مطالعات برنامه درسی

مطالعات برنامه درسی

بررسی تفاوت تاثیر بازخورد چت جی پی تی با بازخورد معلم بر درگیری دانش‌آموزان در فرایند یادگیری و بازده های شناختی

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشجوی دکترای تکنولوژی آموزشی. گروه علوم تربیتی، دانشکده علوم انسانی. دانشگاه تربیت مدرس. تهران. ایران
2 گروه تعلیم و تربیت، دانشکده علوم انسانی، دانشگاه تربیت مدرس، تهران، ایران
3 استاد گروه علوم تربیتی. دانشکده علوم انسانی. دانشگاه تربیت مدرس. تهران. ایران
4 استاد گروه اطلاعات و دانش شناسی. دانشکده مدیریت و اقتصاد. دانشگاه تربیت مدرس. تهران. ایران
چکیده
پژوهش حاضر با هدف تعیین تاثیر بازخورد مبتنی بر چت‌جی‌پی‌تی و بازخورد معلم بر درگیری دانش‌آموزان در فرایند یادگیری و دستیابی به اهداف شناختی در درس ریاضی انجام شد. روش مطالعه، شبه‌آزمایشی با طرح پیش‌آزمون–پس‌آزمون بود. نمونه: 68 دانش‌آموزان پایه نهم بود که به‌صورت تصادفی خوشه‌ای مرحله‌ای در دو گروه بازخورد گمارده شدند. ابزارهای پژوهش، پرسشنامه درگیری تحصیلی ریو و آزمون معلم ساخته عملکرد شناختی بود. یافته‌ها با استفاده از آزمون ناپارامتریک یومن‌ویتنی تحلیل شدند، نشان دادند که میانگین نمرات درگیری تحصیلی در گروه بازخورد چت‌جی‌پی‌تی به‌طور معناداری بالاتر از گروه بازخورد معلم بود. در حوزه یادگیری شناختی نیز بازخورد چت‌جی‌پی‌تی در سطوح تحلیل و ارزیابی عملکرد بهتری نسبت به معلم نشان داد. هرچند در سطوح دانش، فهم و کاربرد تفاوت معناداری مشاهده نشد. بااین‌حال، نمره کل یادگیری شناختی با برتری گروه بازخورد چت‌جی‌پی‌تی تفاوت معناداری داشت. بنابراین، چت‌جی‌پی‌تی به‌عنوان یک ابزار مکمل می‌تواند اثربخشی مشابه یا فراتر از بازخورد معلم در ارتقای درگیری تحصیلی و یادگیری شناختی فراهم کند.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Examining the Effectiveness of ChatGPT Feedback Compared to Teacher Feedback on Student Engagement and Cognitive Outcomes

نویسندگان English

Rezvan Nazari 1
Esmaeil Azimi 2
Javad Hatami 3
Mohammad Hasanzadeh 4
1 PhD student in Educational Technology. Department of Educational Sciences, Faculty of Humanities. Tarbiat Modares University. Tehran. Iran
2 Department of Education, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran
3 Professor, Department of Educational Sciences. Faculty of Humanities. Tarbiat Modares University. Tehran. Iran
4 Professor, Department of Information and Knowledge. Faculty of Management and Economics. Tarbiat Modares University. Tehran. Iran
چکیده English

The present study aimed todetermine the extent of the impact of ChatGPT-based feedback versus teacher feedback on student engagement in the learning process and the achievement of cognitive objectives in mathematics. The research method was quasi-experimental with a pretest-posttest design. The study sample consisted of 68 ninth-grade students who were randomly assigned to two groups—ChatGPT feedback and teacher feedback—using a staged cluster sampling method. The research instruments included Reeve’s Academic Engagement Questionnaire, and agentic engagement, as well as a teacher-made cognitive performance test. The findings, analyzed using the non-parametric Mann-Whitney U test, revealed that the mean scores of the four dimensions of academic engagement in the ChatGPT feedback group were significantly higher than those in the teacher feedback group. In the domain of cognitive learning, ChatGPT feedback demonstrated superior performance at the analysis and evaluation levels compared to teacher feedback. However, no significant differences were observed at the knowledge, comprehension, and application levels. Nevertheless, the total cognitive learning score showed a significant advantage for the ChatGPT feedback group. Accordingly, ChatGPT can provide effectiveness similar to or even surpassing teacher feedback in enhancing academic engagement and cognitive learning, and it can be utilized as a reliable complementary tool in educational processes.

کلیدواژه‌ها English

Feedback
ChatGPT
Academic Engagement
Cognitive Learning
Mathematics
Alcívar, K. E. L.; Carrera, E. N. A.; Zambrano, M. E. S.; & Bravo, M. A. Z. (2020). Feedback and Improvement on Teaching-Learning Process for Basic General Education Students. International Journal of Social Sciences, 3(1), 39-46.
Ali, D., Fatemi, Y., Boskabadi, E., Nikfar, M., Ugwuoke, J., & Ali, H. (2024). ChatGPT in teaching and learning: A systematic review. Education Sciences, 14(6), 643.
Cao, S., & Zhong, L. (2023). Exploring the effectiveness of ChatGPT-based feedback compared with teacher feedback and self-feedback: Evidence from Chinese to English translation. arXiv preprint arXiv:2309.01645.
Chan, C. K. Y., & Tsi, L. H. (2023). The AI revolution in education: will AI replace or assist teachers in higher education?. arXiv preprint arXiv:2305.01185.
Cheng, X. (2024). Engaging secondary school students with peer feedback in L2 classrooms: A mixed-methods study. Studies in Educational Research, 12(3), 215–232.
Choi, W. (2023). Assessment of the capacity of ChatGPT as a self-learning tool in medical pharmacology: a study using MCQs. BMC Medical Education, 23(1), 864.
De Castro, C. A. (2023). A discussion about the impact of ChatGPT in education: Benefits and concerns. Journal of Business Theory and Practice, 11(2), 28.
Deci, E. L., & Ryan, R. M. (2000). The" what" and" why" of goal pursuits: Human needs and the self-determination of behavior. Psychological inquiry, 11(4), 227-268.
Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2024). Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies. Computers & Education, 105224.
Ertesvåg, S. K., Vaaland, G. S., & Lerkkanen, M. K. (2022). Enhancing upper secondary students’ engagement and learning through the INTERACT online, video-based teacher coaching intervention: Protocol for a mixed-methods cluster randomized controlled trial and process evaluation. International Journal of Educational Research, 114, 102013.
Fathi, F., Fathi Vajargah, K., Jafari, J., & Vahidi Asl, M. (2025). Rethinking curriculum in the age of artificial intelligence: A New Approach in The Multicontextualisation movement. Curriculum Studies, 19 (75), 31–52.
Gupta, U., & Zheng, R. Z. (2020). Cognitive Load in Solving Mathematics Problems: Validating the Role of Motivation and the Interaction among Prior Knowledge, Worked Examples, and Task Difficulty. European Journal of STEM Education, 5(1), 5.
Han, J., & Li, M. (2024). Exploring ChatGPT-supported teacher feedback in the EFL context. System, 126, 103502.
Hatami, J., Rezaei, E., Maleki, M., & Najafi Zaman, L. (2020). Assessment and evaluation in electronic learning. Tarbiat Modares University. [In Persian]
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of educational research, 77(1), 81-112.
Hijazi, A. (2024). Unveiling the Impact of ChatGPT on Mathematical Dialogue and Engagement: A Thematic Case Study.
Hilčenko, S. (2017). How Generation “Z” Learns Better?. European Journal of Social Science Education and Research, 4(6), 379-389.
Huang, H., Liang, Z., Fang, Z., Wang, Z., Chen, M., Hong, Y.,... & Shang, P. (2024, April). A Concise Review of Long Context in Large Language Models. In Proceedings of the International Conference on Algorithms, Software Engineering, and Network Security (pp. 563-566).
Jayatissa, K. A. D. U. (2023). Generation Z–A new lifeline: A systematic literature review. Sri Lanka Journal of Social Sciences and Humanities, 3(2).
Jeong, S., Clyburn, J., Bhatia, N. S., McCourt, J., & Lemons, P. P. (2022). Student thinking in the professional development of college biology instructors: An analysis through the lens of sociocultural theory. CBE—Life Sciences Education, 21(2), ar30.
Jukiewicz, M., & Wyrwa, M. (2025). Can chatgpt replace the teacher in assessment? a review of research on the use of large language models in grading and providing feedback. Preprints URL: https://doi. org/10.20944/preprints202509, 1233, v1.
Karthika, V., & Alamelu, R. (2024, August). E-mentoring: A mathematical cohort for the Gen Z higher education learners. In AIP Conference Proceedings (Vol. 3180, No. 1, p. 050002). AIP Publishing LLC.
Kim, M., & Adlof, L. (2023). Adapting to the Future: Chatgpt as a Means for Supporting Constructivist Learning Environments. TechTrends, 1-10.
Latifi, S., Noroozi, O., & Talaee, E. (2021a). Peer feedback or peer feedforward? Enhancing students’ argumentative peer learning processes and outcomes. British Journal of Educational Technology, 52(2), 768–784. https://doi.org/10.1111/bjet.13054
Lelepary, H. L., Rachmawati, R., Zani, B. N., & Maharjan, K. (2023). GPT Chat: Opportunities and Challenges in the Learning Process of Arabic Language in Higher Education. JILTECH: Journal International of Lingua & Technology, 2(1).
Li, L., Ma, Z., Fan, L., Lee, S., Yu, H., & Hemphill, L. (2023). Chatgpt in education: A discourse analysis of worries and concerns on social media. arXiv preprint arXiv:2305.02201.
Lipnevich, A. A., & Panadero, E. (2021, December). A review of feedback models and theories: Descriptions, definitions, and conclusions. In Frontiers in Education (Vol. 6, p. 720195). Frontiers.
Liu, F., & Luo, W. (2025). Exploring the effects of online peer feedback on tertiary students’ peer feedback literacy in English writing: Focusing on design elements. Studies in Educational Evaluation, 87, 101516.
Lundberg, S. (2024). ChatGPT vs. Teacher Feedback Provision: An investigation on the efficacy of ChatGPT feedback provision on written production across proficiency levels.
Mangiapanello, K. A., & Hemmes, N. S. (2015). An analysis of feedback from a behavior analytic perspective. The Behavior Analyst, 38(1), 51-75.
Maula, S. R., Aprillian, S. D., Rachman, A. W., & Azman, M. N. M. (2024). Ketergantungan Mahasiswa Universitas Jember Terhadap Artificial Intelligence (AI). ALADALAH: Jurnal Politik, Sosial, Hukum dan Humaniora, 2(1), 01-14.
Memarian, B., & Doleck, T. (2023). ChatGPT in education: Methods, potentials, and limitations. Computers in Human Behavior: Artificial Humans1(2), 100022.
Moser, A. (2020). Written corrective feedback: The role of learner engagement. Cham: Springer.
Muñoz, S. A. S., Gayoso, G. G., Huambo, A. C., Tapia, R. D. C., Incaluque, J. L., Aguila, O. E. P.,... & Arias-Gonzáles, J. L. (2023). Examining the impacts of Chatgpt on student motivation and engagement. Social Space, 23(1), 1-27.
Nazari, R., & Hatami, J. (2022). Feedback in online learning assessment. Paper presented at the 15th National and 9th International Conference on E-Learning and E-Teaching of Iran, Tehran, Iran. [In Persian]
Nematollahi, N., Khademi Ashkezari, K., Moluk, M., Seraji, F., Abdollahi, A., & Farzaneh, F. (2025). Analyzing artificial intelligence education programs for upper primary school students: A scoping review Curriculum Studies, 20 (77), 161–200
Nie, A., Chandak, Y., Suzara, M., Malik, A., Woodrow, J., Peng, M.,... & Piech, C. (2024). The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters’ Exam Performances (No. qy8zd). Center for Open Science.
Phan, H. P., Ngu, B. H., & Yeung, A. S. (2017). Achieving optimal best: Instructional efficiency and the use of cognitive load theory in mathematical problem solving. Educational Psychology Review, 29(4), 667-692.
Prananta, A. W., Susanto, N., & Raule, J. H. (2023). Transforming Education and Learning through Chatgpt: A Systematic Literature Review. Jurnal Penelitian Pendidikan IPA, 9(11), 1031-1037.
Qian, Y. (2025). Pedagogical Applications of Generative AI in Higher Education: A Systematic Review of the Field. TechTrends, 1-16.
Rasul, T., Nair, S., Kalendra, D., Robin, M., de Oliveira Santini, F., Ladeira, W. J.,... & Heathcote, L. (2023). The role of Chatgpt in higher education: Benefits, challenges, and future research directions. Journal of Applied Learning and Teaching, 6(1).
Reeve, J., & Tseng, C. M. (2011). Agency as a fourth aspect of students’ engagement during learning activities. Contemporary Educational Psychology, 36(4), 257-267
Saracostti, M., De Toro, X., Miranda, H., Miranda-Zapara, E., Lara, L., & Hernández, M. T. (2024, July). Associations between contextual factors and school engagement: a longitudinal study of profiles. In Frontiers in Education (Vol. 9, p. 1365789). Frontiers Media SA.
Shang, H. F. (2022). Exploring online peer feedback and automated corrective feedback on EFL writing performance.Interactive Learning Environments, 30(1), 4–16.
Siregar, F. H., Hasmayni, B., & Lubis, A. H. (2023). The Analysis of Chatgpt Usage Impact on Learning Motivation among Scout Students. International Journal of Research and Review, 10(7), 632-638.
Solak, E. (2024). Examining writing feedback dynamics from CHATGPT AI and human educators: A comparative study. Педагогика, 96(7), 955-970.
Solovey, O. Z. (2024). Comparing Peer, ChatGPT, and Teacher Corrective Feedback in EFL Writing: Students' Perceptions and Preferences. Technology in Language Teaching & Learning, 6(3), n3.
Steiss, J., Tate, T., Graham, S., Cruz, J., Hebert, M., Wang, J.,... & Olson, C. B. (2024). Comparing the quality of human and ChatGPT feedback of students’ writing. Learning and Instruction, 91, 101894.
Steiss, J., Tate, T., Graham, S., Cruz, J., Hebert, M., Wang, J.,... & Olson, C. B. (2024). Comparing the quality of human and ChatGPT feedback of students’ writing. Learning and Instruction, 91, 101894.
Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in science education, 48(6), 1273-1296.
Vasileva, O., & Balyasnikova, N. (2019). (Re) introducing Vygotsky’s thought: From historical overview to contemporary psychology. Frontiers in psychology, 10, 1515.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (Vol. 86). Harvard university press.
Wang, J., & Fan, W. (2025). The effect of Chatgpt on students’ learning performance, learning perception, and higher-order thinking: insights from a meta-analysis. Humanities and Social Sciences Communications, 12(1), 1-21.
Wang, T., Zhou, K., & Zhu, Q. (2023). Can ChatGPT provide quality feedback on student essays? Computers & Education: Artificial Intelligence.
Wardat, Y., Tashtoush, M. A., AlAli, R., & Jarrah, A. M. (2023). Chatgpt: A revolutionary tool for teaching and learning mathematics. Eurasia Journal of Mathematics, Science and Technology Education, 19(7), em2286.
Woreta, G. T. (2024). Predictors of academic engagement of high school students: Academic socialization and motivational beliefs. Frontiers in Psychology, 15, Article 1347163. https://doi.org/10.3389/fpsyg.2024.1347163
Xie, T., Pentina, I., & Hancock, T. (2023). Friend, mentor, lover: does chatbot engagement lead to psychological dependence?. Journal of Service Management.
Xu, Q., Liu, Y., & Li, X. (2025). Unlocking student potential: How AI-driven personalized feedback shapes goal achievement, self-efficacy, and learning engagement through a self-determination lens. Learning and Motivation, 91, 102138.
Xu, X., Shi, Z., Bos, N. A., & Wu, H. (2023). Student engagement and learning outcomes: an empirical study applying a four-dimensional framework. Medical Education Online, 28(1), 2268347.
Youssef, E., Medhat, M., Abdellatif, S., & Al Malek, M. (2024). Examining the effect of ChatGPT usage on students’ academic learning and achievement: A survey-based study in Ajman, UAE. Computers and Education: Artificial Intelligence, 7, 100316.
Zeevy-Solovey, O. (2024). Comparing peer, ChatGPT, and teacher corrective feedback in EFL writing: Students' perceptions and preferences. Technology in Language Teaching & Learning, 6(3), 1482-1482
Zhan, Y., Wan, Z. H., & Sun, D. (2022). Online formative peer feedback in Chinese contexts at the tertiary level: A critical review on its design, impacts and influencing factors. Computers & Education, 176, 104341. https://doi.org/10.1016/j.compedu.2021.104341
Zhang, Y., Schunn, C. D., & Wu, Y. (2024). What does it mean to be good at peer reviewing? A multidimensional scaling and cluster analysis study of behavioral indicators of peer feedback literacy. International Journal of Educational Technology in Higher Education, 21(1), 26.
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into practice, 41(2), 64-70.
Zou, S., Guo, K., Wang, J., & Liu, Y. (2024). Investigating students’ uptake of teacher-and ChatGPT-generated feedback in EFL writing: A comparison study. Computer Assisted Language Learning, 1-30.

  • تاریخ دریافت 04 آبان 1404
  • تاریخ بازنگری 11 آذر 1404
  • تاریخ پذیرش 05 بهمن 1404