The Motivational Effects of the Classroom Environment in Facilitating Self-Regulated Learning

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2005 27: 25Journal of Marketing EducationMark R. Young

The Motivational Effects of the Classroom Environment in Facilitating Self-Regulated Learning

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APRIL 2005JOURNAL OF MARKETING EDUCATION

The Motivational Effects of the Classroom Environmentin Facilitating Self-Regulated Learning

Mark R. Young

Students can be proactive and engaged or, alternatively, lackinitiative and responsibility for their learning. Self-regulatedlearning involves learning strategies and mental processesthat learners deliberately engage to help themselves learnand perform better academically. The results of this studyprovide empirical support for the theoretical relationshipsamong cognitive evaluation theory, achievement goal theory,and self-regulated learning strategies in the context of theclassroom. Superficial learning strategies were linked toextrinsic motivation, while intrinsic motivation determineddeep cognitive and metacognitive strategy usage. Perceivedautonomy, perceived competence, and task mastery orienta-tion mediated the classroom environment’s effect on intrinsicmotivation. These findings suggest that active application-oriented experience delivered by enthusiastic faculty, whoprovide high interaction, supportive feedback, and cleargoals that emphasize learning over grades, will increaseintrinsic motivation and the use of self-regulated learningstrategies. Teaching guidelines and pedagogical examplesfor enhancing intrinsic motivation are provided.

Keywords: motivation; self-regulated learning; classroomenvironment; goal orientation; cognitive evalua-tion theory

Assumptions that learning automatically occurs in associ-ation with simply attending class have largely disappeared.The Association to Advance Collegiate Schools of Busi-ness’s (AACSB 2003) new standards now explicitly include a‘student educational responsibility’ standard stating that stu-dents have an obligation to actively participate in their educa-tional experiences, and that learning outcomes should clearlyshow evidence of significant student engagement (http://www.aacsb.edu/accreditation/brc/standards-4-25.pdf, p. 52).Students’ increased involvement in their own learning pro-cess is thought to better prepare them for rapidly changingtechnologies and business paradigms by developing theirability to learn how to learn in preparation for careers thatdemand lifelong learning skills. Chonko (2003) suggested

that the most important thing marketing educators can do fortheir students is convince them to take complete responsibil-ity for their education. Taking responsibility for learningrequires active participation by the learners to initiate andcontrol their learning process along with supportive learningstrategies (Loranger 1994).

Meaningful learning involves the active process of inte-grating and organizing information, constructing meaning,and monitoring comprehension in order to develop a soundunderstanding of a subject matter (Meece, Blumenfeld, andHoyle 1988). Self-regulated learning refers to this active pro-cess and is defined as the deliberate planning and monitoringof the cognitive and affective processes that are involved inthe successful completion of academic tasks (Corno andMandinach 1983). Self-regulation involves self-monitoringand self-correction of three general aspects of learning: self-regulation of behavior, self-regulation of motivation, andself-regulation of cognition (Zimmerman 1995). Thus, a self-regulated learner is empowered and able to make sense of thelearning task, to create goals and strategies, and to implementactions to meet his or her goals within a learning context(Ridley et al. 1992). Equipping students with self-regulatoryabilities not only contributes to success in formal educationbut also promotes lifelong learning (Bandura 1993) andrepresents the highest form of cognitive engagement (Corno1986).

Traditional learning models, where the teacher prescribesand the students perform, do not support self-regulated learn-ing and, in fact, can deter it (Boekaerts 1997). Alternatively,creating classroom environments that actively engage stu-dents both experientially and cognitively have the potential ofstimulating the development of self-regulated learning.Existing marketing literature provides numerous examplesof classroom techniques to actively engage students, such asstudent management groups (Lilly and Tippins 2002),documented course participation (Peterson 2001), student-

25

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Mark R. Young is a professor of marketing in the Department of Marketing atWinona State University, Winona, MN 5598; e-mail: [email protected].

Journal of Marketing Education, Vol. 27 No. 1, April 2005 25-40DOI: 10.1177/0273475304273346© 2005 Sage Publications

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operated Internet businesses (Daly 2001), Web-based pro-jects (Siegel 2000), marketing trade shows (Taylor 1998), andexperiential learning exercises (Gremler et al. 2000).However, the existing literature has not offered a comprehen-sive model to understand the effects of these changes in theclassroom environment on the development and use of self-regulated learning skills. The purpose of this study is toenhance our understanding of how instructor-createdclassroom environments affect students’ motivation to learn,which in turn facilitates or diminishes the use of self-regulatedlearning strategies. Specifically, I address three basicresearch questions:

1. Do intrinsically motivated students employ different learn-ing strategies than extrinsically motivated students?

2. How does a student’s achievement goal orientation, percep-tion of competence, and sense of autonomy affect the degreehe or she tends to be intrinsically or extrinsically motivated?

3. How do social factors created by the classroom environmentinteract with motivational cognitions to facilitate self-regulated learning?

A relevant conceptual framework for investigating self-regulated learning and factors that facilitate or diminish theuse of these learning strategies is the social cognitive learningframework. Bandura’s (1986) social cognitive learningframework is based on three primary factors (the social envi-ronment, personal cognitive factors, and actual behavior) thatinteract so that people are both products and producers oftheir environments. Learning is viewed as knowledge acqui-sition through cognitive possessing of information, acquiredboth from being a part of society and from individual thoughtprocesses. Students’ perceptions of the social environment(classroom environment) and their personal cognitive factors

(self-regulated cognitions and self-regulated motivations) arehypothesized to affect the extent and nature of their behavior(self-regulated learning strategies) employed in an academicsetting. Figure 1 presents our conceptual model of the class-room environment and its effect on motivation and self-regu-lated learning within the social cognitive framework.

This article begins with a brief review of a continuum oflearning strategies that represents varying levels of self-regulated learning behavior. Next, hypotheses are developedusing the personal cognitive factors (self-regulated motiva-tion, self-regulated cognitions) and the social environment(classroom) antecedents. This is followed by an overview ofthe methodology and a presentation and discussion of thefindings. Finally, conclusions and implications are offered toenhance teaching and learning effectiveness.

Self-Regulated Learning Strategies

Students can be described as self-regulated learners to theextent that they use metacognitive, cognitive, and motiva-tional skills as part of their learning process (Zimmerman1989). Essential to self-regulated learning are the learningstrategies or mental processes that learners can deliberatelyrecruit to help themselves learn and understand somethingnew (Brandt 1988). A variety of different taxonomies forlearning strategies exist in the literature (Pintrich and Garcia1991; Weinstein and Mayer 1986); however, there are threegeneral levels of learning strategies that are important inunderstanding self-regulated learning. First, self-regulatedlearning includes strategies, referred to as metacognitivestrategies, that are used for controlling and executing yourown learning process. Metacognitive refers to one’s self-awareness about one’s cognitions and includes planning,monitoring, and regulating cognitions and factors in thelearning process (Pintrich and De Groot 1990; Somuncuoglu

26 APRIL 2005

FIGURE 1: A Social Cognitive Framework for Self-Regulated LearningNOTE: Arrows represent hypothesized relations.



and Yildirim 1999). Second, cognitive strategies are used toretrieve, encode, and organize new information and can besubdivided into two levels. Deep cognitive strategies facili-tate long-term retention through elaboration, organization,and critical thinking, resulting in a higher level of cognitiveengagement. Third, superficial cognitive strategies refer torehearsal strategies that help encode new information intoshort-term memory by repetition, highlighting, andmemorization (Pintrich 1988).

The particular learning strategies that students actually useare thought to be context-specific traits rather than generaltraits (Somuncuoglu and Yildirim 1999). Situationaldemands are the initiating factors that shape students’ cogni-tive and motivational orientations, which in turn lead to vari-ance in students’use of learning strategies (Ames and Archer1988). Considerable research indicates that use of self-regulated learning strategies (metacognitive and deep cogni-tive) is highly related to quality of learning, performance, andpositive academic outcomes (Ainley 1993; Das, Naglieri, andMurphy 1995; Hwang and Vrongistinos 2002; Pintrich andDeGroot 1990; Pintrich and Garcia 1991; Weinstein andMayer 1986; Zimmerman and Martinez-Pons 1986). A holis-tic perception of learning suggests that learners must have arepertoire of various learning strategies and know when touse each strategy most effectively (Weinstein et al. 1989).

HYPOTHESES DEVELOPMENT

Self-Regulation of Motivation

Students simply knowing about metacognitive andcognitive learning strategies are not enough to promote theiractive engagement in the learning process and their use ofself-regulated learning. Students must also be motivated toimplement and regulate appropriate learning strategies andbehaviors (Pintrich 1988, 1989). Theories of motivationattempt to explain factors mediating learning behavior in aquest for an understanding of background reasons for studenteffort and action (Somuncuoglu and Yildirim 1999). Motiva-tion may be defined as a driving force for students’ learninggoals, the activities they choose to engage in to reach thosegoals, and the intensity with which they engage in the activi-ties (Rothstein 1990; Woolfolk 1990).

Students can be moved to act by very different factors. Insome cases, it may be an inherent interest in the subject, a per-sonal commitment to excel, or because they value the activity.These factors contrast greatly with occasions when there is astrong external coercion, bribe, or fear of failure that drivesbehavior. These two basic types of motivational orientations,intrinsic and extrinsic (Harter 1981), are thought to havepotentially different consequences for self-regulated learn-ing. Intrinsic motivation refers to the performance of an activ-ity for the inherent satisfaction of the activity itself, whiledoing the activity in order to attain some separable outcome,

is extrinsic motivation. Intrinsically motivated students arethought to seek out challenges, to extend and exercise theircapabilities, and to explore and learn, compared with extrinsi-cally motivated students who seek rewards such as grades,ego enhancement, and social recognition (Ryan and Deci2000).

Students’motivated behaviors regarding choice of tasks aswell as their effort and persistence in academic tasks havebeen directly related to their level of intrinsic motivation(Ferrer-Caja and Weiss 2000, 2002). In addition, Pintrich andGarcia (1991) reported a very strong relationship (r = .73)between intrinsic motivation and the use of self-regulatedlearning strategies; in particular, students who had highintrinsic motivation were more likely to use metacognitivestrategies.

Extrinsically motivated students look for social approvaland reinforcement, prefer easy schoolwork, and depend onthe teacher for feedback and direction (Meece, Blumenfeld,and Hoyle 1988). Empirical studies have supported the con-tention that students who are mainly motivated by extrinsicfactors tend to engage in academic tasks that require superfi-cial cognitive strategies (Ames 1992; Dweck and Leggett1988; Pintrinch and De Groot 1990). Hwang andVrongistinos (2002) found both high and low academicachievers reported frequent use of extrinsic motivations suchas grades and rewards. Therefore, extrinsic motivation mayproduce positive academic outcomes but may do so at theexpense of self-regulated learning, making it even moreimportant to understand the effects of motivation in the learn-ing process. Therefore, I hypothesize the following:

Hypothesis 1a: Extrinsically motivated students will use superfi-cial learning strategies.

Hypothesis 1b: Intrinsically motivated students will use deepcognitive and metacognitive strategies.

Self-Regulation of Cognitions

The way students perceive and construe meaning from theclassroom environment that leads to individual differences inan intrinsic or extrinsic motivational response may be exam-ined with social cognitive theories of motivation. Two rele-vant and complementary motivation theories are achievementgoal theory (Nicholls 1989), which focuses on the effect oftask and ego involvement on motivation, and cognitive eval-uation theory (Deci and Ryan 1985), which examines howperceived competence (self-efficacy) and autonomy (self-determination) affect motivation. Perceived competence iscentral to both theories. However, achievement goal theoryviews competence as either differentiated or undifferentiatedability, whereas cognitive evaluation theory regards compe-tence as a human need to be satisfied. These two theories haveextensive application in educational psychology, tend to beinclusive of other motivational frameworks (Somuncuogluand Yildirim 1999), and may be the most influential in facili-

JOURNAL OF MARKETING EDUCATION 27



tating our understanding of cognitive factors that mediatemotivated behavior (Ntoumanis 2001), thus forming the the-oretical foundation for this investigation.

Achievement goal theory postulates that variation in goalorientations can lead to differences in motivations and behav-ior (Duda and Whitehead 1998). Goal orientations aredispositional tendencies, reflecting different ways ofcognitively processing outcomes of a given activity to formachievement criteria for defining success (Ntoumanis 2001).Nicholls (1989) proposed two primary goal orientations oftask mastery orientation and ego-social orientation. Situa-tional cues in the social environment may influence thedegree to which one perceives a differentiation in his or hercompetence as the primary achievement criteria. If the situa-tional cues emphasize competition, normative standards, andpublic evaluation, then achievement success is demonstratedby showing superior ability (differentiated competence) andan ego-social orientation is prevalent (Ntoumanis 2001). Peo-ple with high ego-social orientation, focusing on the relativeadequacy of their ability in defining success, demonstrateextrinsically motivated behaviors (Brunel 1999). Empiri-cally, Somuncuoglu and Yildirim (1999) found a correlationof .40 between an ego-social orientation and superficial cog-nitive strategy usage. However, when the situational cues donot emphasize differentiated competence but insteademphasize mastering the task itself (e.g., learning) or self-improvement, then a task mastery orientation is likely. Hightask mastery orientation is assumed to lead to intrinsicallymotivated behaviors, regardless of perceived competence,because these individuals do not judge their success on theirability to demonstrate superiority. Task orientation has posi-tively predicted intrinsic motivation in accordance to goal ori-entation theory (Dorobantu and Biddle 1997; Ntoumanis2001; Somuncuoglu and Yildirim 1999; Vlachopoulos andBiddle 1996) and, thus, should enhance the use of deep cogni-tive and metacognitive learning strategies. Therefore, I pro-pose the following hypotheses:

Hypothesis 2a: High ego-social orientation will be positivelyassociated with extrinsic motivation.

Hypothesis 2b: High task mastery orientation will be positivelyassociated with intrinsic motivation.

Cognitive evaluation theory focuses on environmentalfactors that affect the fundamental needs of competence andautonomy, which in turn account for the variability in intrin-sic motivation. Cognitive evaluation theory is a subtheorywithin Deci and Ryan’s (1985) self-determinationmetatheory that assumes that people have an inherent intrin-sic motivation that will be catalyzed when individuals are inconditions conducive toward its expression. Ryan and Deci(2000) provided a comprehensive summary of their theoriesand reported that intrinsic motivation has been stronglylinked with the satisfaction of the needs for autonomy and

competence. Autonomy is characterized by an internal locusof control and the perception that behaviors are freely chosen.Increasing perceived autonomy, by giving students somecontrol over their learning experiences, tends to increaseintrinsic motivation (Van Voorhis 1995). The perception ofbeing effective in the things we do and the feeling of masterycharacterizes competence. Harter (1981) reported that chil-dren who perceive themselves as academically competentgenerally develop an intrinsic motivation orientation, com-pared with children with low perceived competence whoexhibit an extrinsic motivation orientation. Perceived compe-tence was also found to be positively related to the use of cog-nitive strategies, metacognitive strategies, and persistency incompleting academic tasks (Pintrich and De Groot 1990).Consequently, I hypothesize the following:

Hypothesis 2c: High perceived autonomy will be positively asso-ciated with intrinsic motivation.

Hypothesis 2d: High perceived competence will be positivelyassociated with intrinsic motivation.

Social Environment

Vallerand (1997) proposed a framework in which thesocial environmental factors, cognitive mediators, motiva-tion, and consequences were separated in an effort to examinethe broader multivariate relationships underlying intrinsicmotivation. Ferrer-Caja and Weiss (2000, 2002) found empir-ical support for this framework with different student samplestaking courses both as requirements and as electives. Ferrer-Caja and Weiss specified the relevant social environment asconsisting of factors that created the motivational climate inthe classroom such as the learning climate, the performanceclimate, and teaching style. In their structural equation mod-eling analysis, they concluded that the greatest degree of sup-port was for the model that separated social environmentalfactors from personal cognitive factors, which led to intrinsicmotivation.

Classroom environments that enhance perceived auton-omy by providing student choices and opportunities for self-direction have been associated with increased intrinsic moti-vation, while extrinsic rewards were found to undermineintrinsic motivation (Deci 1975). Results from a comprehen-sive meta-analysis (Deci, Koestner, and Ryan 1999) suggestthat offering tangible rewards contingent on task perfor-mance will undermine intrinsic motivation because of theexternal perceived locus of causality and the diminishedsense of self-determination. Evidence also shows that teach-ers who are autonomy supportive instill greater levels ofintrinsic motivation (Deci, Nezlek, and Sheinman 1981;Flink, Boggiano, and Barrett 1990), while students taught in amore controlling environment lose initiative and learn lesseffectively (Amabile 1996; Utman 1997).

Recent articles in the marketing education literature pro-vide examples of designing the classroom environment (Lilly

28 APRIL 2005



and Tippins 2002) and using teaching techniques (Peterson2001) specifically to enhance student autonomy, leading togreater intrinsic motivation and participation. Creating anactive learning environment, as compared to the traditionalclassroom, has been linked to higher student motivation (Gar-cia and Pontrich 1996; Stipek, Salmon, and Givven 1998) andenhanced intellectual development (McKeachie 1990).

Students who perceived their classroom environment asemphasizing competition and norm-referenced criteriareported adopting a social comparison as a means to assesstheir success. In contrast, students who perceived theirclasses focused on learning used self-improvement criteria(task mastery) as their success indicator (Ferrer-Caja andWeiss 2002). This same study also reported that teachers per-ceived as being flexible in allowing students to set their owngoals and organize their activities were viewed as enhancingstudents’ self-determination. Data from this study, and theirprevious study (Ferrer-Caja and Weiss 2000), support amodel in which goal orientation, perceived autonomy, andperceived competence mediate the influence of social factorson motivation. The mediating influence of personal cognitivefactors on the classroom-environment’s effect on motivationis consistent with the two social cognitive motivation theoriespresented above, in addition to the social cognitive learningframework modeled in Figure 1. Therefore, I hypothesize thefollowing:

Hypothesis 3a: The effect of classroom-environmental factorson motivation will be mediated by achievement goalorientation.

Hypothesis 3b: The effect of classroom-environmental factorson motivation will be mediated by perceived autonomy andcompetence.

METHOD

Data Collection

The data were collected midway through spring semester2003 by administering an in-class survey to each section ofPrinciples of Marketing, Market Analysis, Marketing Plan-ning, and Marketing Management, which are the requiredcore courses in the marketing curriculum at a midwestern 4-year public university. The sequence of courses is designed tosystematically expose students to a variety of instructionalmethods and cover the traditional marketing curriculum in anintegrated manner. Market Analysis is structured aroundgroup research projects, Marketing Planning uses Internetresearch to analyze cases, and Marketing Management isstructured around decision making based on computer simu-lations. In addition, all classes require written communica-tions and oral presentations. Class size for Principles of Mar-keting is approximately 45 students per section, while theother three courses are limited to 25 students per section andare team taught.

A typical absenteeism rate on the day of the survey pro-duced a response rate of approximately 88%, yielding aneffective sample of 257. The four-course sequence preventedduplicative responses since students may take only one of thefour classes in a given semester. The distribution of the com-pleted sample across classes was Principles of Marketing(four sections), n = 168 (65%); Market Analysis (two sec-tions), n = 36 (14%); Marketing Planning (two sections), n =38 (15%); and Marketing Management (one section), n = 15(6%). Demographically, the sample can be described as tradi-tional undergraduates, 49% female, 31% marketing majors,and 23% marketing minors. In addition, the Principles ofMarketing students closely mirrored the College of Busi-ness’s distribution of majors (accounting 19%, businessadministration 42%, marketing 18%, and other business21%). The grade point average for the sample was 3.0, and thenumber of credit hours completed ranged from 19 to 128,with the average number of credits of 70. The researcher/author was not an instructor in any of the courses comprisingthe sample. In summary, the sample seems to represent typi-cal undergraduate students at various stages of completing atraditional marketing curriculum.

Measures

Students responded to a four-page self-report question-naire with scales for each of the major variables groupedtogether with individual items randomly ordered within thescale. A variety of response anchors, scales, and number ofresponse points were used to reduce halo effect andmulticollinearity. For consistency, scales were modified sothey were presented in the first person and referenced the spe-cific marketing class being taken.

Self-regulated learning. Self-regulated learning is definedand measured as a composite index (a linear sum of a set ofmeasurements) composed of three levels with sevensubstrategies. A formative indicator specification was chosenfor the measurement model to represent the causal priorityrunning from the measured indicators to the latent constructself-regulated learning. If any one of the seven subscalesincreases, self-regulated learning would increase; conversely,if a student’s self-regulated learning increases, this would notbe accompanied by an increase in all seven subscales.

The construction of the index first proceeded with a clearspecification of the scope of the latent variable. Self-regulatedlearning is conceptualized as three general types of learningstrategies with seven substrategies: (a) superficial cognitive(rehearsal), (b) deep cognitive (elaboration, organization, andcritical thinking), and (c) metacognitive (planning, regulat-ing, and monitoring) (Hwang and Vrongistinos 2002;Somuncuoglu and Yildirim 1999). Next, items used as indi-cators for each of the substrategies were specified to ensurecoverage of the entire scope of self-regulated learning. TheMotivated Strategies for Learning Questionnaire (Pintrich




and De Groot 1990), the College Students’ Self-RegulatedLearning Questionnaire (Hwang and Vrongistinos 2002),and items from Somuncuoglu and Yildirm’s (1999) Self-Regulated Learning Questionnaire formed the pool of itemsfor specifying the domain of the construct. Items were elimi-nated that pertained to subscales not included in our defini-tion of self-regulated learning such as test anxiety, effort man-agement, and persistence, as well as duplicative items acrossscales. The remaining items were categorized into the sevensubscales of self-regulated learning. Nonredundant itemswere then selected, by researcher judgment, in an effort toensure that each subscale was adequately defined. Each of themore commonly used substrategies (rehearsal, organization,and elaboration) were measured with 3 items, while thehigher level learning strategies were composed of 2 items,each creating a 17-item index, which is presented in Table 1.The 17 items defining self-regulated learning strategies wererandomly ordered, and a 5-point scale (never, rarely, some-times, often, and always) was used to indicate how often thestudent used a given learning strategy in his or her specificmarketing course. The above process seems consistent withDiamantopoulos and Winklhofer’s (2001) index creationguidelines. In addition, from a practical data collectiondemand perspective, this process also reduced an excessivenumber of indicators to a more manageable level.

The suitability of this formative index was then examined.First, the issue of multicollinearity among the items wasassessed. Each indicator should provide a unique influenceon the latent variable with minimal redundancy since the for-

mative measurement model is based on a multiple regression.This is in contrast to the traditional internal consistency mea-sures used with reflective measures, which are inappropriatefor assessing indices (Bagozzi 1994). Examining thepairwise correlations did identify one relatively high correla-tion; however, both the correlated items were retained forconceptual reasons. In addition, the variance inflation factorsranged between 1.2 and 1.8, suggesting the degree ofmulticollinearity is acceptable based on the less-than-10threshold suggested by Kleinbaum, Kupper, and Muller(1988).

The next issue is to assess the external validity of the indexby examining the theoretical relationships of the constructwith other constructs in its nomological net. The relationshipbetween self-regulated learning and academic performancehas been previously established in the literature (Ainley1993; Das, Naglieri, and Murphy 1995; Hwang andVrongistinos 2002; Pintrich and DeGroot 1990; Pintrich andGarcia 1991; Weinstein and Mayer 1986; Zimmerman andMartinez-Pons 1986). In this study, seven different measuresof self-reported performance were significantly correlated (r= .19 to .36, p < .00) with the self-regulated learning index,thus suggesting a degree of external validity.

The final analysis of this index examined the usefulness ofthe subscales within the overall self-regulated learning index.If the intrasubscale item correlations are systematicallyhigher than the intersubscale item correlations, it suggests thejustification of subscales (Clark and Watson 1995).Intrasubscale correlations (.36 to .44) were substantially

30 APRIL 2005

TABLE 1Measures of Self-Regulated Learning Strategies

Strategy Subscale Formative Indicators

Superficial Rehearsal I try to memorize everything that might be asked on the exam.I memorize lists of important terms and concepts.I read my class notes and the course readings over and over again so I will remember them.

Deep cognitive Organization I go over my class notes and make an outline of important concepts and ideas.I organize the information from all my class notes and the readings into simple charts,

diagrams, or tables.I write brief summaries of the main ideas and concepts from the readings and the lectures

Elaboration I try to make connections between the readings and the concepts from lectures in order tocomprehend the course as a whole.

I try to relate concepts and ideas from this course to those in my other courses wheneverpossible.

I try to apply ideas from course readings to other class activities such as lecture and discussion.Critical Thinking I think about possible alternatives whenever I hear an assertion or conclusion in this class.

I try to decide if there is supporting evidence for conclusions, interpretations, or theories thatare presented.

Metacognitive Planning I set goals for myself in order to direct my study activities.I skim through the chapter to see how it is organized before I read it thoroughly.

Monitoring If I become confused about something I read, I go back to my previous notes and sort it out.I try to determine which concepts I don’t understand well.

Regulating I ask myself questions to make sure I understand the material.I try to determine the way I study according to the course requirements and the instructor’s

teaching style.

NOTE: All items scored on a 5-point scale ranging from 1 (never) to 5 (always).



higher than intersubscale correlations (.13 to .22), with theexception of the Planning subscale, suggesting the usefulnessof subscales within the overall self-regulated learningconstruct.

Motivation. Intrinsic and extrinsic motivations were alsoconceptualized and measured as formative indicators com-posed of 4-item composite indices. Intrinsically motivatedbehaviors are driven by satisfaction, enjoyment, excitement,and/or challenge of engaging in the activity and tap Deci andRyan’s (1985) definition of intrinsic motivation to know, toaccomplish things, and to experience stimulation. The Aca-demic Motivation Scale (Vallerand et al. 1992) provided theindicators (Table 2) for intrinsic motivation. The indicatorsallowed each of the above definitional aspects to be repre-sented in the index. The interitem correlations (r = .43 to .65)of this index are relatively high; however, the variance infla-tion factors (1.7 to 2.1) are below the cutoff of 10. Even withsome redundancy among indicators, conceptual consider-ations suggest all four items remain part of the intrinsicmotivation index.

Compared with intrinsic motivation, extrinsically moti-vated behaviors are undertaken for reasons other than theactivity itself, such as external rewards, benefits, punish-ments, or obligations (Deci and Ryan 1985). This studydefined extrinsic motivation as externally regulated behav-iors performed to satisfy an external demand or reward con-tingency. Indicators for extrinsic motivation were alsoselected from the Academic Motivation Scale with an itemrepresenting each of the four external reasons specifiedabove. Correlations and variance inflation factors amongthese items were low (.05 to .35), indicating multicollinearityshould not be an issue.

Perceived Autonomy is the degree to which studentsbelieve they have control and choice of their behaviors (Deciand Ryan 1985). Zhou (1998) presented three dimensions of

autonomy: choice, process, and outcome. The present studyfocuses on the more global level of autonomy, the outcomedimension, involving students’ perception of the control theyhave over factors that affect their final grade in the course.This notion of perceived autonomy is conceptualized as hav-ing reflective indicators and, therefore, a multi-item scale isused to measure the construct. Students responded to the fol-lowing two items on a 7-point strongly agree/disagree scale:“My marketing grade is determined by things I cannot control(luck, other students, instructor)” (reversed coded), and “Mymarketing grade reflects my ability and effort, and I can con-trol how well I do in this class.” Coefficient alpha for thesetwo items is .69.

Perceived Competence represents the perceived confi-dence students have in their competence or their ability toaccomplish some behavior. The judgment of one’s capabilityto execute given types of performances is central in the mea-surement of the construct. Bandura’s (2001) guide for con-structing self-efficacy scales was used to develop this scalefor general classroom activities.

The scale was patterned after examples of efficacy scalesprovided in Bandura’s guide with the inclusion of items rep-resenting the classroom domain. Five items sample thedomain of typical classroom performance–related behaviorsand are presented in Table 3. Students indicated confidencethey could perform each of the behaviors on a 10-point scaleanchored with cannot do at all to certain can do. The instruc-tions were the following: “Rate your degree of confidencethat you have the ability to successfully complete . . . on a reg-ular basis throughout this Marketing course.” Bandura (2001)recommended assessing the scales’ internal consistency withitem analysis and Cronbach’s alpha. This analysis produced aCronbach’s alpha of .81, and the item analysis indicated theremoval of any item would reduce the overall alpha level, sug-gesting good internal consistency. In addition, the scale’sexternal validity should provide evidence that people whoscore high on perceived competence differ in distinct ways, asspecified by theory, from those who score low (Bandura2001). Perceived competence in one’s ability to successfullyperform classroom tasks and behaviors is theoretically asso-ciated with actual classroom performance (Gist and Mitchell1992). A strong positive correlation (r = .43, p < .00) wasfound between the sum of the five-item Perceived Compe-tence Scale and the sum of the seven-item performance mea-sures. In addition, statistically significant positive correla-tions were observed between each of the individualcompetence items and the performance measures. The aboveanalysis indicates that higher perceived competence is relatedto higher classroom performance, which is consistent withtheory, therefore suggesting a degree of external validity.

Achievement Goal Orientations represent a student’sachievement criteria or what he or she desires from taking acourse. Two contrasting goal orientations, conceptualized byMeece, Blumenfeld, and Hoyle (1988), represent task


TABLE 2Measures of Motivation

Formative Indicators

Your reasons for participating in this Marketing course . . .Intrinsic motivation

I will have the satisfaction of improving my personal knowledgeand skills.

I will have a sense of personal accomplishment.I will have completed exciting and challenging class activities.I will have enjoyed learning about an interesting subject.

Extrinsic motivationI think the required time will have a negative effect on my social

life and other grades.I will have simply completed a required course, nothing more.I will receive a good grade that will help my GPA.I will make other people proud of me.

NOTE: All items scored on a 10-point completely agree/disagreescale. GPA = grade point average.



mastery orientation and ego-social orientation. Task masteryorientation represents achievement as mastery and under-standing with an emphasis on learning or self-development.Ego-social orientation emphasizes achieving high grades andoutperforming others for social approval and/or ego enhance-ment. A 7-point strongly agree/disagree scale was used forstudents to respond to items adapted from the MotivatedStrategies for Learning Questionnaire (Pintrich and De Groot1990) and are similar to items found in scales used by Park(1992), Meece and Holt (1993), and Nolen (1986).

In the beginning of the questionnaire, students were asked,“Success in this class: Think of when you feel most success-ful in this Marketing class, and indicate your degree of agree-ment or disagreement with each of the following statements.”Table 3 presents the six items representing the two goal orien-tations along with factor loadings and coefficient alphas.Although the coefficient alphas are lower than desired, thetwo dimensions were produced with principal componentsfactor analysis, and each item loaded on its respectivedimension.

The three items for the ego-social subscale were reversecoded, and then all six items were summed, creating one mea-sure for achievement goal orientation. High scores representtask orientation that was defined as scoring high (agreeingwith the three task items) on task statements and low (dis-agreeing with the three ego-social items) on ego-social items.Ego-social orientation represented those students who scored

high on ego-social items and low on task-oriented items andare represented by low scores on this Goal Orientation Scale.Approximately 20% of the sample would be considered hightask mastery, 20% high ego-social orientated, 58% as highon both orientations, and the remaining 2% as low on bothorientations.1

Classroom Environment was conceptualized based on theLearning and Performance Orientations in Physical Educa-tion Classes Questionnaire (Papaioannou 1994) to assess theperceived motivational climate. Items from the above scalewere selected and modified to represent the contrasting learn-ing climates conceptualized as the tradition paradigm (pas-sive learning approach) versus the new paradigm (activelearning approach) (Wright, Bitner, and Zeithaml 1994).Three general subcategories for classroom environment, con-sisting of the learning climate, the performance climate, andthe instructor climate, were created similar in categorizationto those reported in the study by Ferrer-Caja and Weiss(2002). A 7-point semantic differential scale format was usedto present pairs of statements representing the twocontrasting paradigms for the classroom environment.

Learning climate, performance climate, and instructor cli-mate were considered as three separate scales as presented inTable 4. Principal components analysis with varimax rotationproduced three factors with the expected loadings and 67% ofthe variance explained. In addition, the intrascale correlations(.40 to .64) were substantially higher than the interscale cor-

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TABLE 3Measures of Cognitions

Standardized Coefficient VarianceConstruct and Scale Items Loadings Alpha Extracted

Perceived Autonomy .69 .67My marketing grade is determined by things I cannot control (luck, other students, instructor).

(reverse coded) .816My marketing grade reflects my ability and effort, and I can control how well I do in this class. .816

Perceived Competence .81 .58Rate your degree of confidence that you have the ability to successfully complete the following

on a regular basis throughout this Marketing course.In-class activities, discussions, and attendance .669Group work or team assignments .770Individual requirements, papers, or assignments .820Formal evaluations like quizzes and exams .771The understanding of marketing concepts and applications .774

Achievement Goal OrientationsSuccess in this class: Think of when you feel most successful in this Marketing class

Task Mastery Orientation .75 .66I feel most successful in this course, when I learn new skills. .867To me, comprehending the course content well is more important than the grade I get. .755I want to learn and understand as much as possible in this course. .818

Ego-Social Orientation .58 .52I aim at accomplishing this course with a high grade because I want to improve my GPA. .703If I finish this course with a high grade, I will have shown my ability to others. .748It is important to me to do better than other students in this class. .704

NOTE: Perceived Competence scored on a 10-point certain can/cannot do at all scale, Perceived Autonomy and Goal Orientation scored on 7-point strongly agree/disagree scales, and Goal Orientations scored on a 10-point completely agree/disagree scale.GPA = grade point average.



relations (.05 to .12), supporting the treatment of separatescales. The mean interitem correlations for each of the threescales (.64, .44, .40) seem appropriate for these constructs,even though the coefficient alphas were .78, .65, and .67,respectively. Clark and Watson (1995) argued that the meaninteritem correlation is a more useful index for internal con-sistency than coefficient alpha, especially if one is to avoidthe “attenuation paradox” in which high item redundancy is atthe expense of the breadth of the construct.

Method of Analysis

The proposed model and the hypothesized relationshipswere examined with path analysis. Path analysis is a methodthat allows the study of both direct and indirect effects ofindependent variables on dependent variables (Dillion andGoldstein 1984). In this case, the classroom environment ishypothesized to indirectly affect self-regulated learningbehaviors through its direct effect on motivational cognitions.Direct effects are estimated with standardized regressioncoefficients, and indirect effects are the product of the respec-tive direct path coefficients.

Given that the proposed model includes multiple depend-ent variables that are significantly correlated as seen in Table5, performing separate regression analyses would not incor-porate the information provided by the interrelationshipsamong these dependent variables. Therefore, multivariatemultiple regression analysis was performed using the generallinear model multivariate procedure in the Statistical Packagefor the Social Sciences software. First, the dependent vari-ables were examined for departures from multivariate nor-mality by performing Kolmogorov-Smirnov’s (Lilliefors sig-nificant correction) test of normality and by examiningnormal Q-Q plots. The results (all significant values were p =.000) of these tests suggest no departures from normality. Inaddition, Box’s test of equality of covariance matrices of thedependent variables across groups (p = .661) and Levene’stest of equality of error variances across groups for each of the

dependent variables (all greater than p = .05) could not berejected; therefore, it seems reasonable to proceed with themultivariate analysis.

Scatter plots of independent variables versus dependentvariables revealed no departure from the linearity assumptionof path analysis. Error terms are assumed to be uncorrelated,which is reasonable in this analysis based on Durbin-Watsonstatistics (1.92 to 2.02) and visual examination of standard-ized residual plots (Dillion and Goldstein 1984). Typically,variance inflation factors greater than 10 and tolerance limitsless then .1 would indicate multicollinearity (Mendenhall andSincich 1996). No evidence of multicollinearity was discov-ered by examining the variance inflation factors (highest was1.5) and the tolerance limits (lowest .66) for each of theregression equations. In summary, the data appear to meet theconditions and assumptions for effective use of path analysis.

Previous research has provided mixed results for theeffects of gender and its relationship with goal orientation andmotivational tendencies. Ferrer-Caja and Weiss (2002)reported that women have higher task mastery orientation


TABLE 4Measures of the Classroom Environment

Construct and Scale Items Standardized Coefficient VarianceLoadings Alpha Extracted

Instructor Climate .67 .61Enthusiastic instructor versus apathetic instructor .783High student-instructor personal interaction versus low student-/instructor interaction .777Informative, supportive positive feedback versus graded comparative corrective feedback .775

Learning Climate .78 .82Traditional learning, lecture, and readings versus active learning, hands-on experiences .91Textbook focused, exam oriented versus real-world focused, application oriented .91

Performance Climate .65 .56Individual performance determines grades versus group performance determines grades .833Clear course goals and expectations versus unspecified course goals and expectations .793Learning the material is emphasized versus earning a grade is emphasized .596

NOTE: Seven-point semantic differential scale format.

TABLE 5Correlations Among Self-Regulated Learning Strategies

1 2 3 4 5 6 7

1. Rehearsal2. Organization .4093. Elaboration .347 .3624. Critical thinking .245 .414 .3195. Planning .291 .389 .335 .3646. Regulating .248 .331 .550 .378 .3947. Monitoring .350 .386 .468 .268 .368 .463

M 10.15 8.83 10.67 5.22 6.26 6.59 7.25SD 2.41 2.03 1.89 1.42 1.49 1.39 1.41Number of items 3 3 3 2 2 2 2

NOTE: N = 257. All coefficients are significant at the .000 level.



than men; however, Ntoumanis (2001) and Cokley et al.(2001) did not find significant effects of gender. In our study,gender (130 men and 127 women) was included as a controlvariable in each of the regressions. I found a significant coef-ficient for gender in predicting goal orientation, suggestingthat women are higher in task mastery goal orientation; how-ever, no relationship was found with intrinsic or extrinsicmotivation.

In addition to controlling for gender, grade point averageand total completed credit hours were used to control for gen-eral intelligence and academic achievement. Prior researchhas suggested that goals and orientations may be related toschool performance (Hagborg 1992; Licht and Dweck 1984).Higher grade point averages were found to be related tohigher levels of perceived competence and higher levels ofego-social orientations in our analysis. This may indicate thatobtaining higher grades is a type of feedback that raises one’sperception of competence and that students who focus ongrades (ego-social oriented) actually do accomplish theirgoals and outperform those students who are task masteryoriented. Higher credit hour completion was related to taskmastery orientation and intrinsic motivation. This relation-ship probably reflects that students with higher credit hoursare taking elective courses in their major compared withunderclassmen taking Principles of Marketing as a requiredcourse.

RESULTS AND DISCUSSION

The path analysis diagram and coefficients are displayedin Figure 2, and the total effects of the independent variablesare presented in Table 6. All paths included in the model aresignificant at the .05 level. The first set of hypotheses speci-fies the relationships between extrinsic and intrinsic motiva-tion and self-regulated learning strategies. As hypothesized,extrinsic motivation has a direct path to rehearsal (superficiallearning strategies) and has no paths to deeper cognitive learn-ing or metacognitive learning strategies; therefore, Hypothesis1a is supported. Significant direct path coefficients betweenintrinsic motivation and each of the self-regulated learningstrategies provide support for Hypothesis 1b. The above find-ings are consistent with the literature (Meece, Blumenfeld,and Hoyle 1988; Nolen 1988; Pintrich and De Groot 1990)and provide a very significant insight for marketing educatorsand our efforts to instill self-regulated learning skills. If stu-dents are highly motivated by external rewards and competi-tion, it may result in the use of short-term rehearsal strategiesthat focus on rote memorization and minimally meet therequirements necessary for the rewards at the expense of inte-grating material and higher order learning. However, whenstudents believe the subject matter is interesting and impor-tant, they are more likely to use higher level learning strate-gies and become more cognitively engaged.

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FIGURE 2: Path Diagram of Self-Regulated Learning StrategiesNOTE: N = 257, all coefficients are significant at the .05 level. For diagram clarity, correlations among the seven learning strategies are presentedin Table 5.



The direct path coefficients to each of the deep cognitiveand metacognitive strategies are about the same magnitude(.33 to .36), indicating the relatively equal importance ofintrinsic motivation to each of these learning strategies. It isalso noteworthy that the coefficient from intrinsic motivationto the superficial rehearsal strategy is significantly smaller(.20) than all of the deeper learning strategy paths. The per-centage of variance explained, or adjusted R2, ranged from.12 to .28. The variance explained in these regressions wasrelatively small; however, it is consistent with similar studiessuch as Ntoumanis (2001), who reported an average R2 of .16for predicting motivation with goal orientations and per-ceived competence, and Pintrich and De Groot’s (1990)reported R2 of .22 obtained when predicting academic perfor-mance with self-efficacy and self-regulation. Thus, theanswer to our first research question is that intrinsically moti-vated students do use different learning strategies than extrin-sically motivated students, and, clearly, intrinsic motivationis the key for meaningful learning by facilitating the use ofself-regulated learning strategies.

Goal orientation directly affects extrinsic motivation witha negative path coefficient (–.32) and positively affects intrin-sic motivation (.29). Recall that the Goal Orientation Scalerepresents task mastery with high scores, indicating that hightask mastery leads to high intrinsic motivation and that lowscores represent high ego-social orientations leading to highextrinsic motivation. Thus, Hypotheses 2a and 2b aresupported.

An R2 of .32 was estimated for intrinsic motivation withperceived autonomy and perceived competence as the signifi-cant independent variables with positive regression coeffi-cients, thus supporting Hypotheses 2c and 2d. Perceivedautonomy has the greater direct effect (.27) on intrinsic moti-vation as compared with perceived competence (.22), whichis consistent with self-determination theory (Deci and Ryan1985). Students who perceived they had the capability to per-form well showed higher intrinsic motivation and reportedgreater use of self-regulating strategies, which correspondswith Pintrich and De Groot’s (1990) findings.

These results provide insight into our second researchquestion regarding factors that influence the tendency to beintrinsically motivated versus extrinsically motivated. Stu-dents who are task mastery oriented and have a high sense ofperceived autonomy and perceived competence tend to beintrinsically motivated and, thus, make greater use of self-regulated learning strategies. This is in sharp contrast to stu-dents who have a high ego-social orientation, which leads toextrinsic motivation and superficial learning strategies.

Next, I examined the factors that help explain the environ-mental conditions and personal cognitions that lead to extrin-sic and intrinsic motivation. It should be noted that the aboveanalysis established the existence of direct path coefficientsbetween the three proposed mediating variables (goal orien-tation, autonomy, and competence) and the dependent vari-ables (intrinsic and extrinsic motivation). In addition, signifi-cant path coefficients were calculated between the classroomenvironment variables and the three proposed mediating vari-


TABLE 6Total Effects on Self-Regulated Learning and Motivation

Dependent Variables

Independent Variables Rehearsal Organize Elaborate Critical Monitor Plan Regulate

Extrinsic motivation .13Intrinsic motivation .20 .33 .36 .33 .36 .33 .35Goal orientation –.19 .10 .10 .10 .10 .10 .10Autonomy .05 .09 .10 .09 .10 –.06 .10Competence .04 .07 .08 .07 .08 .07 .21Instructor –.05 .02 .02 .02 .02 .02 .02Learning –.02 .04 .05 .04 .05 .15 .07Performance .03 .09 .05 .09 .05 .20 .07R2 .26 .14 .21 .12 .23 .16 .28

Extrinsic Intrinsic

Goal orientation –.32 .29Autonomy .27Competence .22Instructor –.07 .07Learning –.05 .13Performance .13R2 .16 .32

NOTE: N = 257. All coefficients are significant at the .05 level.



ables as seen in Figure 2. Finally, no significant direct pathcoefficients between the classroom environment variablesand the dependent motivation variables were observed whenthe above paths were controlled. These results meet the crite-ria for establishing the functioning of mediating variables(Baron and Kenny 1986) and indicate that achievement goalorientation mediates the effect of instructor climate and learn-ing climate on both extrinsic and intrinsic motivation, provid-ing support for Hypothesis 3a. In addition, perceived auton-omy and perceived competence mediate the effect ofclassroom-environmental factors’ learning climate and per-formance climate (no direct paths to intrinsic motivation) onthe dependent variable intrinsic motivation, supportingHypothesis 3b.

To address the third research question, I examine the indi-rect effects of the classroom climate variables on the learningstrategies. The superficial learning strategy rehearsal is indi-rectly influenced by all three climate variables through bothextrinsic and intrinsic motivation. Students reported less useof superficial learning strategies (overall indirect effect of–.05) when they were taught by enthusiastic instructors whoprovided supportive feedback. In addition, an active application-oriented learning climate also reduces the use of superficiallearning strategies as indicated by an indirect effect of –.02.However, an increased use of superficial learning strategies(total indirect effect of .03) was found in performance cli-mates where there were clear learning goals and where gradeswere determined by an individual’s performance. This maybe due to an overemphasis on performance expectations andgoal accomplishment, thereby focusing too much on narrowperformance requirements.

Given that intrinsic motivation has approximately thesame direct effect on each of the deep cognitive andmetacognitive learning strategies, I discuss the indirecteffects of the classroom climate on intrinsic motivation. Theenthusiastic, supportive, and highly interpersonal instructorincreases task mastery orientation and provides an indirecteffect of .07 on intrinsic motivation. An active learning envi-ronment positively affects goal orientation, perceived auton-omy, and perceived competence, thereby indirectly affectingintrinsic motivation (.13). The performance climate also pro-vides a total indirect effect on intrinsic motivation of .13.These findings indicate that to maximally affect the use ofself-regulated learning strategies, a combination of activelearning experiences with clear learning expectations, deliv-ered by a supportive instructor, are required. This combina-tion appears to decrease superficial learning strategies inaddition to increasing intrinsic motivation, leading to the useof higher level learning strategies.

In addition to the above expected paths, severalnonhypothesized direct paths to learning strategies were alsosignificant. The metacognitive strategy planning had a directpath from performance climate and a negative direct pathfrom perceived autonomy. It may be that when there is a

highly structured performance climate, in terms of clearlydefined goals and expectations, it assists students in settingtheir goals and planning their own learning activities. How-ever, the more students feel they can control how well theycan do in the class, the less they feel they need to set goals todirect their studies. The path from perceived competence toregulated learning indicates that students with a high sense ofcompetence can adjust their learning strategies to fit theinstructor and course requirements, and the students also takesteps to make sure they understand the material. Not surpris-ing is a negative direct path from goal orientation to rehearsalstrategies that complements the indirect path through extrin-sic motivation and emphasizes the relationship between highego-social orientation and rehearsal strategies.

The interpretation of these findings is that classrooms fea-turing real-world active learning, providing clear learninggoals, and emphasizing individual performance will enhancestudents’perception of their perceived autonomy and compe-tence and, thus, increase intrinsic motivation and use of self-regulation learning strategies.

CONCLUSIONS AND IMPLICATIONS

The results of this study provide empirical support for thetheoretical relationships within and between cognitive evalu-ation theory, achievement goal theory, and self-regulatedlearning strategies in the context of the classroom. Superficiallearning strategies were linked to extrinsic motivation, whileintrinsic motivation determined deep cognitive andmetacognitive strategy usage. In accordance with cognitiveevaluation theory, intrinsic motivation was enhanced whenstudents perceived they were competent and when they hadcontrol over their performances. All three aspects of theclassroom environment indirectly influenced the use of learn-ing strategies through the motivational components. Theresults suggest that active application-oriented experiencedelivered by enthusiastic faculty members who provide highpersonal interaction, along with supportive feedback, cleargoals, and expectations emphasizing learning over gradeswill increase intrinsic motivation and the use of self-regulatedlearning strategies. These findings are supportive of market-ing education’s trend toward active experiential learning(Frontczak 1998). In addition, the results are consistent withthe American Association for Higher Education’s statementof principles for good undergraduate education. These sevenprinciples assert that good educational practice (1) encour-ages active learning, (2) encourages student-faculty contact,(3) gives prompt feedback, (4) communicates high expecta-tions, (5) emphasizes time on task, (6) encouragescooperation among students, and (7) respects diverse talentsand ways of learning (Chickering and Gamson 1987).

From a marketing educator’s perspective, the theories andempirical findings lead to the following guidelines forenhancing teaching effectiveness. First, instructors must be

36 APRIL 2005



aware that all aspects of the classroom affect motivation andlearning strategies. Therefore, careful planning must be doneto ensure the overall desired effects. For example, providingactive learning exercises that stress competitive performance(e.g., computer simulations) may result in an unexpectedoverall effect that increases extrinsic motivation and superfi-cial learning. Ferrer-Caja and Weiss (2002) suggested struc-turing the class in such a way as to emphasize the importanceof the learning process, to encourage participation, and toincorporate effort and improvement in the evaluation.

Second, metacognitive strategies may be specificallyemphasized by incorporating self-study or self-regulatedcourse activities that raise the students’ awareness of plan-ning (set learning goals), monitoring (self-testing), and regu-lating (determine best way to learn) (Somuncuoglu andYildirim 1999). Examples of classroom assignments consis-tent with these recommendations are Celuch and Slama’s(1998) consumer behavior critical thinking assignments thatare designed to stimulate self-regulated learning. The learn-ing benefits of these assignments have been favorablyassessed with student surveys (Celuch and Slama 2000) andexperimentally controlled feedback (Celuch and Slama2002).

Third, intrinsic motivation may be enhanced by increasingperceived autonomy, perceived competence, and/or task mas-tery goal orientation. Stressing the importance of the learningprocess, providing choice and allowing opportunities forself-direction have been found to enhance intrinsic motiva-tion by increasing the feeling of autonomy (Deci and Ryan1985). Providing numerous opportunities to practice, learn,and master the task at hand will enhance intrinsic motivationby developing students’ competencies (Ferrer-Caja andWeiss 2002). Kilpatrick, Hebert, and Jacobsen (2002) usedthe concepts from self-determination theory to develop thefollowing guidelines to assist in creating programs that willinfluence both the intensity and direction of effort to helpfacilitate increased participation in motivated behaviors.Implementing these guidelines in the classroom shouldincrease students’ intrinsic motivation and lead to greater useof self-regulated learning strategies. Following each guide-line are specific examples from the marketing educationliterature of pedagogies that could be used to implement thatparticular guideline.

• Give positive feedback that supports the development ofcompetence and task mastery orientation, whereas negativefeedback can reduce the sense of competence.

Examples of assignments that incorporate performance-enhancing feedback are provided by Celuch and Slama(1998). Their assignments clearly state comprehensive crite-ria and standards for judging the elements of critical thinkingassignments along with explicit performance levels forassigning grades. Students’ability to assess and continuously

improve their own thinking is enhanced by receiving timelyand continuous feedback based on these standards, as well asparticipating in the evaluation process themselves. In addi-tion, they stress the relevance of the assignments and thethinking process and allow opportunity for students to makechoices in the examples they chose to write about in theindividual and group assignments.

• Provide activity choice and rationale to support the develop-ment of self-determination and the need for autonomy.

Student management groups are presented as a method toenhance students’ autonomy in class governance (Lilly andTippins (2002). Factors ranging from content coverage tograding policies are submitted to the student managementgroup for input. In addition, the group collects feedback onmany aspects of the course such as understanding of the mate-rial, assignment difficulty, and even professor-studentinteraction.

Course participation assignments (Peterson 2001) havebeen successfully used to increase student responsibility fortheir own learning behavior. Documenting the tasks and pro-cess of learning is thought to support autonomy developmentand task mastery goal orientation. The course participationassignments also allow students to select their own ways ofclass participation (autonomy) based on what the studentsfeel would benefit their learning the most. Both verbal andwritten feedback was provided throughout the semester, aswell as student input in assigning value to the variousparticipation activities.

• Encourage social connections in learning that support theneed for relatedness.

To enhance social connections, team learning can beincorporated. To stimulate positive interdependence and indi-vidual accountability among students, cooperative learningstructures may be used (Hernandez 2002). Implemented atthe Principles of Marketing level, the team learning pedagogypresented by Hernandez is designed to facilitate higher levelthinking and active learning. Central in this pedagogy is theinstructional activity sequence that is initiated with individualstudy and assessment, followed by team assessment andinstructor feedback, and then finished with application-oriented activities.

• Use rewards carefully and sparingly because rewards contin-gent on task performance do reliably undermine intrinsicmotivation and can promote ego-social goal orientations.Avoid threats, deadlines, directives, pressured evaluations,and imposed goals because they foster an external locus ofcausality and thus diminish intrinsic motivation (Ryan andDeci 2000).




Students will be intrinsically motivated only for activitiesthey find intrinsically interesting. These are activities thathave the appeal of novelty, challenge, or aesthetical value(Ryan and Deci 2000) and are primarily found in upper levelelective courses that students select within their majors. Forrequired courses, such as Principles of Marketing, and activi-ties that do not have such appeal, some degree of extrinsicmotivation will be operative. However, Miller (2000) foundalmost any activity can be made intrinsically interesting byselecting challenges that match a learner’s perceived capabil-ities, combined with feedback on their progress. The mostimportant variable is the feedback, which is necessary tomaintain a learner’s level of interest.

As seen in the above pedagogical examples, feedback onlearning and performance is central to the classroom environ-ment and has important implications for promoting differenttypes of motivation. Feedback may provide positive informa-tion on performance leading to enhanced perceived compe-tence, or it may be construed as controlling and reduce thesense of autonomy (Ryan and Deci 2000). Delivering feed-back in an informational style does not impose the feedbackgiver’s demands but suggests the recipient is in control of hisor her own behaviors and offers informative supportive feed-back. Informational feedback maintains the sense of per-ceived autonomy and increases intrinsic motivation. In con-trast, a controlling style of feedback stresses the particularoutcomes that should or must be achieved and makes theexternal forces salient. As a result, the individual may no lon-ger feel he or she is the cause of his or her own actions,thereby reducing perceived autonomy and intrinsicmotivation (Ryan 1982).

Teaching style can also be described as autonomy support-ive or controlling. In an experimental setting, Reeve, Bolt,and Cai (1999) found that autonomy-supportive teachers andcontrolling teachers both engage in many of the same instruc-tional behaviors—gaining students’ attention, asking ques-tions, giving feedback, encouraging persistence, and demon-strating skills. However, autonomy-supportive teacherssought student initiative, listened more, resisted giving solu-tions, verbalized fewer directives, responded to more student-generated questions, allowed time for independent work, andvolunteered more perspective-taking statements. This is con-trasted by controlling teachers who sought students’ compli-ance in activities by introducing consequences and verbaldirectives, talked more, communicated with should state-ments, used frequent praise and criticism, asked controllingquestions, stated deadlines, and generally created an environ-ment characterized as pressure. Cognitive evaluation theorypredicts that providing a classroom environment with hightask autonomy, together with positive feedback in aninformational style, will maximally increase intrinsicmotivation (Zhou 1998).

RESEARCH LIMITATIONS

Although this article provides clear empirical support forthe proposed model, overcoming the potential limitations ofthis study provides guidance for further research. First, thisstudy was based on a sample from one university, suggestingthat replication in alternative educational settings is neededfor greater generalization. Second, refinement of thepsychometric properties of the measures, by adding items toeach variable’s index, could also increase the diagnostic valueof the measures. In addition to enhancing existing variables,many other aspects of the classroom environment could beexamined along with the interactions among these social-con-textual factors. The scope of this study involved a relativelyholistic framework that integrated two motivation theories,several classroom-environmental factors, and seven self-regulated learning behaviors that required a general level ofanalysis. Additional insight may be gained from examiningmany of the relationships presented in the framework in a nar-rower, more focused detail. In particular, the degree to whichdifferent aspects of the classroom environment fulfill cogni-tive evaluation theory’s basic needs of competence andautonomy could provide valuable insights into instructionaldesign.

Integrating these two theoretical models of motivationwithin the social cognitive framework provides a more com-prehensive understanding of classroom influences on motiva-tion and self-regulated learning and, it is hoped, provides aframework for assisting researchers in the analysis of pro-posed learning pedagogies. Great opportunities exist for fac-ulty to develop classroom learning environments that facili-tate students’needs and motivations, leading to proactive andengaged learners using self-regulated learning skills.

NOTE

1. The single goal orientation index does not distinguish between thejointly high or jointly low orientations; however, the index retains intervalscale properties allowing regressions of the antecedent environmental vari-ables. Given the small percentage of jointly low orientations, this trade-offwas preferred over categorizing the variable into four categories. However, tocheck the robustness of the results, the equations of the path analysis thatcould incorporate goal orientations as categorical were estimated. The resultswere essentially the same as those obtained with the single variable indexexcept for an additional direct path from joint high goal orientation to theplanning learning strategy.

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The Motivational Effects of the Classroom Environment in Facilitating Self-Regulated Learning