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A regression analysis of problem -based learning student variables

Jacqueline Y Fergusson, University of Nebraska - Lincoln

Abstract

This mixed methods study used a combination of survey research and written interviews to investigate whether student variables were useful predictors of their success in Problem Based Learning (PBL). Quantitative data were analyzed using regression analysis, qualitative data by inductive analysis. ^ Student research participants were drawn from 6 states in the U.S. and faculty participants from North America. The Motivated Strategies for Learning Questionnaire (MSLQ) was used with permission to collect quantitative data from students on motivation and learning strategies. Other instruments used to gather data were a Demographics Sheet, a Student Rating Inventory, a Students' Improvement Inventory, a Students' PBL Outcomes Sheet, and an Interview Questionnaire. ^ Student surveys were mailed to 217 students in 8 institutions. The 23 selected predictor student variables fell under the 3 categories demographic, learning-related, and institutional. There were 4 student outcome dependent variables: self-directed learning, collaboration, knowledge acquisition, and problem solving. Multiple regression analysis detected significant correlations between 3 predictor variables and the outcome dependent variables. ^ 20 Interview Questionnaires were mailed to faculty members. Inductive analysis of the responses from the Interview Questionnaires generally supported the quantitative findings and provided additional insights. ^ This study identified three student variables that are useful predictors of student success in PBL. Areas of further research included replicating the study in different forms and investigating specific issues in PBL that had been uncovered as areas of concern in the study. ^

Subject Area

Education, Educational Psychology|Education, Curriculum and Instruction

Recommended Citation

Fergusson, Jacqueline Y, "A regression analysis of problem -based learning student variables" (2003). ETD collection for University of Nebraska - Lincoln. AAI3116573.
http://digitalcommons.unl.edu/dissertations/AAI3116573

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