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Measuring Changes In Motivation And Learning Strategies: Comparing Freshman To Other Undergraduates

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2006 Annual Conference & Exposition


Chicago, Illinois

Publication Date

June 18, 2006

Start Date

June 18, 2006

End Date

June 21, 2006



Conference Session

Knowing Our Students II

Tagged Division

Educational Research and Methods

Page Count


Page Numbers

11.916.1 - 11.916.11



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Paper Authors

author page

Todd Johnson Washington State University

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract


The purpose of this study was to understand reported motivation and learning strategies for students enrolled in an introductory computer science course (n = 111). Comparisons were made between freshman (n = 57) and other undergraduates (n = 54) [sophomores (n = 24) and juniors (n = 30)]. A commonly used instrument called the Motivational Strategies for Learning Questionnaire (MSLQ) was used to assess motivations (value, expectancy, and affective) and learning strategies (cognitive/metacognitive and resource management strategies) of these students. Results showed variations in both motivation and learning strategies between the two groups with freshman reporting a greater task value in the course, while other undergraduates reported a greater reliance on peer learning and the use of rehearsal strategies. In comparison to other undergraduates, freshman also reported having a greater confidence in reading. While more research is needed at the classroom level to understand individual student differences, the MSLQ does appear to provide insight for caring faculty using a learner centered approach to teaching.


Solving engineering student learning and retention problems requires adoption of proven educational practices1. Major investments of the National Science Foundation, US Department of Education, and other agencies have been directed toward understanding issues and identifying solutions to student learning and retention. As summarized by Svinicki2 at the First Annual Meeting of the Center for the Advancement of Scholarship in Engineering Education (CASEE), students learn best when they set goals for study, engage in active study, add meaning to what they are learning, explain their understanding to others, and self-monitor their success in achieving goals. For several researchers in computer sciences, self-regulation and the constructs of motivation and learning strategies have started to be explored to understanding student learning and retention3-7.

Self-regulation of learning has been shown in social cognitive research to be linked with academic achievement8-11 and has been deemed by some as a desirable goal for the 21st century university student12. Today, self-regulation is defined as encompassing a students' active control of learning resources (e.g., time, effort, peers), motivation (e.g., goals, self-efficacy), and strategies (deep processing) 13-14. Self-regulation of learning means that the student has the ability to develop knowledge, skills, and attitudes which enhance and facilitate future learning and can be transferred to other learning situations. According to Ertmer and Newby15, motivation and learning strategies that define self-regulation are essential to the performance of expert students who are faced with solving problems in novel situations. In novel situations, an understanding of "how" to learn by using specific cognitive skills and strategies distinguishes expert students from novices who may have an equal unfamiliarity with the content.

Student retention is, in part, due to their performance in individual courses. As educators, it is a desire that students exit courses not only knowledgeable about the content, but also possessing a

Johnson, T. (2006, June), Measuring Changes In Motivation And Learning Strategies: Comparing Freshman To Other Undergraduates Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--273

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