Retroalimentación generada por inteligencia artificial y autorregulación del aprendizaje en estudiantes universitarios
Palabras clave:
Inteligencia artificial, educación superior, aprendizaje activo, tecnología educativa, (Tesauro UNESCO).
Resumen
El objetivo fue analizar la evidencia empírica sobre la retroalimentación generada o mediada por inteligencia artificial y su relación con la autorregulación del aprendizaje universitario. Se realizó una revisión sistemática de publicaciones entre 2021 y 2026 en OpenAlex, ERIC y DOAJ. Se aplicaron criterios de elegibilidad, una evaluación de la calidad metodológica y se integraron por una síntesis narrativa. Se trabajó con un total de 38 estudios de 2300 identificados. Como resultado predominaron los estudios en enseñanza de las lenguas y escritura académica, muestras pequeñas y medidas mediante autoinforme. La retroalimentación directa mediante inteligencia artificial se asoció con mejoras en el desempeño inmediato, las modalidades reflexivas e híbridas mostraron mayor frecuencia en los resultados favorables vinculados con la autoevaluación y el juicio formativo. Los hallazgos sugieren que los beneficios de la retroalimentación mediante inteligencia artificial dependen más del diseño de interacción del estudiante que de la herramienta utilizada.
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Citas
Afzaal, M., Zia, A., Nouri, J., & Fors, U. (2024). Informative feedback and explainable AI-based recommendations to support students’ self-regulation. Technology, Knowledge and Learning, 29, 331–354. https://doi.org/10.1007/s10758-023-09650-0
Alaoui Mhamdi, N. (2026). AI-mediated feedback in English learning: Moroccan graduate students’ accounts of motivation, autonomy, and trust conditions. Computers and Education Open, 10, 100356. https://doi.org/10.1016/j.caeo.2026.100356
Alzahrani, M. A. (2026). AI-based feedback in academic writing: Insights from EFL undergraduate students at Saudi higher education. International Journal of Language and Literary Studies, 8(5), 50–68. https://doi.org/10.36892/ijlls.v8i5.2737
Apriani, E., Cardoso, L., Obaid, A. J., Muthmainnah, M., Wijayanti, E., Esmianti, F., & Supardan, D. (2024). Impact of AI-powered chatbots on EFL students’ writing skills, self-efficacy, and self-regulation: A mixed-methods study. Global Educational Research Review, 1(2), 57–72. https://doi.org/10.71380/GERR-08-2024-8
Ates, H. (2026). Human-centered GenAI feedback design in higher education: A multisite experiment on direct, reflective, and hybrid approaches to scientific argumentation. International Journal of Educational Technology in Higher Education, 23, Article 38. https://doi.org/10.1186/s41239-026-00614-9
Campos, M. (2025). AI-assisted feedback in CLIL courses as a self-regulated language learning mechanism: Students’ perceptions and experiences. European Public & Social Innovation Review, 10, 1–14. https://doi.org/10.31637/epsir-2025-1568
Carless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315–1325. https://doi.org/10.1080/02602938.2018.1463354
Chen, M.-R. A. (2026). Generative AI, visual scaffolds, and metacognition in EFL writing. Language Learning & Technology, 30(1), 1–26. https://doi.org/10.64152/10125/73695
Dai, Z. (2026). Rethinking AI-assisted writing instruction: Feedback literacy scripts, calibration training, and student writing development. Frontiers in Psychology, 17, 1829268. https://doi.org/10.3389/fpsyg.2026.1829268
Gu, J., Chen, J., & Yan, Z. (2026). Fostering feedback literacy by scaffolding self-regulated feedback: A comparative study of GenAI and human peers. Frontiers in Education, 10, 1736446. https://doi.org/10.3389/feduc.2025.1736446
Hawkins, B., Taylor-Griffiths, D., & Lodge, J. M. (2026). Summarise, elaborate, try again: exploring the effect of feedback literacy on AI-enhanced essay writing. Assessment & Evaluation in Higher Education, 51(5), 879–891. https://doi.org/10.1080/02602938.2025.2492070
Hilliger, I., Pérez-Sanagustín, M., González, C., Villalobos, E., & Celis, S. (2026). A GAI-based chatbot for scaffolding self-regulated learning: Insights from a design-based research approach. Journal of Learning Analytics, 13(1), 74–88. https://doi.org/10.18608/jla.2026.9143
Hongxia, H., & Razali, A. B. (2026). Impact of AI-assisted peer feedback on EFL students’ self-regulated learning, self-efficacy, and motivation in English academic writing. International Journal of Instruction, 19(2), 163–182. https://doi.org/10.29333/iji.2026.1929a
Ironsi, C. S., & Bostanci, H. B. (2026). Enhancing the reading comprehension and autonomy of foreign language students using generative AI-integrated assistant. Frontiers in Education, 11, 1763238. https://doi.org/10.3389/feduc.2026.1763238
Lan, M., & Zhou, X. (2025). A qualitative systematic review on AI-empowered self-regulated learning in higher education. npj Science of Learning, 10, Article 21. https://doi.org/10.1038/s41539-025-00319-0
Lee, H.-Y., Chen, P.-H., Wang, W.-S., Huang, Y.-M., & Wu, T.-T. (2024). Empowering ChatGPT with guidance mechanism in blended learning: Effect of self-regulated learning, higher-order thinking skills, and knowledge construction. International Journal of Educational Technology in Higher Education, 21, Article 16. https://doi.org/10.1186/s41239-024-00447-4
Lee, S. S., & Moore, R. L. (2024). Harnessing generative AI (GenAI) for automated feedback in higher education: A systematic review. Online Learning, 28(3), 82–104. https://doi.org/10.24059/olj.v28i3.4593
Lee, Y.-F., Hwang, G.-J., & Chen, P.-Y. (2025). Technology-based interactive guidance to promote learning performance and self-regulation: A chatbot-assisted self-regulated learning approach. Educational Technology Research and Development, 73, 2279–2304. https://doi.org/10.1007/s11423-025-10478-x
Li, L., & Kim, M. (2024). It is like a friend to me: Critical usage of automated feedback systems by self-regulating English learners in higher education. Australasian Journal of Educational Technology, 40(1), 1–18. https://doi.org/10.14742/ajet.8821
Liu, C.-C., Hwang, G.-J., Yu, P., Tu, Y.-F., & Wang, Y. (2025). Effects of an automated corrective feedback-based peer assessment approach on students’ learning achievement, motivation, and self-regulated learning conceptions in foreign language pronunciation. Educational Technology Research and Development, 73, 2403–2424. https://doi.org/10.1007/s11423-025-10484-z
Lu, Q., Yao, Y., Xiao, L., Zhu, X., & Yin, H. (2026). Exploring the impact of a GenAI-supported feedback practice on student feedback literacy in L2 writing. Computer Assisted Language Learning. Advance online publication. https://doi.org/10.1080/09588221.2025.2605541
Lukešová, A., & Jennings, P. J. (2026). Clue before correction: ChatGPT-enhanced strategy for promoting autonomous and reflective language learning. Innovation in Language Learning and Teaching, 1–29. https://doi.org/10.1080/17501229.2025.2612532
Mekheimer, M. (2025). Generative AI-assisted feedback and EFL writing: A study on proficiency, revision frequency and writing quality. Discover Education, 4, Article 170. https://doi.org/10.1007/s44217-025-00602-7
Nicol, D. J., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199–218. https://doi.org/10.1080/03075070600572090
Ortega-Ochoa, E., Quiroga-Pérez, J., Arguedas, M., Daradoumis, T., & Marquès-Puig, J. M. (2024). The effectiveness of empathic chatbot feedback for developing computer competencies, motivation, self-regulation, and metacognitive reasoning in online higher education. Internet of Things, 25, 101101. https://doi.org/10.1016/j.iot.2024.101101
Ouzzani, M., Hammady, H., Fedorowicz, Z., & Elmagarmid, A. (2016). Rayyan—a web and mobile app for systematic reviews. Systematic Reviews, 5, Article 210. https://doi.org/10.1186/s13643-016-0384-4
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Pan, M., Lai, C., & Guo, K. (2025). Effects of GenAI-empowered interactive support on university EFL students’ self-regulated strategy use and engagement in reading. The Internet and Higher Education, 65, 100991. https://doi.org/10.1016/j.iheduc.2024.100991
Purnomo, R., Rif’attullah, M., Wandira, S., Kaufmann, T., Deng, Z., & Az-Zahra, A. M. (2026). Exploring EFL university students’ experiences of engaging with ChatGPT-generated feedback during academic writing: A qualitative case study. Script Journal: Journal of Linguistics and English Teaching, 11(2), 418–436. https://doi.org/10.24903/sj.v11i2.2397
Qiao, H., & Zhao, A. (2023). Artificial intelligence-based language learning: Illuminating the impact on speaking skills and self-regulation in Chinese EFL context. Frontiers in Psychology, 14, 1255594. https://doi.org/10.3389/fpsyg.2023.1255594
Selvi, A. E., Irgatoğlu, A., Yurttadur, O., & Dağbaşı, G. (2026). Sustainable L2 writing pedagogy in Turkish higher education: Effects of AI-mediated feedback on self-regulated learning and writing performance. PLOS ONE, 21(7), e0344618. https://doi.org/10.1371/journal.pone.0344618
Smaoui, A., & Bensalem, H. (2026). Scaffolded GenAI in higher education academic writing: An exploratory mixed-methods study of self-regulated intercultural learning. International Journal of English Linguistics, 16(4), 1–19. https://doi.org/10.5539/ijel.v16n4p1
Sun, D., Xu, P., Zhang, J., Liu, R., & Zhang, J. (2025). How self-regulated learning is affected by feedback based on large language models: Data-driven sustainable development in computer programming learning. Electronics, 14(1), 194. https://doi.org/10.3390/electronics14010194
Sun, H. (2026). The dynamic relationships among AI-assisted formative assessment in music teaching, feedback literacy, and music learning engagement. Frontiers in Psychology, 17, 1919875. https://doi.org/10.3389/fpsyg.2026.1919875
Teng, M. F. (2025). Metacognitive awareness and EFL learners’ perceptions and experiences in utilising ChatGPT for writing feedback. European Journal of Education, 60, e12811. https://doi.org/10.1111/ejed.12811
van de Schoot, R., de Bruin, J., Schram, R., Zahedi, P., de Boer, J., Weijdema, F., Kramer, B., Huijts, M., Hoogerwerf, M., Ferdinands, G., Harkema, A., Willemsen, J., Ma, Y., Fang, Q., Hindriks, S., Tummers, L., & Oberski, D. L. (2021). An open-source machine learning framework for efficient and transparent systematic reviews. Nature Machine Intelligence, 3, 125–133. https://doi.org/10.1038/s42256-020-00287-7
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4
Wang, K., Qin, S., Shen, Y., Guo, J., Ruan, Q., & Jia, T. (2026). Effects of AI chatbot-supported cooperative flipped classroom on student collaboration, self-regulated learning and academic performance: A mastery learning perspective. British Journal of Educational Technology. Advance online publication. https://doi.org/10.1111/bjet.70079
Weber, F., Wambsganss, T., & Söllner, M. (2025). Enhancing legal writing skills: The impact of formative feedback in a hybrid intelligence learning environment. British Journal of Educational Technology, 56(2), 650–677. https://doi.org/10.1111/bjet.13529
Weidlich, J., Gotsch, F., Schudel, K., Marusic-Würscher, C., Mazzarella, J., Bolten, H., Bütler, D., Luger, S., Wohlfender, B., & Maag Merki, K. (2025). Teacher, peer, or AI? Comparing effects of feedback sources in higher education. Computers and Education Open, 9, 100300. https://doi.org/10.1016/j.caeo.2025.100300
Xiangming, L., & Wei, W. (2026). Interplay effects of AI feedback and individual differences on learners’ emotional responses. Education and Information Technologies, 31(11), 4091–4113. https://doi.org/10.1007/s10639-026-13937-x
Xie, X., Zhang, L. J., & Wilson, A. J. (2025). Comparing ChatGPT feedback and peer feedback in shaping students’ evaluative judgement of statistical analysis: A case study. Behavioral Sciences, 15(7), 884. https://doi.org/10.3390/bs15070884
Xue, J., & Chen, M. (2026). Unravelling the relationship between self-efficacy and self-regulated strategies in GenAI-assisted writing of postgraduates: The mediating role of feedback engagement. Frontiers in Psychology, 17, 1786221. https://doi.org/10.3389/fpsyg.2026.1786221
Yilmaz, M., Temur, H. B., Emmungil, L., Çelik, E., Gauthier, A., & Cukurova, M. (2026). Supporting self-regulated learning through generative AI feedback in online higher education: The importance of student perceptions of the source of feedback. International Journal of Educational Technology in Higher Education, 23, Article 16. https://doi.org/10.1186/s41239-026-00592-y
Zhan, Y., & Yan, Z. (2025). Students’ engagement with ChatGPT feedback: Implications for student feedback literacy in the context of generative artificial intelligence. Assessment & Evaluation in Higher Education. Advance online publication. https://doi.org/10.1080/02602938.2025.2471821
Zhang, K., & Saeed, M. A. (2026). Chinese EFL learners’ engagement with ChatGPT feedback on academic writing: A case study in Malaysia. Computers and Composition, 79, 102976. https://doi.org/10.1016/j.compcom.2025.102976
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/S15430421TIP4102_2
Alaoui Mhamdi, N. (2026). AI-mediated feedback in English learning: Moroccan graduate students’ accounts of motivation, autonomy, and trust conditions. Computers and Education Open, 10, 100356. https://doi.org/10.1016/j.caeo.2026.100356
Alzahrani, M. A. (2026). AI-based feedback in academic writing: Insights from EFL undergraduate students at Saudi higher education. International Journal of Language and Literary Studies, 8(5), 50–68. https://doi.org/10.36892/ijlls.v8i5.2737
Apriani, E., Cardoso, L., Obaid, A. J., Muthmainnah, M., Wijayanti, E., Esmianti, F., & Supardan, D. (2024). Impact of AI-powered chatbots on EFL students’ writing skills, self-efficacy, and self-regulation: A mixed-methods study. Global Educational Research Review, 1(2), 57–72. https://doi.org/10.71380/GERR-08-2024-8
Ates, H. (2026). Human-centered GenAI feedback design in higher education: A multisite experiment on direct, reflective, and hybrid approaches to scientific argumentation. International Journal of Educational Technology in Higher Education, 23, Article 38. https://doi.org/10.1186/s41239-026-00614-9
Campos, M. (2025). AI-assisted feedback in CLIL courses as a self-regulated language learning mechanism: Students’ perceptions and experiences. European Public & Social Innovation Review, 10, 1–14. https://doi.org/10.31637/epsir-2025-1568
Carless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315–1325. https://doi.org/10.1080/02602938.2018.1463354
Chen, M.-R. A. (2026). Generative AI, visual scaffolds, and metacognition in EFL writing. Language Learning & Technology, 30(1), 1–26. https://doi.org/10.64152/10125/73695
Dai, Z. (2026). Rethinking AI-assisted writing instruction: Feedback literacy scripts, calibration training, and student writing development. Frontiers in Psychology, 17, 1829268. https://doi.org/10.3389/fpsyg.2026.1829268
Gu, J., Chen, J., & Yan, Z. (2026). Fostering feedback literacy by scaffolding self-regulated feedback: A comparative study of GenAI and human peers. Frontiers in Education, 10, 1736446. https://doi.org/10.3389/feduc.2025.1736446
Hawkins, B., Taylor-Griffiths, D., & Lodge, J. M. (2026). Summarise, elaborate, try again: exploring the effect of feedback literacy on AI-enhanced essay writing. Assessment & Evaluation in Higher Education, 51(5), 879–891. https://doi.org/10.1080/02602938.2025.2492070
Hilliger, I., Pérez-Sanagustín, M., González, C., Villalobos, E., & Celis, S. (2026). A GAI-based chatbot for scaffolding self-regulated learning: Insights from a design-based research approach. Journal of Learning Analytics, 13(1), 74–88. https://doi.org/10.18608/jla.2026.9143
Hongxia, H., & Razali, A. B. (2026). Impact of AI-assisted peer feedback on EFL students’ self-regulated learning, self-efficacy, and motivation in English academic writing. International Journal of Instruction, 19(2), 163–182. https://doi.org/10.29333/iji.2026.1929a
Ironsi, C. S., & Bostanci, H. B. (2026). Enhancing the reading comprehension and autonomy of foreign language students using generative AI-integrated assistant. Frontiers in Education, 11, 1763238. https://doi.org/10.3389/feduc.2026.1763238
Lan, M., & Zhou, X. (2025). A qualitative systematic review on AI-empowered self-regulated learning in higher education. npj Science of Learning, 10, Article 21. https://doi.org/10.1038/s41539-025-00319-0
Lee, H.-Y., Chen, P.-H., Wang, W.-S., Huang, Y.-M., & Wu, T.-T. (2024). Empowering ChatGPT with guidance mechanism in blended learning: Effect of self-regulated learning, higher-order thinking skills, and knowledge construction. International Journal of Educational Technology in Higher Education, 21, Article 16. https://doi.org/10.1186/s41239-024-00447-4
Lee, S. S., & Moore, R. L. (2024). Harnessing generative AI (GenAI) for automated feedback in higher education: A systematic review. Online Learning, 28(3), 82–104. https://doi.org/10.24059/olj.v28i3.4593
Lee, Y.-F., Hwang, G.-J., & Chen, P.-Y. (2025). Technology-based interactive guidance to promote learning performance and self-regulation: A chatbot-assisted self-regulated learning approach. Educational Technology Research and Development, 73, 2279–2304. https://doi.org/10.1007/s11423-025-10478-x
Li, L., & Kim, M. (2024). It is like a friend to me: Critical usage of automated feedback systems by self-regulating English learners in higher education. Australasian Journal of Educational Technology, 40(1), 1–18. https://doi.org/10.14742/ajet.8821
Liu, C.-C., Hwang, G.-J., Yu, P., Tu, Y.-F., & Wang, Y. (2025). Effects of an automated corrective feedback-based peer assessment approach on students’ learning achievement, motivation, and self-regulated learning conceptions in foreign language pronunciation. Educational Technology Research and Development, 73, 2403–2424. https://doi.org/10.1007/s11423-025-10484-z
Lu, Q., Yao, Y., Xiao, L., Zhu, X., & Yin, H. (2026). Exploring the impact of a GenAI-supported feedback practice on student feedback literacy in L2 writing. Computer Assisted Language Learning. Advance online publication. https://doi.org/10.1080/09588221.2025.2605541
Lukešová, A., & Jennings, P. J. (2026). Clue before correction: ChatGPT-enhanced strategy for promoting autonomous and reflective language learning. Innovation in Language Learning and Teaching, 1–29. https://doi.org/10.1080/17501229.2025.2612532
Mekheimer, M. (2025). Generative AI-assisted feedback and EFL writing: A study on proficiency, revision frequency and writing quality. Discover Education, 4, Article 170. https://doi.org/10.1007/s44217-025-00602-7
Nicol, D. J., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199–218. https://doi.org/10.1080/03075070600572090
Ortega-Ochoa, E., Quiroga-Pérez, J., Arguedas, M., Daradoumis, T., & Marquès-Puig, J. M. (2024). The effectiveness of empathic chatbot feedback for developing computer competencies, motivation, self-regulation, and metacognitive reasoning in online higher education. Internet of Things, 25, 101101. https://doi.org/10.1016/j.iot.2024.101101
Ouzzani, M., Hammady, H., Fedorowicz, Z., & Elmagarmid, A. (2016). Rayyan—a web and mobile app for systematic reviews. Systematic Reviews, 5, Article 210. https://doi.org/10.1186/s13643-016-0384-4
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Pan, M., Lai, C., & Guo, K. (2025). Effects of GenAI-empowered interactive support on university EFL students’ self-regulated strategy use and engagement in reading. The Internet and Higher Education, 65, 100991. https://doi.org/10.1016/j.iheduc.2024.100991
Purnomo, R., Rif’attullah, M., Wandira, S., Kaufmann, T., Deng, Z., & Az-Zahra, A. M. (2026). Exploring EFL university students’ experiences of engaging with ChatGPT-generated feedback during academic writing: A qualitative case study. Script Journal: Journal of Linguistics and English Teaching, 11(2), 418–436. https://doi.org/10.24903/sj.v11i2.2397
Qiao, H., & Zhao, A. (2023). Artificial intelligence-based language learning: Illuminating the impact on speaking skills and self-regulation in Chinese EFL context. Frontiers in Psychology, 14, 1255594. https://doi.org/10.3389/fpsyg.2023.1255594
Selvi, A. E., Irgatoğlu, A., Yurttadur, O., & Dağbaşı, G. (2026). Sustainable L2 writing pedagogy in Turkish higher education: Effects of AI-mediated feedback on self-regulated learning and writing performance. PLOS ONE, 21(7), e0344618. https://doi.org/10.1371/journal.pone.0344618
Smaoui, A., & Bensalem, H. (2026). Scaffolded GenAI in higher education academic writing: An exploratory mixed-methods study of self-regulated intercultural learning. International Journal of English Linguistics, 16(4), 1–19. https://doi.org/10.5539/ijel.v16n4p1
Sun, D., Xu, P., Zhang, J., Liu, R., & Zhang, J. (2025). How self-regulated learning is affected by feedback based on large language models: Data-driven sustainable development in computer programming learning. Electronics, 14(1), 194. https://doi.org/10.3390/electronics14010194
Sun, H. (2026). The dynamic relationships among AI-assisted formative assessment in music teaching, feedback literacy, and music learning engagement. Frontiers in Psychology, 17, 1919875. https://doi.org/10.3389/fpsyg.2026.1919875
Teng, M. F. (2025). Metacognitive awareness and EFL learners’ perceptions and experiences in utilising ChatGPT for writing feedback. European Journal of Education, 60, e12811. https://doi.org/10.1111/ejed.12811
van de Schoot, R., de Bruin, J., Schram, R., Zahedi, P., de Boer, J., Weijdema, F., Kramer, B., Huijts, M., Hoogerwerf, M., Ferdinands, G., Harkema, A., Willemsen, J., Ma, Y., Fang, Q., Hindriks, S., Tummers, L., & Oberski, D. L. (2021). An open-source machine learning framework for efficient and transparent systematic reviews. Nature Machine Intelligence, 3, 125–133. https://doi.org/10.1038/s42256-020-00287-7
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4
Wang, K., Qin, S., Shen, Y., Guo, J., Ruan, Q., & Jia, T. (2026). Effects of AI chatbot-supported cooperative flipped classroom on student collaboration, self-regulated learning and academic performance: A mastery learning perspective. British Journal of Educational Technology. Advance online publication. https://doi.org/10.1111/bjet.70079
Weber, F., Wambsganss, T., & Söllner, M. (2025). Enhancing legal writing skills: The impact of formative feedback in a hybrid intelligence learning environment. British Journal of Educational Technology, 56(2), 650–677. https://doi.org/10.1111/bjet.13529
Weidlich, J., Gotsch, F., Schudel, K., Marusic-Würscher, C., Mazzarella, J., Bolten, H., Bütler, D., Luger, S., Wohlfender, B., & Maag Merki, K. (2025). Teacher, peer, or AI? Comparing effects of feedback sources in higher education. Computers and Education Open, 9, 100300. https://doi.org/10.1016/j.caeo.2025.100300
Xiangming, L., & Wei, W. (2026). Interplay effects of AI feedback and individual differences on learners’ emotional responses. Education and Information Technologies, 31(11), 4091–4113. https://doi.org/10.1007/s10639-026-13937-x
Xie, X., Zhang, L. J., & Wilson, A. J. (2025). Comparing ChatGPT feedback and peer feedback in shaping students’ evaluative judgement of statistical analysis: A case study. Behavioral Sciences, 15(7), 884. https://doi.org/10.3390/bs15070884
Xue, J., & Chen, M. (2026). Unravelling the relationship between self-efficacy and self-regulated strategies in GenAI-assisted writing of postgraduates: The mediating role of feedback engagement. Frontiers in Psychology, 17, 1786221. https://doi.org/10.3389/fpsyg.2026.1786221
Yilmaz, M., Temur, H. B., Emmungil, L., Çelik, E., Gauthier, A., & Cukurova, M. (2026). Supporting self-regulated learning through generative AI feedback in online higher education: The importance of student perceptions of the source of feedback. International Journal of Educational Technology in Higher Education, 23, Article 16. https://doi.org/10.1186/s41239-026-00592-y
Zhan, Y., & Yan, Z. (2025). Students’ engagement with ChatGPT feedback: Implications for student feedback literacy in the context of generative artificial intelligence. Assessment & Evaluation in Higher Education. Advance online publication. https://doi.org/10.1080/02602938.2025.2471821
Zhang, K., & Saeed, M. A. (2026). Chinese EFL learners’ engagement with ChatGPT feedback on academic writing: A case study in Malaysia. Computers and Composition, 79, 102976. https://doi.org/10.1016/j.compcom.2025.102976
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/S15430421TIP4102_2
Publicado
2026-07-01
Sección
De Investigación
Derechos de autor 2026 Claudia Patricia Caballero-de Lamarque, Manuel de Jesús Azpilcueta-Ruiz Esparza, Elia Trejo-Trejo, Diego Fernando Nava-Cuevas
Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0.
LICENCIA DE CONTENIDO
Creative Commons
Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
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