Hypothesis is a hypothesis is fundamental concept in the world of research and statistics. It is a testable statement that explains what is happening or observed. It proposes the relation between the various participating variables.
Hypothesis is also called Theory, Thesis, Guess, Assumption, or Suggestion . Hypothesis creates a structure that guides the search for knowledge.
In this article, we will learn what hypothesis is, its characteristics, types, and examples. We will also learn how hypothesis helps in scientific research.
Table of Content
Characteristics of hypothesis, sources of hypothesis, types of hypothesis, functions of hypothesis, how hypothesis help in scientific research.
Hypothesis is a suggested idea or an educated guess or a proposed explanation made based on limited evidence, serving as a starting point for further study. They are meant to lead to more investigation.
It’s mainly a smart guess or suggested answer to a problem that can be checked through study and trial. In science work, we make guesses called hypotheses to try and figure out what will happen in tests or watching. These are not sure things but rather ideas that can be proved or disproved based on real-life proofs. A good theory is clear and can be tested and found wrong if the proof doesn’t support it.
A hypothesis is a proposed statement that is testable and is given for something that happens or observed.
Here are some key characteristics of a hypothesis:
Hypotheses can come from different places based on what you’re studying and the kind of research. Here are some common sources from which hypotheses may originate:
Here are some common types of hypotheses:
Complex hypothesis, directional hypothesis.
Alternative hypothesis (h1 or ha), statistical hypothesis, research hypothesis, associative hypothesis, causal hypothesis.
Simple Hypothesis guesses a connection between two things. It says that there is a connection or difference between variables, but it doesn’t tell us which way the relationship goes. Example: Studying more can help you do better on tests. Getting more sun makes people have higher amounts of vitamin D.
Complex Hypothesis tells us what will happen when more than two things are connected. It looks at how different things interact and may be linked together. Example: How rich you are, how easy it is to get education and healthcare greatly affects the number of years people live. A new medicine’s success relies on the amount used, how old a person is who takes it and their genes.
Directional Hypothesis says how one thing is related to another. For example, it guesses that one thing will help or hurt another thing. Example: Drinking more sweet drinks is linked to a higher body weight score. Too much stress makes people less productive at work.
Non-Directional Hypothesis are the one that don’t say how the relationship between things will be. They just say that there is a connection, without telling which way it goes. Example: Drinking caffeine can affect how well you sleep. People often like different kinds of music based on their gender.
Null hypothesis is a statement that says there’s no connection or difference between different things. It implies that any seen impacts are because of luck or random changes in the information. Example: The average test scores of Group A and Group B are not much different. There is no connection between using a certain fertilizer and how much it helps crops grow.
Alternative Hypothesis is different from the null hypothesis and shows that there’s a big connection or gap between variables. Scientists want to say no to the null hypothesis and choose the alternative one. Example: Patients on Diet A have much different cholesterol levels than those following Diet B. Exposure to a certain type of light can change how plants grow compared to normal sunlight.
Statistical Hypothesis are used in math testing and include making ideas about what groups or bits of them look like. You aim to get information or test certain things using these top-level, common words only. Example: The average smarts score of kids in a certain school area is 100. The usual time it takes to finish a job using Method A is the same as with Method B.
Research Hypothesis comes from the research question and tells what link is expected between things or factors. It leads the study and chooses where to look more closely. Example: Having more kids go to early learning classes helps them do better in school when they get older. Using specific ways of talking affects how much customers get involved in marketing activities.
Associative Hypothesis guesses that there is a link or connection between things without really saying it caused them. It means that when one thing changes, it is connected to another thing changing. Example: Regular exercise helps to lower the chances of heart disease. Going to school more can help people make more money.
Causal Hypothesis are different from other ideas because they say that one thing causes another. This means there’s a cause and effect relationship between variables involved in the situation. They say that when one thing changes, it directly makes another thing change. Example: Playing violent video games makes teens more likely to act aggressively. Less clean air directly impacts breathing health in city populations.
Hypotheses have many important jobs in the process of scientific research. Here are the key functions of hypotheses:
Researchers use hypotheses to put down their thoughts directing how the experiment would take place. Following are the steps that are involved in the scientific method:
Mathematics Maths Formulas Branches of Mathematics
Hypothesis is a testable statement serving as an initial explanation for phenomena, based on observations, theories, or existing knowledge . It acts as a guiding light for scientific research, proposing potential relationships between variables that can be empirically tested through experiments and observations.
The hypothesis must be specific, testable, falsifiable, and grounded in prior research or observation, laying out a predictive, if-then scenario that details a cause-and-effect relationship. It originates from various sources including existing theories, observations, previous research, and even personal curiosity, leading to different types, such as simple, complex, directional, non-directional, null, and alternative hypotheses, each serving distinct roles in research methodology .
The hypothesis not only guides the research process by shaping objectives and designing experiments but also facilitates objective analysis and interpretation of data , ultimately driving scientific progress through a cycle of testing, validation, and refinement.
What is a hypothesis.
A guess is a possible explanation or forecast that can be checked by doing research and experiments.
The components of a Hypothesis are Independent Variable, Dependent Variable, Relationship between Variables, Directionality etc.
Testability, Falsifiability, Clarity and Precision, Relevance are some parameters that makes a Good Hypothesis
You cannot prove conclusively that most hypotheses are true because it’s generally impossible to examine all possible cases for exceptions that would disprove them.
Hypothesis testing is used to assess the plausibility of a hypothesis by using sample data
Yes, you can change or improve your ideas based on new information discovered during the research process.
Hypotheses are used to support scientific research and bring about advancements in knowledge.
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Feedback plays an indispensable role in pre-service teachers’ microteaching practice. It provides essential information about their microteaching performance, which is of great significance in their reflection and improvement. As AI and teaching analytics advance, feedback is no longer exclusively human-generated. AI technologies are increasingly capable of delivering feedback on microteaching performance. Yet, the effects of differing feedback types on the microteaching practices of pre-service teachers are not well documented. This study examines the impact of three types of feedback—observation-based, teaching analytics-based, and combined (a combination of both)—on pre-service teachers’ microteaching performance, scope of reflection, perceived usefulness, and satisfaction through an experimental research design. Sixty-five pre-service teachers voluntarily participated and were randomly assigned to three groups: observation-based feedback ( N = 21), teaching analytics-based feedback ( N = 23), and combined feedback ( N = 21). The findings indicate that combined feedback was most effective in enhancing pre-service teachers’ scope of teaching reflection, perceived usefulness of feedback, and satisfaction, but not on microteaching performance. However, when only teaching analytics-based feedback was provided, pre-service teachers perceived it as least useful and were least satisfied. The study discusses the implications of different types of feedback in teacher education.
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Ahuja, K., Kim, D., Xhakaj, F., Varga, V., Xie, A., Zhang, S., & Agarwal, Y. (2019). EduSense: Practical classroom sensing at scale. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies , 3 (3), 1–26.
Article Google Scholar
Banihashem, S. K., Noroozi, O., van Ginkel, S., Macfadyen, L. P., & Biemans, H. J. (2022). A systematic review of the role of learning analytics in enhancing feedback practices in higher education. Educational Research Review , 37 , 100489.
Bardach, L., Klassen, R. M., Durksen, T. L., Rushby, J. V., Bostwick, K. C., & Sheridan, L. (2021). The power of feedback and reflection: Testing an online scenario-based learning intervention for student teachers. Computers & Education , 169 , 104194.
Bollenbach, J., Halbrügge, S., Wederhake, L., Weibelzahl, M., & Wolf, L. (2024). Customer satisfaction at large charging parks: Expectation-disconfirmation theory for fast charging. Applied Energy , 365 , 122735.
Buczynski, S., & Hansen, C. B. (2010). Impact of professional development on teacher practice: Uncovering connections. Teaching and Teacher Education , 26 (3), 599–607.
Carless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education , 43 (8), 1315–1325.
Cavalcanti, A. P., Barbosa, A., Carvalho, R., Freitas, F., Tsai, Y. S., Gašević, D., & Mello, R. F. (2021). Automatic feedback in online learning environments: A systematic literature review. Computers and Education: Artificial Intelligence , 2 , 100027.
Google Scholar
Cavanaugh, S. (2022). Microteaching: Theoretical origins and practice. Educational Practice and Theory , 44 (1), 23–40.
Chan, C. K., & Lee, K. K. (2021). Reflection literacy: A multilevel perspective on the challenges of using reflections in higher education through a comprehensive literature review. Educational Research Review , 32 , 100376.
Chen, Z., Li, J., Liu, H., Wang, X., Wang, H., & Zheng, Q. (2023). Learning multi-scale features for speech emotion recognition with connection attention mechanism. Expert Systems with Applications, 214 , 118943.
Chernikova, O., Heitzmann, N., Fink, M. C., Timothy, V., Seidel, T., Fischer, F., & DFG Research group COSIMA. (2020). Facilitating diagnostic competences in higher education—a meta-analysis in medical and teacher education. Educational Psychology Review , 32 , 157–196.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Daltoè, T., Ruth-Herbein, E., Brucker, B., Jaekel, A. K., Trautwein, U., Fauth, B., & Göllner, R. (2024). Immersive insights: Unveiling the impact of 360-degree videos on preservice teachers’ classroom observation experiences and teaching-quality ratings. Computers & Education , 213 , 104976.
Dawson, P., Henderson, M., Mahoney, P., Phillips, M., Ryan, T., Boud, D., & Molloy, E. (2019). What makes for effective feedback: Staff and student perspectives. Assessment & Evaluation in Higher Education , 44 (1), 25–36.
Demszky, D., Liu, J., Hill, H. C., Jurafsky, D., & Piech, C. (2023). Can automated feedback improve teachers’ uptake of student ideas? Evidence from a randomized controlled trial in a large-scale online course (p. 01623737231169270). Educational Evaluation and Policy Analysis.
Floman, J. L., Hagelskamp, C., Brackett, M. A., & Rivers, S. E. (2017). Emotional bias in classroom observations: Within-rater positive emotion predicts favorable assessments of classroom quality. Journal of Psychoeducational Assessment , 35 (3), 291–301.
Fong, C. J., Patall, E. A., Vasquez, A. C., & Stautberg, S. (2019). A meta-analysis of negative feedback on intrinsic motivation. Educational Psychology Review , 31 , 121–162.
Fougnie, D., & Marois, R. (2006). Distinct capacity limits for attention and working memory: Evidence from attentive tracking and visual working memory paradigms. Psychological Science , 17 (6), 526–534.
Garino, A. (2020). Ready, willing and able: A model to explain successful use of feedback. Advances in Health Sciences Education , 25 (2), 337–361.
Garvey, B. (1978). Microteaching: Developing the concept for practical training. British Journal of Educational Technology, 9 (2), 142–149.
Goldberg, P., Sümer, Ö., Stürmer, K., Wagner, W., Göllner, R., Gerjets, P., & Trautwein, U. (2021). Attentive or not? Toward a machine learning approach to assessing students’ visible engagement in classroom instruction. Educational Psychology Review , 33 , 27–49.
Grainger, P. (2020). How do pre-service teacher education students respond to assessment feedback? Assessment & Evaluation in Higher Education , 45 (7), 913–925.
Harks, B., Rakoczy, K., Hattie, J., Besser, M., & Klieme, E. (2014). The effects of feedback on achievement, interest and self-evaluation: The role of feedback’s perceived usefulness. Educational Psychology , 34 (3), 269–290.
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research , 77 (1), 81–112.
Heitzmann, N., Fischer, F., & Fischer, M. R. (2018). Worked examples with errors: When self-explanation prompts hinder learning of teachers diagnostic competences on problem-based learning. Instructional Science , 46 , 245–271.
Hoban, G. (2000). Making practice problematic: Listening to student interviews as a catalyst for teacher reflection. Asia-Pacific Journal of Teacher Education , 28 (2), 133–147.
Hoban, G., & Hastings, G. (2006). Developing different forms of student feedback to promote teacher reflection: A 10-year collaboration. Teaching and Teacher Education , 22 (8), 1006–1019.
Huang, Y., Richter, E., Kleickmann, T., Wiepke, A., & Richter, D. (2021). Classroom complexity affects student teachers’ behavior in a VR classroom. Computers & Education , 163 , 104100.
Hussain, B., Riaz, A., & Shahzadi, U. (2019). Quantity of feedback provision: University students’ perceptions from gender perspectives and association with achievement. Review of Education Administration & Law , 2 (1), 1–9.
Ilgen, D. R., Fisher, C. D., & Taylor, M. S. (1979). Consequences of individual feedback on behavior in organizations. Journal of Applied Psychology , 64 (4), 349.
Ion, G., Sánchez Martí, A., & Agud Morell, I. (2019). Giving or receiving feedback: Which is more beneficial to students’ learning? Assessment & Evaluation in Higher Education , 44 (1), 124–138.
Jacobs, J., Scornavacco, K., Clevenger, C., Suresh, A., & Sumner, T. (2024). Automated feedback on discourse moves: Teachers’ perceived utility of a professional learning tool. Educational Technology Research and Development , 1–23.
Jacobs, J., Scornavacco, K., Harty, C., Suresh, A., Lai, V., & Sumner, T. (2022). Promoting rich discussions in mathematics classrooms: Using personalized, automated feedback to support reflection and instructional change. Teaching and Teacher Education , 112 , 103631.
Jiao, R., Wang, G., & Liu, L. (2010). The development of the vocational maturity questionnaire for pre-service teachers. Psychological Development and Education , (2), 183–188.
Johnson, M. (2016). Feedback effectiveness in professional learning contexts. Review of Education , 4 (2), 195–229.
King, P. E., Schrodt, P., & Weisel, J. J. (2009). The instructional feedback orientation scale: Conceptualizing and validating a new measure for assessing perceptions of instructional feedback. Communication Education , 58 (2), 235–261.
Kirkpatrick, D., & Kirkpatrick, J. (2006). Evaluating training programs: The four levels. Berrett-Koehler Publisher s.
Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin , 119 (2), 254.
Kwakman, K. (2003). Factors affecting teachers’ participation in professional learning activities. Teaching and Teacher Education , 19 (2), 149–170.
Latham, G. P., & Locke, E. A. (1991). Self-regulation through goal setting. Organizational Behavior and Human Decision Processes , 50 (2), 212–247.
Link, S., Mehrzad, M., & Rahimi, M. (2022). Impact of automated writing evaluation on teacher feedback, student revision, and writing improvement. Computer Assisted Language Learning , 35 (4), 605–634.
Lipnevich, A. A., & Panadero, E. (2021). December). A review of feedback models and theories: Descriptions, definitions, and conclusions. Frontiers in Education , 6 , 720195.
Marcos, J. J. M., & Tillema, H. (2006). Studying studies on teacher reflection and action: An appraisal of research contributions. Educational Research Review , 1 (2), 112–132.
Mayordomo, R. M., Espasa, A., Guasch, T., & Martínez-Melo, M. (2022). Perception of online feedback and its impact on cognitive and emotional engagement with feedback. Education and Information Technologies , 27 (6), 7947–7971.
McGarr, O. (2021). The use of virtual simulations in teacher education to develop pre-service teachers’ behaviour and classroom management skills: Implications for reflective practice. Journal of Education for Teaching , 47 (2), 274–286.
Mohamed, M., Rashid, R. A., & Alqaryouti, M. H. (2022). Conceptualizing the complexity of reflective practice in education. Frontiers in Psychology , 13 , 1008234.
Nagro, S. A. (2020). Reflecting on others before reflecting on self: Using video evidence to guide teacher candidates’ reflective practices. Journal of Teacher Education , 71 (4), 420–433.
Narciss, S. (2008). Feedback strategies for interactive learning tasks. In J. M. Spector, M. D. Merrill, van J. J. G. Merrienboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd ed., pp. 125–144). Lawrence Erlbaum Associates.
Narciss, S. (2013). Designing and evaluating tutoring feedback strategies for digital learning. Digital Education Review , 23 , 7–26.
Ndukwe, I. G., & Daniel, B. K. (2020). Teaching analytics, value and tools for teacher data literacy: A systematic and tripartite approach. International Journal of Educational Technology in Higher Education , 17 , 1–31.
Nelson, M. M., & Schunn, C. D. (2009). The nature of feedback: How different types of peer feedback affect writing performance. Instructional Science, 37 , 375–401.
Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies , 28 (4), 4221–4241.
Panadero, E., & Jonsson, A. (2013). The use of scoring rubrics for formative assessment purposes revisited: A review. Educational Research Review , 9 , 129–144.
Parsons, M., & Stephenson, M. (2005). Developing reflective practice in student teachers: Collaboration and critical partnerships. Teachers and Teaching , 11 , 116–195.
Patra, I., Alazemi, A., Al-Jamal, D., & Gheisari, A. (2022). The effectiveness of teachers’ written and verbal corrective feedback (CF) during formative assessment (FA) on male language learners’ academic anxiety (AA), academic performance (AP), and attitude toward learning (ATL). Language Testing in Asia , 12 (1), 1–21.
Perlberg, A. (1970). Microteaching: A new procedure to improve teaching and training. British Journal of Educational Technology , 1 (1), 35–43.
Pourdana, N., Nour, P., & Yousefi, F. (2021). Investigating metalinguistic written corrective feedback focused on EFL learners’ discourse markers accuracy in mobile-mediated context. Asian-Pacific Journal of Second and Foreign Language Education , 6 , 1–18.
Prilop, C. N., Weber, K. E., & Kleinknecht, M. (2020). Effects of digital video-based feedback environments on pre-service teachers’ feedback competence. Computers in Human Behavior , 102 , 120–131.
Prilop, C. N., Weber, K. E., & Kleinknecht, M. (2021). The role of expert feedback in the development of pre-service teachers’ professional vision of classroom management in an online blended learning environment. Teaching and Teacher Education , 99 , 103276. https://doi.org/10.1016/j.tate.2020.103276
Quddus, L., Khalid, M., & Khan, W. A., M (2019). Teachers’ self-assessment of their teaching effectiveness at higher secondary level in Pakistan: A case study. KnE Social Sciences , 3 (22), 807–817.
Rakoczy, K., Pinger, P., Hochweber, J., Klieme, E., Schütze, B., & Besser, M. (2019). Formative assessment in mathematics: Mediated by feedback’s perceived usefulness and students’ self-efficacy. Learning and Instruction , 60 , 154–165.
Ryan, T., Henderson, M., Ryan, K., & Kennedy, G. (2023). Identifying the components of effective learner-centred feedback information. Teaching in Higher Education , 28 (7), 1565–1582.
Sancar, R., Atal, D., & Deryakulu, D. (2021). A new framework for teachers’ professional development. Teaching and Teacher Education , 101 , 103305.
Scheeler, M. C., Ruhl, K. L., & McAfee, J. K. (2004). Providing performance feedback to teachers: A review. Teacher Education and Special Education , 27 (4), 396–407.
Schön, D. A. (1987). Educating the reflective practitioner: Toward a new design for teaching and learning in the professions. Jossey-Bass .
Sergis, S., & Sampson, D. G. (2017). Teaching and learning analytics to support teacher inquiry: A systematic literature review. Learning Analytics: Fundaments, Applications, and Trends: A View of the Current State of the Art to Enhance e-Learning , 25–63.
Sergis, S., Sampson, D. G., Rodríguez-Triana, M. J., Gillet, D., Pelliccione, L., & de Jong, T. (2019). Using educational data from teaching and learning to inform teachers’ reflective educational design in inquiry-based STEM education. Computers in Human Behavior , 92 , 724–738.
Strijbos, J. W., Narciss, S., & Dünnebier, K. (2010). Peer feedback content and sender’s competence level in academic writing revision tasks: Are they critical for feedback perceptions and efficiency? Learning and Instruction , 20 (4), 291–303.
Suraworachet, W., Zhou, Q., & Cukurova, M. (2023). Impact of combining human and analytics feedback on students’ engagement with, and performance in, reflective writing tasks. International Journal of Educational Technology in Higher Education , 20 (1), 1–24.
Tang, J., Zhang, P., & Zhang, J. (2023). Design and implementation of intelligent evaluation system based on pattern recognition for microteaching skills training. International Journal of Innovative Computing Information and Control , 1 (19), 153–162.
Thurlings, M., Vermeulen, M., Bastiaens, T., & Stijnen, S. (2013). Understanding feedback: A learning theory perspective. Educational Research Review , 9 , 1–15.
Tian Lan, Z., Zhizhen, Chen, & Yujiao (2015). A study on the Effect of Video in promoting pre-service teachers’ reflection on Microteaching. Modern Educational Technology , 10 , 54–60. (In Chinese).
Van de Ridder, J. M., Peters, C. M., Stokking, K. M., de Ru, J. A., & Ten Cate, O. T. J. (2015). Framing of feedback impacts student’s satisfaction, self-efficacy and performance. Advances in Health Sciences Education , 20 , 803–816.
Van der Kleij, F. M., & Lipnevich, A. A. (2021). Student perceptions of assessment feedback: A critical scoping review and call for research. Educational Assessment Evaluation and Accountability , 33 , 345–373.
Wang, M., Luo, L., Chen, Z., Zheng, Q., Li, J., & Gao, W. (2022, December). Intelligent multimodal analysis framework for teacher-student interaction. In IEEE International Conference on Intelligent Education and Intelligent Research (IEIR) (pp. 65–70).
Wang, Y. S. (2003). Assessment of learner satisfaction with asynchronous electronic learning systems. Information & Management , 41 (1), 75–86. https://doi.org/10.1016/s0378-7206(03)00028-4
Wang, Z., & Han, F. (2022). The effects of teacher feedback and automated feedback on cognitive and psychological aspects of foreign language writing: A mixed-methods research. Frontiers in Psychology , 13 , 909802.
Warner, R., & Miller, J. (2015). Cultural dimensions of feedback at an Australian university: A study of international students with English as an additional language. Higher Education Research & Development , 34 (2), 420–435.
Weaver, M. R. (2006). Do students value feedback? Student perceptions of tutors’ written responses. Assessment & Evaluation in Higher Education , 31 (3), 379–394.
Weng, X., Ng, O. L., & Chiu, T. K. (2023). Competency development of pre-service teachers during video-based learning: A systematic literature review and meta-analysis. Computers & Education , 199 , 104790.
Winstone, N., Boud, D., Dawson, P., & Heron, M. (2022). From feedback-as-information to feedback-as-process: A linguistic analysis of the feedback literature. Assessment & Evaluation in Higher Education , 47 (2), 213–230. https://doi.org/10.1080/02602938.2021.1902467
Yu Guoliang, X., Tao, & Shen Joliang. (1995). Teachers’ teaching efficacy: A study on its structure and influencing factors. Journal of Psychology (02). (In Chinese).
Zhang, Y., Chen, H., Pi, Z., & Yang, J. (2024). Interactive equality in peer assessment: The impacts on preservice teachers’ technology-enhanced learning design and feedback uptake. Teaching and Teacher Education , 138 , 104408.
Zheng, Q., Chen, Z., Wang, M., Shi, Y., Chen, S., & Liu, Z. (2024). Automated multi-mode teaching behavior analysis: A pipeline based event segmentation and description. IEEE Transactions on Learning Technologies, 17 , 1717–1733.
Zhou, L., Gao, Y., Hu, J., Tu, X., & Zhang, X. (2022). Effects of perceived teacher support on motivation and engagement amongst Chinese college students: Need satisfaction as the mediator. Frontiers in Psychology , 13 , 949495.
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We would like to express our sincere gratitude to all the colleagues, teachers, and pre-service teachers who participated in this study.
This work was supported by the National Natural Science Foundation of China (Project No. 62077022), Central China Normal University (Project No. CCNU24ai013), the Postgraduate Education Innovation Funding Project of Central China Normal University (Project No. 30106230470), and the China Scholarship Council (CSC202306770066).
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Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, Hubei, 430079, China
Mengke Wang, Taotao Long, Yawen Shi & Zengzhao Chen
School of Mathematics and Statistics, Central China Normal University, Wuhan, Hubei, 430079, China
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Correspondence to Zengzhao Chen .
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The study involving participants was reviewed and approved by the Ethics Committee of the Faculty of Artificial Intelligence in Education, Central China Normal University.
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Microteaching performance evaluation
Microteaching Performance Evaluation | ||
---|---|---|
Dimension | Content | Score |
Teaching objective | Objectives are clearly defined, aligning with curriculum standards and students’ actual needs. | 3 |
Teaching content | Key concepts are clearly articulated; Difficult topics are appropriately addressed. Attention is paid to students’ existing knowledge and experiences, with a focus on skills development.Classroom interaction is emphasized, and knowledge is accurately explained. | 5 |
Teaching methods | The instructional content is processed in line with the philosophy of the new curriculum standards, effectively implementing teaching objectives. Approaches to autonomous, inquiry-based, and collaborative learning are highlighted, reflecting diverse learning methods and enabling effective teacher-student interaction. | 7 |
Teaching process | Overall instructional planning is logical, with well-organized phases and clear structure. Textbooks are used creatively; distinctive teaching features are emphasized. Multimedia materials are used appropriately to supplement instruction, and teaching demonstrations are standardized. | 7 |
Teaching quality | The teacher displays a natural and friendly demeanour, appropriate conduct, and pays attention to eye contact. Instructional language is standard, precise, lively, and concise. | 4 |
Teaching effectiveness | Teaching tasks are completed on time, with a high level of objective achievement. | 4 |
Teaching innovation | The teaching process is creative; textbooks are used innovatively. Teaching methods are flexible and diverse, with distinctive features. | 5 |
Blackboard content alignment | Blackboard writing reflects the intent of the teaching design, emphasizing key and difficult points and successfully engaging student initiative and enthusiasm. | 4 |
Blackboard composition | Blackboard writing designs are clever and creative, with natural layouts and visually intuitive illustrations that significantly assist the teaching process. | 4 |
Blackboard writing | Blackboard writing is quick and smooth, with appropriately sized and shaped characters, a clear and neat presentation, and a standard and aesthetically pleasing appearance. | 2 |
| 45 |
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Wang, M., Long, T., Li, N. et al. The impact of different types of feedback on pre-service teachers’ microteaching practice and perceptions. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-13024-z
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Published : 13 September 2024
DOI : https://doi.org/10.1007/s10639-024-13024-z
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Simple hypothesis. A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, "Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking. 4.
An empirical hypothesis is the opposite of a logical hypothesis. It is a hypothesis that is currently being tested using scientific analysis. We can also call this a 'working hypothesis'. We can to separate research into two types: theoretical and empirical. Theoretical research relies on logic and thought experiments.
It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis. 7.
Examples. A research hypothesis, in its plural form "hypotheses," is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.
Definition: Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation. Hypothesis is often used in scientific research to guide the design of experiments ...
A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process. Consider a study designed to examine the relationship between sleep deprivation and test ...
These different types of research hypotheses provide researchers with various options to explore and test the relationships between variables in a thesis. The choice of hypothesis depends on the research question, the nature of the variables, and the available data.
A research hypothesis helps test theories. A hypothesis plays a pivotal role in the scientific method by providing a basis for testing existing theories. For example, a hypothesis might test the predictive power of a psychological theory on human behavior. It serves as a great platform for investigation activities.
5. Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable. If a first-year student starts attending more lectures, then their exam scores will improve.
To form a solid theory, the vital first step is creating a hypothesis. See the various types of hypotheses and how they can lead you on the path to discovery. To form a solid theory, the vital first step is creating a hypothesis. ... Different Types in Science and Research By Jennifer Betts, B.A. , Staff Writer . Updated September 24, 2021 ...
However, both research questions and hypotheses serve different purposes and can be beneficial when used together. Research Questions Clarify the research's aim (Farrugia et al., 2010) ... Types of Research Hypothesis. Y- and X-Centered Research Designs Y-Centered Research Design Hypothesis In a Y-centered research design, the focus is on the ...
There are seven different types of research hypotheses. Simple Hypothesis. A simple hypothesis predicts the relationship between a single dependent variable and a single independent variable. Complex Hypothesis. A complex hypothesis predicts the relationship between two or more independent and dependent variables. Directional Hypothesis.
Null Hypothesis. A hypothesis predicts the relationship between independent and dependent variables. An independent variable is something you change as part of an experiment such as the amount of water given to a plant. A dependent variable is something that is predicted to change as a result such as the growth rate of a plant.
HYPOTHESIS TESTING. A clinical trial begins with an assumption or belief, and then proceeds to either prove or disprove this assumption. In statistical terms, this belief or assumption is known as a hypothesis. Counterintuitively, what the researcher believes in (or is trying to prove) is called the "alternate" hypothesis, and the opposite ...
This refers to a lack of relationship between different variables. For example, plants would grow irrespective of the source of water, natural or artificial. It proposes a negative statement to support the researcher's discovery, showing that no relationship exists between the two variables. 7. Alternative Hypothesis.
A hypothesis is defined as a testable prediction, and is used primarily in scientific experiments as a potential or predicted outcome that scientists attempt to prove or disprove (Atkinson et al., 2021; Tan, 2022).. In my types of hypothesis article, I outlined 13 different hypotheses, including the directional hypothesis (which makes a prediction about an effect of a treatment will be ...
A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes - specificity, clarity and testability. Let's take a look at these more closely.
INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...
In this segment, we shall discover the different types of hypotheses and understand the role they play in hypothesis testing. Alternative Hypothesis . Alternative Hypothesis (H1) or the research hypothesis states that there is a relationship between two variables (where one variable affects the other).
A hypothesis is a tentative relationship between two or more variables. These variables are related to various aspects of the research inquiry. A hypothesis is a testable prediction. It can be a false or a true statement that is tested in the research to check its authenticity. A researcher has to explore various aspects of the research topic.
There are four types of hypothesis scientists can use in their experimental designs: null, directional, nondirectional and causal hypotheses. The hypothesis chosen by researchers will influence the design of the study or experiment they go on to perform, and will direct the way that the study's results are communicated in academic papers.
Hypothesis is a prediction of the outcome of a study. Hypotheses are drawn from theories and research questions or from direct observations. In fact, a research problem can be formulated as a hypothesis. To test the hypothesis we need to formulate it in terms that can actually be analysed with statistical tools.
Hypothesis is a hypothesis is fundamental concept in the world of research and statistics. It is a testable statement that explains what is happening or observed. It proposes the relation between the various participating variables. Hypothesis is also called Theory, Thesis, Guess, Assumption, or Suggestion. Hypothesis creates a structure that ...
Feedback plays an indispensable role in pre-service teachers' microteaching practice. It provides essential information about their microteaching performance, which is of great significance in their reflection and improvement. As AI and teaching analytics advance, feedback is no longer exclusively human-generated. AI technologies are increasingly capable of delivering feedback on ...
The elongated structure of dry-type bushings makes them susceptible to stress concentration under external loads. In this study, a three-dimensional force field analysis model of the transformer-dry-type bushing system was established to investigate the distribution of the primary stresses in the dry-type bushing. This aims to reveal the weak areas of the bushing under external forces.