actively lecturing on theoretical knowledge in a relatively uniform manner [ 9 ], which may hinder nursing students from taking an active and enthusiastic approach toward geriatric nursing knowledge, consequently failing to significantly improve their positive attitude toward serving the elderly. In recent years, nursing educators have recognized the importance of improving nursing students’ knowledge mastery and their attitude toward the elderly. As a result, new teaching methods have been devised and substantiated with distinct applied advantages within geriatric nursing education, such as simulation-based learning (SBL), service learning combined with traditional teaching method (SL+TTM), problem-based learning (PBL), and learning with older people programme (LOPP). However, the comparative study of these teaching methods on the impact of knowledge and attitude of nursing students about the elderly is limited, making it imperative to assess and compare the efficacy of different teaching methods. Traditional Meta-analysis cannot compare the effects of different interventions, thus fails in choosing the best teaching method for elderly nursing.

This study employs a network meta-analysis to comparatively assess the effects of six distinct geriatric nursing instructional methods on the enhancement of nursing students’ knowledge and attitude toward the elderly. The findings offer valuable insights for informing the selection of geriatric nursing teaching paradigms.

Materials and methods

Search strategy.

The systematic review adhered to the PRISMA-NMA guidelines during its execution and reporting (shown in S1 Table ). PubMed, The Cochrane Library, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), China Biology Medicine (CBM), VIP and Wanfang databases were systematically searched from the inception of these databases up to January 2024. A combination of subject terms and free-text terms were used in the search strategies, as follows: (nursing students or Students, Nursing or Nursing Student or Pupil Nurses or Nurses, Pupil or Nurse, Pupil or Pupil Nurse) AND (Geriatric nursing or gerontology or Geriatric or curriculum of gerontological nursing or gerontological nursing education or education) AND (simulation-based learning or SBL or simulation-based education or SBE or simulation or experiential learning or experiential teaching or service learning or problem-based learning or PBL or lecture-based learning or LBL or Learning with older people programme or LOPP or traditional teaching method) AND [knowledge or final examination scores or final course scores or test scores or school marks or scholastic achievement or theoretical knowledge or academic performance or course grade or exam scores or final exam scores or attitude* or attitude(s) toward(s)/to older/geriatric/old/elderly/aged/aging/seniors/geriatrics], and trace has been added into the literature references do. The initial search strategy for PubMed is shown in S2 Table .

Inclusion and exclusion criteria

Inclusion criteria..

① Study design: Randomized Controlled Trials (RCTs) or quasi-experimental studies; ② Participants: Nursing students receiving geriatric nursing education; ③ Intervention: Comparisons of novel teaching methods with placebo simulation-based learning or traditional teaching method; novel teaching methods: Simulation-based learning (SBL), Service learning + traditional teaching method (SL+TTM), Problem-based learning (PBL), and Learning with older people programme (LOPP); ④ Outcomes: Nursing students’ knowledge mastery and their attitude toward the elderly, and no restriction on the measurement types or evaluation methods of nursing students’ knowledge and attitude is applied.

Exclusion criteria.

① Single arm trials, Self-control studies or mixed method studies; ② Interventions that do not include the above teaching methods; ③ Reviews, meta-analysis, conference abstracts, studies with non-full text and duplicate publications; ④ Lack of data on knowledge and attitude toward the elderly.

Literature screening and data extraction

Two nursing postgraduate students will read the title, abstract and full text of the literature according to the inclusion and exclusion criteria for independent screening, data extraction and cross-checking. The disputes will be resolved through expert discussion or consultation with the tutor. The extraction content mainly includes: first author, source of research objects, sample size, age, gender, education background, intervention measures, Outcomes and measuring tool, and research type.

Quality assessment

The included RCTs were independently evaluated according to the 5 aspects of the revised Cochrane Collaboration’s Risk of Bias 2 (RoB2) tool [ 10 ], and the 7 aspects of the Risk of Bias in Non-randomized studies of interventions (ROBINS-I) tool [ 11 ] were used to independently evaluate the included quasi-experimental studies. The bias risk for each RCT was categorized as low, some concerns, or high, whereas for each quasi-experimental study, it was categorized as low, moderate, serious, or critical. Each study assessment was conducted independently by two nursing master’s students. Disputes regarding the results were resolved through expert discussion or consultation with the tutor. Finally, risk of bias VISualization (robvis) tool [ 12 ] was used to create the figures.

Statistical methods

Stata16.0 software was used for data analysis and graph drawing. Standardized mean difference (SMD) and 95% confidence interval (95% CI) were used for comparative analysis of measurement data. The results of network meta-analysis were presented through forest maps, and the application effects of each method were compared by the surface under the cumulative ranking (SUCRA) graph. A comprehensive evaluation of teaching methods ranking is presented by drawing a scatter plot based on the SUCRA values obtained by each intervention in terms of both knowledge and skill attitude. The node analysis method is used to test the inconsistency. If the direct comparison and the indirect comparison P > 0.05, the consistency model can be adopted. Publication bias was assessed using funnel plots and Egger’s test.

Literature screening results and basic characteristics

A total of 1453 articles were retrieved for the first time, and 62 articles were left after re-screening, excluding articles that did not meet the inclusion criteria. And 39 literatures were finally included based on further reading the full text. The whole selection process is shown in Fig 1 . The included literatures were from China, Turkey, Iran, Finland with a total sample size of 5310 nursing students. The basic characteristics are shown in Table 1 .

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0300618.g001

https://doi.org/10.1371/journal.pone.0300618.t001

Quality of studies

According to the RoB2 tool, among the 27 RCTs, one has an overall bias risk score categorized as "low risk," 17 as "some concerns," and 9 are categorized as "high risk," as illustrated in Fig 2 . Regarding the overall bias risk in non-randomized controlled trials (ROBINS-I), among the 12 quasi-experimental studies, 1 is rated as "low risk," 8 as "moderate bias risk," and 3 are rated as "serious bias risk," as illustrated in Fig 3 .

https://doi.org/10.1371/journal.pone.0300618.g002

https://doi.org/10.1371/journal.pone.0300618.g003

Results of network meta-analysis

Network diagram..

The network depiction illustrating the impact of diverse teaching methods on nursing students’ knowledge and their attitude toward the elderly is presented in Fig 4 . Each teaching method is represented by a distinct data point, with the size corresponding to the level of acceptance among nursing students regarding the intervention of the given teaching method. Furthermore, the thickness of the solid lines connecting the data points reflects the extent of direct comparative research conducted between the respective pairs of teaching methodologies.

https://doi.org/10.1371/journal.pone.0300618.g004

Network meta-analysis.

36 studies [ 13 , 14 , 16 , 18 , 19 , 21 – 51 ] provided data on nursing students’ knowledge, involving 5 teaching methods, including SBL, SL + TTM, LOPP, PBL, TTM. The results of network Meta-analysis reveal that the results of inconsistency test were non-significant inconsistency (P > 0.05). Consequently, the adoption of the consistency model for fitting is warranted. Statistical significance is observed in the comparison between SL + TTM, SBL, PBL and traditional teaching method in terms of application effect (P < 0.05), as illustrated in Fig 5 .

https://doi.org/10.1371/journal.pone.0300618.g005

13 studies [ 13 – 25 ] provided data on nursing students’ attitude toward the elderly, involving 6 teaching methods, including SBL, Placebo SBL, SL + TTM, LOPP, PBL, TTM. The results of network Meta-analysis reveal that the results of inconsistency test were non-significant inconsistency (P > 0.05). Statistical significance is observed in the comparison between SBL, SL + TTM and traditional teaching method in terms of applied effects (P < 0.05), as illustrated in Fig 5 .

A higher SUCRA value indicates that the corresponding teaching method yields a more favorable application effect in enhancing the knowledge level of nursing students and their attitude toward the elderly.

The ranking for knowledge is as follows: PBL > SL + TTM > SBL > LOPP > TTM; for attitude: SBL > Placebo SBL > SL + TTM > LOPP > PBL > TTM, as shown in Table 2 . Additionally, SL + TTM performs the best in terms of the comprehensive aspect of knowledge and attitude, as indicated by the scatter plot ( Fig 6 ) generated from the SUCRA values for knowledge and attitude.

https://doi.org/10.1371/journal.pone.0300618.g006

https://doi.org/10.1371/journal.pone.0300618.t002

Publication bias analysis.

In terms of knowledge, both Egger’s test (P = 0.001) and an asymmetric funnel plot suggest a potential publication bias. For attitudes, Egger’s test (P = 0.329) and a symmetric funnel plot indicate the absence of publication bias. The funnel plot is shown in Fig 7 . Sensitivity analysis was performed by one by one exclusion method, and no significant change was found after the exclusion of any literature, indicating that the results of this study were basically stable.

https://doi.org/10.1371/journal.pone.0300618.g007

To the best of our knowledge, this study represents the first attempt to conduct a network meta-analysis of different teaching methods in the context of geriatric nursing education, particularly focusing on the impact of these methods on nursing students’ attitude toward the elderly. The effectiveness of six teaching strategies was evaluated, and literature results were collected from 39 studies involving 5310 nursing students. It was found in results of network meta-analysis that SBL, PBL, and SL+TTM showed statistically significant advantages over TTM in influencing nursing students’ acquisition of knowledge and improvement in attitude, either in single or dual aspects. Specifically, PBL is most effective in enhancing nursing students’ knowledge understanding of geriatric nursing, while SBL demonstrates the best application effect in improving nursing students’ attitude toward the elderly. When considering both indicators simultaneously, SL+TTM is found to exhibit the most optimal comprehensive effectiveness.

Numerous teaching methods have been developed in nursing education to improve the teaching process and enhance the practical effectiveness of nursing education. However, while nursing education has been enriched by these various nursing teaching methods, teachers are burdened in selecting teaching methods, especially when certain learning and usage costs are entailed by these methods. Therefore, evaluating the effectiveness of teaching methods in geriatric nursing education to provide insights into geriatric nursing education is a pressing challenge. Therefore, network meta-analysis was used to examine the effects of teaching methods on nursing students’ knowledge acquisition and attitude toward the elderly, assessing the statistical significance of teaching method comparisons, and analyzing the relative effectiveness of various teaching methods based on SUCRA rankings. Based on the comparative results, teaching methods can be selected by teachers according to teaching objectives to reduce teaching costs and achieve better teaching outcomes.

When the acquisition of theoretical knowledge is used to evaluate the effectiveness of geriatric nursing education, PBL yields the best results. It has been shown by Sayyah et al.’s meta-analysis [ 52 ] that it can significantly enhance students’ knowledge levels. This may be because students are actively guided by teachers to learn, actively think, and solve problems together in groups, thereby enhancing their understanding of geriatric nursing knowledge. Furthermore, PBL is widely applied by most educators in the clinical practice teaching of nursing students, promoting students’ comprehension abilities and critical thinking skills [ 53 , 54 ]. Therefore, PBL enhances nursing students’ ability to analyze and apply geriatric nursing knowledge, leading to effective teaching outcomes.

When attention is dedicated to nursing students’ attitude toward the elderly, SBL emerges as the optimal method. Eost‐Telling et al.’s systematic review [ 55 ] indicates that the application of simulation teaching in geriatric nursing education can significantly enhance nursing students’ attitude toward the elderly. This enhancement is primarily attributed to the immersive nature of simulation teaching, wherein nursing students wear elderly simulation suits or other sensory impairment devices, thus simulating and experiencing the sensory limitations typical of the elderly, including visual, auditory, olfactory, thermal, and joint limitations. By actively engaging in activities such as participating in the daily routines of the elderly, assuming the roles of elderly patients, or interacting with the elderly in nursing homes, nursing students are prompted to reflect deeply on their experiences. Consequently, this active reflection fosters the development of positive attitude toward the elderly while simultaneously reducing negative attitude among nursing students.

It is worth noting that SL + TTM performs best when the applying effect in knowledge and attitude are taken into account comprehensively. Through collaboration between schools and communities [ 56 ], nursing students are organized to provide services to the elderly in nursing homes or communities with clear learning objectives. SL+TTM allows nursing students to integrate theoretical knowledge with practical application, engage in reflection and discussion, and thereby enhance their understanding of the aging process. Consequently, this method not only improves nursing students’ knowledge levels [ 57 ] but also fosters positive attitude toward the elderly [ 58 ]. This suggests that SL+TTM is a teaching method worthy of promotion due to its ability to effectively enhance both knowledge acquisition and attitude improvement among nursing students.

Limitations: the methodological quality is relatively low, with 12 articles being quasi-experimental studies and thus possessing a lower level of evidence. Furthermore, some of the teaching methods have limited literature containing outcome indicators related to this study, potentially influencing the results. Therefore, in future research designs, direct comparisons among different teaching methods, supported by RCTs, can be conducted to provide recommended insights into selecting more effective geriatric nursing education models.

Conclusions

In summary, we conducted a network meta-analysis to study the effects of six teaching methods on improving nursing students’ understanding of elderly care knowledge and their attitude toward the elderly. The results indicate that PBL is most effective in enhancing nursing students’ knowledge of geriatric nursing, while SBL is most effective in improving nursing students’ attitude toward the elderly. When considering both knowledge and attitude, SL + TTM demonstrates the best comprehensive effectiveness. Therefore, educators in geriatric nursing education should prioritize the adoption of these teaching methods to enhance nursing students’ knowledge and improve attitude.

Supporting information

S1 table. the prisma network meta-analysis checklist..

https://doi.org/10.1371/journal.pone.0300618.s001

S2 Table. The initial search strategy for PubMed.

https://doi.org/10.1371/journal.pone.0300618.s002

Acknowledgments

We thank The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine for support.

• View Article
• Google Scholar
• PubMed/NCBI

Top 10 Challenges to Teaching Math and Science Using Real Problems

• Share article

Nine in ten educators believe that using a problem-solving approach to teaching math and science can be motivating for students, according to an EdWeek Research Center survey.

But that doesn’t mean it’s easy.

Teachers perceive lack of time as a big hurdle. In fact, a third of educators—35 percent—worry that teaching math or science through real-world problems—rather than focusing on procedures—eats up too many precious instructional minutes.

Other challenges: About another third of educators said they weren’t given sufficient professional development in how to teach using a real-world problem-solving approach. Nearly a third say reading and writing take priority over STEM, leaving little bandwidth for this kind of instruction. About a quarter say that it’s tough to find instructional materials that embrace a problem-solving perspective.

Nearly one in five cited teachers’ lack of confidence in their own problem solving, the belief that this approach isn’t compatible with standardized tests, low parent support, and the belief that student behavior is so poor that this approach would not be feasible.

The nationally representative survey included 1,183 district leaders, school leaders, and teachers, and was conducted from March 27 to April 14. (Note: The chart below lists 11 challenges because the last two on the list—dealing with teacher preparation and student behavior—received the exact percentage of responses.)

Trying to incorporate a problem-solving approach to tackling math can require rethinking long-held beliefs about how students learn, said Elham Kazemi, a professor in the teacher education program at the University of Washington.

Most teachers were taught math using a procedural perspective when they were in school. While Kazemi believes that approach has merit, she advocates for exposing students to both types of instruction.

Many educators have “grown up around a particular model of thinking of teaching and learning as the teacher in the front of the room, imparting knowledge, showing kids how to do things,” Kazemi said.

To be sure, some teachers have figured out how to incorporate some real-world problem solving alongside more traditional methods. But it can be tough for their colleagues to learn from them because “teachers don’t have a lot of time to collaborate with one another and see each other teach,” Kazemi said.

What’s more, there are limited instructional materials emphasizing problem solving, Kazemi said.

Though that’s changing, many of the resources available have “reinforced the idea that the teacher demonstrates solutions for kids,” Kazemi said.

Molly Daley, a regional math coordinator for Education Service District 112, which serves about 30 districts near Vancouver, Wash., has heard teachers raise concerns that teaching math from a problem-solving perspective takes too long—particularly given the pressure to get through all the material students will need to perform well on state tests.

Daley believes, however, that being taught to think about math in a deeper way will help students tackle math questions on state assessments that may look different from what they’ve seen before.

“It’s myth that it’s possible to cover everything that will be on the test,” as it will appear, she said. “There’s actually no way to make sure that kids have seen every single possible thing the way it will show up. That’s kind of a losing proposition.”

But rushing through the material in a purely procedural way may actually be counterproductive, she said.

Teachers don’t want kids to “sit down at the test and say, ‘I haven’t seen this and therefore I can’t do it,’” Daley said. “I think a lot of times teachers can unintentionally foster that because they’re so urgently trying to cover everything. That’s where the kind of mindless [teaching] approaches come in.”

Teachers may think to themselves: “’OK, I’m gonna make this as simple as possible, make sure everyone knows how to follow the steps and then when they see it, they can follow it,” Daley said.

But that strategy might “take away their students’ confidence that they can figure out what to do when they don’t know what to do, which is really what you want them to be thinking when they go to approach a test,” Daley said.

Data analysis for this article was provided by the EdWeek Research Center. Learn more about the center’s work.

Sign Up for EdWeek Update

Edweek top school jobs.

Sign Up & Sign In

• Subscribe Now (Opens in new window)

Your Marine Corps

• Air Force Times (Opens in new window)
• Army Times (Opens in new window)
• Navy Times (Opens in new window)
• Pentagon & Congress
• Defense News (Opens in new window)
• Flashpoints
• Benefits Guide (Opens in new window)
• Military Pay Center
• Military Retirement
• Military Benefits
• VA Loan Center (Opens in new window)
• Discount Depot
• Military Culture
• Military Fitness
• Military Movies & Video Games
• Military Sports
• Transition Guide (Opens in new window)
• Pay It Forward (Opens in new window)
• Black Military History (Opens in new window)
• Congressional Veterans Caucus (Opens in new window)
• Military Appreciation Month (Opens in new window)
• Vietnam Vets & Rolling Thunder (Opens in new window)
• Military History
• Honor the Fallen (Opens in new window)
• Hall of Valor (Opens in new window)
• Service Members of the Year (Opens in new window)
• Create an Obituary (Opens in new window)
• Medals & Misfires
• Installation Guide (Opens in new window)
• Battle Bracket
• CFC Givers Guide
• Task Force Violent
• Photo Galleries
• Newsletters (Opens in new window)
• Early Bird Brief
• Long-Term Care Partners
• Navy Federal
• Digital Edition (Opens in new window)

Marines say no more ‘death by PowerPoint’ as Corps overhauls education

WASHINGTON, D.C. ― Marines and those who teach them will see more direct, problem-solving approaches to how they learn and far less “death by PowerPoint” as the Corps overhauls its education methods .

Decades of lecturers “foot stomping” material for Marines to learn, recall and regurgitate on a test before forgetting most of what they heard is being replaced by “outcomes-based” learning, a method that’s been in use in other fields but only recently brought into military training.

“Instead of teaching them what to think, we’re teaching them how to think,” said Col. Karl Arbogast, director of the policy and standards division at training and education command .

Here’s what’s in the Corps’ new training and education plan

New ranges, tougher swimming. inside the corps' new training blueprint..

Arbogast laid out some of the new methods that the command is using at the center for learning and faculty development while speaking at the Modern Day Marine Expo.

“No more death by PowerPoint,” Arbogast said. “No more ‘sage on the stage’ anymore, it’s the ‘guide on the side.’”

To do that, Lt. Col. Chris Devries, director of the learning and faculty center, is a multiyear process in which the Marines have developed two new military occupational specialties, 0951 and 0952.

The exceptional MOS is in addition to their primary MOS but allows the Marines to quickly identify who among their ranks is qualified to teach using the new methods.

Training for those jobs gives instructors, now called facilitators, an entry-level understanding of how to teach in an outcomes-based learning model.

Devries said the long-term goal is to create two more levels of instructor/facilitator that a Marine could return to in their career, a journeyman level and a master level. Those curricula are still under development.

The new method helps facilitators first learn the technology they’ll need to share material with and guide students. It also teaches them more formal assessment tools so they can gauge how well students are performing.

For the students, they can learn at their own pace. If they grasp the material the group is covering, they’re encouraged to advance in their study, rather than wait for the entire group to master the introductory material.

More responsibility is placed on the students. For example, in a land navigation class, a facilitator might share materials for students to review before class on their own and then immediately jump into working with maps, compasses and protractors on land navigation projects in the next class period, said John deForest, learning and development officer at the center.

That creates more time in the field for those Marines to practice the skills in a realistic setting.

Marines with Marine Medium Tiltrotor Squadron (VMM) 268, Marine Aircraft Group 24, 1st Marine Aircraft Wing, fire M240-B machine guns at the Marine Corps Air Station Kaneohe Bay range, Hawaii, March 5. (Lance Cpl. Tania Guerrero/Marine Corps)

For the infantry Marine course, the school split up the large classroom into squad-sized groups led by a sergeant or staff sergeant, allowing for more individual focus and participation among the students, Arbogast said.

“They have to now prepare activities for the learner to be directly involved in their own learning and then they have to steer and guide the learners correct outcome,” said Timothy Heck, director of the center’s West Coast detachment.

The students are creating products and portfolios of activities in their training instead of simply taking a written test, said Justina Kirkland, a facilitator at the West Coast detachment.

Students are also pushed to discuss problems among themselves and troubleshoot scenarios. The role of the facilitator then is to monitor the conversation and ask probing questions to redirect the group if they get off course, Heck said.

That involves more decision games, decision forcing cases and even wargaming, deForest said.

We “put the student in an active learning experience where they have to grapple with uncertainty, where they have to grapple with the technical skills and the knowledge they need,” deForest said.

That makes the learning more about application than recall, he said.

Todd South has written about crime, courts, government and the military for multiple publications since 2004 and was named a 2014 Pulitzer finalist for a co-written project on witness intimidation. Todd is a Marine veteran of the Iraq War.

In Other News

VA chief to address bonus scandal next week at House hearing

Va's top leader is expected to face harsh questioning about mistakes made in awarding nearly $11 million in senior executive bonuses last year..

Advocates fear growing backlash against aid for homeless veterans

Activists worry that laws aimed at penalizing homelessness and a lack of support resources will hurt efforts to help veterans..

VA urges mortgage firms to extend foreclosure pause until next year

A moratorium on foreclosures of va-backed home loans is set to expire at the end of the week..

More kosher, halal foods needed in commissaries, lawmakers say

Are commissaries meeting the religious dietary needs of troops and families.

VA says its trust scores among veterans are at highest level ever

More than four in five veterans surveyed said they trust the department's programs and outreach efforts..