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Ting, Choo-Yee; Sam, Yok-Cheng; Wong, Chee-Onn – Computers & Education, 2013
Constructing a computational model of conceptual change for a computer-based scientific inquiry learning environment is difficult due to two challenges: (i) externalizing the variables of conceptual change and its related variables is difficult. In addition, defining the causal dependencies among the variables is also not trivial. Such difficulty…
Descriptors: Concept Formation, Bayesian Statistics, Inquiry, Science Instruction
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Laru, Jari; Naykki, Piia; Jarvela, Sanna – Internet and Higher Education, 2012
In this single-case study, small groups of learners were supported by use of multiple social software tools and face-to-face activities in the context of higher education. The aim of the study was to explore how designed learning activities contribute to students' learning outcomes by studying probabilistic dependencies between the variables.…
Descriptors: Web Sites, Electronic Publishing, Cooperative Learning, Group Activities
Novick, Melvin R.; And Others – 1971
The feasibility and effectiveness of a Bayesian method for estimating regressions in m groups is studied by application of the method to data from the Basic Research Service of The American College Testing Program. Evidence supports the belief that in many testing applications the collateral information obtained from each subset of m-1 colleges…
Descriptors: Academic Achievement, Bayesian Statistics, College Students, Colleges
Lunneborg, Clifford E. – 1971
A Bayesian prediction strategy is outlined in which antecedent measures are divided into two subgroups. One subgroup is used to discriminate among criterion groups, the second to provide normal linear predictions for each group. Individualized regression constants are subsequently obtained by computing probabilities of group membership from the…
Descriptors: Academic Achievement, Achievement Tests, Aptitude Tests, Bayesian Statistics
Houston, Walter M.; Sawyer, Richard – 1988
Methods for predicting specific college course grades, based on small numbers of observations, were investigated. These methods use collateral information across potentially diverse institutions to obtain refined within-group parameter estimates. One method, referred to as pooled least squares with adjusted intercepts, assumes that slopes and…
Descriptors: Bayesian Statistics, College Students, Colleges, Comparative Analysis
Houston, Walter M. – 1988
Two methods of using collateral information from similar institutions to predict college freshman grade average were investigated. One central prediction model, referred to as pooled least squares with adjusted intercepts, assumes that slopes and residual variances are homogeneous across selected colleges. The second model, referred to as Bayesian…
Descriptors: Bayesian Statistics, College Freshmen, Colleges, Comparative Analysis
Noble, Julie P.; Sawyer, Richard – 1988
The validity of American College Testing Program (ACT) test scores and self-reported high school grades for predicting grades in specific college freshman courses was studied. Specific course grades are typically used to place students in remedial, standard, or advanced classes. These placement decisions, in turn, have immediate implications for…
Descriptors: Bayesian Statistics, College Freshmen, Comparative Analysis, Evaluation Methods