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Volumn 24, Issue 2, 2008, Pages 153-172

Cluster-based predictive modeling to improve pedagogic reasoning

Author keywords

Artificial intelligence; Human factors engineering; Information systems; Neural networks

Indexed keywords

CLUSTER ANALYSIS; LEARNING SYSTEMS; MULTI AGENT SYSTEMS; NEURAL NETWORKS; PROBLEM SOLVING; STUDENTS;

EID: 38149096294     PISSN: 07475632     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chb.2007.01.007     Document Type: Article
Times cited : (6)

References (53)
  • 4
    • 38149037719 scopus 로고    scopus 로고
    • Arroyo, I., Beck, J., Schultz, K., & Woolf, B. (1999). Piagetian psychology in intelligent tutoring systems. In: Proceedings of the ninth international conference on artificial intelligence in Education (pp. 600-602). Le Mans, France.
  • 5
    • 84944325078 scopus 로고    scopus 로고
    • Macroadapting animal watch to gender and cognitive differences with respect to hint interactivity and symbolism
    • Arroyo I., Beck J., Woolf B., Beal C., and Schultz K. Macroadapting animal watch to gender and cognitive differences with respect to hint interactivity and symbolism. Lecture Notes in Computer Science 1839 (2000) 574-583
    • (2000) Lecture Notes in Computer Science , vol.1839 , pp. 574-583
    • Arroyo, I.1    Beck, J.2    Woolf, B.3    Beal, C.4    Schultz, K.5
  • 6
    • 35048813540 scopus 로고    scopus 로고
    • Inferring unobservable learning variables from students' help seeking behavior
    • Arroyo I., Murray T., Woolf B.P., and Beal C.R. Inferring unobservable learning variables from students' help seeking behavior. Lecture Notes in Computer Science 3220 (2004) 782-784
    • (2004) Lecture Notes in Computer Science , vol.3220 , pp. 782-784
    • Arroyo, I.1    Murray, T.2    Woolf, B.P.3    Beal, C.R.4
  • 7
    • 84944317270 scopus 로고    scopus 로고
    • High-level student modeling with machine learning
    • Beck J.E., and Woolf B.P. High-level student modeling with machine learning. Lecture Notes in Computer Science 1839 (2000) 584-593
    • (2000) Lecture Notes in Computer Science , vol.1839 , pp. 584-593
    • Beck, J.E.1    Woolf, B.P.2
  • 8
    • 38149025360 scopus 로고    scopus 로고
    • Beck, J., Woolf, B. P., & Beal, C. R. (2000). ADVISOR: A machine learning architecture for intelligent tutor construction. In Proceedings of the seventeenth national conference on artificial intelligence (pp. 552-557). Austin, TX.
  • 9
    • 0002607026 scopus 로고    scopus 로고
    • Bayesian classification (AutoClass): Theory and results
    • Fayyad U.M., Piatetsky-Shapiro G., Smyth P., and Uthurusamy R. (Eds), AAAI/MIT Press, Menlo Park, CA
    • Cheeseman P., and Stutz J. Bayesian classification (AutoClass): Theory and results. In: Fayyad U.M., Piatetsky-Shapiro G., Smyth P., and Uthurusamy R. (Eds). Advances in knowledge discovery and data mining (1996), AAAI/MIT Press, Menlo Park, CA 153-180
    • (1996) Advances in knowledge discovery and data mining , pp. 153-180
    • Cheeseman, P.1    Stutz, J.2
  • 10
    • 0031681786 scopus 로고    scopus 로고
    • Using decision trees for agent modeling: improving prediction performance
    • Chiu B.C., and Webb G.I. Using decision trees for agent modeling: improving prediction performance. User Modeling and User-Adapted Interaction 8 1-2 (1998) 131-152
    • (1998) User Modeling and User-Adapted Interaction , vol.8 , Issue.1-2 , pp. 131-152
    • Chiu, B.C.1    Webb, G.I.2
  • 13
    • 0028576346 scopus 로고    scopus 로고
    • Devaney, M., & Ram, A. (1994). Dynamically adjusting categories to accommodate changing contexts. In Proceedings of the twelfth national conference on artificial intelligence (p. 1441). Seattle, Washington.
  • 14
    • 0346276295 scopus 로고
    • The design of a self-improving tutor: PROTO-TEG
    • Dillenbourg P. The design of a self-improving tutor: PROTO-TEG. Instructional Science 18 3 (1989) 193-216
    • (1989) Instructional Science , vol.18 , Issue.3 , pp. 193-216
    • Dillenbourg, P.1
  • 17
    • 0001942419 scopus 로고
    • Learning and teaching styles in engineering education
    • Felder R.M., and Silverman L.K. Learning and teaching styles in engineering education. Engineering Education 78 7 (1988) 674-681
    • (1988) Engineering Education , vol.78 , Issue.7 , pp. 674-681
    • Felder, R.M.1    Silverman, L.K.2
  • 18
    • 0343442766 scopus 로고
    • Knowledge acquisition via incremental conceptual clustering
    • Fisher D. Knowledge acquisition via incremental conceptual clustering. Machine Learning 2 (1987) 139-172
    • (1987) Machine Learning , vol.2 , pp. 139-172
    • Fisher, D.1
  • 19
    • 0031639830 scopus 로고    scopus 로고
    • Gertner, A. S., Conati, C., & VanLehn, K. (1998). Procedural help in ANDES: Generating hints using a Bayesian network student model. In Proceedings of the fifteenth national conference on artificial intelligence (pp. 106-111). Madison, WI.
  • 20
    • 0000783818 scopus 로고
    • Conceptual clustering, categorization, and polymorphy
    • Hanson S.J., and Bauer M. Conceptual clustering, categorization, and polymorphy. Machine Learning 3 (1989) 343-372
    • (1989) Machine Learning , vol.3 , pp. 343-372
    • Hanson, S.J.1    Bauer, M.2
  • 22
    • 38149107323 scopus 로고    scopus 로고
    • John, G. H., & Langley P. (1995). Estimating continuous distributions in Bayesian classifiers. In Proceedings of the eleventh conference on uncertainty in artificial intelligence (pp. 338-345). Montreal, Que.
  • 25
    • 0026992322 scopus 로고    scopus 로고
    • Langley, P., Iba, W., & Thompson, K. (1992). An analysis of Bayesian classifiers. In Proceedings of the tenth national conference on artificial intelligence (pp. 223-228). San Jose, CA.
  • 26
    • 0000166613 scopus 로고
    • Experiments with incremental concept formation: UNIMEM
    • Lebowitz M. Experiments with incremental concept formation: UNIMEM. Machine Learning 2 (1987) 103-138
    • (1987) Machine Learning , vol.2 , pp. 103-138
    • Lebowitz, M.1
  • 27
    • 38149037718 scopus 로고    scopus 로고
    • Predicting high-level student responses using conceptual clustering
    • Towards sustainable and scalable educational innovations informed by the learning sciences. Loi C.K., Jonassen D., and Ikeda M. (Eds), IOS Press
    • Legaspi R., Sison R., Fukui K., and Numao M. Predicting high-level student responses using conceptual clustering. In: Loi C.K., Jonassen D., and Ikeda M. (Eds). Towards sustainable and scalable educational innovations informed by the learning sciences. Frontiers in Artificial Intelligence and Applications vol. 133 (2005), IOS Press 761-764
    • (2005) Frontiers in Artificial Intelligence and Applications , vol.133 , pp. 761-764
    • Legaspi, R.1    Sison, R.2    Fukui, K.3    Numao, M.4
  • 29
    • 38149036384 scopus 로고    scopus 로고
    • Li, C. (1995). Extending ITERATE conceptual clustering scheme in dealing with numeric data. Master's Thesis, Vanderbilt University, Nashville, TN.
  • 31
    • 35048874714 scopus 로고    scopus 로고
    • AgentX: Using reinforcement learning to improve the effectiveness of intelligent tutoring systems
    • Martin K.N., and Arroyo I. AgentX: Using reinforcement learning to improve the effectiveness of intelligent tutoring systems. Lecture Notes in Computer Science 3220 (2004) 564-572
    • (2004) Lecture Notes in Computer Science , vol.3220 , pp. 564-572
    • Martin, K.N.1    Arroyo, I.2
  • 33
    • 38149045586 scopus 로고    scopus 로고
    • Meyer, T. N., Miller, T. M., Steuck, K., & Kretschmer, M. (1999). A multi-year large-scale field study of a learner controlled intelligent tutoring system. In Proceedings of the ninth international conference on artificial intelligence in education (pp. 191-198). Le Mans, France.
  • 35
    • 38149050362 scopus 로고    scopus 로고
    • Mostow, J. (2004). Some useful design tactics for mining ITS data. In Proceedings of the seventh international conference on intelligent tutoring systems workshop on analyzing student-tutor interaction logs to improve educational outcomes (pp. 20-28). Maceio, Alagoas, Brazil.
  • 36
    • 0031379974 scopus 로고    scopus 로고
    • Mostow, J., & Aist, G. (1997). The sounds of silence: Towards automated evaluation of student learning in a reading tutor that listens. In Proceedings of the fourteenth national conference on artificial intelligence (pp. 335-361). Providence, Rhode Island.
  • 37
    • 38149135012 scopus 로고    scopus 로고
    • Mostow, J., Beck, J.E., & Heiner, C. (2004). Which helps? Effects of various types of help on world learning in an automated reading tutor that listens. Paper presented at the eleventh annual meeting of the society for scientific study of reading. Amsterdam, The Netherlands.
  • 39
    • 0347402927 scopus 로고
    • A multidisciplinary model for development of intelligent computer-assisted instruction
    • Park O., and Seidel R.J. A multidisciplinary model for development of intelligent computer-assisted instruction. Educational Technology Research and Development 37 (1989) 72-80
    • (1989) Educational Technology Research and Development , vol.37 , pp. 72-80
    • Park, O.1    Seidel, R.J.2
  • 40
    • 0006820904 scopus 로고
    • How children form mathematical concepts
    • Piaget J. How children form mathematical concepts. Scientific American 189 5 (1953) 74-79
    • (1953) Scientific American , vol.189 , Issue.5 , pp. 74-79
    • Piaget, J.1
  • 43
    • 0008975818 scopus 로고
    • Bypassing the intractable problem of student modeling
    • Frasson C., and Gauthier G. (Eds), Ablex Publishing Corporation, Norwood, NJ
    • Self J.A. Bypassing the intractable problem of student modeling. In: Frasson C., and Gauthier G. (Eds). Intelligent tutoring systems: at the crossroad of artificial intelligence and education (1990), Ablex Publishing Corporation, Norwood, NJ 107-123
    • (1990) Intelligent tutoring systems: at the crossroad of artificial intelligence and education , pp. 107-123
    • Self, J.A.1
  • 44
    • 21344451768 scopus 로고    scopus 로고
    • An experimental system for learning probability: Stat Lady description and evaluation
    • Shute V., Gawlick-Grendell L.A., Young R.K., and Burnham C.A. An experimental system for learning probability: Stat Lady description and evaluation. Instructional Science 24 1 (1996) 25-46
    • (1996) Instructional Science , vol.24 , Issue.1 , pp. 25-46
    • Shute, V.1    Gawlick-Grendell, L.A.2    Young, R.K.3    Burnham, C.A.4
  • 47
    • 38149081110 scopus 로고    scopus 로고
    • Stern, M. K., Beck, J. E., & Woolf, B. P. (1999). Naïve Bayes classifiers for user modeling. http://citeseer.ist.psu.edu/stern99naive.html Accessed 06.07.03.
  • 48
    • 2742530540 scopus 로고
    • MAIS: An intelligent learning system
    • Jonassen D.H. (Ed), Lawrence Earlbaum Associates, Hillsdale, NJ
    • Tennyson R.D., and Christensen D.L. MAIS: An intelligent learning system. In: Jonassen D.H. (Ed). Instructional designs for micro-computer courseware (1988), Lawrence Earlbaum Associates, Hillsdale, NJ 247-274
    • (1988) Instructional designs for micro-computer courseware , pp. 247-274
    • Tennyson, R.D.1    Christensen, D.L.2
  • 49
    • 5444243723 scopus 로고    scopus 로고
    • A framework for the initialization of student models in web-based intelligent tutoring systems
    • Tsiriga V., and Virvou M. A framework for the initialization of student models in web-based intelligent tutoring systems. User Modeling and User-Adapted Interaction 14 4 (2004) 289-316
    • (2004) User Modeling and User-Adapted Interaction , vol.14 , Issue.4 , pp. 289-316
    • Tsiriga, V.1    Virvou, M.2
  • 51
    • 38149090816 scopus 로고    scopus 로고
    • Wasson, B. (1996). Instructional planning and contemporary theories of learning: Is this a self-contradiction?. In P. Brna, A. Paiva, and J. Self (Eds.), Proceedings of European conference on artificial intelligence in education (pp.23-30). Lisbon, Portugal.
  • 53


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.