Hensley psychology procrastination

Learning and Individual Differences 36 (2014) 157–164

Contents lists available at ScienceDirect

Learning and Individual Differences
journal homepage: www.elsevier.com/locate/lindif

Reconsidering active procrastination: Relations to motivation and
achievement in college anatomy
Lauren C. Hensley
Dennis Learning Center, The Ohio State University, 250C Younkin, 1640 Neil Avenue, Columbus, OH, USA

a r t i c l e

i n f o

Article history:
Received 27 January 2014
Received in revised form 11 September 2014
Accepted 27 October 2014
Keywords:
College students
Motivation
Procrastination

a b s t r a c t
This study examined passive and active procrastination among undergraduate anatomy students in terms of
background 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 of
which was closely tied to passive procrastination and behavioral procrastination. Analyses indicated that the
relations to motivational beliefs and grades were markedly different for, on the one hand, two factors of active
procrastination (positive relations) and, on the other hand, passive procrastination and the third factor of active
procrastination (negative relations). After controlling for academic ability, only passive procrastination was a
statistically significant predictor of grades. Results imply that the dimensions of active procrastination that
appear adaptive for learning may not reflect behavioral procrastination, whereas the dimension of active procrastination that involves behavioral procrastination lacks adaptive associations.
© 2014 Elsevier Inc. All rights reserved.

Although procrastination tends to be viewed as problematic, the
trend of investigating adaptive aspects of procrastination (e.g., Schraw,
Wadkins, & Olafson, 2007) suggests that not all procrastination is created
equal. Procrastination is traditionally viewed as a self-defeating behavior with links to self-handicapping, low engagement, a lack of selfregulation, and poor academic performance (Harrington, 2005; Rice,
Richardson, & Clark, 2012). In contrast, conceptions of active procrastination suggest that procrastination enacted in a certain manner may be
motivationally 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 productive attributes (e.g., Choi & Moran, 2009). Such an approach is not without controversy. Some scholars suggest that active procrastination is a
contradiction and theoretical impossibility (e.g., Pychyl, 2009). Others
describe active procrastination not as procrastination, per se, but rather
as delay (Corkin, Yu, & Lindt, 2011). Some scholars argue that active procrastination has an adaptive nature that could justify educators' support
of well-intentioned procrastination efforts (Schraw et al., 2007; Vacha &
McBride, 1993). Others suggest that there are limits to the educational
benefits (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 into
play (McGee, Del Vento, & Bavelas, 1997). The study uses the lens of
motivational beliefs to examine procrastination tendencies in undergraduate human anatomy, a context in which procrastination and poor motivation may be particularly detrimental due to students' need to memorize

E-mail address: [email protected].

http://dx.doi.org/10.1016/j.lindif.2014.10.012
1041-6080/© 2014 Elsevier Inc. All rights reserved.

large amounts of information (Beck, Koons, & Milgrim, 2000). Consistent
with research on procrastination from a self-regulated learning perspective, this study considers contextualized factors, such as beliefs about a
specific course, that explain outcomes beyond the contributions of stable
measures, such as general academic ability (Pintrich & Zusho, 2007;
Wolters, 2003). The focus on a specific course aligns with the definition
of active procrastination as a purposeful behavior reflecting the interaction between the learner and the environment. The study contributes
to discussions surrounding active procrastination by questioning the
degree to which its factors reflect behavioral procrastination and hold
adaptive associations with academic motivation and achievement.
1. Conceptions of passive and active procrastination
As defined by Choi and Moran (2009), four factors comprise active
procrastination. First, outcome satisfaction indicates that the students
are pleased with their results. Second, preference for pressure indicates
that the students like to work quickly under deadlines. Third, intentional
decision indicates that the students deliberately postpone tasks. Fourth,
ability to meet deadlines indicates that the students complete activities
on time. Such definitions reflect marked differences between passive
and active procrastination. Statistically nonsignificant (Choi & Moran,
2009; Chu & Choi, 2005) and negative relations (Corkin et al., 2011) between composite measures of the constructs reinforce their distinctness.
The multidimensionality of active procrastination further distinguishes it from passive procrastination, a unidimensional construct
(Tuckman, 2005). In their validation study of the Active Procrastination
Scale, Choi and Moran (2009) used Confirmatory Factor Analysis to establish 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 examined the composite measure, examining relations of academic and
motivational constructs to the scale as a whole (e.g., Cao, 2012; Choi &
Moran, 2009; Chu & Choi, 2005; Corkin et al., 2011). It is possible that
the composite scale endeavors to measure more distinct constructs than
can coexist within a single tendency. This possibility resonates with
concerns that active procrastination—which combines thoughtful task
delay with a failure to self-regulate—is a self-contradictory concept
(Pychyl, 2009). Should this be the case, inferences based on the suprafactor of active procrastination may be inaccurate.
When examined separately, factors of active procrastination may
contain important differences. Intentional delay is likely unique from
other factors due to its conceptual similarity with arousal procrastination. Arousal procrastination involves purposefully delaying to increase
excitement level and thus motivation; however, this construct is called
into 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 relations
to self-regulation and learning strategies. Hensley and Burgoon (2013)
found no factor but intentional delay had the expected associations
with self-reported postponement. Such findings suggest that a composite scale might obscure differences among the dimensions of active procrastination. Additional inquiry is necessary to explore the structure and
associations of the individual factors.
2. Motivational beliefs in relation to procrastination
Beliefs about learning inform students' academic motivation, which
directs efforts toward educational goals (Eccles, 1983; Schommer,
1994). Previous research established certain motivational beliefs as
adaptive due to their consistent connections to effort, persistence, and
learning (Paulsen & Feldman, 2007; Wolters, Yu, & Pintrich, 1996).
The degree to which procrastination exhibits or lacks associations
with motivational beliefs indicates whether it is adaptive or maladaptive (Corkin et al., 2011). At the center of this study are three motivational 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).

draw of engagement in terms of level of interest, instrumentality to
goals, or consistency with how students view themselves (Eccles &
Wigfield, 1995). Each belief is likely to explain variance in procrastination, though the combination of self-efficacy and task value may be
greater than the sum of its parts. In their study of general procrastination tendencies, Gröpel and Steel (2008) demonstrated the conditional
effects of interest-enhancement and goal-setting strategies, and they
urged researchers to explore additional potential interactions. Steel
(2007) proposed a model of temporal motivation in which the desirability of a given action resulted from self-efficacy and task value, taking
into account the amount of time remaining for task completion. A natural extension of Steel and his colleagues' work is to examine differences
in procrastination based on the conditional effects of these two key motivational variables.
The association between low self-efficacy and passive procrastination is well established (Tuckman, 1991; Wolters, 2003). When individuals have low self-efficacy for tasks, they are not likely to engage
in them (Bandura, 1986). Students who doubt their ability to perform
well procrastinate to avoid the emotional discomfort of studying
(Schouwenburg, 1992). Task aversion is another root of passive procrastination, as students avoid working on academic activities they perceive
to be unclear or overly difficult (Ackerman & Gross, 2005). Together,
low confidence and low appeal may make a task appear especially
unattainable and not worth the effort; as such, the combination of
self-efficacy and task value is likely to explain variance in passive
procrastination.
Whereas low self-efficacy accompanies passive procrastination, high
self-efficacy accompanies active procrastination (Cao, 2012; Chu & Choi,
2005; Corkin et al., 2011). Active procrastinators are academically confident yet delay engagement (Choi & Moran, 2009). This association
stands in contrast with the expectation that students with high selfconfidence “should participate more eagerly” in academic activities
(Schunk & Zimmerman, 2006, p. 356). Active procrastinators' delay
of engagement may be explained by low task value, with students
delaying unappealing tasks so that external circumstances make them
appear more challenging and interesting (Brinthaupt & Shin, 2001).
Since active procrastinators have high self-efficacy, they may be prone
to viewing easy tasks as uninteresting. Examining self-efficacy and
task value together may help explain this dynamic.

2.1. Speed of knowledge acquisition
3. Academic ability and achievement in relation to procrastination
Epistemological beliefs are a “component of the cognitive and affective
conditions of a task…[that] influence[s] the standards students set when
goals are produced” (Muis, 2007, pp. 179–180). These standards include
the learning strategies students report enacting (e.g., Paulsen &
Feldman, 2007). By extension, they may also involve choices about how
much time is needed for learning and how this time should be structured.
A particular epistemological belief likely to inform procrastination is the
belief about the speed of knowledge acquisition (Wood & Kardash,
2002). When learning does not occur quickly, students either believe
they cannot learn or that time and effort are a natural part of the process.
Students' beliefs about the speed of knowledge acquisition hold importance for learning outcomes and behaviors. A belief in speedy learning has been linked to low reading comprehension, overconfidence in
one'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 effective learning strategies (Cano & Cardelle-Elawar, 2008). Further ties to
procrastination seem feasible but have received little attention.

Whether scholars consider procrastination to be educationally
adaptive is based on links to motivation, discussed above, as well as
to academic achievement (Corkin et al., 2011). Prior research has
established a strong negative association between passive procrastination and grades (Strunk & Steele, 2011; Tice & Baumeister, 1997). Conversely, college students describe intentional procrastination as having
either no effect or a positive effect on grades (Schraw et al., 2007). Choi
and Moran (2009) reported an interesting disparity: a positive correlation between business majors' active procrastination and perceived
academic performance relative to other students, but no statistically significant correlation between active procrastination and actual gradepoint average (GPA). There is evidence that active procrastination positively correlates with GPA (Chu & Choi, 2005) and predicts course grades
(Corkin et al., 2011), but no known study has controlled for the contribution of academic ability to active procrastinators' academic outcomes.
It remains unclear whether active procrastination itself, as opposed to
the tendency for active procrastinators to have high ability, contributes
to achievement.

2.2. Self-efficacy and task value

4. The present study

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

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

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

contribution of academic ability. There is also a need to test the construct validity of active procrastination and establish whether its factors
reflect procrastination behaviorally. The present study addresses these
needs, with the major purpose of examining the factors of active procrastination and their differential relations to motivation, academic
ability and achievement, and behavioral measures of procrastination.
Three research questions guided the study.
First, what is the factor structure of active procrastination among
undergraduate anatomy students? Do all factors reflect procrastination
behaviorally? The researcher anticipated that only the intentional delay
factor would be validated as behavioral procrastination.
Second, what differences exist in the relations between procrastination measures and motivation variables (i.e., beliefs about the speed of
knowledge acquisition, self-efficacy, and task value, as well as the interaction between self-efficacy and task value)? The researcher hypothesized
that intentional delay would have negative relations to the motivation
variables, 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 of
exam and course grades in anatomy? The researcher anticipated that
active procrastination factors would not predict achievement.
5. Method
The following section provides an overview of participants and the
measures they completed. Scales measured motivation and procrastination. Behavioral measures provided evidence of task delay.
5.1. Participants
The study took place at a large, public university in the Midwestern
United States during spring 2013. The participants were 320 traditionally
aged (Md = 19 years old) undergraduate students enrolled in Human
Anatomy, a four-credit prerequisite course. This required course served
primarily first- and second-year students from multiple areas, including
pre-nursing and pre-allied medical professions. Consistent with typical
course enrollment, most participants (78%) were female. Eighty-three
percent were White, five percent were Asian, and three percent each
were Hispanic, African–American, or two or more ethnicities.
5.2. Procedure
The study took place during a two-week period as the students
began to work on Unit II: The Back and Upper Limb. This time period
was chosen to allow the students sufficient familiarity with the course
to develop motivational beliefs about it. The timing also situated the
measurement of motivation and procrastination prior to achievement.
The researcher visited class to describe the opportunity for students to
complete a confidential online survey. As an incentive, the students
could enter a drawing to win one of five $25 gift cards; no course credit
was awarded.
5.3. Measures
Demographic information came from university records. The central
measures selected for the study were based on motivational theory and
previous research (Choi & Moran, 2009; Pintrich, Smith, Garcia, &
McKeachie, 1991; Tuckman, 1991; Wood & Kardash, 2002). With the
exception of the procrastination measures used to ascertain validity,
described below, all items were placed on seven-point Likert-type
scales with anchored end points (1 = not at all true of me, 7 = very
true of me) and a neutral middle option.
5.3.1. Passive procrastination
Passive procrastination was measured using the 15-item
course-specific adaption (Hensley & Burgoon, 2013) of the Tuckman

159

Procrastination Scale (TPS; Tuckman, 1991). The scale measured
delaying course-related tasks and activities, reflecting avoidant tendencies (sample item = “In this course, I'm an incurable time waster”).
5.3.2. Active procrastination
Active procrastination was measured using the 16-item coursespecific adaption (Hensley & Burgoon, 2013) of the Active Procrastination Scale (Choi & Moran, 2009). The scale measured purposeful and
beneficial procrastination (sample item = “In this course, I intentionally
put off work to maximize motivation”). As with the TPS, the scale contained the same content as the original, with only minor changes introduced through the phrase “in this course.” The underlying factors of the
scale were the focus of analyses in the present study.
5.3.3. Other measures of procrastination and task delay
To test concurrent validity, three measures indicated procrastination
and task delay behaviors. First, an adaptation of the frequency of procrastination subscale from the Procrastination Assessment ScaleStudents (PASS; Solomon & Rothblum, 1984) measured self-reported
procrastination on major course activities: studying for exams, keeping
up with weekly readings, and keeping up with assignments. Second,
students self-reported the number of days prior to the Unit I anatomy
exam they had begun to prepare (where 0 = the day of the exam).
Third, timestamps indicated the amount of time before the deadline students had submitted the Unit I online homework quiz. The timestamp
was subtracted from the due date/time (e.g., 1.50 indicated 36 h before
the deadline). Low numbers reflected high procrastination.
5.3.4. Speed of knowledge acquisition
The eight-item Speed of Knowledge Acquisition scale (Wood &
Kardash, 2002) measured the belief that learning should occur either
quickly or as a gradual process. Items were reverse-coded so that high
scores represented more cognitively complex beliefs, defined as a more
mature or adaptive way of thinking about knowledge (Nist & Holschuh,
2005).
5.3.5. Self-efficacy and task values
The survey included the eight-item Self-Efficacy and six-item Task
Value subscales from the Motivated Strategies for Learning Questionnaire (Pintrich et al., 1991). A sample self-efficacy item was “I'm confident I can understand the most complex material presented by the
instructor in this course” (p. 13). A sample task-value item was “It is
important for me to learn the course material in this class” (p. 11).
5.3.6. Academic ability and achievement
Academic data came from university records. Students' composite ACT
scores served as a proxy of academic ability (e.g., Alarcon & Edwards,
2012). The Unit II exam grade and final course grade indicated achievement in anatomy in a specific instance and over the entirety of the semester. The non-comprehensive, objective exam consisted of 50 multiplechoice, matching, and diagram-identification questions. The final grade
consisted of four non-comprehensive objective exams and four online
homework quizzes.
5.4. Research design
Factor analysis, correlations, and regression analyses addressed the
research questions. Because the Active Procrastination Scale had not
been developed in the context of anatomy at an American university,
it was possible that the measurement would exhibit a different factor
structure in the present study. Factor analysis aimed to identify the underlying factor structure. Bivariate correlations permitted investigation
of basic covariance between variables and testing of concurrent validity
with behavioral measures. Hierarchical regression analyses examined
the relative importance of each variable in explaining variance in

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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 relations
to motivational beliefs and achievement, with particular emphasis on
differentiating between passive procrastination and the dimensions of
active procrastination. Presented first is the factor structure of active
procrastination, followed by the results of correlational analyses. Next
are the regression analyses that test models predicting procrastination
and achievement.
6.1. Factor analysis
The researcher conducted exploratory factor analysis using the maximum likelihood extraction method (Costello & Osborne, 2005). Visual
examination of the scree plot revealed three discrete factors (Cattell,
1966, as cited in Hellman & Caselman, 2004). Oblique rotation indicated
the items' loadings on each of the three correlated factors (Costello &
Osborne, 2005). The composition of factors resulted from considering
factor loadings and the contribution of items to interpretability
(Pajares, 2011). Item 5 loaded nearly equally on two factors. It was included in factor 1 due to its conceptual closeness to the other items
with high loadings on this factor, which centered on aspects of working
under pressure (e.g., Miller, Greene, Montalvo, Ravindran, & Nicholson,
1996). Table 1 presents statistics for each item and factor, with a sideby-side comparison to the factor originally associated with each item.
Two factors reflected Choi and Moran's (2009) original structure: intentional decision to delay (i.e., deliberate postponement of academic
activities) and ability to meet deadlines (i.e., on-time completion of
academic activities). The third factor combined two of Choi and
Moran's factors and was named satisfying outcomes under pressure
(i.e., achieving acceptable results on academic activities when working
within a limited timeframe). Intentional decision to delay contained
the same items as in Choi and Moran's work but, unlike the previous
findings, exhibited negative correlations with the other two factors.

6.2. Descriptive statistics and bivariate correlations
Table 2 presents descriptive statistics and correlations of the continuous variables. All scales had reliability coefficients of .75 or above, except for the composite form of active procrastination.
Bivariate correlations revealed that passive procrastination and the
intentional decision to delay factor had a strong positive correlation.
The two constructs exhibited concurrent validity with the three corroborating procrastination and task delay measures. They both had negative correlations with the belief in gradual acquisition of knowledge,
value of anatomy-related tasks, self-efficacy in anatomy, and academic
achievement. These findings suggest that it is valid to interpret the
two constructs as related or causally generated by a common latent
construct.
Two factors of active procrastination—ability to meet deadlines and
satisfying outcomes under pressure—were positively related to one
another and distinct from passive procrastination and intentional decision to delay. These two factors received no validation from the behavioral measures and instead reflected a tendency to work ahead of
deadlines. They had positive correlations with motivational beliefs and
academic achievement. The composite active procrastination scale had
a lower internal consistency than any of its underlying factors and
an exceptionally high correlation with the satisfying outcomes under
pressure factor; the composite scale was not retained in subsequent
analyses.

6.3. Hierarchical regression analyses
The first set of multiple regression analyses examined relations
of motivational beliefs to passive procrastination and the three active
procrastination factors. The interaction of self-efficacy and task value
was tested in the second step of the model. The second set of regression
analyses examined procrastination variables as predictors of exam and
course grades. The use of hierarchical regression permitted examination
of whether procrastination explained differences in performance beyond what might be explained by academic aptitude and beliefs.

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

Choi and Moran (2009)

Factor and items

M

SD

Factor 1: Ability to meet deadlines
Item 15 (R)
Item 13 (R)
Item 14 (R)
Item 16 (R)

4.91
5.14
5.06
5.49

1.68
1.67
1.66
1.42

Factor 2: Satisfying outcomes under pressure
Item 8 (R)
Item 1 (R)
Item 7 (R)
Item 2 (R)
Item 3 (R)
Item 4 (R)
Item 5 (R)
Item 6 (R)

3.68
3.95
4.28
3.14
3.33
2.53
4.93
4.96

3.37
3.21
2.71
3.64

Factor 3: Intentional decision to delay
Item 9
Item 11
Item 10
Item 12
Eigenvalue
Percentage of variance explained
Cronbach's a

1

2

3

Highest factor loading

.93
.68
.65
.48

−.07
.12
.20
.14

.04
−.11
.01
−.20

Ability to meet deadlines
Ability to meet deadlines
Ability to meet deadlines
Ability to meet deadlines

.73
.74
.73
.60

1.75
1.76
1.70
1.57
1.73
1.37
1.59
1.56

.09
.24
.27
.04
.02
−.23
.42
.17

.62
.61
.57
.54
.50
.47
.40
.38

−.16
−.07
−.04
.00
.07
.12
−.20
−.29

Preference for pressure
Outcome satisfaction
Preference for pressure
Outcome satisfaction
Outcome satisfaction
Outcome satisfaction
Preference for pressure
Preference for pressure

.61
.78
.74
.76
.75
.72
.82
.79

1.68
1.65
1.52
1.81

.15
−.03
−.32
−.20
5.99
37.45
.85

−.02
.03
.07
.06
2.28
14.25
.81

.88
.78
.40
.36
.97
6.04
.75

Intentional decision to delay
Intentional decision to delay
Intentional decision to delay
Intentional decision to delay

.79
.67
.70
.58

Note. “In this course” incorporated into each item. Factor-loading information in the two rightmost columns adapted from Choi and Moran (2009). For text of original items and full factor
loadings, refer to Choi and Moran (2009). In the present study, analyses focused on the three above-identified factors of active procrastination, rather than the 16-item Active Procrastination Scale as a whole. Bold text indicates the factor-loading value selected for each item and its associated factor. In all cases but one, values set in bold represent the highest loading for
each item.

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

161

Table 2
Means, standard deviations, alpha coefficients, and bivariate correlations.
M
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.

SD

α

Passive procrastination
3.26
1.26 .95
Active procrastination
4.02
0.70 .70
(composite)
Ability to meet
5.15
1.33 .85
deadlines
Satisfying outcomes
3.85
1.07 .81
under pressure
Intentional decision
3.23
1.26 .75
6.43
4.39 n/a
Days of advance
studyinga
2.37
3.28 n/a
Days of advance quiz
submissionb
2.85
0.89 .75
Frequency of
procrastination
5.60
0.89 .80
Speed beliefc
Self-efficacy
5.44
1.15 .94
Task value
6.18
0.87 .88
ACT score
26.62
3.49 n/a
Exam grade
81.12 14.86 n/a
Course grade
83.12 12.29 n/a

1

2

3

4

5

6

7

8

9

10

11

12

13

__
.31⁎⁎⁎
.25⁎⁎⁎
.11
.20⁎⁎⁎
.27⁎⁎⁎

__
.54⁎⁎⁎
.15⁎⁎
.36⁎⁎⁎
.43⁎⁎⁎

__
.07
__
.14⁎ .34⁎⁎⁎ __
⁎⁎
.20
.35⁎⁎⁎ .86⁎⁎⁎

__
−.51⁎⁎⁎ __
−.86⁎⁎⁎

.66⁎⁎⁎ __

−.52⁎⁎⁎

.92⁎⁎⁎

.59⁎⁎⁎ __

.66⁎⁎⁎
−.45⁎⁎⁎ −.59⁎⁎⁎ −.28⁎⁎
−.50⁎⁎⁎
.16⁎⁎
.40⁎⁎⁎
.17⁎⁎

__
−.36⁎⁎⁎ __

−.18⁎⁎

−.14⁎

.75⁎⁎⁎
−.17⁎⁎
−.53⁎⁎⁎
−.37⁎⁎⁎
−.03
−.29⁎⁎⁎
−.37⁎⁎⁎

.13⁎

.20⁎⁎⁎

.14⁎

−.33⁎⁎⁎ −.65⁎⁎⁎ −.31⁎⁎⁎
.12⁎
.45⁎⁎⁎
.17⁎⁎
.11
.28⁎⁎⁎
.34⁎⁎⁎

.21⁎⁎⁎
.56⁎⁎⁎
.36⁎⁎⁎
.11
.32⁎⁎⁎
.42⁎⁎⁎

.16⁎⁎
.41⁎⁎⁎
.17⁎⁎
.12⁎
.25⁎⁎⁎
.30⁎⁎⁎

.20⁎⁎⁎ __

.50⁎⁎⁎ −.50⁎⁎⁎ −.16⁎⁎ __
−.22⁎⁎⁎
.06
−.29⁎⁎⁎
.24⁎⁎⁎
−.28⁎⁎⁎
.22⁎⁎⁎
−.06
−.10
−.14⁎
.16⁎⁎
−.19⁎⁎
.21⁎⁎⁎

.02
.05
.03
.06
.13⁎
.12⁎

−.17⁎⁎
−.42⁎⁎
−.34⁎⁎⁎
.05
−.21⁎⁎⁎
−.32⁎⁎⁎

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
How many 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).

6.3.1. Prediction of procrastination
Table 3 presents the results of regression analyses for passive procrastination and the three active procrastination factors. Self-efficacy
was the most important predictor variable in all four models. Notably,
the relation of self-efficacy to intentional decision to delay was negative.
Although the three active procrastination factors derived from the same
pool of items intended to measure a single construct, they appeared to
point to different sources of motivation. Two factors were tendencies
of high-efficacy students, consistent with previous definitions of active
procrastination as a whole. The other factor revealed a trifecta of poor
motivation; intentional decision to delay reflected students' beliefs
that knowledge acquisition had to occur quickly, that they were unlikely
to do well in anatomy, and that learning anatomy was not valuable. In
this way, the intentional decision to delay resonated more with traditional definitions of passive rather than active procrastination.
The interaction of self-efficacy and task value explained unique
variance in passive procrastination and ability to meet deadlines, above
the contribution of other variables. Having a certain level of task value
did little to distinguish between students with low self-efficacy. For
students with high self-efficacy, the level of task value made a difference in that highly efficacious students with high task values were
especially unlikely to report passive procrastination and especially

likely to report an ability to meet deadlines. Figs. 1 and 2 depict the
interactions.
6.3.2. Prediction of procrastination
Additional 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 entire
semester (final course grade).
More than any other variable, academic ability predicted achievement. When accounting for ACT score, self-efficacy remained an important predictor of grades, indicating that students with high perceived
competence in anatomy performed at high levels. The belief about
speed of knowledge acquisition was a positive predictor of overall
course grade; students who believed knowledge was acquired gradually
performed better in the course. This belief was not a statistically significant predictor of performance on the unit exam, which took place in
the first half of the semester. It seems the speed-related belief played
its most salient role in the longer term, as successful students had to
persist in their learning efforts for the duration of the semester. Beyond
the role of academic ability and motivational beliefs, passive procrastination held importance for academic outcomes. Passive procrastinators
performed poorly in anatomy to an extent beyond what might be

Table 3
Hierarchical regression analyses predicting procrastination variables.
Passive procrastination

Ability to meet deadlines

Satisfying outcomes under pressure

Intentional decision to delay

Predictor variables

β Step 1

β Step 2

β Step 1

β Step 2

β Step 1

β Step 1

Step 1
Speed belief
Self-efficacy
Task value

.00
−.46***
−.13***

.01
−.48***
−.18**

.04
.52***
.07

.03
.54***
.13*

.04
.44***
−.08

−.13*
−.16*
−.16*

.29***
.29***

−.14**
.31***
.02**

.32***
.32***

.17***
.35***
.03***

.17***
.17***

Step 2
Self-efficacy x task value
R2
ΔR2

.11***
.11***

Note. Ability to meet deadlines, satisfying outcomes under pressure, and intentional decision to delay are the three factors of active procrastination.
β indicates the standardized regression coefficient. The self-efficacy x task value interaction, tested in Step 2 for all four models, did not explain a significant amount of additional variance
in 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 level of .013 (.05/4) for the procrastination analyses.
*p b .05; **p b .01; ***p b .001.

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

1.5

Table 4
Hierarchical regression analyses predicting grades.

Passive Procrastination

1

Unit II exam grade

0.5

-0.5
-1

Low Self-Efficacy
Low Task Value

High Self-Efficacy
High Task Value

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

expected due to aptitude or beliefs, and the negative role was particularly notable for overall course grade. Satisfying outcomes under pressure and intentional decision to delay were not statistically significant
predictors of grades when the equation accounted for other relevant
variables.

7. Discussion
The findings distinguished among self-reported passive procrastination and active procrastination factors in terms of motivation, achievement, and behavioral procrastination. The results demonstrated the
salience of students' academic ability and beliefs about the nature, attainability, and value of learning anatomy. The study's key contributions relate to the measurement and conceptualization of active procrastination.

Ability to Meet Deadlines

Step 1
ACT

.34***

Step 3
Passive
procrastination
Satisfying outcomes
under pressure
Intentional decision
to delay
R2
ΔR2

.29***

.30*** .35***

.08
.10
.33***
.23**
−.07
−.09

.28***

.13*
.14*
.37***
.24***
−.05
−.07

−.21*

.12***
.12***

.22***
.10***

.30***

−.29***

.02

.02

.09

.09

.24*** .12***
.02*
.12***

.28***
.15***

.32***
.04**

Note. Ability to meet deadlines was omitted from the model due to issues of multicollinearity
caused by high correlations with other predictor variables. β indicates the standardized
regression coefficient. As the study examined more than one criterion variable, it used a
more 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.

7.1. Measurement of active procrastination
Factor analysis of active procrastination in anatomy revealed similarities to Choi and Moran's (2009) factor structure but was not identical. Importantly, intentional decision to delay was negatively correlated
with the two other resulting factors. Intentional decision to delay was
the only factor to exhibit concurrent validity with behavioral measures
of procrastination. Negative associations with motivational beliefs suggest that this active procrastination factor lacks an adaptive nature.
The other two factors had positive associations with motivational beliefs. Ability to meet deadlines and satisfying outcomes under pressure
may thus be viewed as adaptive—but not as procrastination. These findings emphasize the need to revisit how scholars measure and describe
active procrastination (Bui, 2010). A unifactor structure may be insufficient to capture the nuances of active procrastinators' tendencies.

7.2. Differences in motivation and achievement

1.5
1
0.5
0
-0.5
-1
-1.5

β Step 1 β Step 2 β Step 3 β Step 1 β Step 2 β Step 3

Step 2
Speed belief
Self-efficacy
Task value

0

Course grade

Predictor variables

Low Self-Efficacy
Low Task Value

High Self-Efficacy
High Task Value

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

Distinctions among the forms of procrastination revealed individual
differences in motivational beliefs. Viewing oneself as attaining satisfying outcomes under pressure may depend little on whether the task
itself is appealing; instead, the perception may boil down to whether
students view themselves as capable of performing competently, even
under time constraints. Some scholars have argued that procrastination is nearly always irrational (Gröpel & Steel, 2008), yet active procrastinators' actions appear purposeful. The students who
intentionally delay expect learning to occur quickly; such students
may procrastinate to spur themselves to efficient action. In the present
study, connections between intentional delay and low task value suggest students “put off work to maximize [their] motivation” (Choi &
Moran, 2009, p. 203) when they have low confidence or find the content unappealing—that is, when the academic work itself is not motivating. If students simply need a way of completing academic tasks
without respect to quality, they may achieve this goal via procrastination. If students instead believe that procrastination provides a means
of achieving high grades, this approach is irrational. Contrary to arguments that active procrastination can be a pathway to academic
achievement (Chu & Choi, 2005; Schraw et al., 2007; Vacha &
McBride, 1993), the models predicting grades in the present study
show no connection between active procrastination and grades.

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

In terms of achievement, passive procrastination was detrimental
and both high self-efficacy and the belief that knowledge developed
gradually were beneficial. These links were particularly strong for overall course grade, perhaps because of the time and effort required to sustain a high level of performance. This explanation is consistent with the
finding that students who expect learning to occur quickly tend to demonstrate a lack of resilience (Cano & Cardelle-Elawar, 2008). The study
also adds to the evidence that grades are not just a reflection of underlying ability but also relate to students' beliefs about learning and perceived ability to understand a subject (Wolters et al., 1996). Moreover,
the bivariate correlation between satisfying outcomes under pressure
and grades was accounted for by shared variance with other variables
in the regression analyses. This finding supports the notion that positive
relations between active procrastination and grades are a matter of correlation and not causation.

163

Although the combination of variables accounted for a statistically
significant amount of variance, additional variance remained unexplained. Variables not included in this study are likely to further explain
the nature of active procrastination. Future research should include
other motivation-related variables, such as sensation-seeking or need
for cognition. Open-ended, qualitative approaches can also guide efforts
to revisit the conceptualization of active procrastination. The factor
structure in the present study reflects oblique rotation, whereas prior
studies used orthogonal rotation. Future studies that compare and contrast factor-analytical approaches vis-à-vis active procrastination may
provide further insights. Additionally, it is possible that the findings reflect the dynamics of science courses. Future research should contextualize active procrastination within other disciplines to replicate or qualify
the present study's findings.
7.5. Conclusion

7.3. Educational relevance
Task value was particularly important for students with high selfefficacy, perhaps because this combination enhanced the students'
sense of personal connection to study tasks. This finding is consistent
with past research related to the expectancy-value theory of achievement motivation, which describes both aspects as essential to motivation (Wigfield & Eccles, 2000). It also reinforces the theoretical
framing of self-efficacy and task value as key components in temporal
(i.e., time-related) motivation (Steel, 2007) and contributes to evidence
on the multiplicative effects of motivational beliefs (Gröpel & Steel,
2008). When students do not receive a boost of confidence from
believing they can learn, the importance or usefulness of a task may
not drastically change passive procrastination or the ability to meet
deadlines. When students think not only that the task matters
but also that they can be successful, the avoidant tendencies of passive
procrastination are unlikely. Under these circumstances, students
are also apt to motivate themselves to meet deadlines. Faculty and staff
who work to support students' academic strategy use may find their efforts most effective when they help raise levels of perceived competence.
Intentional delay was more similar to passive procrastination than
it was to the other two active procrastination factors, but it was still a
distinct construct. Although both passive procrastination and intentional delay reflected low confidence, the association was much stronger
for passive procrastination. Intentional decision to delay was unique in
that it involved believing that knowledge should be acquired quickly.
Passive procrastination explained variance in low grades when accounting for other variables, but intentional decision to delay did not. To the
extent that the intentional decision to delay involves a greater element
of choice or volition than passive procrastination, it does appear to
be both active and procrastination. Even so, negative associations with
motivational beliefs suggest that encouraging students to delay in an intentional manner is not the wisest practical application of these findings. As Sirois (2004) cautioned, “focusing on how things were not as
bad as they could have been…engenders a sense of satisfaction and complacency that may result in less thought about how to act in a more timely manner in the future” (p. 280). Educators should remain wary about
even those forms of procrastination that students describe as purposeful.
7.4. Limitations and future directions
A limitation of the study was the reliance on self-report measures, as
students may have misrepresented their beliefs and tendencies
(Bowman & Hill, 2011). The students completed the survey online in a
private space, however, and may have been more likely to respond honestly than if completing the survey in the presence of other students or
the instructor (Kreuter, Presser, & Tourangeau, 2008). Still, the findings
may be constrained by the subjective nature of the self-report data, and
future research should incorporate additional objective and behavioral
measures.

Scholars have traditionally described procrastination as educationally
maladaptive, though more recent research considers the potentially
adaptive nature of active procrastination. In the context of undergraduate
anatomy, this study demonstrates that the underlying factors of active
procrastination are distinct from one another and do not uniformly
reflect adaptive features of motivation and achievement. The study suggests limits to viewing active procrastination as educationally productive
postponement, in large part because the two factors with adaptive associations did not involve behavioral delay. An active–passive dichotomy
appears to be an oversimplification, and measuring an overarching construct of active procrastination may obscure key differences. As the debate regarding active procrastination and its educational implications
evolves, scholars should pay careful attention to the definition and validation of factors that speak to the benefits of procrastination.
References
Ackerman, D.S., & Gross, B.L. (2005). My instructor made me do it: Task characteristics of
procrastination. Journal of Marketing Education, 27(1), 5–13. http://dx.doi.org/10.
1177/0273475304273842.
Alarcon, G.M., & Edwards, J.M. (2012). Ability and motivation: Assessing individual factors
that contribute to university retention. Journal of Educational Psychology, 105. http://
dx.doi.org/10.1037/a0028496.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory.
Englewood Cliffs, NJ: Prentice-Hall.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
Beck, B.L., Koons, S.R., & Milgrim, D.L. (2000). Correlates and consequences of behavioral
procrastination: The effects of academic procrastination, self-consciousness, selfesteem, and self-handicapping. Journal of Social Behavior and Personality, 15(5), 3–13.
Bowman, N.A., & Hill, P.L. (2011). Measuring how college affects students: Social desirability and other potential biases in college student self-reported gains. New
Directions for Institutional Research, 150, 73–85. http://dx.doi.org/10.1002/ir.
Brinthaupt, T.M., & Shin, C.M. (2001). The relationship of academic cramming to flow
experience. College Student Journal, 35, 457–472.
Bui, N.H. (2010). Effect of evaluation threat on procrastination behavior. The Journal of
Social Psychology, 147(3), 197–209.
Cano, F., & Cardelle-Elawar, M. (2008). Family environment, epistemological beliefs,
learning strategies, and academic performance: A path analysis. In M.S. Khine (Ed.),
Knowing, knowledge, and beliefs: Epistemological studies across diverse cultures
(pp. 219–239). New York: Springer.
Cao, L. (2012). Examining “active” procrastination from a self-regulated learning perspective. Educational Psychology An International Journal of Experimental Educational
Psychology, 32, 515–545.
Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral
Research, 1, 245–276.
Choi, J.N., & Moran, S.V. (2009). Why not procrastinate? Development and validation of a
new active procrastination scale. The Journal of Social Psychology, 149(2), 195–212.
Chu, A.H.C., & Choi, J.N. (2005). Rethinking procrastination: Positive effects of “active”
procrastination behavior on attitudes and performance. The Journal of Social
Psychology, 145(3), 245–264. http://dx.doi.org/10.3200/SOCP. 145.3.245-264.
Corkin, D.M., Yu, S.L., & Lindt, S.F. (2011). Comparing active delay and procrastination
from a self-regulated learning perspective. Learning and Individual Differences,
21(5), 602–606. http://dx.doi.org/10.1016/j.lindif.2011.07.005.
Costello, A.B., & Osborne, J.W. (2005). Best practices in exploratory factor analysis: Four
recommendations for getting the most from your analysis. Practical Assessment
Research & Evaluation, 10, 1–9.
Eccles, J.S. (1983). Expectancies, values and academic behaviors. In J.T. Spence (Ed.),
Achievement and achievement motives: Psychological and sociological approaches
(pp. 76–146). San Francisco, CA: W. H. Freeman.

164

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

Eccles, J.S., & Wigfield, A. (1995). In the mind of the actor: The structure of adolescents'
achievement task values and expectancy-related beliefs. Personality and Social
Psychology Bulletin, 21, 215–225 (Retrieved from http://deepblue.lib.umich.edu/handle/
2027.42/69045).
Gröpel, P., & Steel, P. (2008). A mega-trial investigation of goal setting, interest enhancement, and energy on procrastination. Personality and Individual Differences, 45,
406–411. http://dx.doi.org/10.1016/j.paid.2008.05.015.
Harrington, N. (2005). It's too difficult! Frustration intolerance beliefs and procrastination. Personality and Individual Differences, 39(5), 873–883. http://dx.doi.org/10.
1016/j.paid.2004.12.018.
Hellman, C.M., & Caselman, T.D. (2004). A psychometric evaluation of the Harvey Imposter Phenomenon Scale. Journal of Personality Assessment, 83(2), 161–166. http://dx.
doi.org/10.1207/s15327752jpa8302_10.
Hensley, L.C., & Burgoon, J.M. (2013). Active and passive procrastination: Overall tendencies
or domain-specific behaviors? Paper presented at the annual meeting of the American
Educational Research Association, San Francisco, April 27–May 1, 2013.
Keith, T.K. (2006). Multiple regression and beyond. Boston: Pearson Education.
Kreuter, F., Presser, S., & Tourangeau, R. (2008). Social desirability bias in CATI, IVR, and
web surveys: The effects of mode and question sensitivity. Public Opinion Quarterly,
72, 847–865.
McGee, D., Del Vento, A., & Bavelas, J.B. (1997). Trait and situational factors in procrastination: An interactional model. Journal of Social Behavior and Personality, 12(4), 889–903.
Miller, R.B., Greene, B.A., Montalvo, G., Ravindran, B., & Nicholson, J. (1996). Engagement
in academic work: The role of learning goals, future consequences, pleasing others,
and perceived ability. Contemporary Educational Psychology, 21, 388–422 (Retrieved
from http://www.ncbi.nlm.nih.gov/pubmed/8979871).
Muis, K.R. (2007). The role of epistemic beliefs in self-regulated learning. Educational
Psychologist, 42(3), 173–190.
Nist, S.L., & Holschuh, J.P. (2005). Practical applications of the research on epistemological
beliefs. Journal of College Reading and Learning, 35(2), 84–93.
Pajares, F. (2011). Toward a positive psychology of academic motivation. The Journal of
Educational Research, 95(1), 27–35.
Paulsen, M.B., & Feldman, K.A. (2007). The conditional and interaction effects of epistemological beliefs on the self-regulated learning of college students: Cognitive and
behavioral strategies. Research in Higher Education, 48(3), 353–401. http://dx.doi.org/
10.1007/s11162-006-9029-0.
Pintrich, P.R., Smith, D.A.F., Garcia, T., & McKeachie, W.J. (1991). A manual for the use of the
Motivated Strategies for Learning Questionnaire (MSLQ). Ann Arbor, MI: National Center for Research to Improve Postsecondary Teaching and Learning, University of
Michigan.
Pintrich, P.R., & Zusho, A. (2007). Student motivation and self-regulated learning in the college classroom. In R.P. Perry, & J.C. Smart (Eds.), The scholarship of teaching and learning
in higher education: An evidence-based practice (pp. 731–810). New York: Springer.
Pychyl, T.A. (2009). Active procrastination: Thoughts on oxymorons. Retrieved June 12,
2012, from. http://www.psychologytoday.com/blog/dont-delay/200907/activeprocrastination-thoughts-oxymorons.
Rice, K.G., Richardson, C.M.E., & Clark, D. (2012). Perfectionism, procrastination, and psychological distress. Journal of Counseling Psychology, 59, 288–302. http://dx.doi.org/
10.1037/a0026643.
Schommer, M. (1990). Effects of beliefs about the nature of knowledge on comprehension. Journal of Educational Psychology, 82, 498–504. http://dx.doi.org/10.1037//
0022-0663.82.3.498.
Schommer, M. (1993). Comparisons of beliefs about the nature of knowledge and learning among postsecondary students. Research in Higher Education, 34, 355–370.
Schommer, M. (1994). Synthesizing epistemological belief research: Tentative understanding and provocative confusions. Educational Psychology Review, 6, 293–319.
Schommer-Aikins, M., & Easter, M. (2008). Epistemological beliefs' contributions to study
strategies of Asian Americans and European Americans. Journal of Educational
Psychology, 100(4), 920–929. http://dx.doi.org/10.1037/0022-0663.100.4.920.

Schouwenburg, H.C. (1992). Procrastinators and fear of failure: An exploration of reasons
for procrastination. European Journal of Personality, 6, 225–236.
Schraw, G., Wadkins, T., & Olafson, L. (2007). Doing the things we do: A grounded theory
of academic procrastination. Journal of Educational Psychology, 99(1), 12–25. http://
dx.doi.org/10.1037/0022-0663.99.1.12.
Schunk, D.H., & Zimmerman, B.J. (2006). Competence and control beliefs: Distinguishing
the means and ends. In P.A. Alexander, & P.H. Winne (Eds.), Handbook of educational
psychology (pp. 349–367) (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.
Simpson, W.K., & Pychyl, T.A. (2009). In search of the arousal procrastinator: Investigating
the relation between procrastination, arousal-based personality traits and beliefs
about procrastination motivations. Personality and Individual Differences, 47(8),
906–911. http://dx.doi.org/10.1016/j.paid.2009.07.013.
Sirois, F.M. (2004). Procrastination and counterfactual thinking: Avoiding what might
have been. The British Journal of Social Psychology, 43, 269–286. http://dx.doi.org/10.
1348/0144666041501660.
Solomon, L.J., & Rothblum, E.D. (1984). Procrastination Assessment Scale for Students
(PASS).
Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of
quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65–94. http://dx.
doi.org/10.1037/0033-2909.133.1.65.
Steel, P. (2010). Arousal, avoidant and decisional procrastinators: Do they exist. Personality
and Individual Differences, 48, 926–934.
Strunk, K.K., & Steele, M.R. (2011). Relative contributions of self-efficacy, self-regulation,
and self-handicapping in predicting student procrastination. Psychological Reports,
109(3), 983–989. http://dx.doi.org/10.2466/07.09.20.PR0.109.6.983-989.
Tice, D.M., & Baumeister, R.F. (1997). Longitudinal study of procrastination, performance,
stress, and health: The costs and benefits of dawdling. Psychological Science, 8(6),
454–458.
Tuckman, B.W. (1991). The development and concurrent validity of the Tuckman
Procrastination Scale. Educational and Psychological Measurement, 51, 473–489.
Tuckman, B.W. (2005). Relations of academic procrastination, rationalizations, and
performance in a web course with deadlines. Psychological Reports, 96, 1015–1021.
Vacha, E.F., & McBride, M.J. (1993). Cramming: A barrier to student success, a way to beat
the system or an effective learning strategy? College Student Journal, 27(1), 2–11.
Wigfield, A., & Eccles, J.S. (2000). Expectancy-value theory of achievement motivation.
Contemporary Educational Psychology, 25(1), 68–81. http://dx.doi.org/10.1006/ceps.
1999.1015.
Wolters, C.A. (2003). Understanding procrastination from a self-regulated learning perspective. Journal of Educational Psychology, 95(1), 179–187. http://dx.doi.org/10.
1037/0022-0663.95.1.179.
Wolters, C. A., & Benzon, M. B. (2013). Assessing and predicting college students’ use of
strategies for the self-regulation of motivation. Journal of Experimental Education, 81,
199–221.
Wolters, C.A., Hussain, M., & Young, J. (2013). Connecting college students' self-regulated
learning, time management, and procrastination. Paper presented at the Annual Meeting of the American Educational Research Association, San Francisco, CA.
Wolters, C.A., Yu, S.L., & Pintrich, P.R. (1996). The relation between goal orientation and
students' motivational beliefs and self-regulated learning. Learning and Individual
Differences, 8, 211–238 (Retrieved from http://www.sciencedirect.com/science/article/
pii/S1041608096900151).
Wood, P.K., & Kardash, C. (2002). Critical elements in the design and analysis of studies of
epistemology. In B.K. Hofer, & P.R. Pintrich (Eds.), Personal epistemology: The psychology
of beliefs about knowledge and knowing (pp. 231–260). Mahwah, NJ: Lawrence Erlbaum
Associates.