Intelligent tutoring systems |
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Contents
Intelligent tutoring systems 1 | 16 |
Misconceptions in students understanding 13 | 16 |
Towards a process model for high school algebra errors | 25 |
Copyright | |
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AICAI algebra algorithm answer approach ARGUMENT arithmetic Artificial Intelligence assertions assumptions behavior Beranek and Newman binary operator Borrow Brown Burton cave circuit coach Cognitive Cognitive Science column complex component Computer Aided Instruction concept construct correct d-rule debugging deduction describe diagnostic dialogue discuss domain equations errors evaluation evidence example expert explanation explore 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