Abstract:

This study investigated self-regulated learning behaviors and their relationships with academic performance in web-based courses. The participants (n = 106) were students taking distance learning courses offered by a community college in the United States. The theoretical framework for this study was based on social cognitive theory. Data was collected using 28 items from the Motivated Strategies for Learning Questionnaire (MSLQ) and other items relevant to demographic data collection. The 28 items addressed four subscales (categories) relevant to self regulated learning behaviors: extrinsic goal orientation, intrinsic goal orientation, metacognitive self regulation and time and study management. The Motivated Strategies for Learning Questionnaire has been empirically proven to be valid and reliable in assessing the use of self regulated learning behaviors in traditional, non-technical learning environments. This study employed techniques to validate the instrument in technical, distance delivery contexts. Data analysis included factor analyses, multivariate analysis of variance, and regression analyses. The employment of self-regulated learning behaviors differed between humanities and technical courses (p =.0138). Time and study environment management (p = .0009) and intrinsic goal orientation (p = .0373) categories reported significant findings in their relationship to academic performance. A major outcome of this study is to develop a replicable modelt that can be implemented to use the Motivated Strategies for Learning Questionnaire as a predictor of academic performance in web-based environments. The factors affiliated with time and study environment management and intrinsic goal orientation were used as predictors in the development of a mathematical formula used to determine academic success in a web-based course. These predictors explain 21 percent of the variance in the academic success rating calculated using the mathematical formula developed from this study.

Keywords:

self regulated learning, metacognition, web-based instruction.