Toward Intelligent Systems for Testing. Technical Report LSP-1 [electronic resource] / Alan Lesgold and Others.
This report illustrates one way in which the technologies of testing might combine with cognitive science techniques to help steer instruction. Steering testing is brief diagnostic testing that steers, or individualizes, the course of instruction. Steering testing uses simple heuristics for reasonin...
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| Format: | Electronic eBook |
| Language: | English |
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[S.l.] :
Distributed by ERIC Clearinghouse,
1987.
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MARC
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| 100 | 1 | |a Lesgold, Alan. | |
| 245 | 1 | 0 | |a Toward Intelligent Systems for Testing. Technical Report LSP-1 |h [electronic resource] / |c Alan Lesgold and Others. |
| 260 | |a [S.l.] : |b Distributed by ERIC Clearinghouse, |c 1987. | ||
| 300 | |a 32 p. | ||
| 500 | |a ERIC Document Number: ED283857. | ||
| 500 | |a Sponsoring Agency: Office of Naval Research, Arlington, VA. Personnel and Training Research Programs Office. |5 ericd. | ||
| 500 | |a Contract Number: N00014-85-K-0655. |5 ericd. | ||
| 520 | |a This report illustrates one way in which the technologies of testing might combine with cognitive science techniques to help steer instruction. Steering testing is brief diagnostic testing that steers, or individualizes, the course of instruction. Steering testing uses simple heuristics for reasoning about the level of a student's competence in a particular subskill and intelligently manufactures practice opportunities that will be especially revealing about the student's current competences. Theoretically, steering testing should permit a partly logical constraining of diagnosis and should be based on a representation of the knowledge needed to exercise the skill it purports to measure. Four types of knowledge, involved in dealing with a student, need clarification when designing computer systems for steering testing: (1) domain expertise; (2) curriculum knowledge; (3) planning knowledge; and (4) treatment knowledge. In addition, a student model, a knowledge structure specifying which subskills a student is thought to know or to not know, is embedded in the curricular goal structure of the system. When a diagnosis is needed, the student model is examined to identify areas of competence about which more information is needed. These areas represent constraints on the type of test item that will be informative. Once the constraints are posted, an intelligent item generator constructs test items that satisfy them. To illustrate these ideas, an intelligent computer-based tutor, with a problem solving mode, that teaches basic electrical principles is discussed. (BS) | ||
| 650 | 1 | 7 | |a Adaptive Testing. |2 ericd. |
| 650 | 1 | 7 | |a Artificial Intelligence. |2 ericd. |
| 650 | 1 | 7 | |a Cognitive Measurement. |2 ericd. |
| 650 | 0 | 7 | |a Computer Assisted Instruction. |2 ericd. |
| 650 | 1 | 7 | |a Computer Assisted Testing. |2 ericd. |
| 650 | 0 | 7 | |a Course Objectives. |2 ericd. |
| 650 | 0 | 7 | |a Criterion Referenced Tests. |2 ericd. |
| 650 | 1 | 7 | |a Diagnostic Tests. |2 ericd. |
| 650 | 1 | 7 | |a Individualized Instruction. |2 ericd. |
| 650 | 0 | 7 | |a Instructional Development. |2 ericd. |
| 650 | 0 | 7 | |a Test Construction. |2 ericd. |
| 710 | 2 | |a University of Pittsburgh. |b Learning Research and Development Center. | |
| 856 | 4 | 0 | |u http://files.eric.ed.gov/fulltext/ED283857.pdf |z Full Text (via ERIC) |
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