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Examining the relations of time management and procrastination within a model of self-regulated learning

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Abstract

The primary goal of this study was to investigate whether college students’ academic time management could be used to understand their engagement in traditional and active forms of procrastination within a model of self-regulated learning. College students (N = 446) completed a self-report survey that assessed motivational and strategic aspects of self-regulated learning, time management, and procrastination. Results of regression analyses indicated that self-efficacy and metacognitive strategies initially were significant predictors of traditional and active forms of procrastination. Incorporating time management in the analyses increased the amount of the variance explained and, even in the presence of the motivation and strategy variables, time management emerged as an important predictor of both traditional and active forms of procrastination. Findings support the conclusion that academic time management is a key aspect of self-regulated learning and, as such, it can be useful for understanding the extent to which college students procrastinate when doing their academic work.

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Notes

  1. Because gender differences in self-regulated learning, time management and procrastination have been found in some studies (Macan et al. 1990; Meece and Painter 2008; Steel 2007), we investigated whether accounting for sex was necessary for properly understanding the relations examined by our analyses. When included as part of the SRL model, findings indicated that sex was a significant predictor for just one aspect of procrastination (i.e., it was a significant but relatively weak negative predictor for intentional delay). More critically, accounting for sex produced no noticeable changes in the pattern of findings for the SRL or time management predictors. As a result, we did not include sex in the final analyses presented here.

  2. To provide a check on these findings, we conducted a second set of regressions in which the Time Management model was entered in Step 1, and the SRL model was added in Step 2. Results for Step 1 of these supplemental analyses indicated that the standardized coefficients for the three time management variables were substantially equivalent to those presented in Table 2. In addition, adding the SRL variables as a group increased the amount of variance explained only for Ability to Meet Deadlines (ΔR 2 = .03, p < .001) and Preference for Pressure (ΔR 2 = .04, p <. 001). Findings from these supplementary analyses, therefore, are overwhelmingly consistent with those presented and discussed here.

  3. Although these relations have the opposite sign/valence for the ability to meet deadlines, the fact that this scale is constructed by reverse coding all four of the individual items makes this distinction trivial. It would be a simple, and perhaps well-justified, step to retain the original valence of these items and conceive of the resulting scale as the extent to which students expressed difficulty meeting deadlines. This change would result in a strong positive correlation with traditional procrastination, and a pattern of results that was substantially equivalent.

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Authors and Affiliations

  1. Dennis Learning Center, Department of Educational Studies, The Ohio State University, Columbus, OH, 43210, USA

    Christopher A. Wolters & Sungjun Won

  2. University of Delaware, Newark, DE, 19716, USA

    Maryam Hussain

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  1. Christopher A. Wolters
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  2. Sungjun Won
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Correspondence to Christopher A. Wolters.

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The authors declare that they have no conflict of interest pertaining to this study or manuscript. As well, the research reported here was conducted in accordance with the ethical guidelines of the American Psychological Association.

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Wolters, C.A., Won, S. & Hussain, M. Examining the relations of time management and procrastination within a model of self-regulated learning. Metacognition Learning 12, 381–399 (2017). https://doi.org/10.1007/s11409-017-9174-1

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