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Foley, Brett P. – Practical Assessment, Research & Evaluation, 2016
There is always a chance that examinees will answer multiple choice (MC) items correctly by guessing. Design choices in some modern exams have created situations where guessing at random through the full exam--rather than only for a subset of items where the examinee does not know the answer--can be an effective strategy to pass the exam. This…
Descriptors: Guessing (Tests), Multiple Choice Tests, Case Studies, Test Construction
Fiedler, Daniela; Tröbst, Steffen; Harms, Ute – CBE - Life Sciences Education, 2017
Students of all ages face severe conceptual difficulties regarding key aspects of evolution-- the central, unifying, and overarching theme in biology. Aspects strongly related to abstract "threshold" concepts like randomness and probability appear to pose particular difficulties. A further problem is the lack of an appropriate instrument…
Descriptors: College Students, Concept Formation, Probability, Evolution
Sadaghiani, Homeyra R.; Pollock, Steven J. – Physical Review Special Topics - Physics Education Research, 2015
As part of an ongoing investigation of students' learning in first semester upper-division quantum mechanics, we needed a high-quality conceptual assessment instrument for comparing outcomes of different curricular approaches. The process of developing such a tool started with converting a preliminary version of a 14-item open-ended quantum…
Descriptors: Science Instruction, Quantum Mechanics, Mechanics (Physics), Multiple Choice Tests
Peer reviewedDyck, Walter; Plancke-Schuyten, Gilberte – Educational and Psychological Measurement, 1976
Previous knowledge of the difficulty index and the intercorrelations of the items will allow group results to be predicted and manipulated. A compound bionomial probability function of a testscore is established for which a computer program has been written. Three item selections and the appropriate probability distributions are given which give…
Descriptors: Computer Programs, Multiple Choice Tests, Prediction, Probability
Frary, Robert B.; Zimmerman, Donald W. – Educ Psychol Meas, 1970
Descriptors: Error of Measurement, Guessing (Tests), Multiple Choice Tests, Probability
Suhadolnik, Debra; Weiss, David J. – 1983
The present study was an attempt to alleviate some of the difficulties inherent in multiple-choice items by having examinees respond to multiple-choice items in a probabilistic manner. Using this format, examinees are able to respond to each alternative and to provide indications of any partial knowledge they may possess concerning the item. The…
Descriptors: Confidence Testing, Multiple Choice Tests, Probability, Response Style (Tests)
Landa, Suzanne – 1976
Instructions are provided on how to create and take computer aided admissible probability measurement (CAAPM) tests using programs available on PLATO IV. Admissible probability measurement is a testing procedure that permits a user to express a degree of uncertainty as to the correctness of alternative answers. Section II describes PLATO IV, an…
Descriptors: Computer Oriented Programs, Confidence Testing, Multiple Choice Tests, Online Systems
Sibley, William L. – 1974
The use of computers in areas of testing, selection, and placement processes for those in military services' training programs are viewed in this paper. Also discussed is a review of the motivational and theoretical foundation of admissible probability testing, the role of the computer in admissible probability testing, and the authors' experience…
Descriptors: Computer Oriented Programs, Computers, Interaction, Military Training
PDF pending restorationCivil Service Commission, Washington, DC. Personnel Research and Development Center. – 1976
This pamphlet reprints three papers and an invited discussion of them, read at a Division 5 Symposium at the 1975 American Psychological Association Convention. The first paper describes a Bayesian tailored testing process and shows how it demonstrates the importance of using test items with high discrimination, low guessing probability, and a…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Oriented Programs, Computer Programs
Shuford, Emir H., Jr.; Brown, Thomas A. – 1974
A student's choice of an answer to a test question is a coarse measure of his knowledge about the subject matter of the question. Much finer measurement might be achieved if the student were asked to estimate, for each possible answer, the probability that it is the correct one. Such a procedure could yield two classes of benefits: (a) students…
Descriptors: Bias, Computer Programs, Confidence Testing, Decision Making
Levine, Michael V.; Rubin, Donald B. – 1976
Appropriateness indexes (statistical formulas) for detecting suspiciously high or low scores on aptitude tests were presented, based on a simulation of the Scholastic Aptitude Test (SAT) with 3,000 simulated scores--2,800 normal and 200 suspicious. The traditional index--marginal probability--uses a model for the normal examinee's test-taking…
Descriptors: Academic Ability, Aptitude Tests, College Entrance Examinations, High Schools

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