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Meyer, Katrina A.; Xu, Yonghong Jade – Journal of Asynchronous Learning Networks, 2009
Based on earlier studies using the 1999 and 2004 National Study of Postsecondary Faculty (NSOPF) data [1, 2], a causal model explaining faculty technology use was constructed. Path analysis was used to test the causal effects of age, gender, highest degree, discipline (health science or not), recent research productivity, and teaching load on…
Descriptors: College Instruction, Intellectual Disciplines, Causal Models, Teaching Load

Lottes, Ilsa L.; And Others – Teaching Sociology, 1996
Defines and illustrates basic concepts of dichotomous logistic regression (DLR) and presents strategies for teaching these concepts. Strategies include using analogies between ordinary least squares regression and logistic regression; illustrating concepts with contingency tables; and linking logistic regression concepts to interpretation of…
Descriptors: Analysis of Variance, Causal Models, Higher Education, Instructional Improvement
Hsu, Wen-Kai K.; Huang, Show-Hui S. – Journal of Educational Computing Research, 2006
The purpose of this article is to discuss determinants of computer self-efficacy from the perspective of participant internal learning motivations and external learning environments. The former consisted of three motivations--interest, trend, and employment--while the latter comprised two environments--home and school. Through an intermediate…
Descriptors: Family Environment, Educational Environment, Computer Uses in Education, Causal Models

Vaage, Gjermund; Kohn, Robert E. – Journal of Economic Education, 1998
Examines two classes of production functions in which the long-run competitive equilibrium scale of the firm increases when the relative price of the dominant factor decreases. Compares these with a third class of production functions where the equilibrium scale is independent of the relative price of the dominant factor. (MJP)
Descriptors: Business Cycles, Causal Models, Competition, Cost Indexes

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