5. Recording learner behavior and student modeling
The intelligent tutoring systems in ICALL had this knowledge stored in a student model (Schulze, 2012). Student modeling (e.g., Bull, 1993; Bull, 1994, 2000; Mabbott & Bull, 2004; McCalla, 1992; Michaud & McCoy, 2000; Schulze, 2008; Self, 1974; Tsiriga & Virvou, 2003) is a challenging endeavor; student data needs to be recorded and structured into a student profile, then inferences can be drawn to construct a student model over time. The model has structured information about prior learning, learner beliefs, strategies, and preferences, and language beliefs. Basically, it models the information teachers have about their students both through student records and the teacher’s experience. Such information helps to tailor instructional sequences, guidance and help, and corrective feedback individually so that it becomes relevant and most effective. GenAIs have LLMs which contain enormous information about language and languages (Wolfram, 2023, February 14); their knowledge of the learner is often non-existent or serendipitous at best. Currently and in the context of language education and especially in the context of previous research in ICALL and student modeling in general, the lack of a student model means that GenAIs cannot be treated nor employed as an intelligent tutoring system (ITS), because ITS consist of a knowledge base, a student model, and a pedagogical module (Wikipedia contributors, 2024, December 20) to imitate the behavior of a human tutor and provide individualized tutoring.
My inspiration for this title came from the book
Snyder, T. (2017). On tyranny: Twenty lessons from the twentieth century. Tim Duggan Books.
I am sharing these early drafts of a book chapter I published in
Yijen Wang, Antonie Alm, & Gilbert Dizon (Eds.) (2025),
Insights into AI and language teaching and learning. Castledown Publishers.
https://doi.org/10.29140/9781763711600-02.
Thus far, I have given a historical introduction and talked about the necessary exposure to authentic language, communication in context, interaction in language learning with GenAI, and appropriate error correction and contingent feedback. The following describes the basis for lesson #5.
References
Bull, S. (1993). Towards User/System Collaboration in Developing a Student Model for Intelligent Computer-Assisted Language Learning. Computer Assisted Language Learning, 8, 3-8.
Bull, S. (1994). Student modeling for second language acquisition. Computers and Education, 23(1-2), 13-20.
Bull, S. (2000). ‘Do It Yourself’ Student Models for Collaborative Student Modelling and Peer Interaction. In B. P. Goettl, H. M. Halff, C. Redfield Luckhardt, & V. J. Shute (Eds.), Intelligent Tutoring Systems. 4th International Conference, ITS ’98, San Antonio, Texas, USA, August 16-19, 1998 Proceedings (pp. 176-185). Springer Verlag.
Mabbott, A., & Bull, S. (2004). Alternative Views on Knowledge: Presentation of Open Learner Models. In J. C. Lester, R. M. Vicari, & F. Paraguacu (Eds.), Intelligent Tutoring Systems: 7th International Conference (pp. 689-698). Springer-Verlag.
McCalla, G. I. (1992). The Centrality of Student Modelling to Intelligent Tutoring Systems. In E. Costa (Ed.), New Directions for Intelligent Tutoring Systems (pp. 107-131). Springer Verlag.
Michaud, L. N., & McCoy, K. F. (2000). Supporting Intelligent Tutoring in CALL by Modeling the User’s Grammar. In Proceedings of the Thirteenth Annual International Florida Artificial Intelligence Research Symposium, May 22-24, 2000, Orlando, Florida (pp. 50-54). AAAI Press.
Schulze, M. (2008). Modeling SLA Processes Using NLP. In C. Chapelle, Y.-R. Chung, & J. Xu (Eds.), Towards Adaptive CALL: Natural Language Processing for Diagnostic Assessment. (pp. 149-166). Iowa State University. https://apling.engl.iastate.edu/wp-content/uploads/sites/221/2015/05/5thTSLL2007_proceedings.pdf
Schulze, M. (2012). Learner modeling. In C. A. Chapelle (Ed.), The Encyclopaedia of Applied Linguistics. 10 volumes (pp. online n.p.). Wiley-Blackwell.
Self, J. A. (1974). Student Models in Computer-Aided Instruction. International Journal of Man-Machine Studies, 6, 261-276.
Tsiriga, V., & Virvou, M. (2003). Modelling the Student to Individualise Tutoring in a Web-Based ICALL. International Journal of Continuing Engineering Education and Life-Long Learning, 13(3-4), 350-365.
Wikipedia contributors. (2024, December 20). Intelligent tutoring system. In Wikipedia, The Free Encyclopedia.
Wolfram, S. (2023, February 14). What is ChatGPT doing … and why does it work? Stephen Wolfram Writings. https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work
Panta Rhei Enterprise 