Journal of Research in Science TeachingVolume 21, Issue 9 p. 953-955 Comments and CriticismFree Access Mathematical modeling of learning Peter F. W. Preece, Peter F. W. Preece The School of Education, University of Exeter, St. Luke's, Exeter, EX 1 2LU, EnglandSearch for more papers by this authorO. R. Anderson, O. R. AndersonSearch for more papers by this author Peter F. W. Preece, Peter F. W. Preece The School of Education, University of Exeter, St. Luke's, Exeter, EX 1 2LU, EnglandSearch for more papers by this authorO. R. Anderson, O. R. AndersonSearch for more papers by this author First published: December 1984 https://doi.org/10.1002/tea.3660210910Citations: 2AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL References Anderson, O. R. (1983). A neuromathematical model of human information processing and its application to science content acquisition. Journal of Research in Science Teaching, 20, 603– 620. Hicklin, W. J. (1976). A model for mastery learning based on dynamic equilibrium theory. Journal of Mathematical Psychology, 13, 79– 88. Preece, P. F. W. (1982). The fan-spread hypothesis and the adjustment for initial differences between groups in uncontrolied studies. Educational and Psychological Measurement, 42, 759– 762. Restle, F. (1971). Mathematical models in psychology. Harmondsworth: Penguin. Anderson, O. R. (1983). A neuromathematical model of human information processing and its application to science content acquisition. Journal of Research in Science Teaching, 20, 603– 620. Citing Literature Volume21, Issue9December 1984Pages 953-955 ReferencesRelatedInformation