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Simon, Sharotka M.; Meldrum, Helen; Ndung'u, Eric; Ledley, Fred D. – CBE - Life Sciences Education, 2018
The majority of students who enroll in undergraduate biology courses will eventually be employed in non-STEM (science, technology, engineering, and mathematics) business occupations. This work explores how representations of industry in undergraduate biology textbooks could impact STEM learning for these students and their ability to apply this…
Descriptors: STEM Education, Introductory Courses, Biology, Undergraduate Students
Jorgensen, Estelle R.; Ward-Steinman, Patrice Madura – Journal of Research in Music Education, 2015
The purpose of this study was to examine evidence of a hypothesized shift in the operative research paradigms in music education during the first quarter century of the publication of the "Journal of Research in Music Education," during the period 1953 to 1978. This shift was from humanities-oriented historical and philosophical studies…
Descriptors: Music Education, Educational Research, Educational History, Educational Change
Garner, Pamela W.; Mahatmya, Duhita; Brown, Elizabeth L.; Vesely, Colleen K. – Educational Psychology Review, 2014
The primary goal of this article is to situate the findings from evidence-based studies of social emotional learning (SEL) interventions into a broader social context by reframing the discussion to consider how aspects of sociocultural competence impact the development and delivery of programs. The limitations of current SEL intervention efforts…
Descriptors: Heuristics, Emotional Development, Social Development, Intervention
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