Generative Computer Assisted Instruction: An Application of Artificial Intelligence to CAI.
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| Title: | Generative Computer Assisted Instruction: An Application of Artificial Intelligence to CAI. |
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| Authors: | Koffman, Elliot B., Connecticut Univ., Storrs. Dept. of Electrical Engineering. |
| Peer Reviewed: | N |
| Page Count: | 8 |
| Publication Date: | 1972 |
| Sponsoring Agency: | National Center for Educational Research and Development (DHEW/OE), Washington, DC. National Science Foundation, Washington, DC. Office of Computing Activities. |
| Descriptors: | Algorithms, Artificial Intelligence, Computer Assisted Instruction, Computers, Problem Solving, Programed Instructional Materials, State of the Art Reviews, Textbooks |
| Abstract: | Frame-oriented computer-assisted instruction (CAI) systems dominate the field, but these mechanized programed texts utilize the computational power of the computer to a minimal degree and are difficult to modify. Newer, generative CAI systems which are supplied with a knowledge of subject matter can generate their own problems and solutions, can provide extensive drill and tutoring, and can diagnose learner problems and prescribe remedial feedback. These systems reduce the amount of instructor effort required to teach new material and encourage students to assume the initiative in studying new topics. Information-Structure Oriented (ISO) systems have capabilities for natural language communication and are useful in the humanities and social sciences. Quantitative systems rely on algorithms and are oriented toward providing students with practice in problem-solving. While the existing generative systems are still experimental it is expected that their use will become more widespread as research continues and as CAI facilities become more available and economical. (PB) |
| Entry Date: | 1973 |
| Accession Number: | ED078648 |
| Database: | ERIC |
| Abstract: | Frame-oriented computer-assisted instruction (CAI) systems dominate the field, but these mechanized programed texts utilize the computational power of the computer to a minimal degree and are difficult to modify. Newer, generative CAI systems which are supplied with a knowledge of subject matter can generate their own problems and solutions, can provide extensive drill and tutoring, and can diagnose learner problems and prescribe remedial feedback. These systems reduce the amount of instructor effort required to teach new material and encourage students to assume the initiative in studying new topics. Information-Structure Oriented (ISO) systems have capabilities for natural language communication and are useful in the humanities and social sciences. Quantitative systems rely on algorithms and are oriented toward providing students with practice in problem-solving. While the existing generative systems are still experimental it is expected that their use will become more widespread as research continues and as CAI facilities become more available and economical. (PB) |
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