Abstract
If a student to machine response falls outside a predetermined range during computer based instruction, then some off line procedures (or an ignore command) must be invoked. This observation points out that student to machine response is generally that of a multiple choice format with a perhaps large, but still finite, list of possible responses. In this paper we will discuss the uses of information theory and the Bayesian philosophy of probability to evaluate student to machine responses when there is a well defined set of possible answers.
- 1 Brillouin, L. (1962). Science and Information Theory. New York: Academic Press.Google Scholar
- 2 Goldman, Stanford (1953). Information Theory. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
- 3 Reza, R. M. (1961). An Introduction to Information Theory. New York: McGraw-Hill.Google Scholar
- 4 Savage, L. J. (1971). Elicitation of personal probabilities and expectations. J. of Am. Stat. Assoc. 66, 783-801.Google Scholar
Cross Ref
- 5 Shuford, E. H., Albert, A., and Massengill, H. E. (1966). Admissible probability measurements procedures. Psychometrika 31, 125-145.Google Scholar
Cross Ref
- 6 Vawter, Richard (1972). Information theory personal probabilities, and the evaluation of multiple choice examinations W.W.S.C. Report available upon request from the authorGoogle Scholar
- 7 Vawter, Richard (1975). Entropy state of a multiple choice examination and the evaluation of understanding. Am. J. of Phys. (in press)Google Scholar
- 8 Watanabe, Satosi (1969). Knowing and Guessing. New York: John Wiley.Google Scholar
Index Terms
The use of information theory and personal probabilities in computer based learning
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The use of information theory and personal probabilities in computer based learning
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