Motivated Strategies for Learning Questionnaire

Pintrich, Paul R.; Groot, Elisabeth Vialpando De

doi:10.1037/t09161-000

Cited by 462 publications

(517 citation statements)

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“…Research shows that self-efficacy is an important factor related to positive learning outcomes and can moderate the amount of effort learners put forth in achieving a specific learning objectives 20 . In this study, intrinsic motivation, extrinsic motivation, and self-efficacy were measured using selected subscales from the Motivated Strategies for Learning Questionnaire (MSLQ) 21 . The MSLQ is a widely used and validated 81-question Likert-scaled instrument designed to assess motivation and use of learning strategies by college students.…”

Section: Methodsmentioning

confidence: 99%

Problem-based learning in photonics technology education: assessing student learning

et al. 2009

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Problem-based learning (PBL) is an instructional approach whereby students learn course content by collaboratively solving complex real-world problems and reflecting on their experience. Research shows that PBL improves student knowledge and retention, motivation, problem-solving skills, and the ability to skillfully apply knowledge in new situations. One of the challenges with PBL, however, is that real-world problems are typically open-ended with more than one possible solution, which poses a challenge to educators with regard to assessing student performance. In this paper, we describe an approach to assessing student performance in PBL developed by the Photon PBL Project, a three-year National Science Foundation Advanced Technological Education (NSF-ATE) project in which eight interdisciplinary multimedia PBL "Challenges" were created in collaboration with photonics industry and university partners for use in high school and college math, science and technology courses. Assessment included measures of content knowledge, conceptual knowledge, problem-solving skills, motivation, self-efficacy, and metacognitive ability. Results from pilot testing at four community college photonics technology programs are presented.

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Section: Methodsmentioning

confidence: 99%

Problem-based learning in photonics technology education: assessing student learning

et al. 2009

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“…Some items were adapted to be applicable to an engineering course from the Motivated Strategies for Learning Questionnaire (MSLQ) 31,32 . Other survey items were written in three sections 16 : a 13 item goal orientation section, a 28 item FTP section, and 16 items on task and course specific problem-solving self-efficacy 33 .…”

Section: Phase Imentioning

confidence: 99%

“…Other survey items were written in three sections 16 : a 13 item goal orientation section, a 28 item FTP section, and 16 items on task and course specific problem-solving self-efficacy 33 . The MSLQ 31,34,35 has been well-documented, and the MSLQ and MAE survey 36 have both been tested for validity and reliability. Only the 28 items from the FTP section of the end of semester survey were included in a cluster analysis (see Appendix A) due to the research questions for this pilot study.…”

Section: Phase Imentioning

confidence: 99%

Future Time Perspective and Self-Regulated Learning: Multiple Case Studies in Industrial Engineering

Chasmar¹,

Benson²

2016 ASEE Annual Conference &Amp; Exposition Proceedings

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Lisa Benson is an Associate Professor of Engineering and Science Education at Clemson University, with a joint appointment in Bioengineering. Her research focuses on the interactions between student motivation and their learning experiences. Her projects involve the study of student perceptions, beliefs and attitudes towards becoming engineers and scientists, and their problem solving processes. Other projects in the Benson group include effects of student-centered active learning, self-regulated learning, and incorporating engineering into secondary science and mathematics classrooms. Her education includes a B.S. This research paper is a pilot of a larger, mixed methods study that aims to capture the experience of sophomore engineering students' self-regulated learning (SRL) strategy use and the connections with the student's motivation with respect to the future. The overarching goal of the project is to understand the motivations and attitudes of undergraduate students in engineering, which is vital to answering the call for increasing the number of engineering graduates. Our project aim is to study engineering students' future time perspective (FTP) and how their FTP affects their use of SRL strategies. The quantitative portion of this study describes a cluster analysis of data from a motivation survey that characterizes students' FTP (n=118). The qualitative portion consists of case studies (n=4) which assess connections between students' FTP and SRL use. The cluster analysis showed three clusters of student FTP's. Interviews showed that clustering matched the FTP interview results, a variety of SRL strategy use among FTP's, and connections between FTP and SRL including perceived instrumentality and a timeline of short and/or long term goals. Future work will focus on the connection between FTP and SRL with the intent that practitioners may use this work to create programming related to these themes to increase SRL use among undergraduate engineering students.

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“…This model stresses the learners' use of cognitive strategies and self-regulatory strategies, self-efficacy beliefs (individuals' judgements of their capabilities to perform a task), task value beliefs (the importance of, interest in and value associated with a task) and goal orientation (intrinsic and extrinsic goal orientation), (further details provided in Pintrich (1999)). The MSLQ (Pintrich (1991b)), a self-report instrument designed to measure students' motivation and self-regulated learning in classroom contexts, was used to measure this model. The MSLQ is composed of two sections: a motivation section Predicting Introductory Programming Performance 313 and a learning strategies section.…”

Section: Instrumentsmentioning

confidence: 99%

Predicting introductory programming performance: A multi-institutional multivariate study

Bergin

Reilly

2006

Computer Science Education

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A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined.

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Motivated Strategies for Learning Questionnaire

Abstract: Please rate the following items based on your behavior in this class. Your rating should be on a 7point scale where 1= not at all true of me to 7=very true of me .

Cited by 462 publications

References 0 publications

Problem-based learning in photonics technology education: assessing student learning

Problem-based learning in photonics technology education: assessing student learning

Future Time Perspective and Self-Regulated Learning: Multiple Case Studies in Industrial Engineering

Predicting introductory programming performance: A multi-institutional multivariate study

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