Intelligent Tutoring SystemsD. Sleeman, J. S. Brown |
Contents
Intelligent tutoring systems | 1 |
A Friendly interfaces | 4 |
Special purpose deduction techniques | 7 |
Copyright | |
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AICAI air mass algebra algorithm analogy answer approach ARGUMENT arithmetic Artificial Intelligence assertions assumptions behavior Beranek and Newman Borrow Brown Burton caves circuit coach Cognitive Cognitive Science column complex component concept correct d-rule debugging deduction describe diagnostic dialogue diode discussed domain equations errors evaluation evidence example expert explanation extrapolation techniques fault FIRES-RESULT functional genetic graph goal Goldstein GROUP IS C H GUIDON heuristic Homunculus hypothesis implemented incorrect inference intelligent tutoring systems interaction interface Issues John Seely Brown learning MACSYMA mal-rules methods misconceptions mode module move multiple MYCIN nodes operator particular PEAK possible primitive bugs problem problem-solving procedure production rules propagation rainfall representation result rules sequence simulation skills Sleeman solution solving SOPHIE Spade-0 specific steps strategy structure student model subgoals subskills subtraction task teaching theory troubleshooting tutor underlying voltage Wumpus zero