Integration of technology and pedagogy in intelligent tutoring systems
DOI:
https://doi.org/10.21556/edutec.2024.89.3199Keywords:
Intelligent Tutoring Systems, technology - pedagogy integration, constructivist approaches, multimedia learningAbstract
Intelligent Tutoring Systems (ITS) have demonstrated their potential to enhance the teaching-learning process by providing personalized and adaptive instruction. However, effectively integrating technology and pedagogy within these systems remains a challenge. This study aimed to analyze the most effective approaches and strategies for achieving this integration. A mixed-method methodology was employed, combining bibliometric analysis, text mining, content analysis, and expert interviews. The results highlight the importance of using accurate student models, incorporating constructivist and multimedia learning approaches, applying adaptive feedback and scaffolding, and designing engaging interfaces. Challenges related to accessibility, scalability, and ethical considerations were also identified. The study concludes that an optimal combination of technological advancements, sound pedagogical principles, and a deep understanding of individual student needs is crucial for the success of ITS in improving learning outcomes.
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Arroyo, I., Burleson, W., Tai, M., Muldner, K., & Woolf, B. P. (2014). A multimedia intelligent tutoring system for scaffolding self-regulated learning. International Journal of Artificial Intelligence in Education, 24(2), 168-207. https://doi.org/10.1007/s40593-013-0007-9
Azevedo, R., & Aleven, V. (2013). Metacognition and Learning Technologies: An Overview of Current Interdisciplinary Research. In International Handbook of Metacognition and Learning Technologies (pp. 1-16). Springer. https://doi.org/10.1007/978-1-4419-5546-3_1 DOI: https://doi.org/10.1007/978-1-4419-5546-3_1
Brown, J. S., Collins, A., & Duguid, P. (1989). Situated Cognition and the Culture of Learning. Educational Researcher, 18(1), 32-42. https://doi.org/10.3102/0013189X018001032 DOI: https://doi.org/10.3102/0013189X018001032
Conati, C., Gertner, A., & VanLehn, K. (2002). Using Bayesian Networks to Manage Uncertainty in Student Modeling. User Modeling and User-Adapted Interaction, 12(4), 371-417. https://doi.org/10.1023/A:1021258506583 DOI: https://doi.org/10.1023/A:1021258506583
Essa, A. (2016). A Possible Future for Next Generation Adaptive Learning Systems. International Journal of Artificial Intelligence in Education, 26(2), 801-819. https://doi.org/10.1007/s40593-016-0101-y
Graesser, A. C., Chipman, P., Haynes, B. C., & Olney, A. (2005). AutoTutor: An Intelligent Tutoring System with Mixed-Initiative Dialogue. IEEE Transactions on Education, 48(4), 612-618. https://doi.org/10.1109/TE.2005.856149 DOI: https://doi.org/10.1109/TE.2005.856149
Graesser, A. C., Hu, X., & Sottilare, R. (2018). Intelligent Tutoring Systems. In F. Fischer, C. E. Hmelo-Silver, S. R. Goldman, & P. Reimann (Eds.), International Handbook of the Learning Sciences (pp. 246-255). Routledge. https://doi.org/10.4324/9781315617572-24 DOI: https://doi.org/10.4324/9781315617572-24
Jonassen, D. H. (1991). Evaluating Constructivistic Learning. Educational Technology, 31(9), 28-33.
Koedinger, K. R., & Aleven, V. (2007). Exploring the Assistance Dilemma in Experiments with Cognitive Tutors. Educational Psychology Review, 19(3), 239-264. https://doi.org/10.1007/s10648-007-9049-0 DOI: https://doi.org/10.1007/s10648-007-9049-0
Koedinger, K. R., & Corbett, A. T. (2006). Cognitive Tutors: Technology Bringing Learning Sciences to the Classroom. In K. Sawyer (Ed.), The Cambridge Handbook of the Learning Sciences (pp. 61-77). Cambridge University Press. https://doi.org/10.1017/CBO9780511816833.006 DOI: https://doi.org/10.1017/CBO9780511816833.006
Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark, M. A. (2003). Toward a Model of Collaboration and Tutoring in Problem-Solving. Journal of Artificial Intelligence in Education, 12(1), 47-63.
Magnisalis, I., Demetriadis, S., & Karakostas, A. (2011). Adaptive and Intelligent Systems for Collaborative Learning Support: A Review of the Field. IEEE Transactions on Learning Technologies, 4(1), 5-20. https://doi.org/10.1109/TLT.2011.2 DOI: https://doi.org/10.1109/TLT.2011.2
Mayer, R. E. (2004). Should There Be a Three-Strikes Rule Against Pure Discovery Learning? American Psychologist, 59(1), 14-19. DOI: https://doi.org/10.1037/0003-066X.59.1.14
Mayer, R. E. (2009). Multimedia Learning (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511811678 DOI: https://doi.org/10.1017/CBO9780511811678
Mitrovic, A., & Ohlsson, S. (1999). Evaluation of a Constraint-Based Tutor for a Database Language. International Journal of Artificial Intelligence in Education, 10(3-4), 238-256.
Nkambou, R., Mizoguchi, R., & Bourdeau, J. (2010). Advances in Intelligent Tutoring Systems. Springer. https://doi.org/10.1007/978-3-642-14363-2 DOI: https://doi.org/10.1007/978-3-642-14363-2
Piaget, J. (1970). Science of Education and the Psychology of the Child. Orion Press.
Roll, I., Aleven, V., McLaren, B. M., & Koedinger, K. R. (2007). Designing for Metacognition - Applying Cognitive Tutoring Principles to the Tutoring of Help Seeking. Metacognition and Learning, 2(2-3), 125-140. https://doi.org/10.1007/s11409-007-9010-9 DOI: https://doi.org/10.1007/s11409-007-9010-0
Schroeder, N. L., & Adesope, O. O. (2014). A Systematic Review of Pedagogical Agents' Persona, Motivation, and Cognitive Load Implications for Learners. Journal of Research on Technology in Education, 46(3), 229-251. DOI: https://doi.org/10.1080/15391523.2014.888265
Schwartz, D. L., Chase, C. C., Oppezzo, M. A., & Chin, D. B. (2011). Practicing Versus Inventing with Contrasting Cases: The Effects of Telling First on Learning and Transfer. Journal of Educational Psychology, 103(4), 759-775. https://doi.org/10.1037/a0025140 DOI: https://doi.org/10.1037/a0025140
Shute, V. J. (2008). Focus on Formative Feedback. Review of Educational Research, 78(1), 153-189. https://doi.org/10.3102/0034654307313795 DOI: https://doi.org/10.3102/0034654307313795
Soh, L. K., Tan, L. C., Wong, J., Lim, M., & Chen, X. (2017). A Pedagogical Framework for Integrating Effective Tutoring Strategies in Intelligent Tutoring Systems. In Proceedings of the 25th International Conference on Computers in Education (pp. 196-205). Asia-Pacific Society for Computers in Education.
Soller, A., Martínez, A., Jermann, P., & Muehlenbrock, M. (2005). From Mirroring to Guiding: A Review of State of the Art Technology for Supporting Collaborative Learning. International Journal of Artificial Intelligence in Education, 15(4), 261-290.
Tsai, C. C., Shen, P. D., & Lu, Y. J. (2020). Adaptive Computer-Assisted Learning Systems: Behavior, Motivation and Performance. Educational Technology & Society, 23(2), 90-106.
VanLehn, K. (2011). The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems. Educational Psychologist, 46(4), 197-221. https://doi.org/10.1080/00461520.2011.611369 DOI: https://doi.org/10.1080/00461520.2011.611369
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