Intelligent Tutoring SystemsD. Sleeman, J. S. Brown |
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Page 164
... bug in the borrowing procedure in the remaining columns . 2.4 COMPOUND BUGS Students often have mislearned more than part of the skill , and thus have a combination , or compound , of two or more primitive bugs . In a recent experiment ...
... bug in the borrowing procedure in the remaining columns . 2.4 COMPOUND BUGS Students often have mislearned more than part of the skill , and thus have a combination , or compound , of two or more primitive bugs . In a recent experiment ...
Page 167
D. Sleeman, J. S. Brown. Allowing bugs in an executable model to be arbitrarily combined may result in the implementation problem of loops . For example , if the primitive bug of moving from left to right instead of right to left is not ...
D. Sleeman, J. S. Brown. Allowing bugs in an executable model to be arbitrarily combined may result in the implementation problem of loops . For example , if the primitive bug of moving from left to right instead of right to left is not ...
Page 173
... primitive bugs that are constituents in the final diagnosis have independent evidence in only one problem . If any of these problems had not been on the test , the diagnostic program would not have had the correct diagnosis in its ...
... primitive bugs that are constituents in the final diagnosis have independent evidence in only one problem . If any of these problems had not been on the test , the diagnostic program would not have had the correct diagnosis in its ...
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