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Lee, Young-Jin – International Journal of Information and Learning Technology, 2017
Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…
Descriptors: Problem Solving, Educational Environment, Mathematics Instruction, Computer Assisted Instruction
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List, Alexandra; Alexander, Patricia A.; Stephens, Lori A. – Discourse Processes: A multidisciplinary journal, 2017
Three indicators of undergraduate students' (n = 197) source evaluation were investigated as students completed an academic task requiring the use of multiple texts. The source evaluation metrics examined were students' (1) accessing of document information, (2) trustworthiness ratings, and (3) citation in written responses. All three indicators…
Descriptors: Undergraduate Students, Evaluation Methods, Information Sources, Credibility
Lane, Forrest C.; Henson, Robin K. – Online Submission, 2010
Education research rarely lends itself to large scale experimental research and true randomization, leaving the researcher to quasi-experimental designs. The problem with quasi-experimental research is that underlying factors may impact group selection and lead to potentially biased results. One way to minimize the impact of non-randomization is…
Descriptors: Quasiexperimental Design, Research Methodology, Educational Research, Scores
Lancaster, Brian P. – 1999
Suppressor effects are considered one of the most elusive dynamics in the interpretation of statistical data. A suppressor variable has been defined as a predictor that has a zero correlation with the dependent variable while still, paradoxically, contributing to the predictive validity of the test battery (P. Horst, 1941). This paper explores the…
Descriptors: Correlation, Definitions, Heuristics, Identification
Murthy, Kavita – 1994
Commonality analysis is a procedure for decomposing the coefficient of determination (R superscript 2) in multiple regression analyses into the percent of variance in the dependent variable associated with each independent variable uniquely, and the proportion of explained variance associated with the common effects of predictors in various…
Descriptors: Correlation, Heuristics, Higher Education, Prediction
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Thompson, Bruce – 1989
The relationship between analysis of variance (ANOVA) methods and their analogs (analysis of covariance and multiple analyses of variance and covariance--collectively referred to as OVA methods) and the more general analytic case is explored. A small heuristic data set is used, with a hypothetical sample of 20 subjects, randomly assigned to five…
Descriptors: Analysis of Covariance, Analysis of Variance, Heuristics, Hypothesis Testing
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Maeshiro, Asatoshi – Journal of Economic Education, 1996
Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)
Descriptors: Causal Models, Correlation, Economics Education, Heuristics