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Detecting and reacting to the learner's motivational state

  • Teresa Del Soldato
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 608)

Abstract

Teaching knowledge implemented in current Intelligent Tutoring Systems (ITSs) concerns mostly cognitive aspects of instructional processes. However, teachers often interweave motivational tactics with the instructional decisions, building conditions that stimulate learning. Educational Research has provided several theories of instructional motivation which may be implemented in ITSs, in order to provide more appealing and effective interactions. Relevant aspects of implementing explicit motivational theories are discussed in this paper.

Keywords

Intelligent Tutor System Student Model Motivational Profile Positive Expectancy Puzzling Question 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Anderson, J. R., Boyle, C. F. & Yost, G.: The Geometry Tutor. In Proceedings of the International Joint Conference on Artificial. Intelligence (1985).Google Scholar
  2. Arshad, F.: The Design of Knowledge-based Advisors for Learning. Ph.D. thesis School of Education, University of Leeds (1990).Google Scholar
  3. Burton, R. R. & Brown, J. S.: An investigation of computer coaching for informal learning activities. In Sleeman, D. & Brown, J. (Eds.): Intelligent Tutoring Systems (1982) Academic Press.Google Scholar
  4. Keller, J. M.: Motivational design of instruction. In Reigeluth, C. M. (Ed.): Instructional-design Theories and Models: An Overview of Their Current Status (1983) Lawrence Erlbaum.Google Scholar
  5. Keller, J. M.: Strategies for stimulating the motivation to learn. Performance and Instruction Journal 26 (1987) 1–7Google Scholar
  6. Keller, J. M.: The systematic process of motivational design. Performance and Instruction Journal 26 (1987) 1–8Google Scholar
  7. Lepper, M. R. & Chabay, R. W.: Socializing the intelligent tutor: bringing empathy to computer tutors. In Mandl, H. & Lesgold, A. (Eds.): Learning Issues for Intelligent Tutoring Systems (1988) Springer-Verlag.Google Scholar
  8. Lepper, M. R. & Malone, T.: Intrinsic motivation and instructional effectiveness in computer-based education. In Snow, R. & Farr, M. (Eds.): Aptitude, Learning and Instruction: Conative and Affective Process Analyses (1987) Lawrence Erlbaum.Google Scholar
  9. Malone, T. & Lepper, M. R.: Making learning fun. In Snow, R. & Farr, M. (Eds.): Aptitude, Learning and Instruction: Conative and Affective Process Analyses (1987) Lawrence Erlbaum.Google Scholar
  10. Shuell, T. J.: Designing instructional computing systems for meaningful learning. In Winne, P. H. & Jones, M. (Eds.): Foundations and Frontiers in Instructional Computing Systems (in press) Springer-Verlag.Google Scholar
  11. Tosti, D. T.: Formative feedback. NSPI Journal October (1978).Google Scholar
  12. (Wasson) Brecht, B.: Determining the Focus of Instruction: Content Planning for Intelligent Tutoring Systems. Ph.D. thesis Department of Computational Science, University of Saskatchewan (1990).Google Scholar
  13. Woolf, B. P.: Context-dependent Planning in a Machine Tutor. Ph.D. thesis Department of Computer and Information Science, University of Massachusetts (1984).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Teresa Del Soldato
    • 1
  1. 1.School of Computing and Cognitive SciencesUniversity of SussexFalmerUK

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