The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Reliability and Predictive Validity of the Motivated Strategies for Learning Questionnaire (Mslq)
Abstract
This paper reports on a new self-report, Likert-scaled instrument that was designed to assess motivation and use of learning strategies by college students. The motivation scales tap into three broad areas: (1) value (intrinsic and extrinsic goal orientation, task value), (2) expectancy (control beliefs about learning, self-efficacy); and (3) affect (test anxiety). The learning strategies section is comprised of nine scales which can be distinguished as cognitive, metacognitive, and resource management strategies. The cognitive strategies scales include (a) rehearsal, (b) elaboration, (c) organization, and (d) critical thinking. Metacognitive strategies are assessed by one large scale that includes planning, monitoring, and regulating strategies. Resource management strategies include (a) managing time and study environment; (b) effort management, (c) peer learning, and (d) help-seeking. Scale reliabilities are robust, and confirmatory factor analyses demonstrated good factor structure. In addition, the instrument shows reasonable predictive validity to the actual course performance of students.
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In the citing paper
“Established learning questionnaires (e.g., Pintrich et al. 1993) provide students with strategies or procedures, asking them to indicate whether and/or how often they apply the respective strategies.”
From Transfer of metacognitive skills in self-regulated learning: an experimental training study (2020) · cites this paper as Pintrich et al. 1993
In the citing paper
“As indicated in the original study (Pintrich et al., 1993), this scale demonstrates good reliability and validity (Cronbach's alpha = 0.80).”
From The role of critical thinking on undergraduates' reliance behaviours on generative AI in problem‐solving (2025) · cites this paper as Pintrich et al., 1993
Citations
Cites
Handbook of research on teaching
Wittrock, M. C. (1986) · Bibliothèque et Archives nationales du Québec (Québec government) · Cited by 10,630
Structural Equation Modeling with LISREL: Essentials and Advances.
Land, K. C., & Hayduk, L. A. (1990) · Social Forces · doi:10.2307/2579660 · Cited by 1,313
A Process-Oriented View of Student Motivation and Cognition.
Pintrich, P. (1988) · New Directions for Institutional Research · doi:10.1002/ir.37019885707 · Cited by 255
Self-citationMckeachie, W., Pintrich, P., & Lin, Y.-G. (1985) · Educational Psychologist · doi:10.1207/s15326985ep2003_5 · Cited by 159
Self-citationStructural Equation Modeling with LISREL: Essentials and Advances
Wardrop, J. L., Hayduk, L. A., & Bollen, K. A. (1993) · Journal of Educational Statistics · doi:10.2307/1165186 · Cited by 127
Survey of study habits and attitutes
Brown, W. F., & Holtzman, W. H. (1965) · Bibliothèque et Archives nationales du Québec (Québec government) · Cited by 117
Student learning and college teaching
Pintrich, P. (1988) · New Directions for Teaching and Learning · doi:10.1002/tl.37219883308 · Cited by 103
Self-citationTeaching a Course in Learning to Learn
Pintrich, P. R., McKeachie, W. J., & Lin, Y.-G. (1987) · Teaching of Psychology · doi:10.1207/s15328023top1402_3 · Cited by 80
Self-citationSurvey of Study Habits and Attitudes
Brown, W. F., & Holtzman, W. H. (1953) · PsycTESTS Dataset · doi:10.1037/t06896-000 · Cited by 79
Research works printed but not linked: 2
- Joreskog, K. G., 1986, LISREL: Analysis of linear structural relationships by the method of maximum likelihood: User's guide
- Pintrich, P. R., 1989, Advances in motivation and achievement: Motivation-enhancing environments, 117
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Prather, J., Margulieux, L., Whalley, J., Denny, P., Reeves, B. N., Becker, B. A., Singh, P., Powell, G., & Bosch, N. (2022) · Proceedings of the 2022 ACM Conference on International Computing Education Research - Volume 1 · doi:10.1145/3501385.3543970 · Cited by 31
Does negative teacher behavior influence student self-efficacy and mastery goal orientation?
Shukla, K. D., Kuril, S., & Chand, V. S. (2020) · Learning and Motivation · doi:10.1016/j.lmot.2020.101653 · Cited by 22
Mathematics Strategy Use in Solving Test Items in Varied Formats
Bonner, S. M. (2013) · The Journal of Experimental Education · doi:10.1080/00220973.2012.727886 · Cited by 20
Developing Novice Programmers’ Self-Regulation Skills with Code Replays
Xie, B., Lim, J. O., Pham, P. K. D., Li, M., & Ko, A. J. (2023) · Proceedings of the 2023 ACM Conference on International Computing Education Research V.1 · doi:10.1145/3568813.3600127 · Cited by 18
Nguyen, T. V., Tang, M.-F., Kuo, S.-Y., Hu, S. H., Ngoc, T. D. T., & Chuang, Y.-H. (2023) · Nurse Education in Practice · doi:10.1016/j.nepr.2023.103823 · Cited by 18
Knight, J. K., Weaver, D. C., Peffer, M. E., & Hazlett, Z. S. (2022) · CBE—Life Sciences Education · doi:10.1187/cbe.21-12-0341 · Cited by 18
Kokkinos, C. M., & Voulgaridou, I. (2018) · Educational Psychology · doi:10.1080/01443410.2018.1456651 · Cited by 15
Motivational design for enhancing behavioral engagement in a flipped Chinese course
Zhou, X., Chen, S., Ohno, S., She, J., & Kameda, H. (2024) · Asia Pacific Education Review · doi:10.1007/s12564-023-09849-x · Cited by 12
Aida, S. (2023) · Education Sciences · doi:10.3390/educsci13101005 · Cited by 8
Computing Education Research Today
Fincher, S. A., Tenenberg, J., Dorn, B., Hundhausen, C., McCartney, R., & Murphy, L. (2019) · The Cambridge Handbook of Computing Education Research · doi:10.1017/9781108654555.003 · Cited by 7
Jiang, X., & Yu, Z. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2457352 · Cited by 7
Sun, S. (2024) · Research in Personnel and Human Resources Management · doi:10.1108/s0742-730120240000042002
Metadata
- Authors
- Pintrich, P. R., Smith, D. A. F., Garcia, T., & Mckeachie, W. J.
- Affiliations
- University of Michigan (US)
- The University of Michigan Ann Arbor
- Venue
- Educational and Psychological Measurement
- Publisher
- SAGE Publications
- Published
- 1993-09
- Volume
- 53
- Issue
- 3
- Pages
- 801-813
- ISSN
- 0013-1644 (ISSN-L)
- 1552-3888
- OpenAlex
- W2070635017
- Cited by
- 3,646
- References
- 9
- Citations by year
- 2026: 132 · 2025: 202 · 2024: 219 · 2023: 227 · 2022: 209 · 2021: 226 · 2020: 220 · 2019: 250 · 2018: 184 · 2017: 181 · 2016: 183 · 2015: 200 · 2014: 141 · 2013: 166 · 2012: 130
- FWCI
- 9.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Educational and Psychological Measurement (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Education, Achievement, and Giftedness
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- Motivated Strategies for Learning Questionnaire, learning strategies, academic motivation, self-efficacy, test anxiety, goal orientation, task value, metacognitive strategies, cognitive strategies, resource management strategies, university students, course performance, instrument validation
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