caa a22 4500 467945152 CHVBK 20180323165700.0 cr unu---uuuuu 170328e19900301xx s 000 0 eng 10.1023/A:1022607624441 doi (NATIONALLICENCE)springer-10.1023/A:1022607624441 (NATIONALLICENCE)springer-10.1007/BF00115893 Extending Domain Theories: Two Case Studies in Student Modeling [Elektronische Daten] [D. Sleeman, Haym Hirsh, Ian Ellery, In-Yung Kim] By its very nature, artificial intelligence is concerned with investigating topics that are ill-defined and ill-understood. This paper describes two approaches to expanding a good but incomplete theory of a domain. The first uses the domain theory as far as possible and fills in specific gaps in the reasoning process, generalizing the suggested missing steps and adding them to the domain theory. The second takes existing operators of the domain theory and applies perturbations to form new plausible operators for the theory. The specific domain to which these techniques have been applied is high-school algebra problems. The domain theory is represented as operators corresponding to algebraic manipulations, and the problem of expanding the domain theory becomes one of discovering new algebraic operators. The general framework used is one of generate and test—generating new operators for the domain and using tests to filter out unreasonable ones. The paper compares two algorithms, INFER and MALGEN, examining their performance on actual data collected in two Scottish schools and concluding with a critical discussion of the two methods. Kluwer Academic Publishers, 1990 Incomplete domain theories nationallicence generate and test nationallicence failure-driven learning nationallicence explanation-based learning nationallicence student modeling nationallicence intelligent tutoring systems nationallicence Sleeman D. Computing Science Department, King's College, The University of Aberdeen, AB9 2UB, Aberdeen, Scotland, UK. aut Hirsh Haym Knowledge Systems Laboratory, Computer Science Department, Stanford University, 94304., Palo Alto, CA aut Ellery Ian Computing Science Department, King's College, The University of Aberdeen, AB92UB, Aberdeen, Scotland, UK. aut Kim In-Yung FMC AI Center, Central Engineering Laboratories, 1205 Coleman Avenue, 95052., Santa Clara, CA aut Machine Learning Kluwer Academic Publishers-Plenum Publishers 5/1(1990-03-01), 11-37 0885-6125 5:1<11 1990 5 10994 https://doi.org/10.1023/A:1022607624441 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1022607624441 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Sleeman D. Computing Science Department, King's College, The University of Aberdeen, AB9 2UB, Aberdeen, Scotland, UK aut NATIONALLICENCE 700 1- Hirsh Haym Knowledge Systems Laboratory, Computer Science Department, Stanford University, 94304., Palo Alto, CA aut NATIONALLICENCE 700 1- Ellery Ian Computing Science Department, King's College, The University of Aberdeen, AB92UB, Aberdeen, Scotland, UK aut NATIONALLICENCE 700 1- Kim In-Yung FMC AI Center, Central Engineering Laboratories, 1205 Coleman Avenue, 95052., Santa Clara, CA aut NATIONALLICENCE 773 0- Machine Learning Kluwer Academic Publishers-Plenum Publishers 5/1(1990-03-01), 11-37 0885-6125 5:1<11 1990 5 10994 NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00115893 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Sleeman D. Computing Science Department, King's College, The University of Aberdeen, AB9 2UB, Aberdeen, Scotland, UK aut NATIONALLICENCE 700 1- Hirsh Haym Knowledge Systems Laboratory, Computer Science Department, Stanford University, 94304, Palo Alto, CA aut NATIONALLICENCE 700 1- Ellery Ian Computing Science Department, King's College, The University of Aberdeen, AB9 2UB, Aberdeen, Scotland, UK aut NATIONALLICENCE 700 1- Kim In-Yung Central Engineering Laboratories, FMC AI Center, 1205 Coleman Avenue, 95052, Santa Clara, CA aut NATIONALLICENCE 773 0- Machine Learning Kluwer Academic Publishers 5/1(1990-03-01), 11-37 0885-6125 5:1<11 1990 5 10994 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE NATIONALLICENCE NL-springer