lable at ScienceDirect

Teaching and Teacher Education 27 (2011) 37e42

Contents lists avai

Teaching and Teacher Education

journal homepage: www.elsevier .com/locate/ tate

The role of teachers in facilitating situational interest in an active-learningclassroom

Jerome I. Rotgans a,*, Henk G. Schmidt b

aRepublic Polytechnic, Centre for Educational Development, 9 Woodlands Avenue 9, Singapore 738964b Erasmus University Rotterdam, The Netherlands

a r t i c l e i n f o

Article history:Received 21 September 2009Received in revised form28 June 2010Accepted 29 June 2010

Keywords:Situational interestTeacher characteristicsSocial congruenceSubject-matter expertiseCognitive congruenceProblem-based learning

* Corresponding author. Tel.: þ65 91725213; fax: þE-mail address: jerome_rotgans@rp.sg (J.I. Rotgans

0742-051X/$ e see front matter � 2010 Elsevier Ltd.doi:10.1016/j.tate.2010.06.025

a b s t r a c t

The study sought to explore whether interactional teacher characteristics such as social congruence,subject-matter expertise, and cognitive congruence increase situational interest in students. Correla-tional and path analyses were conducted on a sample of 498 polytechnic students to assess potentialdifferences in situational interest based on these three teacher characteristics and how well thesecharacteristics predicted situational interest. Results revealed that students supported by teachers whoscored high on these characteristics reported significantly higher levels of situational interest. Cognitivecongruence was the most significant predictor of situational interest. Overall, the findings suggest thatteachers play an influential role in increasing students’ situational interest in the active-learningclassroom.

� 2010 Elsevier Ltd. All rights reserved.

1. Introduction

Situational interest has been portrayed as a powerfuleducational construct because this type of interestdunlike indi-vidual interest, which is considered a stable predispositiondcan bemanipulated by instructional materials and is thus more or lessunder the direct control of educators (Hidi & Renninger, 2006). Hidiand Renninger defined situational interest as “focused attentionand an affective reaction that is triggered in the moment byenvironmental stimuli, which may or may not last over time”(p. 113). For instance, research has shown that stimuli such aspuzzles, challenging tasks, well-organized texts, or simplyproviding students with choices in the way they learn and whatthey learn, increase situational interest, which typically manifestitself as a direct affective response, focused attention, and increasedlevels of learning (Hidi, 1990; Hidi & Renninger, 2006; Mitchell,1992).

Indeed, there have been several comprehensive reviews in theeducational literature that suggest how instructional materialsinfluence students’ situational interest. For instance, Schraw,Flowerday, and Lehman (2001) suggest that there are three generalways to increase situational interest in the classroom. That is,

65 64151310.).

All rights reserved.

providing meaningful choices to students in what and how theystudy; selecting well-organized, structured, and vivid texts thatpromote interest; and providing relevant background knowledgeneeded to fully understand a topic. In addition, they stress thatencouraging students to be active learners (bymeans of predictingorsummarizing what they already know, want to know, and havelearned) can increase situational interest. In a similar review byBergin (1999) on the factors influencing classroom interest, hesuggests that instructional aspects such as hands-on activities,discrepancy (i.e., confronting students with a misconception theyhold),noveltyof learningstimuli, social interactionbymeansofgroupwork, modeling experts, using games and puzzles (see also Mitchell,1992; Schoenfeld, 1989), humor, and narrative (attracting interestthrough telling a story) can increase students’ situational interest.

These accounts provide suggestions on how instructionalmaterials can be used to increase the possibility of students’becoming situationally interested. However, largely missing in thediscussion are the possible effects of teachers’ personal character-istics on increasing students’ situational interest. For instance,whether teacher characteristicsdsuch as a teacher’s expertise ina subject domain, social concern for the students, and his or herability to “tune in” to the students and discuss educational mate-rials in away they understanddhave a direct influence on students’situational interest has not been studied extensively. This issurprising since interest researchers have stressed the potentialinfluence teachers have on students’ situational interest and

J.I. Rotgans, H.G. Schmidt / Teaching and Teacher Education 27 (2011) 37e4238

interest development in general (Bergin,1999; Hidi, 2006; Mitchell,1992; Schraw et al., 2001).

According to Hidi and Renninger (2006) teachers influencestudents’ interest in particular during the initial two phases in theirfour-phase model of interest development (i.e. when situationalinterest is triggered and maintained). Sloboda and Davidson (1995,inHidi & Renninger, 2006) reportedfindings of a study that indicatesthat for music students to persevere the most important character-istics of their teachers were to be able to communicate well (i.e.,being friendly, encouraging, talkative) and to pass on their love formusic. In a second study Hidi and Renninger referred to Long andMurphy (2005), who found that a teacher’s interest in the subjectmatterwas to somedegree related to students’ subject interest in theclassroom (see also Long, 2003). Although these studies come closeto describing the influence of teacher characteristics, such as theteacher’s own interest in orpassion for the subject and their ability tocommunicate well or be friendly, these accounts seemmore relatedto students’ stable and enduring individual or topic interest ratherthan to their situational interest. With the present study we were,however, particularly interested in the extent towhich interpersonalandcognitive teacher characteristics influenced the level of students’situational interest. If we were able to demonstrate such influence,this would reveal whether more could be done to increase students’situational interest in the classroomdnot only by providing stimu-lating instructional materials, but also by selecting (and possiblytraining) teacherswhohavedistinct teaching characteristics that areconducive to increasing situational interest.

In our case, the classroomwas an active-learning, problem-basedclassroom,which is characterizedby (1) authentic learning tasks, (2)collaborative learning, (3) limited direct instruction from teachers,and (4) self-initiated individual learning activities (Schmidt, Van derMolen, Te Winkel, & Wijnen, 2009). In such a problem-basedlearning (PBL) environment teaches assume a less dominant role inthe sense that they do not engage in direct instruction, but guide thestudents through conversation and questioning (Barrows, 1985). InPBL the problem comes firstdthe teacher is secondary and is oftencharacterized as a facilitator of student learning rather than aninformation transmitter. A problem is usually a description of a set ofphenomena or events that need to be explained in terms of a theoryor an underlying principle. Students work collaboratively in teamson the problems and come up with tentative explanations andhypotheses that may provide an answer to the problem. Subse-quently, students engage in self-study to acquire knowledge aboutthe problem at hand. Students then share their insights gainedduring self-study, synthesize the information with the help of theteacher, and elaborate on their findings. The objective of the teacherin PBL is to create a learning conducive and friendly environmentthat encourages everyone to participate in the discussion and sharehis or her knowledge. Sometimes, the teacher also engages in thediscussion by providing a short and precise explanation or by askingquestions to elicit whether students truly have mastered thenecessary knowledge during self-study. If that is the case, the classwill move on and start working on a subsequent problem.

Over the past 40 years, PBL has been adopted as an instructionalapproach across the world and for a wide-range of subject areas.For instance, many medical schools in the United Stated, Australia,Europe, and Asia use PBL as their instructional method (Antepohl &Herzig, 1999; Khoo, 2003; Sanson-Fisher & Lynagh, 2005; Schmidtet al., 2009; Tiwari, Lai, So, & Yuen, 2006). Moreover, PBL has beenadopted inmany other disciplines, such as Engineering (Dahlgren &Dahlgren, 2002), Psychology (Reynolds, 1997), Economics andBusiness Studies (Gijselaers et al., 1995), Law (Moust & Nuy, 1987),and Biology (Kendler & Grove, 2004).

Research findings have demonstrated that certain teachercharacteristics are particularly conducive to student learning in

PBL. Three distinct teacher characteristics have been identified thatseem to influence the effectiveness of student learning andachievement: (1) social congruence, (2) subject-matter expertise,and (3) cognitive congruence (De Grave, Dolmans, & van derVleuten, 1999; Grave, Dolmans, & Vleuten, 1998; Lockspeiser,O’Sullivan, Teherani, & Muller, 2008; Moust, 1993; Schmidt &Moust, 1995, 2000; Solomon & Crowe, 2001).

Social congruence refers to a teacher’s personal interest in orconcern for his/her students (Grave et al., 1998; Schmidt & Moust,2000). Students who experience a socially congruent teacher aretypically not afraid to tell him or her if they do not understandsomething; they typically try harder, and are not afraid of makingmistakes. We hypothesized that the enhanced social climatecreated by a socially congruent teacher and the mutual respectbetween teacher and student would have a positive influence onstudents’ situational interest in a classroom.

A second significant teacher characteristic is a teacher’s subject-matter expertise. Research has shown that the degree of knowledgea teacher has positively affects student achievement in theactive-learning classroom (Schmidt & Moust, 1995; Schmidt, Vander Arend, Moust, Kokx, & Boon, 1993). We hypothesized thatstudents’ perceptions about the level of a teacher’s expertise mightpositively influence situational interest as well, because theywouldbe more willing to exert effort for a knowledgeable teacher than fora not-so-knowledgeable teacher. Put negatively, it is unlikely thatstudents take a learning task seriously and are willing to engage inlearning when they feel that the teacher lacks knowledge of thetopic. In addition, receiving hints or short explanations at criticalmoments in the learning process may help students overcometemporary setbacks and, hence, fuel situational interest in subjectmatter.

Cognitive congruence refers to the ability to express oneself ina language students can understand, using concepts they use andexplaining concepts in ways easily grasped by students (Schmidt &Moust, 1995). For instance, if a cognitive congruent teacher knowsthat a particular concept is difficult to understand, he or she willbreak it down for the students by asking questions that guide themto reach the desired level of understanding. Moreover, a cognitivecongruent teacher does not disrupt an ongoing discussion and puthimorherself in the center of the learningprocess.Wehypothesizedthat this form of scaffolding would result in providing students onthe one hand with structure in their thinking and on the other withconfidence that they can master the topic on their own, whicheventually would result in increased levels of situational interest.

With the present study we hypothesized that the three distinctPBL teacher characteristics would contribute to increased students’situational interest in the active-learning classroom. Data froma regular program evaluation, which measured teachers’ scores onthe three characteristics were extracted. A month later, we admin-istered a short situational interest self-report questionnaire to 498students. The short questionnairewas administeredsix timesduringa learning event and an aggregated score was generated to capturestudents’ overall level of situational interest. A correlation analysiswas carried out to determine the level of association between thethree teacher characteristics and situational interest. In addition,weused path analysis to examine how much of the variance in situa-tional interestwas explained byeach of the three components of theteacher characteristics studied and how they were interrelated.

2. Method

2.1. Participants

The sample consisted of 498 participants (52% femaleand 48% male) with an average age of 19.43 years (SD¼ 1.62).

J.I. Rotgans, H.G. Schmidt / Teaching and Teacher Education 27 (2011) 37e42 39

The participants were enrolled in various diploma programs(37 classes) at a polytechnic in Singapore.

2.2. Educational context

In this polytechnic, the instructional method is PBL for all itsmodules and programs. In this approach five students worktogether in one team under the guidance of a teacher. Each classcomprises four to five teams. Unique to this polytechnic’s approachto PBL is that students work on one problem during the course ofeach day (Alwis & O’Grady, 2002) A typical day starts with thepresentation of a problem. Students discuss in their teams whatthey know, do not know, and what they need to find out. Doing so,students activate their prior knowledge, come up with tentativeexplanations for the problem, and formulate their own learninggoals (Barrows, 1988; Hmelo-Silver, 2004; Schmidt, 1983, 1993).Subsequently, a period of self-study follows, in which studentsindividually and collaboratively try to find information to addressthe learning goals. At the end of the day the teams come together topresent, elaborate upon, and synthesize their findings.

2.3. Measures

2.3.1. Teacher characteristicsIn order to measure the teacher characteristics of interest,

a rating scalewas adapted fromSchmidt andMoust (1995); the scaleis used on a regular basis as a program evaluation questionnaire atthe polytechnic. Three subscales were administered: (1) socialcongruence (Items: The facilitator showed that he/she liked informalcontact with us; I was not afraid to tell the facilitator when I did notunderstand something; The facilitator appreciated our efforts; and Thefacilitator showed interest in our personal lives), (2) subject-matterexpertise (Items: The facilitator used his or her content knowledge tohelp us; and The facilitator has a lot of content knowledge about thismodule), and (3) cognitive congruence (Items: The facilitator askedquestions we could understand; The facilitator interrupted us severaltimes, which disturbed the progress of the group discussion; and Thefacilitator used words or jargon that were difficult for me to under-stand). The items of the rating scales were scored on a 5-point Likertscale: 1 (not true at all), 2 (not true forme), 3 (neutral), 4 (true for me),and 5 (very true for me). The validity of the instrument was estab-lished elsewhere (see Schmidt & Moust, 1995). The reliability of themeasurewas determined bycalculatingHancock’s coefficientH. Thecoefficient H is a construct reliability measure for latent variablesystems that represents an adequate alternative to the conventionalCronbach’s alpha (Bentler, 2009; Green & Yang, 2009; Hancock &Mueller, 2001; Sijtsma, 2009). Hancock recommended a cut-offvalue for the coefficient H of .70. The coefficient Hwas .75 for socialcongruence, .80 for subject-matter expertise, and .79 for cognitivecongruence (average: .78) and deemed adequate.

2.3.2. Situational interest measureA six-item situational interest scale (SI-present-state) was

adapted from Rotgans and Schmidt (2009) to determine students’situational interest. The items were: (1) I want to know more abouttoday’s topic; (2) I will enjoy working on today’ topic; (3) I thinktoday’s topic is interesting; (4) I expect tomaster today’s topic well; (5)I am fully focused in today’s topic; I am not distracted by other things;and (6) presently I feel bored. The items were scored on a 5-pointLikert scale: 1 (not true at all), 2 (not true for me), 3 (neutral), 4 (truefor me), and 5 (very true for me). The construct validity of the scalewas established elsewhere and deemed adequate (see Rotgans &Schmidt, 2009). The coefficient H for the situational interest scalewas .95. Overall, the results demonstrate that the psychometriccharacteristics of situational interest measure are adequate.

2.4. Procedure

Data concerning the three teacher characteristics were extrac-ted from a routine program evaluation, which is conducted everysemester at the polytechnic for all its programs. About a monthlater, the situational interest measure was administered online inthese classes at six critical occasions during a PBL day. Each of theselected measurement occasionsdfirst confrontation with theproblem, small-group discussion about the problem, self-directedstudy activities, continued discussion of the problem, and elabo-ration on what was learneddrepresented critical events that weresupposed to foster situational interest (Rotgans & Schmidt, inpress). The questionnaires appeared in the students’ regularlearning environment. The regular teacher in class activateda pop-up window, which appeared on each student’s computerscreen. It took students about 30 seconds to respond to each of thesix-item questionnaires. Once the data were collected, aggregatedmean values of situational interest for the day were generated. Thiswas done to obtain one single measure of students’ situationalinterest that represents their overall level of situational interestover the course of the learning event.

2.5. Analysis

Responses to negatively stated items were reversed so that forall items the highest score was indicative of a positive rating. Next,a bivariate correlation analysis was carried out to examine theassociations between the teacher characteristics and situationalinterest. In order to test whether the relationships between themeasured variables are linear, we conducted an ANOVA test oflinearity. The results revealed that the non-linear components of allthe relationships between the variables were not statisticallysignificant. This outcome suggests that the relationships betweenthe measured variables are linear.

In order to determine which of the three teacher characteristicspredicted situational interest best and the degree to which itcontributed in explaining the variance in situational interest, pathanalysis was carried out. For the model, Chi-square accompaniedwith degrees of freedom, p-value, and the root mean square error ofapproximation (RMSEA) were used as indices of absolute fitbetween the models and the data. The Chi-square is a statisticalmeasure to test the closeness of fit between the observed andpredicted covariance matrix. A small Chi-square value, relative tothe degrees of freedom, indicates a good fit (Byrne, 2001). A Chi-square/df ratio of less than 3 is considered to be indicative of a goodfit. RMSEA is sensitive to model specification and is minimallyinfluenced by sample size and not overly affected by estimationmethod (Fan, Thompson, & Wang, 1999). The lower the RMSEAvalue, the better the fit. A commonly reported cut-off value is .06(Hu & Bentler, 1999). In addition to these absolute fit indices, thecomparative fit index (CFI) was calculated. The CFI value rangesfrom zero to one and a value greater than .95 is considered a goodmodel fit (Byrne, 2001).

It should be noted that a common concern for this kind ofanalyses is that the responses may be nested in the classes (i.e. the37 teachers). In order to test whether this is the case for the presentdataset, we examined the portion of the variance explained by theclasses as compared to the variance explained by the students. Theanalysis was carried out with SPSS AMOS 5.0 (Arbuckle, 2003), aswell as multiple regression analysis in SPSS 16.0 (SPSS, 2007). Theresults suggest that less than 1% of the variance in situationalinterest is explained by differences between classes and about 19%by differences between the students. This outcome demonstratesthat there is no need to suspect that responses may be class-dependent.

Social congruence

Subject-matter expertise

Cognitive congruence

Situational Interest

.02

.34*

.13

z .28

R2 = .14

Fig. 1. Path model displaying the relationships between social congruence, subject-matter expertise, cognitive congruence, and situational interest. Note: the numbersabove the arrows are standardised regression weights (b), *significant at the 5% level.

Social congruence

J.I. Rotgans, H.G. Schmidt / Teaching and Teacher Education 27 (2011) 37e4240

3. Results and discussion

The results of the correlation analysis are depicted in Table 1. AllPearson’s correlation coefficients were statistical significant at the1% level.

The weakest correlation coefficient was observed betweensocial congruence and situational interest (r¼ .25, p< .01), thestrongest between cognitive congruence and situational interest(r¼ .43, p< .01). Overall, the results of the correlation analysissuggest that the three teacher characteristics are significantlyassociated with students’ situational interest.

Testing the path model (see Fig. 1 for an overview) revealeda rather poor model fit; the fit indices were: Chi-square/df¼ 53.11,p< .01, CFI¼ .40, and RMSEA¼ .67. In the model, cognitivecongruence was the strongest and only significant factor (b¼ .34,p¼ .01). The other path coefficients were weak and did not reachstatistical significance. Overall, the results suggest that about 14% ofthe variance in situational interest could be explained by the threeteacher characteristics.

Most notable is that for both analyses cognitive congruenceemerged as the strongest factor. This outcome suggests thatteachers who are cognitively aligned with their studentsdthat is,provide the students with scaffolds and structure in their thinkingprocessesdhave a strong positive influence on students’ situationalinterest. Social congruence and subject-matter knowledge hada relatively weaker effect on situational interest.

The poor model fit of the path model is, however, worrisome;there seems to be a large misfit between the hypothesized modeland the data. In order to address this issue, we tested an alternativemodel. There are some cognitive congruence researchers who havesuggested that both social congruence and subject-matter exper-tise are necessary conditions for cognitive congruence to occur,rather than influences on situational interest in their own right(Grave et al., 1998). As such, these two factors may be seen as theantecedents of cognitive congruence. Schmidt and Moust (1995)tested this assumption empirically by means of path analysis andfound that expertise (b¼ .55, p< .01) and social congruence(b¼ .41, p< .01) explained about 45% of the variance in cognitivecongruence. In other words, cognitive congruence, subject-matterexpertise, and social congruence are not three equal-level factors;rather, it appears that cognitive congruence is the result of a teacherhaving both a fair amount of subject-matter knowledge and socialconcern for the students.

We examined whether this was the case for our sample as well.We tested a second model in which social congruence and subject-matter expertise were used as input variables for cognitivecongruence, and cognitive congruence as a predictor of situationalinterest (see Fig. 2 for an overview of the model).

The data fitted the modified model very well: Chi-square/df¼ .58, p¼ .56, CFI¼ 1.00, and RMSEA¼ .00. Comparing themodelfit between the two models by means of a difference in Chi-squaretest revealed that the alternative model produced a significantlybetter model fit (Dc2¼105.07, p< .01), thus replicating the findingsin the cognitive congruence literature. In fact in our sample, social

Table 1Intercorrelations between teacher characteristics and situational interest.

Teacher characteristics 1 2 3 4 5

1. Overall (mean of all threeteacher characteristics)

e .80** .84** .95** .44**

2. Social congruence e .61** .64** .25**3. Subject-matter expertise e .70** .30**4. Cognitive congruence e .43**5. Situational interest e

Note: *p< .05, **p< .01.

congruence and subject-matter expertise explained about 60% ofthe variance in cognitive congruence. In turn, cognitive congruencewas a relatively strong predictor of situational interest (b¼ .45,p< .01), explaining about 20% of the variance in situational interest.

Overall, these findings suggest that when making predictionsabout the level of situational interest based on teacher character-istics, social congruence, and subject-matter expertise are notdirectly related to situational interest but play a significant role inexplaining a large portion of the variance in cognitive congruence.In our sample, subject-matter expertise showed a strongerrelationship with cognitive congruence than social congruence did(b¼ .58 vs. b¼ .28). Cognitive congruence in turn was a relativelystrong predictor of student’s situational interest. As such, whenconsidering the relationship between teacher characteristics andsituational interest, cognitive congruence seems to be the strongestand most significant factor to consider.

4. General discussion

Most existing situational interest studies have examined how farinstructional materials such as puzzles, vivid texts, or games, influ-ence students’ situational interest (Bergin, 1999; Mitchell, 1992;Schraw et al., 2001; Schraw & Lehman, 2001). With the presentstudy we investigated how far the teacher characteristics socialcongruence, subject-matter expertise, and cognitive congruence,contributed to students’ situational interest. The results revealedthat social congruence and subject-matter expertise are not directlyrelated to situational interest, but are antecedent variables ofa teacher’s cognitive congruence. Our findings imply that beingfriendly, socially and emotionally connected with the students aswell as having a large body of knowledge about a topic are highlypredictive of how cognitively congruent a teacher is. Being cogni-tively congruent, that is helping students to understand the topic byproviding scaffolds and structure to the topic,was a significant factorin predicting students’ level of situational interest in the classroom.

Subject-matter expertise

Cognitive congruence Situational Interest

.28

.58

.43

z .16 z .29

R2 = .19

Fig. 2. Path model displaying the relationships between social congruence, subject-matter expertise, cognitive congruence, and situational interest. Note: the numbersabove the arrows are standardised regression weights (b). All standardised regressionweights were significant at the 1% level.

J.I. Rotgans, H.G. Schmidt / Teaching and Teacher Education 27 (2011) 37e42 41

The findings of this study allow for two conclusions. On the onehand, our data suggest that teacher characteristics and in particularteacher’s cognitive congruence have a significant influence onstudents’ situational interest; they explained about 20% of thevariance in situational interest. Considering this relatively largeeffect, cognitive congruence theory may play a significant part inteacher training programs. For instance, teacher educators may betrained to help teacher candidates and in-service teachers developtheir cognitive congruence to increase students’ situational interestand eventually their learning. A second conclusion is that if oneattempts to increase students’ situational interest by means ofcontrolling for teacher characteristics, there are (at least) twooptions: one is to increase a teacher’s social congruence, and theother is to increase a teacher’s subject-matter expertise, thuseventually increasing cognitive congruence and indirectly affectingsituational interest. Social congruence seems to be a rather dispo-sitional quality of a person, which may make it challenging to bemanipulated via short-term interventions. However subject-matterexpertise seems adjustable and should be able to be enhancedthrough interventions such as providing additional resource mate-rials or providing additional briefing sessions for teachers who lackdeeper knowledge about the subject matter or the problem at hand.

Projecting our findings against the larger picture of classroompractices, what kind of general implications do our findings have?Following the developments in the self-regulated learning litera-ture, one can observe a shift toward student-centered learningpractices and away from the teacher; students are asked to exercisemuch more actual control and regulation of the academic tasks andclassroom climate and structure (Pintrich, 2004). For instance, ina reviewof 30 years of research in thefield of self-regulated learningParis and Paris (2001) described self-regulated learning as aneducational paradigm that “emphasizes autonomy and control bythe individual who monitors, directs, and regulates actions towardgoals of information acquisition, expanding expertise, and self-improvement” (p. 89). Similarly, Zimmerman (2008) emphasizedthe importance of self-directive processes and self-beliefs thatenable learners to develop their mental abilities in a proactivemanner. In a similar vein, self-determination theory stressed theimportance for student autonomy as a basic human need (Black &Deci, 2000; Deci, 1992; Ryan & Deci, 2000). Deci (1992) hassuggested that classrooms that promote student autonomy andchoice increase intrinsic motivation, interest, and promote studentlearning (see also Cordova & Lepper, 1996; Schraw et al., 2001).Besides the fewaccountsmentioned here, there aremanymore thatemphasize student-centeredness and encourage autonomous self-regulation. Considering the findings of the present study, however,it is suggested that the significant influential role teachers play inthe development of student interest and learning not beoverlooked. It is surprising to see that this is even the case in theproblem-based, active-learning classroom, a rather successfuloperationalization of the ideas of self-regulated learning andstudent autonomy (Schmidt et al., 2009). In PBL, teachers playa largely supportive role without much direct instruction, leadingsome to suggest that PBL is a formofminimally guidance instruction(Kirschner, Sweller, & Clark, 2006). Nevertheless, we found sizableeffects of teachers’ behavior on students’ situational interest.

The strength of the present study is also its limitation: results aresomewhat restricted to the active-learning classroom. Itmaywell bepossible that in a more conventional classroom other teacher char-acteristics, such as, strictness, teaching styles, or leadership (seeBrok, Brekelmans, & Wubbels, 2004), may influence students’situational interest as well. It would also be interesting to see if thefindings of this study can be replicated in the context of primary andsecondary education in which increasingly more indirect teachingmethods are being applied. In addition, future studies should be

extended to include instructional factors such as the problem type,the learningmaterials, and assessment strategies to explainmore ofthe remaining part of the variance in students’ situational interest.

References

Alwis, W. A. M., & O’Grady, G. (2002). One day-one problem at Republic Polytechnic.Paper presented at the 4th Asia-Pacific conference on PBL.

Antepohl, W., & Herzig, S. (1999). Problem-based learning versus lecture-basedlearning in a course of basic pharmacology: a controlled, randomized study.Medical Education, 33(2), 106e113.

Arbuckle, J. L. (2003). Amos 5.0 update to the Amos user’s guide. Marketing Dept.,SPSS Inc., SmallWaters Corp.

Barrows, H. S. (1985). How to design a problem-based curriculum for the preclinicalyears. New York: Springer Publishing.

Barrows,H. S. (1988).The tutorial process. Springfield, IL:UniversitySchoolofMedicine.Bentler, P. M. (2009). Alpha, dimension-free, and model-based internal consistency

reliability. Psychometrika, 74(1), 137e143.Bergin, D. A. (1999). Influences on classroom interest. Educational Psychologist, 34

(2), 87e98.Black, A. E., & Deci, E. L. (2000). The effects of instructors’ autonomy support

and students’ autonomous motivation on learning organic chemistry: a self-determination theory perspective. Science Education, 84(6), 740e756.

Brok, P., Brekelmans, M., & Wubbels, T. (2004). Interpersonal teaching behaviourand student outcomes. School Effectiveness and School Improvement, 15(3e4),407e442.

Byrne, B. M. (2001). Structural equation modeling with Amos: Basic concepts,applications and programming. Mahwah, N.J.: Lawrence Erlbaum Associates Inc.

Cordova, D. I., & Lepper, M. R. (1996). Intrinsic motivation and the process oflearning: beneficial effects of contextualization, personalization, and choice.Journal of Educational Psychology, 88(4), 715e730.

Dahlgren, M. A., & Dahlgren, L. O. (2002). Portraits of PBL: students’ experiences ofthe characteristics of problem-based learning in physiotherapy, computerengineering and psychology. Instructional Science, 30(2), 111e127.

De Grave, W. S., Dolmans, D., & van der Vleuten, C. P. M. (1999). Profiles of effectivetutors in problem-based learning: scaffolding student learning. MedicalEducation, 33(12), 901e906.

Deci, E. L. (1992). The relation of interest to the motivation of behavior: a self-determination theory perspective. In K. A. Renninger, S. Hidi, & A. Krapp (Eds.),The role of interest in learning and development (pp. 43e70). Hillsdale, NJ:Lawrence Erlbaum Associates.

Fan, X., Thompson, B., & Wang, L. (1999). Effects of sample size, estimation methods,and model specification on structural equation. Structural Equation Modeling, 6(1), 56e83.

Gijselaers, W. H., Tempelaar, D. T., Keizer, P. K., Blommaert, J. M., Bernard, E. M., &Kasper, H. (1995). Educational innovation in economics and business education:The case of problem-based learning. Dordrecht: Kluwer Academic.

Grave, W. S. D., Dolmans, D., & Vleuten, C. P. M. (1998). Tutor intervention profile:reliability and validity. Medical Education, 32(3), 262e268.

Green, S. B., & Yang, Y. (2009). Commentary on coefficient alpha: a cautionary tale.Psychometrika, 74(1), 121e135.

Hancock, G. R., & Mueller, R. O. (2001). Rethinking construct reliability within latentsystems. In R. Cudeck, S. D. Toit, & D. Sörbom (Eds.), Structural equationmodeling: Present and future e A festschrift in honor of Karl Jöreskog (pp.195e216). Lincolnwood, IL: Scientific Software International.

Hidi, S. (1990). Interest and its contribution as a mental resource for learning.Review of Educational Research, 60(4), 549e571.

Hidi, S. (2006). Interest: a unique motivational variable. Educational ResearchReview, 1(2), 69e82.

Hidi, S., & Renninger, K. A. (2006). The four-phase model of interest development.Educational Psychologist, 41(2), 111e127.

Hmelo-Silver, C. E. (2004). Problem-based learning: what and how do studentslearn? Educational Psychology Review, 16(3), 235e266.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structureanalysis: conventional criteria versus new alternatives. Structural EquationModeling, 6(1), 1e55.

Kendler, B. S., & Grove, P. A. (2004). Problem-based learning in the biology curric-ulum. American Biology Teacher, 66(5), 348e354.

Khoo, H. E. (2003). Implementation of problem-based learning in Asian medicalschools and students’ perceptions of their experience. Medical Education, 37(5),401e409.

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance duringinstruction does not work: an analysis of the failure of constructivist, discovery,problem-based, experiential, and inquiry-based teaching. Educational Psychol-ogist, 41(2), 75e86.

Lockspeiser, T. M., O’Sullivan, P., Teherani, A., & Muller, J. (2008). Understanding theexperience of being taught by peers: the value of social and cognitivecongruence. Advances in Health Sciences Education, 13(3), 361e372.

Long, J. F. (2003). Connecting with the content: How teacher interest affects studentinterest in a core course. Ohio State University.

Long, J. F., & Murphy, P. K. (2005). Connecting through content: The responsiveness ofteacher and student interest in a core course. Paper presented at the annualmeeting of the American Educational Research Association.

J.I. Rotgans, H.G. Schmidt / Teaching and Teacher Education 27 (2011) 37e4242

Mitchell, M. (1992). Situational interest: its multifaceted structure in the secondarymathematics classroom. Journal of Educational Psychology, 85(3), 424e436.

Moust, J. H. C. (1993). The role of tutors in problem-based learning. Contrasts betweenstudent- and staff-tutors. Maastricht: University of Limburg.

Moust, J. H. C., & Nuy, H. J. (1987). Preparing teachers for a problem-based student-centred law course. Journal of Professional Legal Education, 5(1), 16e30.

Paris, S. G., & Paris, A. H. (2001). Classroom applications of research on self-regulated learning. Educational Psychologist, 36(2), 89e101.

Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regu-lated learning in college students. Educational Psychology Review, 16(4), 385e407.

Reynolds, F. (1997). Studyingpsychologyatdegree level:wouldproblem-based learningenhance students’ experiences? Studies in Higher Education, 22(3), 263e275.

Rotgans, J. I., & Schmidt, H. G. Situational interest and achievement in the active-learning classroom. Learning and Instruction, in press doi:10.1016/j.learninstruc.2009.11.001.

Rotgans, J. I., & Schmidt, H. G. (2009). Situational interest, task engagement, andachievement in an active-learning environment. Paper presented at the AmericanEducational Research Association.

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation ofintrinsic motivation, social development, and well-being. American Psychologist,55(1), 68e78.

Sanson-Fisher, R. W., & Lynagh, M. C. (2005). Problem-based learning: a dissemi-nation success story? Medical Journal of Australia, 183(5), 258e260.

Schmidt, H. G. (1983). Problem-based learning: rationale and description. MedicalEducation, 17(1), 11e16.

Schmidt, H. G. (1993). Foundations of problem-based learning: some explanatorynotes. Medical Education, 27(5), 422e432.

Schmidt, H. G., & Moust, J. H. C. (1995). What makes a tutor effective? A structuralequations modelling approach to learning in problem-based curricula.Academic Medicine, 70(1), 708e714.

Schmidt, H. G., & Moust, J. H. C. (2000). Factors affecting small-group tutoriallearning: a review of research. In D. H. Evensen, & C. E. Hmelo-Silver (Eds.),

Problem-based learning: A research perspective in learning interactions (pp.19e52).Mahwah, NJ: Lawrence Erlbaum.

Schmidt, H. G., Van der Arend, A., Moust, J. H. C., Kokx, I., & Boon, L. (1993). Influenceof tutors’ subject-matter expertise on student effort and achievement inproblem-based learning. Academic Medicine, 68(10), 784e791.

Schmidt, H. G., Van der Molen, H. T., Te Winkel, W. W. R., & Wijnen, W. H. F. W.(2009). Constructivist, problem-based, learning does work: a meta-analysisof curricular comparisons involving a single medical school. EducationalPsychologist, 44(4), 227e249.

Schoenfeld, A. H. (1989). Teaching mathematical thinking and problem solving. InL. B. Resnick, & L. E. Klopfer (Eds.), Toward the thinking curriculum: Currentcognitive research (pp. 83e103). Alexandria, VA: Association for Supervision andCurriculum Development.

Schraw, G., Flowerday, T., & Lehman, S. (2001). Increasing situational interest in theclassroom. Educational Psychology Review, 13(3), 211e224.

Schraw, G., & Lehman, S. (2001). Situational interest: a review of the literatureand directions for future research. Educational Psychology Review, 13(1),23e52.

Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness ofCronbach’s alpha. Psychometrika, 74(1), 107e120.

Sloboda, J. A., & Davidson, J. W. (1995). The young performing musician. InI. Deliege, & J. A. Sloboda (Eds.), The origins and development of musicalcompetence (pp. 171e190). London: Oxford University Press.

Solomon, P., & Crowe, J. (2001). Perceptions of student peer tutors in a problem-based learning programme. Medical Teacher, 23(2), 181e186.

SPSS. (2007). SPSS 16.0 base user’s guide. Chicago: SPSS Inc.Tiwari, A., Lai, P., So, M., & Yuen, K. (2006). A comparison of the effects of problem-

based learning and lecturing on the development of students’ critical thinking.Medical Education, 40(6), 547e554.

Zimmerman, B. J. (2008). Investigating self-regulation and motivation: historicalbackground, methodological developments, and future prospects. AmericanEducational Research Journal, 45(1), 166e183.