Comparing active delay and procrastination from a self-regulated learning perspective
Highlights
► We examined active delay; a form of delay different from procrastination. ► Some adaptive self-regulated learning facets were related to active delay. ► Active delay and procrastination were inversely related. ► Achievement goals related differently to active delay vs. procrastination. ► Active delay was positively associated with grades; procrastination was not.
Section snippets
Distinguishing procrastination and active delay
Contrasting the irrational nature of procrastination, researchers have acknowledged that postponing a task can sometimes be an intentional and rational decision (Schouwenburg, 2004, Simpson and Pychyl, 2009). Examples of potentially adaptive types of delay include when individuals postpone a task because they have prioritized other more important tasks or when more information/resources are needed before the target task is executed (Ferrari, 2010). Other adaptive reasons for delaying work
Motivational beliefs and procrastination
Perhaps due to procrastination being characterized as a type of self-regulatory failure, a logical direction research has taken is to examine this phenomenon within a self-regulated learning framework. Common motivational beliefs examined within a self-regulated learning perspective are achievement goals and self-efficacy (e.g., Wolters, 2003).
Achievement goals reflect four different purposes for engaging in achievement behaviors: mastery-approach (learning content), mastery-avoidance (avoiding
The current study
No studies identified to date have examined active delay within a self-regulated learning framework. Therefore, we examined whether the relations between aspects of self-regulated learning (i.e., achievement goals) and active delay would be distinct from the relations these aspects of self-regulated learning have with procrastination. Since procrastination typically is associated with less desirable motivational beliefs and lower strategy usage, we hypothesized that active delay would relate to
Participants
Participants were 206 (74% female; mean age = 24.4; S.D. = 5.5) college students enrolled in a section of a human development course across three different semesters. The sample was ethnically diverse: Hispanic (26%), Caucasian (28%), African American (22%), Asian/Asian American (20%), and Other (4%). Each course section utilized the same syllabus and curriculum, and we controlled for semester in the analyses.
Procedure
Participants completed an online survey consisting of demographics and Likert-scaled items
Descriptive statistics and bivariate correlations
Alpha coefficients, descriptive statistics, and correlations among the main variables are reported in Table 1. Pearson correlations indicate that active delay was significantly related to four out of five motivational variables and cognitive and metacognitive strategies. As expected, students with greater self-efficacy (r = .16, p < .05) were more likely to report actively delaying, and students who adopted mastery-avoidance (r = −.54, p < .001) and performance-avoidance goals (r = −.19, p < .01) were less
Discussion
The purpose of this study was to examine whether active delay could be distinguished from procrastination and would be more consistent with certain facets of self-regulated learning. Our results add credence to the notion that active delay differs from procrastination and may be a more adaptive form of delay. This is supported by three main findings: a) active delay and procrastination were found to be inversely related, b) procrastination was negatively related to adaptive self-regulatory
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