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Peer reviewedWhite, George M.; Haddad, Michel – Computers and Education, 1983
Describes an algorithm used at the University of Ottawa to create examination schedules that are not only conflict free and minimize number of consecutive examinations for individual students, but provide for the scheduling of certain proper subsets of examinations into proper time slots and minimal overall number of consecutive examinations. (MBR)
Descriptors: Algorithms, Day Students, Evening Students, Higher Education
Peer reviewedArganbright, Deane E. – College Mathematics Journal, 1984
How to use the electronic spreadsheet (e.g., VisiCalc) creatively is discussed, with computer printouts for a number of algorithms. (MNS)
Descriptors: Algorithms, College Mathematics, Computer Oriented Programs, Computer Programs
Peer reviewedVan Der Flier, Henk; And Others – Journal of Educational Measurement, 1984
Two strategies for assessing item bias are discussed: methods comparing item difficulties unconditional on ability and methods comparing probabilities of response conditional on ability. Results suggest that the iterative logit method is an improvement on the noniterative one and is efficient in detecting biased and unbiased items. (Author/DWH)
Descriptors: Algorithms, Evaluation Methods, Item Analysis, Scores
Peer reviewedBentler, P. M.; Tanaka, Jeffrey S. – Psychometrika, 1983
Rubin and Thayer recently presented equations to implement maximum likelihood estimation in factor analysis via the EM algorithm. It is argued here that the advantages of using the EM algorithm remain to be demonstrated. (Author/JKS)
Descriptors: Algorithms, Factor Analysis, Maximum Likelihood Statistics, Research Problems
Peer reviewedRubin, Donald B.; Thayer, Dorothy T. – Psychometrika, 1983
The authors respond to a criticism of their earlier article concerning the use of the EM algorithm in maximum likelihood factor analysis. Also included are the comments made by the reviewers of this article. (JKS)
Descriptors: Algorithms, Estimation (Mathematics), Factor Analysis, Maximum Likelihood Statistics
Peer reviewedEimer, Rebecca A. – Mathematics Teacher, 1977
An algorithm is given for computing the cube root of any real number on a calculator. (DT)
Descriptors: Algorithms, Calculators, Instruction, Mathematics Education
Download full textGurtner, Jean-Luc, Ed. – 1997
The purpose of this conference sponsored by the French Commission of the Methods of Teaching was to give deep reflection as to the place of algorithms in the teaching curriculum and learning of mathematics. Devoted to the concept of new teaching methods at levels 1-4 of compulsory school education, the debates of this seminar were an occasion for…
Descriptors: Algorithms, Elementary Secondary Education, Mathematics Curriculum, Mathematics Education
Krass, Iosif A.; Thomasson, Gary L. – 1999
New items are being calibrated for the next generation of the computerized adaptive (CAT) version of the Armed Services Vocational Aptitude Battery (ASVAB) (Forms 5 and 6). The requirements that the items be "good" three-parameter logistic (3-PL) model items and typically "like" items in the previous CAT-ASVAB tests have…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Nonparametric Statistics
Performance of Item Exposure Control Methods in Computerized Adaptive Testing: Further Explorations.
Chang, Shun-Wen; Ansley, Timothy N.; Lin, Sieh-Hwa – 2000
This study examined the effectiveness of the Sympson and Hetter conditional procedure (SHC), a modification of the Sympson and Hetter (1985) algorithm, in controlling the exposure rates of items in a computerized adaptive testing (CAT) environment. The properties of the procedure were compared with those of the Davey and Parshall (1995) and the…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Banks
Lau, C. Allen; Wang, Tianyou – 1999
A study was conducted to extend the sequential probability ratio testing (SPRT) procedure with the polytomous model under some practical constraints in computerized classification testing (CCT), such as methods to control item exposure rate, and to study the effects of other variables, including item information algorithms, test difficulties, item…
Descriptors: Algorithms, Computer Assisted Testing, Difficulty Level, Item Banks
Peer reviewedErcolano, Joseph – Arithmetic Teacher, 1974
Descriptors: Algorithms, Elementary School Mathematics, Instruction, Mathematics Education
Peer reviewedBahe, Lowell W. – School Science and Mathematics, 1974
Descriptors: Algorithms, Chemistry, Computation, Mathematical Applications
Peer reviewedTarte, Edward C. – Mathematics Teacher, 1974
Descriptors: Algorithms, Diagrams, Discovery Learning, Instruction
Lea, Wayne A. – Mechanical Translation, 1966
Research supported by grants from the National Science Foundation and the Joint Services Electronics Program. (DD)
Descriptors: Algorithms, Comparative Analysis, Grammar, Graphs
Peer reviewedLiggett, Robin Segerblom – Management Science, 1973
Presents an implicit enumeration algorithm for redrawing school attendance boundaries in order to meet integration requirements. The basis of the approach is the division of the city into smaller areas or zones corresponding to neighborhoods. (Author)
Descriptors: Algorithms, Bus Transportation, Neighborhood Schools, School Desegregation
