Learning and Individual Differences 36 (2014) 157–164

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Learning and Individual Differences

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Reconsidering active procrastination: Relations to motivation andachievement in college anatomy

Lauren C. HensleyDennis Learning Center, The Ohio State University, 250C Younkin, 1640 Neil Avenue, Columbus, OH, USA

E-mail address: hensley.121@osu.edu.

http://dx.doi.org/10.1016/j.lindif.2014.10.0121041-6080/© 2014 Elsevier Inc. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 27 January 2014Received in revised form 11 September 2014Accepted 27 October 2014

Keywords:College studentsMotivationProcrastination

This study examined passive and active procrastination among undergraduate anatomy students in terms ofbackground variables, motivational beliefs (i.e., belief about the speed of knowledge acquisition, self-efficacy,and task value), and grades. Factor analysis revealed three discrete factors of active procrastination, one ofwhich was closely tied to passive procrastination and behavioral procrastination. Analyses indicated that therelations to motivational beliefs and grades were markedly different for, on the one hand, two factors of activeprocrastination (positive relations) and, on the other hand, passive procrastination and the third factor of activeprocrastination (negative relations). After controlling for academic ability, only passive procrastination was astatistically significant predictor of grades. Results imply that the dimensions of active procrastination thatappear adaptive for learningmay not reflect behavioral procrastination,whereas the dimension of active procras-tination that involves behavioral procrastination lacks adaptive associations.

© 2014 Elsevier Inc. All rights reserved.

Although procrastination tends to be viewed as problematic, thetrend of investigating adaptive aspects of procrastination (e.g., Schraw,Wadkins, &Olafson, 2007) suggests that not all procrastination is createdequal. Procrastination is traditionally viewed as a self-defeating behav-ior with links to self-handicapping, low engagement, a lack of self-regulation, and poor academic performance (Harrington, 2005; Rice,Richardson, & Clark, 2012). In contrast, conceptions of active procrasti-nation suggest that procrastination enacted in a certain manner may bemotivationally and academically productive (Choi &Moran, 2009; Chu&Choi, 2005). The emerging construct of active—as opposed to passive—procrastination is defined by and associated with academically produc-tive attributes (e.g., Choi & Moran, 2009). Such an approach is not with-out controversy. Some scholars suggest that active procrastination is acontradiction and theoretical impossibility (e.g., Pychyl, 2009). Othersdescribe active procrastination not as procrastination, per se, but ratheras delay (Corkin, Yu, & Lindt, 2011). Some scholars argue that active pro-crastination has an adaptive nature that could justify educators' supportof well-intentioned procrastination efforts (Schraw et al., 2007; Vacha &McBride, 1993). Others suggest that there are limits to the educationalbenefits (Corkin et al., 2011).

When it comes to the motivation behind delaying an academic task,salient features of both the learner and the learning context come intoplay (McGee, Del Vento, & Bavelas, 1997). The study uses the lens ofmotivational beliefs to examine procrastination tendencies in undergrad-uate human anatomy, a context in which procrastination and poor moti-vationmaybeparticularly detrimental due to students' need tomemorize

large amounts of information (Beck, Koons, & Milgrim, 2000). Consistentwith research on procrastination from a self-regulated learning perspec-tive, this study considers contextualized factors, such as beliefs about aspecific course, that explain outcomes beyond the contributions of stablemeasures, such as general academic ability (Pintrich & Zusho, 2007;Wolters, 2003). The focus on a specific course aligns with the definitionof active procrastination as a purposeful behavior reflecting the interac-tion between the learner and the environment. The study contributesto discussions surrounding active procrastination by questioning thedegree to which its factors reflect behavioral procrastination and holdadaptive associations with academic motivation and achievement.

1. Conceptions of passive and active procrastination

As defined by Choi and Moran (2009), four factors comprise activeprocrastination. First, outcome satisfaction indicates that the studentsare pleased with their results. Second, preference for pressure indicatesthat the students like towork quickly under deadlines. Third, intentionaldecision indicates that the students deliberately postpone tasks. Fourth,ability to meet deadlines indicates that the students complete activitieson time. Such definitions reflect marked differences between passiveand active procrastination. Statistically nonsignificant (Choi & Moran,2009; Chu & Choi, 2005) and negative relations (Corkin et al., 2011) be-tween compositemeasures of the constructs reinforce their distinctness.

The multidimensionality of active procrastination further distin-guishes it from passive procrastination, a unidimensional construct(Tuckman, 2005). In their validation study of the Active ProcrastinationScale, Choi andMoran (2009)usedConfirmatory FactorAnalysis to estab-lish a suprafactor of active procrastination indicated by four underlying

158 L.C. Hensley / Learning and Individual Differences 36 (2014) 157–164

dimensions. The majority of research on active procrastination has ex-amined the composite measure, examining relations of academic andmotivational constructs to the scale as a whole (e.g., Cao, 2012; Choi &Moran, 2009; Chu & Choi, 2005; Corkin et al., 2011). It is possible thatthe composite scale endeavors to measure more distinct constructs thancan coexist within a single tendency. This possibility resonates withconcerns that active procrastination—which combines thoughtful taskdelay with a failure to self-regulate—is a self-contradictory concept(Pychyl, 2009). Should this be the case, inferences based on the supra-factor of active procrastination may be inaccurate.

When examined separately, factors of active procrastination maycontain important differences. Intentional delay is likely unique fromother factors due to its conceptual similarity with arousal procrastina-tion. Arousal procrastination involves purposefully delaying to increaseexcitement level and thus motivation; however, this construct is calledinto question by the argument that all procrastination is irrational(Simpson & Pychyl, 2009; Steel, 2010). Wolters, Hussain, and Young(2013) reported that the intentional delay factor had negative relationsto self-regulation and learning strategies. Hensley and Burgoon (2013)found no factor but intentional delay had the expected associationswith self-reported postponement. Such findings suggest that a compos-ite scale might obscure differences among the dimensions of active pro-crastination. Additional inquiry is necessary to explore the structure andassociations of the individual factors.

2. Motivational beliefs in relation to procrastination

Beliefs about learning inform students' academic motivation, whichdirects efforts toward educational goals (Eccles, 1983; Schommer,1994). Previous research established certain motivational beliefs asadaptive due to their consistent connections to effort, persistence, andlearning (Paulsen & Feldman, 2007; Wolters, Yu, & Pintrich, 1996).The degree to which procrastination exhibits or lacks associationswith motivational beliefs indicates whether it is adaptive or maladap-tive (Corkin et al., 2011). At the center of this study are three motiva-tional beliefs about oneself as a learner: the amount of time learning“should” take (speed of knowledge acquisition), the ability to learn(self-efficacy), and the value of learning (task value).

2.1. Speed of knowledge acquisition

Epistemological beliefs are a “component of the cognitive and affectiveconditions of a task…[that] influence[s] the standards students set whengoals are produced” (Muis, 2007, pp. 179–180). These standards includethe learning strategies students report enacting (e.g., Paulsen &Feldman, 2007). By extension, they may also involve choices about howmuch time is needed for learning and how this time should be structured.A particular epistemological belief likely to inform procrastination is thebelief about the speed of knowledge acquisition (Wood & Kardash,2002). When learning does not occur quickly, students either believethey cannot learn or that time and effort are a natural part of the process.

Students' beliefs about the speed of knowledge acquisition hold im-portance for learning outcomes and behaviors. A belief in speedy learn-ing has been linked to low reading comprehension, overconfidence inone's preparation (Schommer, 1990), and low grades (Schommer,1993). Believing knowledge to be acquired gradually predicts students'self-reported academic confidence, use of test preparation strategies,motivation for academics (Schommer-Aikins & Easter, 2008), and effec-tive learning strategies (Cano & Cardelle-Elawar, 2008). Further ties toprocrastination seem feasible but have received little attention.

2.2. Self-efficacy and task value

Self-efficacy and task value are two key motivational beliefs. Self-efficacy reflects how individuals judge their abilities to successfully ac-complish specific tasks (Bandura, 1997). Task values characterize the

draw of engagement in terms of level of interest, instrumentality togoals, or consistency with how students view themselves (Eccles &Wigfield, 1995). Each belief is likely to explain variance in procrastina-tion, though the combination of self-efficacy and task value may begreater than the sum of its parts. In their study of general procrastina-tion tendencies, Gröpel and Steel (2008) demonstrated the conditionaleffects of interest-enhancement and goal-setting strategies, and theyurged researchers to explore additional potential interactions. Steel(2007) proposed a model of temporal motivation in which the desir-ability of a given action resulted from self-efficacy and task value, takinginto account the amount of time remaining for task completion. A natu-ral extension of Steel and his colleagues' work is to examine differencesin procrastination based on the conditional effects of these two keymo-tivational variables.

The association between low self-efficacy and passive procrastina-tion is well established (Tuckman, 1991;Wolters, 2003).When individ-uals have low self-efficacy for tasks, they are not likely to engagein them (Bandura, 1986). Students who doubt their ability to performwell procrastinate to avoid the emotional discomfort of studying(Schouwenburg, 1992). Task aversion is another root of passive procras-tination, as students avoid working on academic activities they perceiveto be unclear or overly difficult (Ackerman & Gross, 2005). Together,low confidence and low appeal may make a task appear especiallyunattainable and not worth the effort; as such, the combination ofself-efficacy and task value is likely to explain variance in passiveprocrastination.

Whereas low self-efficacy accompanies passive procrastination, highself-efficacy accompanies active procrastination (Cao, 2012; Chu& Choi,2005; Corkin et al., 2011). Active procrastinators are academically con-fident yet delay engagement (Choi & Moran, 2009). This associationstands in contrast with the expectation that students with high self-confidence “should participate more eagerly” in academic activities(Schunk & Zimmerman, 2006, p. 356). Active procrastinators' delayof engagement may be explained by low task value, with studentsdelaying unappealing tasks so that external circumstances make themappear more challenging and interesting (Brinthaupt & Shin, 2001).Since active procrastinators have high self-efficacy, they may be proneto viewing easy tasks as uninteresting. Examining self-efficacy andtask value together may help explain this dynamic.

3. Academic ability and achievement in relation to procrastination

Whether scholars consider procrastination to be educationallyadaptive is based on links to motivation, discussed above, as well asto academic achievement (Corkin et al., 2011). Prior research hasestablished a strong negative association between passive procrastina-tion and grades (Strunk & Steele, 2011; Tice & Baumeister, 1997). Con-versely, college students describe intentional procrastination as havingeither no effect or a positive effect on grades (Schraw et al., 2007). Choiand Moran (2009) reported an interesting disparity: a positive correla-tion between business majors' active procrastination and perceivedacademic performance relative to other students, but no statistically sig-nificant correlation between active procrastination and actual grade-point average (GPA). There is evidence that active procrastination posi-tively correlateswithGPA (Chu&Choi, 2005) and predicts course grades(Corkin et al., 2011), but no known study has controlled for the contri-bution of academic ability to active procrastinators' academic outcomes.It remains unclear whether active procrastination itself, as opposed tothe tendency for active procrastinators to have high ability, contributesto achievement.

4. The present study

Trends in the literature suggest a need to reexamine the factorsof active procrastination with respect to variables that reflect adaptivemotivation and achievement. Such analyses must account for the

159L.C. Hensley / Learning and Individual Differences 36 (2014) 157–164

contribution of academic ability. There is also a need to test the con-struct validity of active procrastination and establishwhether its factorsreflect procrastination behaviorally. The present study addresses theseneeds, with the major purpose of examining the factors of active pro-crastination and their differential relations to motivation, academicability and achievement, and behavioral measures of procrastination.Three research questions guided the study.

First, what is the factor structure of active procrastination amongundergraduate anatomy students? Do all factors reflect procrastinationbehaviorally? The researcher anticipated that only the intentional delayfactor would be validated as behavioral procrastination.

Second, what differences exist in the relations between procrastina-tion measures and motivation variables (i.e., beliefs about the speed ofknowledge acquisition, self-efficacy, and task value, aswell as the interac-tion between self-efficacy and task value)? The researcher hypothesizedthat intentional delay would have negative relations to the motivationvariables, distinct from the other factors of active procrastination.

Third, controlling for ACT score as an indicator of academic ability,is a procrastination measure a statistically significant predictor ofexam and course grades in anatomy? The researcher anticipated thatactive procrastination factors would not predict achievement.

5. Method

The following section provides an overview of participants and themeasures they completed. Scalesmeasuredmotivation and procrastina-tion. Behavioral measures provided evidence of task delay.

5.1. Participants

The study took place at a large, public university in the MidwesternUnited States during spring2013. The participantswere 320 traditionallyaged (Md = 19 years old) undergraduate students enrolled in HumanAnatomy, a four-credit prerequisite course. This required course servedprimarily first- and second-year students frommultiple areas, includingpre-nursing and pre-allied medical professions. Consistent with typicalcourse enrollment, most participants (78%) were female. Eighty-threepercent were White, five percent were Asian, and three percent eachwere Hispanic, African–American, or two or more ethnicities.

5.2. Procedure

The study took place during a two-week period as the studentsbegan to work on Unit II: The Back and Upper Limb. This time periodwas chosen to allow the students sufficient familiarity with the courseto develop motivational beliefs about it. The timing also situated themeasurement of motivation and procrastination prior to achievement.The researcher visited class to describe the opportunity for students tocomplete a confidential online survey. As an incentive, the studentscould enter a drawing to win one of five $25 gift cards; no course creditwas awarded.

5.3. Measures

Demographic information came from university records. The centralmeasures selected for the study were based onmotivational theory andprevious research (Choi & Moran, 2009; Pintrich, Smith, Garcia, &McKeachie, 1991; Tuckman, 1991; Wood & Kardash, 2002). With theexception of the procrastination measures used to ascertain validity,described below, all items were placed on seven-point Likert-typescales with anchored end points (1 = not at all true of me, 7 = verytrue of me) and a neutral middle option.

5.3.1. Passive procrastinationPassive procrastination was measured using the 15-item

course-specific adaption (Hensley & Burgoon, 2013) of the Tuckman

Procrastination Scale (TPS; Tuckman, 1991). The scale measureddelaying course-related tasks and activities, reflecting avoidant tenden-cies (sample item= “In this course, I'm an incurable time waster”).

5.3.2. Active procrastinationActive procrastination was measured using the 16-item course-

specific adaption (Hensley & Burgoon, 2013) of the Active Procrastina-tion Scale (Choi & Moran, 2009). The scale measured purposeful andbeneficial procrastination (sample item= “In this course, I intentionallyput off work to maximize motivation”). As with the TPS, the scale con-tained the same content as the original, with only minor changes intro-duced through the phrase “in this course.” The underlying factors of thescale were the focus of analyses in the present study.

5.3.3. Other measures of procrastination and task delayTo test concurrent validity, threemeasures indicated procrastination

and task delay behaviors. First, an adaptation of the frequency of pro-crastination subscale from the Procrastination Assessment Scale-Students (PASS; Solomon & Rothblum, 1984) measured self-reportedprocrastination on major course activities: studying for exams, keepingup with weekly readings, and keeping up with assignments. Second,students self-reported the number of days prior to the Unit I anatomyexam they had begun to prepare (where 0 = the day of the exam).Third, timestamps indicated the amount of timebefore thedeadline stu-dents had submitted the Unit I online homework quiz. The timestampwas subtracted from the due date/time (e.g., 1.50 indicated 36 h beforethe deadline). Low numbers reflected high procrastination.

5.3.4. Speed of knowledge acquisitionThe eight-item Speed of Knowledge Acquisition scale (Wood &

Kardash, 2002) measured the belief that learning should occur eitherquickly or as a gradual process. Items were reverse-coded so that highscores represented more cognitively complex beliefs, defined as a moremature or adaptive way of thinking about knowledge (Nist & Holschuh,2005).

5.3.5. Self-efficacy and task valuesThe survey included the eight-item Self-Efficacy and six-item Task

Value subscales from the Motivated Strategies for Learning Question-naire (Pintrich et al., 1991). A sample self-efficacy item was “I'm confi-dent I can understand the most complex material presented by theinstructor in this course” (p. 13). A sample task-value item was “It isimportant for me to learn the course material in this class” (p. 11).

5.3.6. Academic ability and achievementAcademic data came fromuniversity records. Students' compositeACT

scores served as a proxy of academic ability (e.g., Alarcon & Edwards,2012). The Unit II exam grade and final course grade indicated achieve-ment in anatomy in a specific instance and over the entirety of the semes-ter. The non-comprehensive, objective exam consisted of 50 multiple-choice, matching, and diagram-identification questions. The final gradeconsisted of four non-comprehensive objective exams and four onlinehomework quizzes.

5.4. Research design

Factor analysis, correlations, and regression analyses addressed theresearch questions. Because the Active Procrastination Scale had notbeen developed in the context of anatomy at an American university,it was possible that the measurement would exhibit a different factorstructure in the present study. Factor analysis aimed to identify the un-derlying factor structure. Bivariate correlations permitted investigationof basic covariance between variables and testing of concurrent validitywith behavioral measures. Hierarchical regression analyses examinedthe relative importance of each variable in explaining variance in

160 L.C. Hensley / Learning and Individual Differences 36 (2014) 157–164

procrastination and achievement when accounting for other variables(Keith, 2006).

6. Results

The following results examine procrastination through relationsto motivational beliefs and achievement, with particular emphasis ondifferentiating between passive procrastination and the dimensions ofactive procrastination. Presented first is the factor structure of activeprocrastination, followed by the results of correlational analyses. Nextare the regression analyses that test models predicting procrastinationand achievement.

6.1. Factor analysis

The researcher conducted exploratory factor analysis using themax-imum likelihood extraction method (Costello & Osborne, 2005). Visualexamination of the scree plot revealed three discrete factors (Cattell,1966, as cited in Hellman & Caselman, 2004). Oblique rotation indicatedthe items' loadings on each of the three correlated factors (Costello &Osborne, 2005). The composition of factors resulted from consideringfactor loadings and the contribution of items to interpretability(Pajares, 2011). Item 5 loaded nearly equally on two factors. It was in-cluded in factor 1 due to its conceptual closeness to the other itemswith high loadings on this factor, which centered on aspects of workingunder pressure (e.g., Miller, Greene, Montalvo, Ravindran, & Nicholson,1996). Table 1 presents statistics for each item and factor, with a side-by-side comparison to the factor originally associated with each item.

Two factors reflected Choi andMoran's (2009) original structure: in-tentional decision to delay (i.e., deliberate postponement of academicactivities) and ability to meet deadlines (i.e., on-time completion ofacademic activities). The third factor combined two of Choi andMoran's factors and was named satisfying outcomes under pressure(i.e., achieving acceptable results on academic activities when workingwithin a limited timeframe). Intentional decision to delay containedthe same items as in Choi and Moran's work but, unlike the previousfindings, exhibited negative correlations with the other two factors.

Table 1Factor Analysis of the Domain-Specific Active Procrastination Scale.

Present study

Factor and items M SD 1

Factor 1: Ability to meet deadlinesItem 15 (R) 4.91 1.68 .93Item 13 (R) 5.14 1.67 .68Item 14 (R) 5.06 1.66 .65Item 16 (R) 5.49 1.42 .48

Factor 2: Satisfying outcomes under pressureItem 8 (R) 3.68 1.75 .09Item 1 (R) 3.95 1.76 .24Item 7 (R) 4.28 1.70 .27Item 2 (R) 3.14 1.57 .04Item 3 (R) 3.33 1.73 .02Item 4 (R) 2.53 1.37 − .23Item 5 (R) 4.93 1.59 .42Item 6 (R) 4.96 1.56 .17

Factor 3: Intentional decision to delayItem 9 3.37 1.68 .15Item 11 3.21 1.65 − .03Item 10 2.71 1.52 − .32Item 12 3.64 1.81 − .20Eigenvalue 5.99Percentage of variance explained 37.45Cronbach's a .85

Note. “In this course” incorporated into each item. Factor-loading information in the two rightmloadings, refer to Choi and Moran (2009). In the present study, analyses focused on the three anation Scale as a whole. Bold text indicates the factor-loading value selected for each item and ieach item.

6.2. Descriptive statistics and bivariate correlations

Table 2 presents descriptive statistics and correlations of the contin-uous variables. All scales had reliability coefficients of .75 or above, ex-cept for the composite form of active procrastination.

Bivariate correlations revealed that passive procrastination and theintentional decision to delay factor had a strong positive correlation.The two constructs exhibited concurrent validity with the three corrob-orating procrastination and task delay measures. They both had nega-tive correlations with the belief in gradual acquisition of knowledge,value of anatomy-related tasks, self-efficacy in anatomy, and academicachievement. These findings suggest that it is valid to interpret thetwo constructs as related or causally generated by a common latentconstruct.

Two factors of active procrastination—ability to meet deadlines andsatisfying outcomes under pressure—were positively related to oneanother and distinct from passive procrastination and intentional deci-sion to delay. These two factors received no validation from the behav-ioral measures and instead reflected a tendency to work ahead ofdeadlines. They had positive correlations with motivational beliefs andacademic achievement. The composite active procrastination scale hada lower internal consistency than any of its underlying factors andan exceptionally high correlation with the satisfying outcomes underpressure factor; the composite scale was not retained in subsequentanalyses.

6.3. Hierarchical regression analyses

The first set of multiple regression analyses examined relationsof motivational beliefs to passive procrastination and the three activeprocrastination factors. The interaction of self-efficacy and task valuewas tested in the second step of themodel. The second set of regressionanalyses examined procrastination variables as predictors of exam andcourse grades. The use of hierarchical regression permitted examinationof whether procrastination explained differences in performance be-yond what might be explained by academic aptitude and beliefs.

Choi and Moran (2009)

2 3 Highest factor loading

− .07 .04 Ability to meet deadlines .73.12 − .11 Ability to meet deadlines .74.20 .01 Ability to meet deadlines .73.14 − .20 Ability to meet deadlines .60

.62 − .16 Preference for pressure .61

.61 − .07 Outcome satisfaction .78

.57 − .04 Preference for pressure .74

.54 .00 Outcome satisfaction .76

.50 .07 Outcome satisfaction .75

.47 .12 Outcome satisfaction .72

.40 − .20 Preference for pressure .82

.38 − .29 Preference for pressure .79

− .02 .88 Intentional decision to delay .79.03 .78 Intentional decision to delay .67.07 .40 Intentional decision to delay .70.06 .36 Intentional decision to delay .58

2.28 .9714.25 6.04

.81 .75

ost columns adapted from Choi andMoran (2009). For text of original items and full factorbove-identified factors of active procrastination, rather than the 16-item Active Procrasti-ts associated factor. In all cases but one, values set in bold represent the highest loading for

Table 2Means, standard deviations, alpha coefficients, and bivariate correlations.

M SD α 1 2 3 4 5 6 7 8 9 10 11 12 13

1. Passive procrastination 3.26 1.26 .95 __2. Active procrastination

(composite)4.02 0.70 .70 − .51⁎⁎⁎ __

3. Ability to meetdeadlines

5.15 1.33 .85 − .86⁎⁎⁎ .66⁎⁎⁎ __

4. Satisfying outcomesunder pressure

3.85 1.07 .81 − .52⁎⁎⁎ .92⁎⁎⁎ .59⁎⁎⁎ __

5. Intentional decision 3.23 1.26 .75 .66⁎⁎⁎ − .45⁎⁎⁎ − .59⁎⁎⁎ − .28⁎⁎ __6. Days of advance

studyinga6.43 4.39 n/a − .50⁎⁎⁎ .16⁎⁎ .40⁎⁎⁎ .17⁎⁎ − .36⁎⁎⁎ __

7. Days of advance quizsubmissionb

2.37 3.28 n/a − .18⁎⁎ .13⁎ .20⁎⁎⁎ .14⁎ − .14⁎ .20⁎⁎⁎ __

8. Frequency ofprocrastination

2.85 0.89 .75 .75⁎⁎⁎ − .33⁎⁎⁎ − .65⁎⁎⁎ − .31⁎⁎⁎ .50⁎⁎⁎ − .50⁎⁎⁎ − .16⁎⁎ __

9. Speed beliefc 5.60 0.89 .80 − .17⁎⁎ .12⁎ .21⁎⁎⁎ .16⁎⁎ − .22⁎⁎⁎ .06 .02 − .17⁎⁎ __10. Self-efficacy 5.44 1.15 .94 − .53⁎⁎⁎ .45⁎⁎⁎ .56⁎⁎⁎ .41⁎⁎⁎ − .29⁎⁎⁎ .24⁎⁎⁎ .05 − .42⁎⁎ .31⁎⁎⁎ __11. Task value 6.18 0.87 .88 − .37⁎⁎⁎ .17⁎⁎ .36⁎⁎⁎ .17⁎⁎ − .28⁎⁎⁎ .22⁎⁎⁎ .03 − .34⁎⁎⁎ .25⁎⁎⁎ .54⁎⁎⁎ __12. ACT score 26.62 3.49 n/a − .03 .11 .11 .12⁎ − .06 − .10 .06 .05 .11 .15⁎⁎ .07 __13. Exam grade 81.12 14.86 n/a − .29⁎⁎⁎ .28⁎⁎⁎ .32⁎⁎⁎ .25⁎⁎⁎ − .14⁎ .16⁎⁎ .13⁎ − .21⁎⁎⁎ .20⁎⁎⁎ .36⁎⁎⁎ .14⁎ .34⁎⁎⁎ __14. Course grade 83.12 12.29 n/a − .37⁎⁎⁎ .34⁎⁎⁎ .42⁎⁎⁎ .30⁎⁎⁎ − .19⁎⁎ .21⁎⁎⁎ .12⁎ − .32⁎⁎⁎ .27⁎⁎⁎ .43⁎⁎⁎ .20⁎⁎ .35⁎⁎⁎ .86⁎⁎⁎

Note. Ability to meet deadlines, satisfying outcomes under pressure, and intentional decision to delay are the three factors of active procrastination.*p b .05; **p b .01; ***p b .001.

a How many days before an exam students began to study; higher numbers represent lower procrastination.b Howmany days before the due date students submitted an online quiz; higher numbers represent lower procrastination.c Reverse coded so that higher scores represent more complex beliefs (i.e., knowledge is acquired gradually).

161L.C. Hensley / Learning and Individual Differences 36 (2014) 157–164

6.3.1. Prediction of procrastinationTable 3 presents the results of regression analyses for passive pro-

crastination and the three active procrastination factors. Self-efficacywas the most important predictor variable in all four models. Notably,the relation of self-efficacy to intentional decision to delaywas negative.Although the three active procrastination factors derived from the samepool of items intended to measure a single construct, they appeared topoint to different sources of motivation. Two factors were tendenciesof high-efficacy students, consistent with previous definitions of activeprocrastination as a whole. The other factor revealed a trifecta of poormotivation; intentional decision to delay reflected students' beliefsthat knowledge acquisition had to occur quickly, that theywere unlikelyto do well in anatomy, and that learning anatomy was not valuable. Inthis way, the intentional decision to delay resonated more with tradi-tional definitions of passive rather than active procrastination.

The interaction of self-efficacy and task value explained uniquevariance in passive procrastination and ability to meet deadlines, abovethe contribution of other variables. Having a certain level of task valuedid little to distinguish between students with low self-efficacy. Forstudents with high self-efficacy, the level of task value made a differ-ence in that highly efficacious students with high task values wereespecially unlikely to report passive procrastination and especially

Table 3Hierarchical regression analyses predicting procrastination variables.

Passive procrastination Ability to meet deadlin

Predictor variables β Step 1 β Step 2 β Step 1 β Ste

Step 1Speed belief .00 .01 .04 .03Self-efficacy − .46*** − .48*** .52*** .54***Task value − .13*** − .18** .07 .13*

Step 2Self-efficacy x task value − .14** .17***R2 .29*** .31*** .32*** .35***ΔR2 .29*** .02** .32*** .03***

Note. Ability to meet deadlines, satisfying outcomes under pressure, and intentional decision toβ indicates the standardized regression coefficient. The self-efficacy x task value interaction, tesin Satisfying outcomes under pressure or Intentional decision to delay (Step 2 not shown).As the study examined more than one criterion variable, it used a more conservative alpha lev*p b .05; **p b .01; ***p b .001.

likely to report an ability to meet deadlines. Figs. 1 and 2 depict theinteractions.

6.3.2. Prediction of procrastinationAdditional analyses addressed academic achievement. Table 4

presents regression analyses predicting grades in the short-term(a single exam) and as the result of students' work over the entiresemester (final course grade).

More than any other variable, academic ability predicted achieve-ment. When accounting for ACT score, self-efficacy remained an impor-tant predictor of grades, indicating that students with high perceivedcompetence in anatomy performed at high levels. The belief aboutspeed of knowledge acquisition was a positive predictor of overallcourse grade; studentswhobelieved knowledgewas acquired graduallyperformed better in the course. This belief was not a statistically signif-icant predictor of performance on the unit exam, which took place inthe first half of the semester. It seems the speed-related belief playedits most salient role in the longer term, as successful students had topersist in their learning efforts for the duration of the semester. Beyondthe role of academic ability and motivational beliefs, passive procrasti-nation held importance for academic outcomes. Passive procrastinatorsperformed poorly in anatomy to an extent beyond what might be

es Satisfying outcomes under pressure Intentional decision to delay

p 2 β Step 1 β Step 1

.04 − .13*

.44*** − .16*− .08 − .16*

.17*** .11***

.17*** .11***

delay are the three factors of active procrastination.ted in Step 2 for all fourmodels, did not explain a significant amount of additional variance

el of .013 (.05/4) for the procrastination analyses.

-1

-0.5

0

0.5

1

1.5P

assi

ve

Pro

cras

tin

atio

n

Low Self-Efficacy High Self-Efficacy

Low Task Value High Task Value

Fig. 1. Variation in passive procrastination as a function of the self-efficacy by task valueinteraction. Note. High/low self-efficacy and task values reflect the amount one standarddeviation above/below their respective means, and passive procrastination and ability tomeet deadlines are centered at their respective means.

Table 4Hierarchical regression analyses predicting grades.

Unit II exam grade Course grade

Predictor variables β Step 1 β Step 2 β Step 3 β Step 1 β Step 2 β Step 3

Step 1ACT .34*** .29*** .30*** .35*** .28*** .30***

Step 2Speed belief .08 .10 .13* .14*Self-efficacy .33*** .23** .37*** .24***Task value − .07 − .09 − .05 − .07

Step 3Passiveprocrastination

− .21* − .29***

Satisfying outcomesunder pressure

.02 .02

Intentional decisionto delay

.09 .09

R2 .12*** .22*** .24*** .12*** .28*** .32***ΔR2 .12*** .10*** .02* .12*** .15*** .04**

Note. Ability tomeet deadlineswas omitted from themodel due to issues ofmulticollinearitycaused by high correlations with other predictor variables. β indicates the standardizedregression coefficient. As the study examined more than one criterion variable, it used amore conservative alpha level of .025 (.05/2) for the grade analyses (e.g., Wolters &Benzon, 2013).*p b .05; **p b .01; ***p b .001.

162 L.C. Hensley / Learning and Individual Differences 36 (2014) 157–164

expected due to aptitude or beliefs, and the negative role was particu-larly notable for overall course grade. Satisfying outcomes under pres-sure and intentional decision to delay were not statistically significantpredictors of grades when the equation accounted for other relevantvariables.

7. Discussion

The findings distinguished among self-reported passive procrastina-tion and active procrastination factors in terms of motivation, achieve-ment, and behavioral procrastination. The results demonstrated thesalience of students' academic ability and beliefs about the nature, attain-ability, and value of learning anatomy. The study's key contributions re-late to themeasurement and conceptualization of active procrastination.

Low Task Value High Task Value

-1.5

-1

-0.5

0

0.5

1

1.5

Ab

ilit

y t

o M

eet

Dea

dli

nes

Low Self-Efficacy High Self-Efficacy

Fig. 2. Variation in ability to meet deadlines as a function of the self-efficacy by task valueinteraction. Note. High/low self-efficacy and task values reflect the amount one standarddeviation above/below their respective means, and passive procrastination and ability tomeet deadlines are centered at their respective means.

7.1. Measurement of active procrastination

Factor analysis of active procrastination in anatomy revealed simi-larities to Choi and Moran's (2009) factor structure but was not identi-cal. Importantly, intentional decision to delay was negatively correlatedwith the two other resulting factors. Intentional decision to delay wasthe only factor to exhibit concurrent validity with behavioral measuresof procrastination. Negative associations with motivational beliefs sug-gest that this active procrastination factor lacks an adaptive nature.The other two factors had positive associations with motivational be-liefs. Ability to meet deadlines and satisfying outcomes under pressuremay thus be viewed as adaptive—but not as procrastination. These find-ings emphasize the need to revisit how scholars measure and describeactive procrastination (Bui, 2010). A unifactor structure may be insuffi-cient to capture the nuances of active procrastinators' tendencies.

7.2. Differences in motivation and achievement

Distinctions among the forms of procrastination revealed individualdifferences in motivational beliefs. Viewing oneself as attaining satisfy-ing outcomes under pressure may depend little on whether the taskitself is appealing; instead, the perception may boil down to whetherstudents view themselves as capable of performing competently, evenunder time constraints. Some scholars have argued that procrastina-tion is nearly always irrational (Gröpel & Steel, 2008), yet active pro-crastinators' actions appear purposeful. The students whointentionally delay expect learning to occur quickly; such studentsmay procrastinate to spur themselves to efficient action. In the presentstudy, connections between intentional delay and low task value sug-gest students “put off work to maximize [their] motivation” (Choi &Moran, 2009, p. 203) when they have low confidence or find the con-tent unappealing—that is, when the academicwork itself is notmotivat-ing. If students simply need a way of completing academic taskswithout respect to quality, they may achieve this goal via procrastina-tion. If students instead believe that procrastination provides a meansof achieving high grades, this approach is irrational. Contrary to argu-ments that active procrastination can be a pathway to academicachievement (Chu & Choi, 2005; Schraw et al., 2007; Vacha &McBride, 1993), the models predicting grades in the present studyshow no connection between active procrastination and grades.

163L.C. Hensley / Learning and Individual Differences 36 (2014) 157–164

In terms of achievement, passive procrastination was detrimentaland both high self-efficacy and the belief that knowledge developedgradually were beneficial. These links were particularly strong for over-all course grade, perhaps because of the time and effort required to sus-tain a high level of performance. This explanation is consistent with thefinding that students who expect learning to occur quickly tend to dem-onstrate a lack of resilience (Cano & Cardelle-Elawar, 2008). The studyalso adds to the evidence that grades are not just a reflection of under-lying ability but also relate to students' beliefs about learning and per-ceived ability to understand a subject (Wolters et al., 1996). Moreover,the bivariate correlation between satisfying outcomes under pressureand grades was accounted for by shared variance with other variablesin the regression analyses. This finding supports the notion that positiverelations between active procrastination and grades are a matter of cor-relation and not causation.

7.3. Educational relevance

Task value was particularly important for students with high self-efficacy, perhaps because this combination enhanced the students'sense of personal connection to study tasks. This finding is consistentwith past research related to the expectancy-value theory of achieve-ment motivation, which describes both aspects as essential to moti-vation (Wigfield & Eccles, 2000). It also reinforces the theoreticalframing of self-efficacy and task value as key components in temporal(i.e., time-related)motivation (Steel, 2007) and contributes to evidenceon the multiplicative effects of motivational beliefs (Gröpel & Steel,2008). When students do not receive a boost of confidence frombelieving they can learn, the importance or usefulness of a task maynot drastically change passive procrastination or the ability to meetdeadlines. When students think not only that the task mattersbut also that they can be successful, the avoidant tendencies of passiveprocrastination are unlikely. Under these circumstances, studentsare also apt to motivate themselves to meet deadlines. Faculty and staffwho work to support students' academic strategy use may find their ef-fortsmost effectivewhen they help raise levels of perceived competence.

Intentional delay was more similar to passive procrastination thanit was to the other two active procrastination factors, but it was still adistinct construct. Although both passive procrastination and intention-al delay reflected low confidence, the association was much strongerfor passive procrastination. Intentional decision to delay was unique inthat it involved believing that knowledge should be acquired quickly.Passive procrastination explained variance in lowgradeswhen account-ing for other variables, but intentional decision to delay did not. To theextent that the intentional decision to delay involves a greater elementof choice or volition than passive procrastination, it does appear tobe both active and procrastination. Even so, negative associations withmotivational beliefs suggest that encouraging students to delay in an in-tentional manner is not the wisest practical application of these find-ings. As Sirois (2004) cautioned, “focusing on how things were not asbad as they could have been…engenders a sense of satisfaction and com-placency thatmay result in less thought about how to act in amore time-ly manner in the future” (p. 280). Educators should remain wary abouteven those forms of procrastination that students describe as purposeful.

7.4. Limitations and future directions

A limitation of the studywas the reliance on self-reportmeasures, asstudents may have misrepresented their beliefs and tendencies(Bowman & Hill, 2011). The students completed the survey online in aprivate space, however, andmay have beenmore likely to respondhon-estly than if completing the survey in the presence of other students orthe instructor (Kreuter, Presser, & Tourangeau, 2008). Still, the findingsmay be constrained by the subjective nature of the self-report data, andfuture research should incorporate additional objective and behavioralmeasures.

Although the combination of variables accounted for a statisticallysignificant amount of variance, additional variance remained unex-plained. Variables not included in this study are likely to further explainthe nature of active procrastination. Future research should includeother motivation-related variables, such as sensation-seeking or needfor cognition. Open-ended, qualitative approaches can also guide effortsto revisit the conceptualization of active procrastination. The factorstructure in the present study reflects oblique rotation, whereas priorstudies used orthogonal rotation. Future studies that compare and con-trast factor-analytical approaches vis-à-vis active procrastination mayprovide further insights. Additionally, it is possible that the findings re-flect the dynamics of science courses. Future research should contextual-ize active procrastination within other disciplines to replicate or qualifythe present study's findings.

7.5. Conclusion

Scholars have traditionally described procrastination as educationallymaladaptive, though more recent research considers the potentiallyadaptive nature of active procrastination. In the context of undergraduateanatomy, this study demonstrates that the underlying factors of activeprocrastination are distinct from one another and do not uniformlyreflect adaptive features of motivation and achievement. The study sug-gests limits to viewing active procrastination as educationally productivepostponement, in large part because the two factors with adaptive asso-ciations did not involve behavioral delay. An active–passive dichotomyappears to be an oversimplification, and measuring an overarching con-struct of active procrastination may obscure key differences. As the de-bate regarding active procrastination and its educational implicationsevolves, scholars should pay careful attention to the definition and vali-dation of factors that speak to the benefits of procrastination.

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