-
THE CONDITIONAL AND INTERACTION EFFECTSOF EPISTEMOLOGICAL
BELIEFS ON THESELF-REGULATED LEARNING OF COLLEGESTUDENTS:
Motivational Strategies
Michael B. Paulsen*, and Kenneth A. Feldman**
................................................................................................................................................................................................
This study examines the conditional and interaction effects of
each of fourdimensions of the epistemological beliefs of college
students regarding the ability tolearn, the speed of learning, the
structure of knowledge, and the stability ofknowledge on six
measures of the motivational components of self-regulatedlearning
strategies (intrinsic goal orientations, extrinisic goal
orientation, task value,self-efficacy, control of learning and test
anxiety). Students with more sophisticatedbeliefs about the nature
of knowledge and learning were more likely than theirpeers to use
educationally productive motivational strategies in their
learning.Beliefs about ones ability to learn and the structure of
knowledge had the mostsignificant and substantial effects on
students use of self-regulated motivationalstrategies. Although a
students belief about the stability of knowledge by itself hada
statistically significant effect on only one motivational strategy,
this belief did havefour statistically significant interaction
effects with beliefs about ability to learn andthe structure of
knowledge. Implications of these findings for theory,
research,policy and practice are examined.
................................................................................................................................................................................................KEY
WORDS: epistemological beliefs; self-regulated learning; student
motivation.
Increased attention on the learner-centered classroomas a
founda-tion for the design of learning environments and reform of
teachingpractice in higher educationhas stimulated the need for
deeper under-standing of how college students learn (Cross and
Steadman, 1996;
*Department of Educational Policy & Leadership Studies, The
University of Iowa, Iowa
City, IA.
**Department of Sociology, State University of New York at Stony
Brook, Stony Brook,
NY.Address correspondence to: Michael B. Paulsen, Professor of
Higher Education,
Educational Policy & Leadership Studies, College of
Education, The University of Iowa,N491 Lindquist Center North,
52242-1529, Iowa City, IA. E-mail: [email protected]
731
0361-0365 05 1100-0731 0 2005 Springer Science+Business Media,
Inc.
Research in Higher Education, Vol. 46, No. 7, November 2005 (
2005)DOI: 10.1007/s11162-004-6224-8
-
Paulsen, 1999; Stage, Muller, Kinzie, and Simmons, 1998;
Svinicki, 2004;Weimer, 2002). The social-cognitive mediation model
of college studentlearning developed by McKeachie, Pintrich and
their colleagues (McKeachie,Pintrich, Lin, Smith, and Sharma, 1990;
Pintrich, 1989; Pintrich andZusho, 2002) has emerged as a
particularly productive framework forexamining various factors that
inuence meaningful learning in the col-lege classroom. This model
assumes that the eects on learning outcomesof the prior background
of students and classroom context are mediatedby the motivational,
cognitive and behavioral strategies students use intheir learning,
including their self-regulation of these strategies.Within this
framework, self-regulated learning is viewed as a process
in which individual students actively and constructively monitor
andcontrol their own motivation, cognition and behavior toward the
suc-cessful completion of academic tasks (Butler and Winne, 1995;
DuBoisand Staley, 1997; Pintrich, 1995; Valle et al., 2003; Winne,
1995;Zimmerman, 1994). Research in this area has consistently
demonstratedthat students use of eective motivational, cognitive
and behavioralprocesses and strategies is directly related to
students academic achieve-ment (Paulsen and Gentry, 1995; Pintrich
and Garcia, 1991; Pintrichand Schrauben, 1992; Pintrich and Zusho,
2002). A relatively new, butvery promising, development in research
on the student mediationmodel of learning is based on investigating
how dierences in epistemo-logical beliefs of students might help
explain variation in their use andself-regulation of their
motivational, cognitive, and behavioral processesand strategies for
learning (Hofer and Pintrich, 1997; Paulsen andFeldman, 1999a,
1999b; Pintrich, 2002; Schommer, 2002).Educational psychologists
typically have viewed epistemological beliefs
as systems of implicit assumptions and beliefs held by students
about thenature of knowledge and its acquisition (Bruning, Schraw,
and Ronning,1999; Hofer and Pintrich, 1997). Most traditional
studies of the episte-mological beliefs of college students are
generally embedded indevelopmental perspectives. Such studies have
viewed students as devel-opmentally advancing through a sequence of
positions or stages in theirepistemological beliefs. For the most
part, these studies see students asprogressing along a primarily
unidimensional continuum from dualisticbeliefs to more relativistic
beliefs about the nature of knowledge andlearning (Baxter Magolda,
1992; Belenky, Clinchy, Goldberger, andTarule, 1986; Kitchener and
King, 1981; Perry, 1970).In the 1990s, Schommer (1990, 1994a,
1994b; Schommer-Aikins,
2004) moved beyond the traditional unidimensional approaches to
theconceptualization and measurement of epistemological beliefs,
proposingan expanded view that re-conceptualized the construct as a
multidimen-
732 PAULSEN AND FELDMAN
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sional system of beliefs about the nature of knowledge and
learning.This multidimensional system comprises beliefs about the
structure ofknowledge, the stability of knowledge, the speed of
knowledge acquisi-tion and the control of knowledge acquisition.
Schommer developed thismultidimensional approach through her eorts
to integrate the work ofa number of scholars who had worked
independently of one anotherwhile they investigated dierent
dimensions of epistemological beliefs(e.g., Dweck and Leggett,
1988; Perry, 1970; Schoenfeld, 1983). As ithappens, her
multidimensional perspective on the conceptualization
andmeasurement of epistemological beliefs has helped stimulate and
redirectresearch in the eld (e.g., see Hofer and Pintrich,
2002).Research has demonstrated that the origins and development of
episte-
mological beliefs are formed and shaped by various pre-college
factors(Unger, Draper, and Pendergrass, 1986), such as background
character-istics like age and gender (Paulsen and Wells, 1998;
Schommer, 1990),parental education and socioeconomic status
(Schommer, 1990, 1993a),characteristics of upbringing in early home
and family environments,including encouragement of independence in
decisions and discussions orstrictness of adherence to rules and
guidelines (Schommer, 1990, 1993a),and pre-college schooling
experiences (Schommer, 1993b; Schommer,Calvert, Garigliette, and
Bajaj, 1997). Yet, research also indicates thatcollege-related
experiences can impact students epistemological beliefs aswell
(Hofer, 2000; Jehng, Johnson, and Anderson, 1993; Kardash
andHowell, 2000; Paulsen and Wells, 1998; Schommer, 1993a).The
development and expansion of theories of epistemology have par-
alleled the growing research in this area. An increasingly
prominentview in the literature is that the epistemological beliefs
of college stu-dents play a potentially critical and central role
in facilitating or con-straining the eectiveness of students
self-regulated learning. Morespecically, reviews of recent research
and emerging theory have con-cluded that students beliefs about the
nature of knowledge and learningcan function as standards,
criteria, implicit theories, or cognitive lensesthrough which
students (1) assess academic tasks and task-related per-formance or
learning, (2) monitor, select, generate, and interpret inter-nal
feedback regarding what constitutes appropriate and
eectiveapproaches to such tasks, and (3) develop motivational,
cognitive, andbehavioral strategies for eective self-regulated
learning (Butler andWinne, 1995; Hofer and Pintrich, 1997;
Pintrich, 2002; Ryan, 1984;Schommer-Aikins, 2002; Winne,
1995).Showing steady support for these propositions, research has
consis-
tently demonstrated signicant relationships between students
epistemo-logical beliefs and a variety of learning outcomes
including academic
EPISTEMOLOGICAL BELIEFS AND MOTIVATIONAL STRATEGIES 733
-
achievement (Bruning et al., 1999; Hofer, 1999, 2000; Hofer
andPintrich, 1997; Ryan, 1984; Schommer, 1994a, 1994b;
Schommer-Aikins,2002, 2004; Schutz, Pintrich, and Young, 1993; Wood
and Kardash,2002). In addition, several initial studies in the area
have already pro-vided preliminary evidence that students
epistemological beliefs may berelated to their engagement in either
the motivational, cognitive orbehavioral aspects of self-regulated
learning, which constitute importantaspects of learning. For
example, Schutz et al. (1993) found that a one-dimensional measure
of epistemological beliefs was related to studentsuse of two types
of cognitive learning strategies and one type of motiva-tional
strategy. Valle et al. (2003) found that a one-dimensional
measureof epistemological beliefs about learning was related to
students use oftwo types of motivational strategies. Schommer,
Crouse, and Rhoads(1992) showed that the eect of one measure of
epistemological beliefsabout learning was mediated by students use
of one type of cognitivelearning strategy, while Kardash and Howell
(2000) found that severaldimensions of the epistemological beliefs
of students were related totheir use of several types of cognitive
strategies. Finally, Hofer (1999)showed that students beliefs about
the nature of mathematics knowl-edge were related to one type of
cognitive strategy and two types ofmotivational strategies.None of
these studies, however, has performed a comprehensive
examination of the relationships between a wide range of
students useof multiple strategies from all three of the primary
categories of self-reg-ulated learning strategiesmotivational,
cognitive, and behavioralandseparate measures of each of the
distinct components of a well-devel-oped, multidimensional system
of students beliefs about the nature ofknowledge and learning.
Earlier studies have tended to focus on sam-ples of students taking
classes in only one or two specic elds, such aspsychology or
mathematics, rather than examining students takingcourses across a
wide range of elds spanning the humanities, social sci-ences and
natural sciences.1 Additionally, initial studies have
providedpreliminary evidence about only the main eects of
epistemologicalbeliefs on students self-regulation, thereby
ignoring the potential condi-tional and interaction eects of
epistemological beliefs on self-regula-tion. Our own research
program has been designed to address thesegaps in the emerging
research literature. Our earlier and preliminarystudies, which were
based on the experiences of students taking under-graduate courses
in education, examined four distinct components of
amultidimensional system of epistemological beliefs and their
relation-ships with six measures of motivational learning
strategies (Paulsen andFeldman, 1999b), four measures of cognitive
learning strategies and
734 PAULSEN AND FELDMAN
-
four measures of behavioral strategies (Paulsen and Feldman,
1999a).In these two studies, two dimensions of epistemological
beliefs weresignicantly related to more than half of the
motivational, cognitive andbehavioral learning strategies examined,
a third dimension was relatedto about one-third of all strategies,
and a fourth measure was unrelatedto such strategies.The present
studyone in a planned set of analysesfurther ad-
vances progress in this line of inquiry by using a sample more
thantwice as large as in our previous studies and by examining
students tak-ing classes in a variety of disciplines representing
the humanities, natu-ral sciences, social sciences and education.
It examines both theconditional and interaction eects of four
dimensions of epistemologicalbeliefs on motivational learning
strategies onlybecause of the com-plexity of the analysis and
consequent space considerations. The eectsof epistemological
beliefs on cognitive and behavioral learning strategiesare analyzed
in a separate article as a companion piece to the
presentreport.
METHODS
The Sample
The subjects for this study were 502 students at a large urban
publicuniversity. They were enrolled in 16 undergraduate classes
oered dur-ing the spring semester of 1996 from a diverse set of
elds including thehumanities (philosophy and English), the natural
sciences (biology andgeology), the social sciences (psychology and
history), and education.About 61% of the students were women and
39% were men; 70.3%were between 17 and 24 years old and 28.7% were
25 years or older. Inthe sample, 51.4% were lower-division
undergraduate students, 41.8%were upper-division undergraduates,
and 6.8% were graduate students,but all were surveyed while taking
undergraduate courses. Finally, 9.6%of the students in the sample
were African American, 3.8% were AsianAmerican, 75.5% were
Caucasian, 6.2% were Hispanic, and about 5%were from Native
American or other backgrounds.
The Variables and their Measurement
This study examines the relations between four measures of
epistemo-logical beliefs (independent variables) and six measures
of motivationallearning strategies (dependent variables) college
students use in their
EPISTEMOLOGICAL BELIEFS AND MOTIVATIONAL STRATEGIES 735
-
courses. The nature and measurement of these variables are
explained inthe sections below.
Epistemological Beliefs
We assessed students epistemological beliefs using the
EpistemologicalQuestionnaire (EQ) developed by Schommer (1990).
This 64-item ques-tionnaire, which is the written instrumentation
for measuring personalepistemology that currently has the most
widespread use (Hofer, 2002,p. 10), has often been used in the
study of college students epistemologi-cal beliefs (Bendixen,
Dunkle, and Schraw, 1994; Kardash and Howell,2000; Kardash and
Scholes, 1996; Paulsen and Feldman, 1999a, 1999b;Paulsen and Wells,
1998; Schommer, 1990, 1993a; Schommer-Aikins,2004; Schommer-Aikins,
Duell, and Barker, 2003; Schommer et al.,1992).The EQ was
administered to all 502 students in the sample during the
second half of the spring semester of 1996. Students responded
to eachitem by rating it on a 5-point Likert scale. The items on
the question-naire were designed to measure students
epistemological beliefs on fourdistinct and largely independent
dimensions: simple knowledge; certainknowledge; xed ability; and
quick learning. The rst two dimensionsmeasure students beliefs
about the nature of knowledgein particular,its structure and its
stability. Scores on the scale for simple knowledgevary along a
continuum ranging from beliefs that knowledge is orga-nized as
isolated bits and pieces to knowledge is organized as
highlyinterwoven concepts (Schommer, 1994a, p. 28). Scores on the
scale forcertain knowledge vary along a continuum ranging from
beliefs thatknowledge is absolute to knowledge is tentative (p.
28). The last twodimensions measure students beliefs about the
nature of learninginparticular, the ability to learn and the speed
of learning. Scores on thescale for xed ability vary along a
continuum ranging from beliefs thatthe ability to learn is xed at
birth to the ability to learn can bechanged (p. 28). Scores on the
scale for quick learning vary along acontinuum ranging from beliefs
that knowledge is acquired quickly ornot-at-all to knowledge is
acquired gradually (p. 28). Each of thesefour continua of
epistemological beliefs is anchored by a more navebelief at one end
and a more sophisticated belief at the other end.Following
Schommers (1990) practice, higher scores on each of thesescales
correspond to more nave beliefs, while lower scores representmore
sophisticated beliefs. In similar fashion, the labels for each
dimen-sion are expressed in terms of the nave form of each
beliefthat is,nave beliefs that knowledge is simple in structure
and certain or
736 PAULSEN AND FELDMAN
-
stable over time, that learning takes place quickly or not at
all, andthat individuals have a xed ability to learn.The
psychometric validity and reliability of the EQ have been
estab-
lished previously in a number of ways. Its underlying
four-factor struc-ture has been consistently replicated with
dierent samples of collegestudents (Bendixen et al., 1994;
Schommer, 1990; Schommer et al.,1992), adults with high school,
college, or graduate school levels of edu-cation (Schommer, 1998),
and high school students (Schommer, 1993b;Schommer and Dunnell,
1994). The underlying factor structure has beensupported by both
exploratory and conrmatory factor analyses(Schommer et al., 1992).
The inter-item reliabilities for the sets of itemsconstituting each
underlying factor range in magnitude from .63 to .85and tests have
revealed an eight-week testretest reliability of .70(Schommer et
al., 1997). Finally, a series of studies has demonstratedthe
instruments ability to predict a variety of meaningful learning
out-comes, such as students motivation to learn, use of cognitive
andbehavioral learning strategies, comprehension,
metacomprehension, testperformance, and level of complexity of
reective judgment (Bendixenet al., 1994; Paulsen and Feldman,
1999a, 1999b; Schommer, 1990;Schommer et al., 1992; Schommer and
Walker, 1995). Although therehave been some recent eorts to develop
alternatives to SchommersEQ, these remain works in progress with no
one highly-regarded alter-native yet available (e.g., see Schraw,
Bendixen, and Dunkle, 2002;Wood and Kardash, 2002). Therefore, to
make the ndings of the pres-ent study comparable with prior work in
our own ongoing researchprogram on epistemological beliefs and
self-regulated learning, we con-tinued to use Schommers EQ to
measure epistemological beliefs in thepresent study. As in our
previous work, students scores on each dimen-sion of belief were
computed by applying factor scoring coecientsdeveloped by Schommer
for use with college students to the actualmeans and standard
deviation measures derived from the sample exam-ined in the present
study.2
Self-regulated Learning Strategies
We assessed students use of self-regulated learning strategies
in theirclasses using the Motivated Strategies for Learning
Questionnaire(MSLQ) developed by Pintrich and colleagues (Pintrich,
Smith, Garcia,and McKeachie, 1991). The items on the questionnaire
were designed tomeasure students use of three sets of
self-regulated learning strate-giesmotivational, cognitive, and
behavioral. The 81-item survey wasadministered to all 502 students
during the second half of the spring
EPISTEMOLOGICAL BELIEFS AND MOTIVATIONAL STRATEGIES 737
-
semester of 1996. Each respondent rated themselves on their use
of spe-cic strategies along a 7-point Likert scale, ranging from
not at all trueof me to very true of me. Students reported on their
attitudes,thoughts and behaviors regarding the specic academic
tasks theyencountered in the context of the particular classes in
which they com-pleted the MSLQ. The psychometric validity and
reliability of theMSLQ have been well established previously
through multiple adminis-trations in small and large classes, in a
wide variety of subjectareas, and at dierent types of institutions
(Paulsen and Feldman,1999a, 1999b; Paulsen and Gentry, 1995;
Pintrich, 1989; Pintrich andGarcia, 1991; Pintrich and Zusho,
2002), and through conrmatory fac-tor analysis (Pintrich, Smith,
Garcia, and McKeachie, 1993). In addi-tion, we calculated internal
reliability coecients (Cronbachalphas)which ranged from .64 to
.90for each of the six scales usedin the present study, as
follows.Thirty one of the 81 survey items assessed the extent to
which stu-
dents used each of six distinct types of motivational learning
strate-gies. The four items of the intrinsic goal orientation scale
(a=.71)assessed the extent to which students perceived themselves
to beengaged in academic tasks to pursue internal rewards like
mastery orseeking to be challenged (e.g., In a class like this, I
prefer course mate-rial that really challenges me so I can learn
new things). The fouritems of the extrinsic goal orientation scale
(a=.64) assessed the extentto which students perceived themselves
to be engaged in academic tasksto pursue external rewards like
approval from others or getting goodgrades (e.g., Getting a good
grade in this class is the most satisfyingthing for me right now).
The six items of the task value scale (a=.90)measured students
assessments regarding how interesting, important, oruseful they
perceived the course to be (e.g., I think I will be able to usewhat
I learn in this course in other courses). The four items of
thecontrol of learning scale (a=.68) measured the extent to which
studentsbelieved that their academic performance was dependent on
factors theycontrolled, such as the amount of their study or eort
(e.g., If I tryhard enough, then I will understand the course
material). The eightitems of the self-ecacy scale (a=.90) measured
the extent to which stu-dents believed that they were competent in
terms of task-related abilitiesand skills and had a high likelihood
of a successful academic perfor-mance (e.g., Considering the
diculty of this course, the teacher, andmy skills, I think I will
do well in this class). The ve items of the testanxiety scale
(a=.80) assessed the extent to which students experienceddiscomfort
or had negative thoughts that could interfere with their test
738 PAULSEN AND FELDMAN
-
performance (e.g., When I take a test, I think about items on
otherparts of the test I cant answer).
The Models and their Estimation
This study uses multiple regression analysis to estimate the
condi-tional and interaction eects of a set of four measures of
epistemologi-cal beliefs (independent variables) on six measures of
students use ofmotivational learning strategies (dependent
variables) in their collegecoursework. Because these independent
variables and dependent vari-ables are continuous measures, the use
of conventional analysis of vari-ance approaches would be
problematic. The arbitrary dichotomization(or some other form of
categorization) of independent variablesrequired by ANOVA-based
procedures (see e.g., Cohen and Cohen,1983) reduces cross-student
variation and statistical power in key vari-ables. Therefore,
multiple regression was used to capitalize on all thecross-student
variation in variables available with the continuous mea-sures
employed. Additionally, all dependent and independent variableswere
standardizedbefore any interaction terms were createdso thatthe
estimates of regression coecients would measure eect sizes
instandard deviation units.
Deriving the Full Two-Way Interaction, Product-Term Model
Equation (1) below represents the general form of a
conventionalmain-eects model estimated using ordinary least squares
regression. Itprovides a useful starting point for the derivation
of the full two-way inter-action, product-term model used in this
study to estimate the conditionaland interaction eects of
epistemological beliefs on students use of moti-vational learning
strategies. Equation (1) includes the dependent vari-ablea
particular motivational learning strategyand four
independentvariables, each corresponding to one of the measures of
four distinctdimensions of epistemological beliefs examined in this
study.
Sij a b1E1i b2E2i b3E3i b4E4i eij 1where i=1,..., n students;
j=1,..., J motivational learning strategy vari-ables; and
Sij =value of the jth motivational learning strategy variable
for theith student;
E1i=value of the rst epistemological belief variable in the
model forthe ith student;
EPISTEMOLOGICAL BELIEFS AND MOTIVATIONAL STRATEGIES 739
-
E2i=value of the second epistemological belief variable in the
modelfor the ith student;
E3i=value of the third epistemological belief variable in the
model forthe ith student;
E4i=value of the fourth epistemological belief variable in the
modelfor the ith student;
a=the intercept term for the model;b1=estimated eect of E1 (the
1st epistemological belief variable in
model) on S (jth motivational learning strategy variable in
themodel);
b2=estimated eect of E2 (the 2nd epistemological belief
variables inmodel) on S (jth motivational learning strategy
variable in themodel);
b3=estimated eect of E3 (the 3rd epistemological belief
variables inmodel) on S (jth motivational learning strategy
variable in themodel);
b4=estimated eect of E4 (the 4th epistemological belief
variables inmodel) on S (jth motivational learning strategy
variable in the model);
eij=the residual or error term for the equation, which is
assumed tomeet the standard assumptions for OLS regression: its
values areindependently and normally distributed, have a mean of
zero, and avariance that is unrelated to one or more of the
independent variables.
Next, the conventional main-eects model of Eq. (1) is used as a
basisfor deriving the full two-way interaction, product-term model
used inthis study to estimate the conditional and interaction eects
of episte-mological beliefs on students use of motivational
learning strategies (seee.g., Aiken and West, 1991; Cohen and
Cohen, 1983; Jaccard andTurrisi, 2003; Jaccard, Turrisi, and Wan,
1990). We follow one popu-lar school of thought [that]
conceptualizes interaction eects in terms ofmoderated relationships
(Jaccard and Turrisi, 2003, p. 3). For example,an interaction eect
would exist if the eect of a particular epistemolog-ical belief on
a motivational learning strategy changed or varied accord-ing to
the values of one or more other epistemological belief variables.In
such cases, the eect of one epistemological belief on the
motiva-tional strategy is moderated by one or more of the other
epistemolog-ical belief variables.Thus, the specication of our
model expresses the hypotheses that
the estimated eects (b1, b2, b3, b4) of each of the
epistemologicalbelief variables in each model (E1, E2, E3, E4,) on
the motivationallearning strategy variable (Sij) for a given model
is a function of, or ismoderated by, the other epistemological
belief variables in each
740 PAULSEN AND FELDMAN
-
modeli.e., b1=f(E2, E3, E4), b2=f(E1, E3, E4), b3=f(E1, E2,
E4),b4=f(E1, E2, E3). Eq. (2) below presents the complete two-way
interac-tion, product-term model, which includes the four
epistemological beliefvariables themselves and all six of the
possible two-way interactionsbetween them.
Sij a b1E1i b2E2i b3E3i b4E4i b5E1iE2i b6E2iE3i b7E1iE3i
b8E2iE4i b9E1iE4i b10E3iE4i eij 2
In this study, Eq. (2) is estimated using multiple regression
analysis, andthe coecient estimates constitute the conditional and
interaction eectsof four distinct dimensions of students
epistemological beliefs on eachof the six measures of motivational
learning strategies.
Interpreting the Coecients on the Interaction Terms
The coecients on the interaction terms (b5, b6, b7, b8, b9, b10)
in Eq.(2) can be readily interpreted. A complete examination of the
eect ofE1 on Sij provides an illustration that generalizes in a
straightforwardmanner to parallel expressions of the eects of E2,
E3, or E4 on Sij.Taking the rst derivative of Sijwith respect to
E1i in Eq. (2) (Sij/E1)indicates that in the full, two-way
interaction, product-term model, theeect of the rst epistemological
belief variable, E1, on a particularmotivational learning strategy
Sij equals b1 + b5 E2 + b7 E3 + b9 E4and is fully expressed as
follows:
Effect of E1 on Sij oSij=oE1 b1 b5E2 b7E3 b9E4 2aTherefore, in
this two-way interaction model, the eect of E1 on Sij canchange
according to, or be moderated by, the values of E2, E3, or E4.In
this illustration, then, E1 is viewed as the focal independent
vari-able and E2, E3, and E4 are the moderator variables (Jaccard
andTurrisi, 2003, p. 3). This means the eect of E1 on Sij could
vary acrossthe values of E2 with the eect of E1 on Sij changing by
the amount b5for each one-unit increase in E2. Similarly, the eect
of E1 on Sij couldvary across the values of E3 with the eect of E1
on Sij changing by theamount b7 for each one-unit increase in E3,
and the eect of E1 on Sijcould vary across the values of E4 with
the eect of E1 on Sij changingby the amount b9 for each one-unit
increase in E3. In other words, b5,b7, and b9 are estimates of
interaction eects and measure theamount by which the eect of E1 on
Sij (i.e., the slope of Sij on E1)changes per one-unit change in
the values of the moderator variables,E2, E3, or E4,
respectively.
EPISTEMOLOGICAL BELIEFS AND MOTIVATIONAL STRATEGIES 741
-
Furthermore, because all the variables were standardized and
thereforemean-centeredprior to the creation of any interaction
termsthemean of each variable is equal to zero. This mean-centering
provides astraightforward process for isolating and considering one
of the interac-tion eect estimates, such as b5, as distinct from
the others (b7, and b9),as desired for purposes of interpretation.
As an illustration, one couldview E1 as the focal independent
variable and E2 as the moderator vari-able and set the other
potential moderator variables equal to zeroi.e.,equal to their mean
values (E3 E4 0). Under these conditions, theeect of the rst
epistemological belief, E1, on a particular motivationallearning
strategy Sij in Eq. (2) equals b1 + b5 E2 and is fully expressed
asfollows:
Effect of E1 on Sij given E3 E4 0 oSij=oE1 b1 b5E2 2bMoreover,
under these conditions (E3 E4 0), Eq. (2) can be rewrit-ten in a
reduced form useful for interpreting and clarifying the meaningof
selected interaction eects. Continuing with the illustration
above,with E1 as the focal independent variable and E2 as the
moderator vari-able, Eq. (2) (given E3 E4 0) can be written as
follows:
Sij a b1E1 b2E2 b5E1E2 3To further facilitate and clarify
interpretation of the interaction eect,Eq. (3) can be rewritten in
interceptslope form as
Sij a b2E2 b1 b5E2E1 3awhere the intercept equals (a + b2E2) and
the slope equals (b1 + b5E2).If the interaction eect b5 is
statistically signicant, then Eqs. (3)and (3a) can be used to
explore the meaning of the interaction eect.Cohen and Cohen (1983)
and Aiken and West (1991) recommendsubstituting into Eq. (3a)
values of the moderator variable E2 equal toone standard deviation
below the mean, equal to the mean, and equalto one standard
deviation above the mean, which in the case of thestandardized
moderator variable E2 would be )1, 0, and 1, respectively.This
approach provides insights into the nature of the signicant
inter-action eect by simulating selected changes in the intercept
and slopeterms of Eq. (3a), and these simulated changes in the
equation for vari-ous values ()1, 0, 1) of a moderator variable can
be plotted on a graphto display the interaction. When presenting
the results of our study, weuse this approach to supplement
traditional tabular and narrativepresentations of ndings about
interaction eects.
742 PAULSEN AND FELDMAN
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Estimating Main Eects versus Conditional Eects
The main-eects model is illustrated by Eq. (1) given earlier.
Thereare four independent variables, four corresponding
regressioncoecients, and no higher-order interaction terms. An
estimate of theregression coecient b1 in Eq. (1) measures the
trends of change inSij per one-unit change in E1 at each value of
E2, E3, or E4, or the gen-eral relationship or constant eect of E1
averaging across all levelsof the ranges of values for E2, E3, and
E4. The meaning of the estimatesof b2, b3, and b4 in Eq. (1) would
be analogous to b1 (Aiken and West,1991; Jaccard and Turrisi, 2003;
Jaccard et al., 1990).The present study focuses on the estimation
of the conditional and
interaction eects of epistemological beliefs on motivational
learningstrategies in a product-term model. This means that the
coecients ofthe product-term interaction eects model presented in
Eq. (2), insteadof Eq. (1), are estimated. In the presence of a
signicant interactioneecti.e., b5, b6, b7, b8, b9, b10 0 in Eq.
2b1, b2, b3, and b4 areno longer estimates of main eects. Instead,
b1, b2, b3, and b4 now rep-resent conditional relationships between
the independent variables(epistemological beliefs) and the
dependent variable (motivational learn-ing strategies) in the
model. In other words, the coecient for E1 (b1)measures the
relationship between E1 and Sij, or the eect of E1 on Sij,,for
specic values of E2, E3, or E4that is, the magnitude of the
rela-tionship is conditional on specic values for the moderator
variables E2,E3, or E4. For example, the regression coecient b1 in
Eq. (2) measuresthe eect of E1 on Sij when E2=E3=E4=0 and the
meaning of the esti-mates of b2, b3, and b4 in Eq. (2) would be
analogous to b1 (Aiken andWest, 1991; Jaccard and Turrisi, 2003).
For some scales, such as certainLikert scales, the value of zero is
not a meaningful value. That mighthave been the case in the present
study. However, it is not, because thisstudy uses standardized
values for all variables; they are all mean-cen-tered, thereby
making zero the mean of the variables, as well as a mean-ingful
value on the transformed scales for all variables in this
study.
RESULTS
The following sections present the results of all the
correlation andregression analyses. The results for the bivariate
correlations provide anintroductory perspective on the
relationships under study, whereas theresults for the regression
analyses oer sets of controlled estimates ofthe eects of
epistemological beliefsand their interactionson stu-dents use of
various motivational learning strategies.
EPISTEMOLOGICAL BELIEFS AND MOTIVATIONAL STRATEGIES 743
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Results for the Bivariate Correlation Analysis
Table 1 presents the bivariate correlations between the four
epistemo-logical beliefs (independent variables in the study) and
all sixmotivational learning strategies (dependent variables in the
study), indi-cating the magnitude and statistical signicance for
each of the bivariatecorrelations estimated. These results provide
an introductory perspectiveon the relationships under study. The
statistically signicant correlationsin Table 1 can be classied as
being in the modest range (i.e., r
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TABLE1.EpistemologicalBeliefs
andMotivationalSelf-RegulatedLearningStrategies:Bivariate
CorrelationalAnalysis
MotivationalSelf-RegulatedLearningStrategies
IntrinsicGoal
Orientation
ExtrinsicGoal
Orientation
Task
Value
Self-Ecacy
Controlof
Learning
Test
Anxiety
EpistemologicalBeliefs
(1)
(2)
(3)
(4)
(5)
(6)
SimpleKnowledge(SK)
)0.27*
0.26*
)0.17*
)0.20*
)0.09
0.27*
Fixed
Ability(FA)
)0.27*
)0.17*
)0.37*
)0.25*
)0.39*
)0.01
Certain
Knowledge(CK)
0.05
0.03
0.03
0.03
0.10*
)0.03
QuickLearning(QL)
)0.05
)0.01
)0.14*
)0.09
)0.13*
0.01
N(samplesize)=
502,*=p
