Study strategies and beliefs about learning as a function of academic achievement and achievement goals

ABSTRACT

Prior research by Hartwig and Dunlosky [(2012). Study strategies of college students: Are self-testing and scheduling related to achievement? Psychonomic Bulletin & Review, 19(1), 126–134] has demonstrated that beliefs about learning and study strategies endorsed by students are related to academic achievement: higher performing students tend to choose more effective study strategies and are more aware of the benefits of self-testing. We examined whether students’ achievement goals, independent of academic achievement, predicted beliefs about learning and endorsement of study strategies. We administered Hartwig and Dunlosky’s survey, along with the Achievement Goals Questionnaire [Elliot, A. J., & McGregor, H. A. (2001). A 2 × 2 achievement goal framework. Journal of Personality & Social Psychology, 80, 501–519] to a large undergraduate biology course. Similar to results by Hartwig and Dunlosky, we found that high-performing students (relative to low-performing students) were more likely to endorse self-testing, less likely to cram, and more likely to plan a study schedule ahead of time. Independent of achievement, however, achievement goals were stronger predictors of certain study behaviours. In particular, avoidance goals (e.g., fear of failure) coincided with increased use of cramming and the tendency to be driven by impending deadlines. Results suggest that individual differences in student achievement, as well as the underlying reasons for achievement, are important predictors of students’ approaches to studying.

KEYWORDS:

• Study habits
• metacognition
• student achievement
• achievement goals

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Discussions of distributed practice often make the distinction between spacing vs. massing (aka “cramming”). This classifies students into two categories that may inflate the estimated frequency associated with each. Including an option to reflect “light cramming” allows a more precise estimate of the proportion of students who truly distribute their study, vs. those who cram their study into a single session (“heavy crammers”) or a couple of sessions (“light crammers”).

2 Estimates of d are based on Chinn’s (2000) method for converting odds ratios to effect sizes.

3 Like previous studies using the current survey, we used self-reported GPA as a proxy for student achievement. Although there is some concern about the construct validity of self-reported GPA (e.g., Kuncel, Credé, & Thomas, 2005), we were able to obtain transcripts from a subset of our sample (n = 304) and observed a strong positive relationship between actual GPA and self-reported GPA (r = .91, p < .001). Exam scores were also available for the entire sample, and we observed a strong positive relationship between average exam scores and self-reported GPA as well, r = .64, p < .001.

Additional information

Funding

This material is based upon work supported by the National Science Foundation under grant Division of Undergraduate Education-1504480, and an Iowa State University Miller Faculty Fellowship. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or Iowa State University.