Abstract
In this paper we maintain that there are benefits to extending the scope of student models to include additional information as part of the explicit student model. We illustrate our argument by describing a student model which focuses on 1. performance in the domain; 2. acquisition order of the target knowledge; 3. analogy; 4. learning strategies; 5. awareness and reflection. The first four of these issues are explicitly represented in the student model. Awareness and reflection should occur as the student model is transparent; it is used to promote learner reflection by encouraging the learner to view, and even negotiate changes to the model. Although the architecture is transferable across domains, each instantiation of the student model will necessarily be domain specific due to the importance of factors such as the relevant background knowledge for analogy, and typical progress through the target material. As an example of this approach we describe the student model of an intelligent computer assisted language learning system which was based on research findings on the above five topics in the field of second language acquisition. Throughout we address the issue of the generality of this model, with particular reference to the possibility of a similar architecture reflecting comparable issues in the domain of learning about electrical circuits.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alexander, P.A., J.M. Kulikowich, and S.K. Schulze: 1994, How Subject-Matter Knowledge Affects Recall and Interest,American Educational Research Journal 31(2), 313–337.
Anderson, J.R., R. Farrell, and R. Sauers: 1984, Learning to Program in LISP,Cognitive Science 8(2), 87–129.
Brna, P.: 1988, Confronting Misconceptions in the Domain of Simple Electrical Circuits,Instructional Science 17, 29–55.
Boohan, R.: 1993, Using Computer-Based Questionnaires to Diagnose Students' Models of Electricity. In: M. Caillot (ed.): Learning Electricity and Electronics with Advanced Educational Technology,NATO ASI Series F, Vol.115, Springer-Verlag, Berlin, pp. 173–195.
Bull, S.: 1994a, Learning Languages: Implications for Student Modelling in ICALL,ReCALL 6(1), 34–39.
Bull, S.: 1994b, Student Modelling for Second Language Acquisition,Computers and Education 23(1/2), 13–20.
Bull, S. and H. Pain: 1995, ‘Did I say what I think I said, and do you agree with me?’: Inspecting and Questioning the Student Model, to appear inProceedings of World Conference on Artificial Intelligence and Education, Washington DC, August.
Bull, S., H. Pain, and P. Brna: 1993, Student Modelling in an Intelligent Computer Assisted Language Learning System: The Issues of Language Transfer and Learning Strategies,Proceedings of the International Conference on Computers in Education, Taipei, Taiwan, pp. 121–126.
Bull, S., H. Pain, and P. Brna: in press, Mr. Collins: a Collaboratively Constructed, Inspectable Student Model for Intelligent Computer Assisted Language Learning,Instructional Science.
Catt, M. and G. Hirst: 1990, An Intelligent CALI System for Grammatical Error Diagnosis,CALL 3, 3–26.
Cohen, R., B. Eylon, and U. Ganiel: 1983, Potential Difference and Current in Simple Electrical Circuits: A Study of Students' Concepts,American Journal of Physics 51(5), 407–412.
Collins, A. and J.S. Brown: 1988, The Computer as a Tool for Learning Through Reflection. In: H. Mandl and A. Lesgold (eds.):Learning Issues for Intelligent Tutoring Systems, Springer-Verlag, New York, pp. 1–18.
Dumont, B.: 1993, A Diagnostic Knowledge-Based System for Fractions. In: H.S. Nwana (ed.):Mathematical Intelligent Learning Environments, Intellect Books, Oxford, pp. 189–198.
Dupin, J.-J.: 1987, Conceptions of French Pupils Concerning Electric Circuits: Structure and Evolution,Journal of Research in Science Teaching 24(9), 791–806.
Ellis, R.: 1992,Second Language Acquisition and Language Pedagogy. Multilingual Matters Ltd., Clevedon.
Escott, J.A. and G.I. McCalla: 1988. Problem Solving by Analogy: A Source of Errors in Novice Lisp Programming,Proceedings of ITS-88, Montreal, pp. 312–319.
Feurzeig, W. and F. Ritter: 1988, Understanding reflective problem solving. In: J. Psotka, L.D. Massey, and S.A. Mutter (eds.):Intelligent Tutoring Systems: Lessons Learned, Lawrence Erlbaum Associates, Hillsdale, NJ, pp. 435–450.
Gagne, R.M.: 1977,The Conditions of Learning, Holt-Saunders, New York.
Gentner, D. and D.R. Gentner: 1983, Flowing Waters or Teeming Crowds: Mental Models of Electricity. In: D. Gentner and A. Stevens (eds.):Mental Models, Lawrence Erlbaum Associates, Hillsdale, New Jersey, pp. 99–129.
Haertel, H.: 1982, The Electric Circuit as a System: A New Approach,European Journal of Science Education 4(1), 45–55.
Johnson, W.L. and E. Soloway: 1985, PROUST: Knowledge-Based Program Understanding,IEEE Transactions of Software Engineering,SE-11(3), 267–275.
Johsua, S. and J.-J. Dupin: 1993, Using ‘Modelling Analogies’ to Teach Basic Electricity: A Critical Analysis. In: M. Caillot (ed.): Learning Electricity and Electronics with Advanced Educational Technology,NATO ASI Series F, vol.115, Springer-Verlag, Berlin, pp. 229–249.
Kay, J.: 1995, The UM Toolkit for cooperative User Modeling,User Modeling and User-Adapted Interaction 4 (3), 149–196.
Kay, J. and K. Crawford: 1991,Interactive Learner Models as a Co-operative Learning Tool, Report 91/3/5.1, Systems Group, University of Sydney.
Kellerman, E.: 1977, Towards a Characterisation of the Strategy of Transfer in Second Language Learning,Interlanguage Studies Bulletin 2(1), 58–145.
Nisbet, J. and J. Shucksmith: 1986,Learning Strategies, Routledge and Kegan Paul, London.
Odlin, T.: 1989.Language Transfer, Cross-Linguistic Influence in Language Learning, Cambridge University Press, Cambridge.
O'Malley, J.M. and A.U. Chamot: 1990,Learning Strategies in Second Language Acquisition, Cambridge University Press, Cambridge.
Osborne, R.J.: 1981, Children's Ideas about Electric Current,New Zealand Science Teacher 29, 12–19.
Oxford, R.: 1990,Language Learning Strategies, What Every Teacher Should Know, Heinle & Heinle Publishers, Boston, Massachusetts.
Pienemann, M.: 1989, Is Language Teachable? Psycholinguistic Experiments and Hypotheses,Applied Linguistics 10(1), 52–79.
Psillos, D., P. Koumaras, and O. Valassiades: 1987, Pupils' Representations of Electric Current before, during and after Instruction on DC Circuits,Research in Science and Technological Education 5(2), 185–99.
Raven, R.J.: 1968, The Development of the Concept of Momentum in Primary School Children,Journal of Research in Science Teaching 5, 216–223.
Ringbom, H.: 1983, Borrowing and Lexical Transfer,Applied Linguistics 4(3), 207–212.
Schmidt, R.W.: 1990, The Role of Consciousness in Second Language Learning,Applied Linguistics 11(2), 129–158.
Schuster, E.: 1986, The Role of Native Grammars in Correcting Errors in Second Language Learning,Computational Intelligence 2, 93–98.
Shipstone, D.M., C. Rhoneck, W. Jung, C. Karrqvist, J.J. Dupin, S. Johsua, and P. Licht: 1988, A Study of Student Understanding of Electricity in Five European Countries,International Journal of Science Education 10(3), 303–316.
van Baalen, T.: 1983, Giving Learners Rules: A Study into the Effect of Grammatical Instruction with Varying Degrees of Explicitness,Interlanguage Studies Bulletin 7(1), 71–100.
Wang, Y. and R. Garigliano: 1992, An Intelligent Language Tutoring System for Handling Errors caused by Transfer,Proceedings of ITS-92, pp. 395–404.
White, B.Y. and J.R. Frederiksen: 1987,Causal Model Progressions as a Foundation for Intelligent Learning Environments, Report No. 6686, BBN Laboratories, Cambridge, Massachusetts.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Bull, S., Brna, P. & Pain, H. Extending the scope of the student model. User Model User-Adap Inter 5, 45–65 (1995). https://doi.org/10.1007/BF01101801
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF01101801