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Vidushi Adlakha; Eric Kuo – Physical Review Physics Education Research, 2023
Recent critiques of physics education research (PER) studies have revoiced the critical issues when drawing causal inferences from observational data where no intervention is present. In response to a call for a "causal reasoning primer" in PER, this paper discusses some of the fundamental issues in statistical causal inference. In…
Descriptors: Physics, Science Education, Statistical Inference, Causal Models
Tagay, Özlem – Eurasian Journal of Educational Research, 2015
Problem Statement: A literature analysis revealed that contact disturbances, self-esteem and life satisfaction have been examined in different studies separately. In particular, the researchers observed that the studies conducted on Gestalt contact disturbances are limited in number. In this study, the variables of contact disturbances,…
Descriptors: Foreign Countries, College Students, Interpersonal Competence, Withdrawal (Psychology)
Sen, Senol; Yilmaz, Ayhan – Science Education International, 2016
The objective of this study is to analyze the relationship between preservice teachers' time and study environment management, effort regulation, self-efficacy beliefs, control of learning beliefs and metacognitive self-regulation. This study also investigates the direct and indirect effects of metacognitive self-regulation on time and study…
Descriptors: Structural Equation Models, Preservice Teachers, Self Efficacy, Self Control
Singaram, Veena S.; van der Vleuten, Cees P. M; Muijtjens, Arno M. M.; Dolmans, Diana H. J. M – Interdisciplinary Journal of Problem-based Learning, 2012
Little is known about the influence of language background in problem-based learning (PBL) tutorial groups on group processes and students' academic achievement. This study investigated the relationship between language background, secondary school score, tutorial group processes, and students' academic achievement in PBL. A validated tutorial…
Descriptors: Correlation, Native Language, Problem Based Learning, Academic Achievement
Fry, Donald W. – ProQuest LLC, 2010
While withdrawal from higher education may be the result of many reasons both within and beyond the control of the student or the institution, the intent of not returning to higher education indicates the acceptance of a permanent disassociation with the pursuit of the higher education endeavor. It is of paramount importance in understanding the…
Descriptors: Higher Education, College Students, Causal Models, Academic Persistence
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

Shedler, Johnathan – Measurement and Evaluation in Counseling and Development, 1995
Discusses linear structural relations, Two Stage Least Squares, and path analysis as statistical procedures that sometimes permit causal inferences from correlational findings. Even though two variables cannot be interpreted causally due to a possible but unknown third variable, these methods are appropriate for handling models with correlated…
Descriptors: Causal Models, Correlation, Higher Education, Path Analysis

Games, Paul A. – Journal of Experimental Education, 1990
The logical flaw of using the methods of path analysis and structural equation modeling to make causative conclusions is demonstrated. A proper evaluation of the role of investigation versus experimentation is cited in the work of W. G. Cochran as explicated by D. R. Rubin (1983). (TJH)
Descriptors: Causal Models, Correlation, Experiments, Methods Research

Kaeley, Gurcham S. – Educational Studies in Mathematics, 1993
Develops a causal model that explains over 40% of the variance in matriculation mathematics achievement of mature internal and external students at the University of Papua New Guinea. Background variables seem more important in the learning of mathematics compared to mediating variables for external students than for internal students. (MDH)
Descriptors: Causal Models, College Students, Correlation, Foreign Countries

Eldredge, J. Lloyd; And Others – Journal of Educational Research, 1990
Findings from a study of 504 second grade students indicate that phonics knowledge has a causal impact on both reading comprehension and vocabulary gains; reading comprehension has a causal effect on vocabulary gains. (Author/IAH)
Descriptors: Causal Models, Correlation, Decoding (Reading), Grade 2
Schmitt, Neal – 1991
Detailed methodology used to evaluate a causal model of school environment is presented in this report. The model depicts societal features that influence school district values and organizational characteristics, which in turn influence school operations and personnel attitudes and values. These school variables affect school community members'…
Descriptors: Analysis of Variance, Causal Models, Correlation, Educational Environment

Kember, David; And Others – American Journal of Distance Education, 1991
Presents a quantitative study of the development of a theoretical model of drop-outs from distance education courses. Data collected by the Distance Education Student Progress (DESP) questionnaire from 1,060 students in Hong Kong investigated how students were able to integrate demands of their academic course with those of families, employers,…
Descriptors: Academic Achievement, Causal Models, Correlation, Distance Education

McPherson, Gary E.; And Others – Journal of Research in Music Education, 1997
Surveys 101 wind instrumentalists to reveal major differences in the pattern of influences leading to the re-creative skill of performing a repertoire of rehearsed music for a formal examination compared to the creative ability of improvising. Uses a path analysis to determine links between the data and theoretical model. (MJP)
Descriptors: Behavioral Objectives, Causal Models, Context Effect, Correlation