Integration of AI helping teachers in traditional teaching roles

Ana Fernández Jiménez

doi:10.31637/epsir-2024-664

Autores/as

Ana Fernández Jiménez Esic Business School https://orcid.org/0000-0002-1937-0007

DOI:

https://doi.org/10.31637/epsir-2024-664

Palabras clave:

aprendizaje, retroalimentación, IA, educación, enseñanza, Inteligencia Atificial Generativa, tecnología, personalización

Resumen

Introducción: Este ensayo examina la situación en la que un estudiante humano se empareja con un profesor humano y se introduce un tutor virtual para asistir en el aprendizaje del estudiante fuera del aula tradicional, como a través de una computadora en casa. Metodología: Con el auge de los tutores virtuales basados en IA, es cada vez más probable ver a estos profesores de IA asumiendo un papel de enseñanza más tradicional. Resultados: Los tutores virtuales pueden personalizar las experiencias de aprendizaje para los estudiantes al analizar el estilo y ritmo de aprendizaje de cada uno. Discusión: Además, pueden proporcionar retroalimentación inmediata, lo que ayuda a mejorar la comprensión del material por parte de los estudiantes y mantenerlos motivados. Conclusiones: La integración de la IA en las prácticas de enseñanza tradicionales tiene el potencial de revolucionar la experiencia educativa tanto para estudiantes como para profesores, proporcionando un entorno de aprendizaje más personalizado y eficaz.

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Citas

Adıgüzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology.

Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(3), 1101. https://doi.org/10.3390/su14031101

Aldosari, A. M., Alramthi, S. M., & Eid, H. F. (2022). Improving social presence in online higher education: Using live virtual classroom to confront learning challenges during COVID-19 pandemic. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2022.994403

Alam, A. (2021). Should robots replace teachers? Mobilisation of AI and learning analytics in education. En 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3) (pp. 1-12). IEEE. http://dx.doi.org/10.1109/ICAC353642.2021.9697300

Alam, A. (2023). Improving Learning Outcomes through Predictive Analytics: Enhancing Teaching and Learning with Educational Data Mining. In 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS) (pp. 249-257). IEEE. http://dx.doi.org/10.1109/ICICCS56967.2023.10142392

Alam, A. (2023). Harnessing the Power of AI to Create Intelligent Tutoring Systems for Enhanced Classroom Experience and Improved Learning Outcomes. In Intelligent Communication Technologies and Virtual Mobile Networks (pp. 571-591). Singapore: Springer Nature Singapore. http://dx.doi.org/10.1007/978-981-99-1767-9_42

Bhutoria, A. (2022). Personalized education and artificial intelligence in the United States, China, and India: A systematic review using a human-in-the-loop model. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2022.100068

Bahrini, A., Khamoshifar, M., Abbasimehr, H., Riggs, R. J., Esmaeili, M., Majdabadkohne, R. M., & Pasehvar, M. (2023, April). ChatGPT: Applications, opportunities, and threats. In 2023 Systems and Information Engineering Design Symposium (SIEDS) (pp. 274-279). IEEE. http://dx.doi.org/10.1109/SIEDS58326.2023.10137850

Celik, I. (2023). Towards Intelligent-TPACK: An empirical study on teachers' professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior. http://dx.doi.org/10.1016/j.chb.2022.107468

Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends. http://dx.doi.org/10.1007/s11528-022-00715-y

Chan, C. K. Y., & Tsi, L. H. Y. (2023). The AI Revolution in Education: Will AI Replace or Assist Teachers in Higher Education?. arXiv preprint arXiv:2305.01185. https://arxiv.org/abs/2305.01185

Checco, A., Bracciale, L., Loreti, P., Pinfield, S., & Bianchi, G. (2021). AI-assisted peer review. Humanities and Social Sciences Communications, 8(1), 1-11. https://www.nature.com/articles/s41599-020-00703-8

Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264-75278. https://doi.org/10.1109/ACCESS.2020.2988510

Chiu, T. K. F., & Chai, C. (2020). Sustainable curriculum planning for artificial intelligence education: A self-determination theory perspective. Sustainability. https://doi.org/10.3390/su12020527

Cortázar, C., Nussbaum, M., Harcha, J., Alvares, D., López, F., Goñi, J., & Cabezas, V. (2021). Promoting critical thinking in an online, project-based course. Computers in Human Behavior, 119, 106705. https://doi.org/10.1016/j.chb.2021.106705

Dai, Y., Chai, C. S., Lin, P. Y., Jong, M. S. Y., Guo, Y., & Qin, J. (2020). Promoting students' well-being by developing their readiness for the artificial intelligence age. Sustainability. http://dx.doi.org/10.3390/su12166597

Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., Johnson, E. E., & Baah, P. K. (2022). The impact of a virtual teaching assistant (chatbot) on students' learning in Ghanaian higher education. International Journal of Educational Technology in Higher Education, 19(1), 57. http://dx.doi.org/10.1186/s41239-022-00362-6

Essa, S. G., Celik, T., & Human-Hendricks, N. E. (2023). Personalized adaptive learning technologies based on machine learning techniques to identify learning styles: A systematic literature review. IEEE Access. http://dx.doi.org/10.1109/ACCESS.2023.3276439

Etiubon, R., & Etiubon, A. (2023). Replacement of Humans in the Classroom by Artificial Intelligence: A Rhetoric. Asian Journal of Educational Technology, 2, 12-21. http://dx.doi.org/10.53402/ajet.v2i1.185

Fernández Jiménez, A. (2024). The use of Chat GPT in university classrooms by university students. In A. Fernández Jiménez (Ed.), Artificial Intelligence Friend or Foe? (pp. 115-122). Peter Lang Publishing Group.

Fitria, T. N. (2023). THE USE OF ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED): CAN AI REPLACE THE TEACHER'S ROLE?. EPIGRAM (e-Journal). https://doi.org/10.55644/epigram.v20i1.637

Gentrup, S., Lorenz, G., Kristen, C., & Kogan, I. (2020). Self-fulfilling prophecies in the classroom: Teacher expectations, teacher feedback and student achievement. Learning and Instruction. http://dx.doi.org/10.1016/j.learninstruc.2019.101296

González-Calatayud, V., Prendes-Espinosa, P., &Roig-Vila, R. (2021). Artificial intelligence for student assessment: A systematic review. Applied Sciences, 11(12), 5467. https://doi.org/10.3390/app11125467

Grassini, S. (2023). Shaping the future of education: exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences. http://dx.doi.org/10.3390/educsci13070692

Holly, M., Pirker, J., Resch, S., Brettschuh, S., & Gütl, C. (2021). Designing VR experiences–expectations for teaching and learning in VR. Educational Technology & Society, 24(2), 107-119. https://www.jstor.org/stable/27004935

Hooda, M., Rana, C., Dahiya, O., Rizwan, A., & Hossain, M. S. (2022). Artificial intelligence for assessment and feedback to enhance student success in higher education. Mathematical Problems in Engineering, 1-19. http://dx.doi.org/10.1155/2022/5215722

Igbokwe, I. C. (2023). Application of artificial intelligence (AI) in educational management. International Journal of Scientific and Research Publications, 13(3), 300-307. https://doi.org/10.29322/IJSRP.13.03.2023.p13536

Kabudi, T., Pappas, I., & Olsen, D. H. (2021). AI-enabled adaptive learning systems: A systematic mapping of the literature. Computers and Education: Artificial Intelligence, 2, 100017. https://doi.org/10.1016/j.caeai.2021.100017

Kem, D. (2022). Personalised and adaptive learning: Emerging learning platforms in the era of digital and smart learning. International Journal of Social Science and Human Research, 5(2), 385-391. https://doi.org/10.47191/ijsshr/v5-i2-02

Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in education. Education and Information Technologies. http://dx.doi.org/10.1007/s10639-021-10831-6

Kim, J., & Park, C. Y. (2020). Education, skill training, and lifelong learning in the era of technological revolution: A review. Asian‐Pacific Economic Literature. http://dx.doi.org/10.2139/ssrn.3590922

Lee, I., & Perret, B. (2022). Preparing high school teachers to integrate AI methods into STEM classrooms. En Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), pp. 12783-12791). https://doi.org/10.1609/aaai.v36i11.21645

Li, K. C., & Wong, B. T. M. (2021). Features and trends of personalised learning: A review of journal publications from 2001 to 2018. Interactive Learning Environments. http://dx.doi.org/10.1080/10494820.2020.1811735

Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., Rakovic, M., Molenaar, I., Moore, J., & Gašević, D. (2023). Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning. Computers in Human Behavior, 139, 107547. http://dx.doi.org/10.1016/j.chb.2022.107547

Maghsudi, S., Lan, A., Xu, J., & van Der Schaar, M. (2021). Personalized education in the artificial intelligence era: what to expect next. IEEE Signal Processing Magazine, 38(3), 37-50. http://dx.doi.org/10.1109/MSP.2021.3055032

Onesi-Ozigagun, O., Ololade, Y. J., Eyo-Udo, N. L., & Ogundipe, D. O. (2024). Revolutionizing education through AI: a comprehensive review of enhancing learning experiences. International Journal of Applied Research in Social Sciences, 6(4), 589-607.

Pratama, M. P., Sampelolo, R., & Lura, H. (2023). Revolutionizing education: harnessing the power of artificial intelligence for personalized learning. Klasikal: Journal of Education, Language Teaching and Science, 5(2), 350-357. http://dx.doi.org/10.52208/klasikal.v5i2.877

Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenannt, I. (2020). A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Computers & Education, 147, 103778. https://doi.org/10.1016/j.compedu.2019.103778

Raj, N. S., & Renumol, V. G. (2022). A systematic literature review on adaptive content recommenders in personalized learning environments from 2015 to 2020. Journal of Computers in Education. http://dx.doi.org/10.1007/s40692-021-00199-4

Rane, N., Choudhary, S., & Rane, J. (2023). Education 4.0 and 5.0: Integrating Artificial Intelligence (AI) for personalized and adaptive learning. SSRN 4638365. https://doi.org/10.2139/ssrn.4638365

Rastrollo-Guerrero, J. L., Gómez-Pulido, J. A., & Durán-Domínguez, A. (2020). Analyzing and predicting students’ performance by means of machine learning: A review. Applied Sciences, 10(3), 1042. https://doi.org/10.3390/app10031042

Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2020). Providing instruction based on students' learning style preferences does not improve learning. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2020.00164

Shi, Y., Ma, Y., MacLeod, J., & Yang, H. H. (2020). College students' cognitive learning outcomes in flipped classroom instruction: a meta-analysis of the empirical literature. Journal of Computers in Education. https://acortar.link/zpIvCB

Skalka, J., Drlik, M., Benko, L., Kapusta, J., Rodriguez del Pino, J. C., Smyrnova-Trybulska, E., Stolinska, A., Svec, P., & Turcinek, P. (2021). Conceptual framework for programming skills development based on microlearning and automated source code evaluation in virtual learning environment. Sustainability, 13(6), 3293. https://doi.org/10.3390/su13063293

Sorour, S., Ahmed, H. M. M., Amin, A. E. A., & Abdelkader, H. (2024). IBEDO-DE: A Novel ChatGPT-Enhanced Model for Improving Educational Outcomes through Data-Driven Insights and Student Perceptions. http://dx.doi.org/10.21203/rs.3.rs-4180848/v1

Taylor, D. L., Yeung, M., & Bashet, A. Z. (2021). Personalized and adaptive learning. En Innovative learning environments in STEM higher education: Opportunities, Challenges, and Looking Forward, 17-34. http://dx.doi.org/10.1007/978-3-030-58948-6_2

Wang, T., Lund, B. D., Marengo, A., Pagano, A., Mannuru, N. R., Teel, Z. A., & Pange, J. (2023). Exploring the potential impact of artificial intelligence (AI) on international students in higher education: Generative AI, chatbots, analytics, and international student success. Applied Sciences, 13(11), 6716. https://doi.org/10.3390/app13116716

Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J. B., Yuan, J., & Li, Y. (2021). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity, 1-18. https://doi.org/10.1155/2021/8812542

Zwiers, J., & Crawford, M. (2023). Academic Conversations (1st ed.). Routledge. https://www.perlego.com/book/4265427