This article was downloaded by: [Laurentian University]On: 11 October 2014, At: 08:27Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

The Journal of Educational ResearchPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/vjer20

Teacher Beliefs as Predictors of Adolescents’ CognitiveEngagement and Achievement in MathematicsIsabelle Archambault a , Michel Janosz a & Roch Chouinard aa Université de Montréal , CanadaPublished online: 02 Aug 2012.

To cite this article: Isabelle Archambault , Michel Janosz & Roch Chouinard (2012) Teacher Beliefs as Predictors ofAdolescents’ Cognitive Engagement and Achievement in Mathematics, The Journal of Educational Research, 105:5, 319-328,DOI: 10.1080/00220671.2011.629694

To link to this article: http://dx.doi.org/10.1080/00220671.2011.629694

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) containedin the publications on our platform. However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of theContent. Any opinions and views expressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon andshould be independently verified with primary sources of information. Taylor and Francis shall not be liable forany losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoeveror howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use ofthe Content.

This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

The Journal of Educational Research, 105:319–328, 2012Copyright C© Taylor & Francis Group, LLCISSN: 0022-0671 print / 1940-0675 onlineDOI:10.1080/00220671.2011.629694

Teacher Beliefs as Predictors ofAdolescents’ Cognitive Engagement and

Achievement in MathematicsISABELLE ARCHAMBAULTMICHEL JANOSZROCH CHOUINARDUniversite de Montreal, Canada

ABSTRACT. The authors explored the moderating effect ofteachers’ expectancies and general sense of efficacy on therelationship between students’ achievement and their cogni-tive engagement and achievement 1 year later. They usedhierarchical linear modeling with a longitudinal sample of79 mathematics teachers and their 1,364 secondary schoolstudents coming from 33 schools serving disadvantaged com-munities in Quebec (Canada). Results indicate that teachers’self-reported beliefs directly influenced student academic ex-perience. However, they did not influence more importantlylow-achieving than high-achieving students. Such findingssuggest that in schools serving low socioeconomic status stu-dents, teachers should be made aware of the role their atti-tudes can play on students’ cognitive engagement and achieve-ment. Special efforts should also be made to help them developpositive attitudes toward all students.

Keywords: achievement, student engagement, teacher prac-tices

A cademic engagement and achievement are centralmarkers of success in most industrialized societies.Youths who are cognitively engaged, that is, who

are willing to invest time and efforts in domains suchas mathematics and science, achieve better outcomes inthose domain-related activities (Eccles, 1984; Eccles et al.,1983; Marsh, Trautwein, Ludtke, Koller, & Baumert, 2005;Pintrich & De Groot, 1990; Pintrich & Schunk, 1996).When entering adulthood, they also present better employ-ment rate and a higher socioeconomic status (Pajares &Graham, 1999; Raudenbush & Kasim, 1998). Unfortunately,many students coming from socioeconomically disadvan-taged backgrounds are unlikely to show active engagementin school (Bradley & Corwyn, 2002). Knowing the adverseconsequences a lack of cognitive engagement and achieve-ment can have on students’ future, researchers have becomeincreasingly interested in understanding how teachers, andespecially mathematics teachers, can promote their students’cognitive engagement and achievement in school. Giventhat mathematics teachers have been criticized for their fail-

ure to foster student interest and motivation (Carr, 1996),knowing more about the environments these teachers arecreating in their classrooms helps us better evaluate how toimprove the fit between the expectations and demands ofthe classroom environment and the students’ developmen-tal needs (Eccles, Midgley, Wigfield, Midgley, et al., 1993;Turner et al., 1998).

Numerous studies have investigated the impact of math-ematics teachers’ beliefs on students’ academic experience(Feldlaufer, Midgley, & Eccles, 1988; Midgley, Feldlaufer,& Eccles, 1988; Muijs & Reynolds, 2000; Patrick, Turner,Meyer, & Midgley, 2003; Tschannen-Moran, WoolfolkHoy, & Hoy, 1998). Yet, most of these studies were cross-sectional or did not take into account the shared perceptionsand experiences that exist between students who belong tothe same classroom and who, therefore, are taught by thesame teacher. Furthermore, most prior research assessed theeffect mathematics teachers’ beliefs may have on averagestudents, without considering the differential impactteachers might potentially have on individuals who presentdifferent characteristics, such as high and low achievers. Toovercome these limitations, we sought to understand howteachers’ beliefs may influence the downward trajectory thatcharacterizes student cognitive engagement and achieve-ment over time (Anderman & Midgley, 1997; Chouinard& Roy, 2008; Jacobs, Lanza, Osgood, Eccles, & Wigfield,2002; Marsh, 1989; Van de Gaer et al., 2009), especiallythat of students who are coming from socioeconomicallydisadvantaged backgrounds (Archambault, Janosz, Morizot,& Pagani, 2009; Janosz, Archambault, Morizot, & Pagani,2008). Based on a stage-environment fit perspective, whichstipulates that underachievement and low motivation arethe result of an inappropriate fit between the environmentand individual needs (Eccles, Midgley, et al., 1993), we

Address correspondence to Isabelle Archambault, Universite deMontreal, C.P. 6128, Succ. Centre-Ville, Montreal, Quebec,H3C3J7, Canada. (E-mail: isabelle.archambault@umontreal.ca)

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4

320 The Journal of Educational Research

explored the moderating effect of teachers’ beliefs’ on therelationship between students’ prior achievement and theircognitive engagement and achievement in mathematics,while taking into account students’ shared experiences insecondary school classrooms.

Teachers’ Beliefs on Student Engagement and Achievement

Teachers’ beliefs play a central role in promoting studentcognitive engagement and achievement in academicactivities (Assor, Kaplan, & Roth, 2002; Feldlaufer et al.,1988; Lee & Loeb, 2000; Midgley et al., 1988; Reeve, Bolt,& Cai, 1999). According to self-determination theory (Deci& Ryan, 1985; Ryan & Deci, 2002) and goal theory (Ames,1992; Ames, & Archer, 1988), students are sensitive to theway teachers respond to their academic success and difficul-ties. When they interact and communicate with students,teachers acknowledge their behavior and successes, and sendimportant messages about their self-worth and the value oflearning (Patrick et al., 2003; Ryan & Patrick, 2001). More-over, on the basis of their beliefs, teachers build a classroomeducational environment that increases or underminesstudents’ achievement and cognitive engagement (Ames,1992; Anderman & Maehr, 1994; Ryan & Patrick, 2001;Wigfield, Eccles, Schiefele, Roeser, & Davis-Kean, 2006).In this study, we explored two types of teacher beliefs knownto have an influence on students’ academic experience:teachers’ expectations and general sense of efficacy.

Previous investigations showed that when teachers havehigh expectations, believe students have the ability to learn,and take responsibility for students’ learning, students aremore engaged, feel more competent while they are learning,learn more, use fewer avoidance strategies when facing dif-ficulties, and perform better (Feldlaufer et al., 1988; Lee &Loeb, 2000; Midgley et al., 1988; Stipek & Daniels, 1988).Moreover, regardless of students’ abilities, when teacherstrust students’ potential and ability to learn, students feelmore competent and report greater engagement and achieve-ment (Brophy, 1983; Connell & Wellborn, 1991; Goddard,Tschannen-Moran, & Hoy, 2001). Conversely, when teach-ers do not trust students, maintain low expectancies, anddoubt students’ ability to succeed because of a perceivedlack of competency or low cognitive abilities, their negativebeliefs act as a self-fulfilling prophecy and greatly interferewith students’ self-perceptions and learning (Rosenthal &Jacobson, 1968). Children inevitably become aware of theseperceptions and are influenced by them, especially in schoolslocated in disadvantaged communities where these negativebeliefs are observed more frequently (Alexander, Entwisle,& Thompson, 1987).

A number of studies also pointed out the important roleof teachers’ self-efficacy on student achievement outcomes(R. Anderson, Greene, & Loewen, 1988; Midgley, Feld-laufer, & Eccles, 1989; Muijs & Reynolds, 2000; Ross,1992). Teachers who possess a high sense of self-efficacy andbelieve in their capacity to help students learn (Pajares &

Graham, 1999; Tschannen-Moran et al., 1998) are usuallymore satisfied with their own work and with their students’behaviors and learning abilities (Caprara, Barbaranelli,Steca, & Malone, 2006). They also report greater profes-sional accomplishments, more stimulating relationshipswith colleagues, and higher enthusiasm regarding their roleas teachers (Evans, 1998; Ross, 1998; Tschannen-Moran &Hoy, 2001). Such positive attitudes eventually have an im-pact on students’ motivation, because satisfied and efficientteachers are more likely to use effective strategies to managestudents’ behaviors and learning, keep them involved andon task, and promote their self-worth and positive attitudesabout school (Ashton & Webb, 1986; Evans, 1998; Podell& Soodak, 1993; Ross, Hogaboam-Gray, & Hannay, 2001).In fact, in schools in which teachers’ collective self-efficacyis strong, students perform better and the influence ofindividual characteristics, such as socioeconomic status(SES) and ethnicity, on achievement is reduced (Bandura,1993; Newmann, Rutter, & Smith, 1989).

The Influence of Teachers’ Beliefs on High and Low Achievers

The fact that students’ previous academic experience rep-resents one of the strongest predictors of their cognitiveengagement and achievement in mathematics is well estab-lished. Indeed, children who display good abilities tend to bemore engaged in school-related activities, put greater effortin those activities, feel more competent while doing them,and achieve better results (Alexander, Entwisle, & Horsey,1997; Pintrich & Schunk, 1996). Conversely, many youthswho do not acquire basic requirements experience repeatedacademic failure and become alienated from school, whichleads to their disengagement, and eventual drop out (Janoszet al., 2008). It was shown that teachers interact differentlywith lower achieving students, have fewer expectations forthem, are less satisfied with their work and behavior, reportmore difficulties teaching them, and maintain more nega-tive beliefs toward them, compared with higher-achievingstudents (Caprara et al., 2006). Thus, students who presentacademic difficulties, and especially when they come fromlow-SES backgrounds (Jussim, Eccles, & Madon, 1996), areless likely to receive the support they need from teachersto be engaged and learn (Hughes & Kwok, 2007). Becausethese students feel less positive about their abilities, theymight rely more on teachers’ perception for motivation andthus might be more negatively affected by teachers’ pes-simistic beliefs than less vulnerable children who alreadypossess a good general sense of self-worth (Eccles, Wigfield,Harold, & Blumenfeld, 1993).

Conversely, research has shown that when they presentpositive expectations toward students, teachers interactmore with them and provide them more positive feed-back (Harris & Rosenthal, 1985), which may ultimatelypromote their engagement and achievement. Teachers ofhigh-achieving students are more likely to experience suc-cess with them and that repeated success may, in turn,

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4

The Journal of Educational Research 321

contribute to and consolidate these students’ positivebeliefs (Caprara et al., 2006). To what extent do students’achievement pathways merely mirror their individual abili-ties without accounting for teachers’ differential beliefs? Todate, relatively little longitudinal research has attempted todisentangle the moderating role of high school teachers’ ex-pectancies and general sense of efficacy on the academicpathways of low and high achievers coming from socioeco-nomically disadvantaged backgrounds. Hence, this knowl-edge would greatly advance the understanding of the wayteachers can better respond to those students’ needs.

Studying Individual Differences Within Classrooms

As pointed out previously, a main issue to consider whenstudying teachers’ influence on students is that individualobservations are not completely independent. Because ateacher–student relationship is strongly embedded withinthe whole classroom’s social context and because classroomtracking (i.e., based on grades) is common in many schools,students who come from the same classroom tend to reportmany similarities. These students share common environ-ments: their classroom and their school. Therefore, theyhave the same teachers, are submitted to the same sets ofrules, and live comparable experiences that can have a com-mon influence on their attitudes and perceptions. As a re-sult, the motivational experiences of these students will besomewhat similar. However, the dependency that lies be-tween students’ scores may possibly lead to false conclusionsbecause it violates an important statistical assumption: theindependence between observations. The violation of thisassumption can introduce a bias in the results because it of-ten influences the standard errors of the estimates and makethem become too small (Raudenbush & Bryk, 2002). Aspointed out by Lau and Nie (2008), if the objective of the re-search is to assess the effect of the classroom, or in the presentcase, the effect of teachers’ beliefs on student outcomes, theclassroom effect should be treated as a second-level predictorand assessed while adjusting for student-level characteristics.Instead of focusing on a single level of analysis by includingclassroom variables in a student-level model, or aggregatingvalues of student-level variables in a classroom-level modelsuch as it is the case in many studies, an analysis has to bedone on two separate levels: student and classroom.

A statistical technique known as hierarchical linear mod-eling (HLM) has been developed to examine both levels si-multaneously (Raudenbush & Bryk, 2002). HLM allows themodeling of student-level outcomes within classrooms andthen the identification and modeling of between-classroomdifferences. According to Miller and Murdock (2007), agreat advantage of this technique when studying the effectof classroom structure is that it makes it possible to disen-tangle student and classroom as the effect accounted for bythe nesting data. Furthermore, estimates obtained by usingHLM are also more reliable because this method adjusts forsampling errors (Raudenbush & Bryk, 2002).

Goal of the Study

The aim of the present study was to explore the effectof teachers’ beliefs on secondary school students’ (Grades7–11) cognitive engagement and achievement in mathe-matics. To take into account the nested structure of ourdata, we used the HLM technique to assess whether teach-ers’ expectancies and general sense of efficacy influencedstudents’ changes in achievement and engagement over a 1-year period, while acknowledging individual characteristicsand shared experiences in the classroom. In line with thisfirst goal, we hypothesized that when teachers report high ex-pectancies and self-efficacy, students would display increasedcognitive engagement and achievement over a year.

Finally, we tested whether teachers’ beliefs moderated therelationships between students’ previous achievement andtheir engagement and achievement one year later. This lastgoal allowed us to evaluate whether teachers’ contributionwas similar for every student, or whether it changed forhigh versus low performers. Based on previous work (Capraraet al., 2006), we hypothesized that underachievers might bemore negatively affected by teachers’ low expectations andgeneral sense of self-efficacy than high-achieving students.Conversely, we expected that when teachers’ report posi-tive subjective beliefs about their students, the impact onstudent achievement and engagement would be greater forhigh versus low achievers.

Method

Sample and Procedure

The sample was drawn from the New Approaches NewSolutions (NANS) longitudinal study. Overall, more than30,000 French-speaking students from 69 low-SES sec-ondary schools (Grades 7–11) across the province of Quebec(Canada) participated in this project. The NANS longitu-dinal study was originally undertaken to assess the effectof a large-scale governmental initiative that meant to in-crease the academic success of adolescents from disadvan-taged communities.

In the present study, we used data collected during twoconsecutives years, in 2004 (T1) and 2005 (T2). To selectour final sample, we chose all students in Grades 7–11 stu-dents who agreed to participate in the project at T1 andmatched those students with the teacher they had duringthe next academic year (T2). Our final sample comprised79 teachers (55% men) and 1,364 students from 33 schools.Students (46.2% boys) were aged between 12 and 18 years(M age = 14.66 years, SD = 1.46 years) and all attended aregular mathematics classroom at T1 (Grades 7–10) and T2(Grades 8–11). Teachers varied in age (M age = 37.76 years,SD = 10.80 years) and in their number of years of experiencein teaching (M = 5 years, SD = 6.09 years).

Between April and June of 2004 (T1) and 2005 (T2),students completed self-report questionnaires administered

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4

322 The Journal of Educational Research

in their classroom by trained graduate students during a 1-hr period. Teachers’ questionnaires were administered onlyat T2, between the months of January and March 2005.We obtained active parental and student consent for allparticipants in the project.

Measures

Teachers’ beliefs. Measures of teachers’ beliefs were specif-ically elaborated for the NANS evaluation project. To en-sure the content validity of these scales, we followed a three-step process. First, a panel of three academic experts devel-oped a list of items measuring teachers’ expectancies, generalsense of efficacy, and satisfaction with students. Second, apanel of four teachers, all pedagogical consultants in theirrespective school boards, read the items and proposed sev-eral modifications. Third, we distributed this questionnaireto 2,152 teachers and conducted exploratory factor analyses(EFA) and internal consistency analyses (Cronbach’s α) totest construct and internal validity. EFA results showed thatitem factor loadings (between .731 and .893) and commu-nalities (between .540 and .803) were high for all scales,which indicates good reliability of the measures. Each scaleis described more deeply subsequently.

Teacher expectancies. Teachers reported on their ex-pectancies about students’ ability to succeed in mathematicsusing three items (Cronbach’s α = .79) that tapped whetherteachers believed their students presented motivational, aca-demic, or cognitive limitations undermining their academicsuccess (e.g., “Indicate the proportion of your students forwhom motivation represents a serious obstacle in their aca-demic development”). For each item, teachers rated theiranswers on a 6-point Likert-type scale ranging from 1 (forpractically no students) to 6 (for practically all of my students).

Teacher general sense of efficacy. Teachers’ self-efficacy wasmeasured using a 3-item self-report scale (Cronbach’s α =.73; e.g., “No matter what I do, the lack of motivation of thestudents in my school keeps them from succeeding”). Re-sponses were evaluated on a 6-point Likert-type scale rang-ing from 1 (completely disagree) to 6 (fully agree). This scalewas reversely coded because the items were stated negatively.

Student Cognitive Engagement and Achievement inMathematics

Cognitive engagement. We measured students’ cognitiveengagement using one validated subscale of the Echelle mul-tidimensionelle de motivation pour les apprentissage scolaires(EMMAS; Ntamakiliro, Monnard, & Gurtner, 2000). Thisscale assessed the time and effort students were ready toinvest in mathematics-related activities (e.g., “How muchtime are you ready to spend in mathematics?”). This scalecomprised three items (Cronbach’s α = .85) and students’

answers were rated on a 7-point Likert-type scale rangingfrom 1 (strongly agree) to 7 (strongly disagree).

Achievement. We assessed students’ T1 and T2 grades inmathematics using one self-report question (e.g., “Duringthis school year, what is your average mark in math?”).Students’ answer to this question was rated on a 35-pointinterval scale (0%–35% to 95%–100%).

Analytic Strategy

Our analytic strategy comprised several steps. First, weexplored the correlations between predictors and outcomes.Next and for the following steps, we used the HLM Soft-ware version 6.2 (Raudenbush & Bryk, 2002). This softwareallowed us to account for the nested structure of our dataand to partition the variance that lies within and betweenclassrooms (Raudenbush & Bryk, 2002). As a first step, weevaluated the proportion of classroom variations by testing aseries of two-level unconditional models that predicted stu-dent performance and cognitive engagement at T2. Thesemodels allowed us to estimate students’ mean engagementand achievement during the school year so as to calculatethe intraclass correlations. The intraclass correlation coef-ficients (ρ) correspond to the proportion of variance thatlies between classrooms. We calculated these coefficientsat T2 for each outcome variable based on the followingformula:

ρ = τ00/(σ 2 + τ00

), (1)

where τ 00 represents the variance of the true classroommeans and σ 2 represents the within-student variability. Toaccount for the between-school variance attributed to stu-dent grades, we next added to the model student performanceat T1 and estimated the proportion of variance explained bythis variable with the following formula:

τ = τ00(random ANOVA) − τ00(MEANGRADES)/τ00(RandomANOVA).

(2)

To examine the effect of teachers’ beliefs on student en-gagement and achievement, we entered teachers’ variablesas Level 2 predictors and estimated the intercept of eachoutcome variable. In both models, we controlled for sex,age, and T1 student achievement as Level 1 predictors. Inthe cognitive engagement model, we also controlled for cog-nitive engagement at T1. To finally test whether teachers’beliefs influence students differently based on their previousgrades, we entered teachers’ expectancies and general senseof efficacy as Level 2 predictors but instead of using thesepredictors to estimate the intercept, we used them to esti-mate the within-classroom slopes for T1 achievement. Forthis step, only the intercept parameter in the Level 1 model

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4

The Journal of Educational Research 323

TABLE 1. Correlations Among All Variables for the Total Sample

Variable 1 2 3 4 5 6 7 8

1. Achievement T2 —2. Cognitive engagement T2 .22∗ —3. Sex −.06∗ .11∗ —4. Age −.12∗ −.13∗ −.05∗ —5. Achievement T1 .47∗ .18∗ .03 −.09∗ —6. Cognitive engagement T1 .07∗ .52∗ .11∗ −.08∗ .11∗ —7. Expectancy .09∗ .01 .03 −.18∗ .02 .03 —8. Self-efficacy .05∗ .03 .03 −.03 −.04 −.04 .55∗ —

∗p < .05.

and student-level variables were assumed to vary accordingto the type of classrooms.

Results

Table 1 presents the correlations between the differentteacher dimensions. As shown in the table, correlationswere all in the expected direction and most of them weresmall (between .07 and .22). Unsurprisingly, correlationsbetween aggregated measures of teachers’ expectancy andself-efficacy and between measures of student achievementand cognitive engagement over time (T1 and T2) were high(around .50).

Next, we assessed classroom variations on studentachievement and cognitive engagement. Student means,standard deviations, and intraclass correlations for eachoutcome are presented in Table 2. Overall, this tableindicates that 14.1% and 7.4% of student variations inachievement and cognitive engagement, respectively, liebetween classrooms. This table also reports that approxi-mately 5% of classroom variations on achievement and cog-nitive engagement is explained by students’ former (T1)achievement.

TABLE 2. Descriptive Statistics, IntraclassCorrelations, and Confidence Interval of PlausibleValues for Achievement and Cognitive Engagement

CognitiveAchievement engagement

M (γ 00) 72.59 5.59SD (σ 2) 13.64 1.18Intraclass correlation 0.141 0.074Variance explained by

achievement0.054 0.046

Predicting Student Achievement and Cognitive Engagement inMathematics

Table 3 first presents the contribution of Level 1 predictorson student achievement in mathematics at T2. As indicatedin this table, results indicate that mathematics achievementat T1 represented a positive predictor of achievement at T2,while sex and age at T1 were not related to this outcome.Shown in Table 3 is the contribution of teachers’ beliefs onstudent mean achievement (β0). We found that teachers’expectancies about students’ success and teachers’ sense ofself-efficacy increased student mean achievement at T2. Fi-nally, when testing the moderating effect of teachers’ beliefson the relationship between students’ previous achievementand their achievement one year later, results indicate thatthe slope for mathematics achievement at T1 was influencedby classroom characteristics. However, it was not influencedby teachers’ beliefs. That is, the influence of teachers’ ex-pectancies and self-efficacy on students’ T2 achievementdid not vary based on students’ grade at T1.

Table 3 also present the contribution of Level 1 predic-tors on student cognitive engagement at T2. Results showthat being a girl, an older student, presenting higher engage-ment and achievement at T1 was significantly related to stu-dents’ engagement. However, teachers’ expectancies aboutstudents’ success and teachers’ sense of self-efficacy were notsignificantly related. Finally, when testing the moderatingeffect of teachers’ beliefs, results indicated that the slope formathematics achievement at T1 did not vary significantlyacross classrooms, suggesting that the relationship betweenstudent T1 achievement and cognitive engagement does notvary based on teachers’ expectancies or sense of efficacy.

Discussion

In recent decades, researchers have become increasinglyinterested in understanding the extent to which teachers’beliefs can promote students’ academic achievement andmotivation. Yet, most studies interested by this topic arecross-sectional and do not account for the independence that

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4

324 The Journal of Educational Research

TABLE 3. Contribution of Level 1 and Level 2 Predictors on Student Achievement and Cognitive Engagement in Mathematicsat T2

Fixed Effects Achievement Cognitive Engagement

Predictors Coefficient SD t ratio Coefficient SD t ratio

Intercept (β0) 46.947 5.59 8.11∗ 2.256 0.41 5.45∗

Expectancy (γ 01) 2.011 0.47 4.29∗ 0.038 0.04 0.91Efficacy (γ 02) 1.133 0.416 2.724 0.018 0.04 0.49Girls (β1) 0.709 0.72 0.98 0.245 0.08 2.90∗

Age (β2) −0.499 0.29 −1.71 −0.043 0.02 −2.55∗

Math achievement (T1) (β3) 0.416 0.03 2.52∗ 0.008 0.01 4.47∗

Expectancy (γ 31) 0.007 0.04 0.17 — — —Efficacy (γ 32) 0.004 0.03 0.12 — — —Engagement at T1 (β4) — — — 0.483 0.02 22.33∗

Random effects Estimate df p Estimate df p

Mean achievement, µ0j 152.512 63 0.000 0.071 63 0.002Math achievement, µ1j 0.0321 63 0.000 0.000 65 0.263Student level, rij 126.977 1.000

∗p < .05.

lies between students of the same classroom. In this studywe addressed these limitations by using a longitudinal sam-ple to examine whether mathematics teachers’ expectanciesand self-efficacy influence low-SES students’ cognitive en-gagement and academic achievement over a year. Further-more, we accounted for the dependency between observa-tions made by students who belong to the same classroomenvironment and who were taught by the same teacher.

As expected, our results first showed that variationsexisted between classrooms. In some classes, studentswere more engaged and achieved better outcomes than inothers. Yet, classroom variations were up to two times moreimportant for performance than for engagement. Moreover,students’ past history of achievement accounted for alarge proportion of these variations. This suggests that thedifferences that lie between classrooms regarding studentengagement and achievement can mostly be attributedto student prior academic difficulties or success and areprobably a direct consequence of the ability grouping pro-cedures that occur in many schools. Overall, such findingsecho earlier work that shows the strength of the associationbetween student prior achievement and later academicperformance and engagement (Anderman & Midgley, 1997;Bouffard, Boileau, & Vezeau, 2001; Eccles et al., 1983).The long-term effect of achievement on adolescents’ effortsand grades constitutes a good news for high performers whohave greater chances of remaining engaged and successfulwhile in school. However, the continuity in adolescents’achievement is far less advantageous for low achieverswho present important difficulties, because the chance thatpast negative experiences become more difficult to changeseems to be greatly increased for these students (Alexander,Entwisle, & Dauber, 1993; Alexander et al., 1997). This

could be even truer when they come from poor families andare placed in classrooms where the teaching methods do notmatch their needs (Eccles, Wigfield, Midgley, et al., 1993).

Apart from their individual characteristics, teachers’ be-liefs directly predicted students’ academic experience inmathematics. As expected, the more teachers maintain highexpectations and the more efficacious they feel in helpingtheir students succeed, the more students’ achievement in-creased over the year. In line with previous work (Ashton& Webb, 1986; Evans, 1998; Podell & Soodak, 1993; Rosset al., 2001), such findings suggest that when teachers feelenthusiastic and competent and transmit their enthusiasmto students by maintaining high standards and sending themthe message that they can succeed, they contribute to stu-dents’ academic attainment. Nevertheless, teachers’ influ-ence in this study seems more limited than it was expectedat the outset. Teachers’ beliefs about students were not re-lated to student engagement. Is it because teachers’ effecton students has been overestimated? That would be surpris-ing. A more plausible explanation might be that students’motivation and willingness to involve time and efforts inmathematics activities might be more stable and difficult tochange within an academic year, compared with students’yearly grades. Therefore, a teacher’s beliefs might not be ableto alter such students’ attitudes during one academic year andthat could be even truer if the practices students are subjectto are quite homogeneous from one year to another. Actu-ally, it would be plausible that students’ behaviors and atti-tudes within the classroom could be influenced by their pastacademic experience and thus, by the different teachers theywere taught by during their academic life-course. Therefore,to understand student engagement within the classroom,research will probably have to look at teaching influences

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4

The Journal of Educational Research 325

rather than teachers’ influence and study the whole set ofpractices used by many different teachers over time.

Finally, teachers’ attitudes did not contribute differen-tially to the academic experience of successful and unsuc-cessful students. Such findings were quite surprising. On onehand, we first expected that the repeated success teachers’ ex-perience with higher achieving students would have consol-idated their positive attitudes about these students (Capraraet al., 2006) and promoted their academic achievement evenmore. However, the fact that this claim was not supportedcould be explained by the presence of a ceiling effect. In-deed, because the grades of high achievers were already farabove the mean, they probably could not have increasedmore substantially, regardless of teachers’ attitudes. On theother hand, we also expected that students who reported lowacademic achievement in the previous school year would bemore negatively affected by teachers’ negative perceptions,than their higher achieving peers. Yet, this claim was alsounsupported. Low achievers’ past history of underachieve-ment and motivation (Alexander et al., 1993) may partlyaccount for this lack of differential effect. Indeed, the atti-tudes of a single teacher during a school year might not beable to significantly change the ongoing academic trajectoryof students presenting great academic difficulties. Rather,a developmental perspective would suggest that the trajec-tory of many of these students is probably strongly imbeddedsince the elementary school years, and is thus more diffi-cult to change (Alexander et al., 1997). The fact that theassessment of teachers’ beliefs was based on teachers ratherthan on students’ perceptions may also somehow explainthe lack of differential effect of teachers’ beliefs. Actually,it is plausible that teachers’ influence on low achievers ismore negative when students themselves perceive negativeattitudes from their teacher (Brattesani, Weinstein, & Mar-shall, 1984). Finally, although unexpected, our results stillremain reassuring. Even if they suggest that all students canbe affected by a mathematics teacher who has a negativeattitude in the classroom, they also suggest that teachersare usually accurate (Jussim & Harber, 2005). Thus, theeffect of teachers’ expectancies and general sense of self-efficacy on student academic accomplishment is similar forall students, regardless of their grades. Clearly, this repre-sents good news for at-risk youths who do not seem to bemore affected by teachers’ beliefs than their higher achievingcounterparts.

Implications for Research

The results from the study point out that teachers’ self-perceived beliefs did not differentially influence students’subjective experience in the classroom according to theirpast experience of achievement. Yet, because teachers’ be-liefs can be interpreted differently from one student to an-other, the way high and low achievers perceive these be-liefs might be more closely related to their engagement andachievement than to their teachers’ perceptions (Ludtke,

Robitzsch, Trautwein, & Kunter, 2009). Therefore, in thefuture, it would be important to study and compare bothstudents’ and teachers’ perceptions to disentangle their re-spective contributions to students’ academic experience.

Another topic to investigate in future researchers wouldbe whether the way teachers evaluate students or managetheir learning and behaviors, could have a more importantdirect or indirect effect on student achievement and engage-ment. As stated by Kyriakides and Creemers (2008), effortsshould be made to understand how teachers’ practices, andmore specifically how the quality of teachers’ practices andthe differentiation of these practices for distinct groups ofstudents, can have an impact on achievement-motivationoutcomes. To get an exhaustive portrayal of youth academicexperience, future researchers should study the whole setof practices used by the different teachers a student meetthroughout his academic experience.

Another important implication for future researcherswould be to look at the role that school factors, such asschool socioeducational climate, play in teacher and studentexperience in class. Although classrooms are very importantcontexts for achieving educational effectiveness, teachers,as well as teaching quality, time, and opportunities are alsoinfluenced by school factors (Creemers, 1994). Future re-searchers should thus look more deeply at the way class-room dynamics might be influenced by the structure andorganization of the whole school. Overall, more work hasto be done before researchers can fully understand the cir-cumstances underlying students’ cognitive engagement andachievement in the classroom. From a transactional per-spective (Sameroff & Fiese, 1990), these circumstances areprobably the result of a complex set of interactions that existbetween students and teachers during classroom activities aswell as between students’ own characteristics and socioeco-nomic background.

Implications for Practice

A lot of work remains before research can clearly under-stand the specific role teachers play on students’ academicexperience. Yet, from now on, it remains necessary to sup-port teachers, make them feel more efficacious, and helpthem develop more positive attitudes about students’ abilityto succeed. For example, our findings should bring schooladministrators and stakeholders to be more aware of theconditions that can favor teachers’ well-being as well asprofessional satisfaction in school environments located inlow-SES communities. Considering that satisfied teachersare more successful with their students (Ashton & Webb,1986; Podell & Soodak, 1993; Ross et al., 2001), such initia-tives could promote a positive classroom climate, improveteacher–student relationships, and ultimately, enhance stu-dents’ achievement-motivation. As underlined by Desimone(2009), to be effective, professional development would haveto focus primarily on subject matter content, favor teach-ers’ collective participation and active learning, be coherent

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4

326 The Journal of Educational Research

with teachers’ past experience and beliefs, and be sufficientlyintensive in duration.

Moreover, it becomes important to develop and financeresearch-intervention projects in partnership with schools,to evaluate different teaching practices that promoteacademic success and motivation for all students. It wouldalso be advisable that these projects integrate and evaluateuniversal and targeted interventions to promote cognitiveengagement and academic achievement for boys and girlspresenting important difficulties. These interventionsought to be inspired by research-based programs knownfor their effectiveness in promoting student motivationand achievement in general (e.g., Check and Connect[A. R. Anderson, Christenson, Sinclair, & Lehr, 2004],First Thing First [The Institute for Research and Reformin Education, 2003], PATHE [Gottfredson, 1986], STEP[Felner, Seitsinger, Brand, Burns, & Bolton, 2007]) orin different subject matters such as mathematics (e.g.,MSP-Motivation Program [Karabenick & Maehr, 2008]).

Finally, our results suggest that the beliefs of one teachercan promote low-SES students’ engagement and academicachievement, but are probably not sufficient to bring aboutdifferential and more significant change to the academicpathway of students with difficulties. To observe real trans-formations in these students, there is a need to developand implement intensive and multimodal interventions tar-geting the development of students’ skills, knowledge, andcompetency beliefs, but also the improvement of teachers’instructional strategies.

Limitations

This study is not without limitations. First, the samplefor this study was composed of students and teachers fromlow-SES secondary schools in Quebec. Therefore, the gen-eralization of our findings is restricted to this population.Second, the assessment of teachers’ beliefs was based onteachers as the only source of measurement. Although teach-ers are usually considered a reliable source (Feldlaufer et al.,1988), their perceptions may be somewhat biased (Wubbels,Brekelmans, & Hooymayers, 1992). Further, there are nu-ances in teachers’ practices that self-report questionnairescannot identify. To study these nuances, classroom observa-tions or student assessments could have been more effectivemethods of data collection. A third limitation of this studywas related to the small classroom variations found on teach-ers’ self-reports of attitudes and practices. These variationsmight reflect a bias in teacher self-assessment or the impor-tant homogeneity that exists in the training of teachers inQuebec. Finally, the limited internal validity of our teacherefficacy scale could also explain the lack of expected findings.

REFERENCES

Alexander, K. L., Entwisle, D. R., & Dauber, S. L. (1993). First-gradeclassroom behavior: Its short- and long-term consequences for schoolperformance. Child Development, 64, 801–814.

Alexander, K. L., Entwisle, D. R., & Horsey, C. S. (1997). From first gradeforward: Early foundations of high school dropout. Sociology of Education,70, 87–107.

Alexander, K. L., Entwisle, D. R., & Thompson, M. S. (1987). Schoolperformance, status relations, and the structure of sentiment: Bringingthe teacher back in. American Sociological Review, 52, 665–682.

Ames, C. (1992). Classrooms: Goals, structures, and student motivation.Journal of Educational Psychology, 84, 261–271.

Ames, C., & Archer, J. (1988). Achievement goals in the classroom: Stu-dents’ learning strategies and motivation processes. Journal of EducationalPsychology, 80, 260–267.

Anderman, E. M., & Maehr, M. L. (1994). Motivation and schooling inthe middle grades. Review of Educational Research, 64, 287–309.

Anderman, E. M., & Midgley, C. (1997). Changes in achievement goal ori-entations, perceived academic competence, and grades across the tran-sition to middle-level schools. Contemporary Educational Psychology, 22,269–298.

Anderson, A. R., Christenson, S. L., Sinclair, M. F., & Lehr, C. A. (2004).Check & connect: The importance of relationships for promoting en-gagement with school. Journal of School Psychology, 42, 95–113.

Anderson, R., Greene, M., & Loewen, P. (1988). Relationships amongteachers’ and students’ thinking skills, sense of efficacy, and studentachievement. The Alberta Journal of Educational Research, 34, 148–165.

Archambault, I., Janosz, M., Morizot, J., & Pagani, L. S. (2009). Adolescentbehavioral, affective, and cognitive engagement in school: Relationshipto dropout. Journal of School Health, 79, 402–409.

Ashton, P. T., & Webb, R. B. (1986). Making a differences: Teachers’ senseof efficacy and student achievement. New York, NY: Longman.

Assor, A., Kaplan, H., & Roth, G. (2002). Choice is good, but relevanceis excellent: Autonomy-enhancing and suppressing teacher behaviourspredicting students’ engagement in schoolwork. British Journal of Educa-tional Psychology, 72, 261–278.

Bandura, A. (1993). Perceived self-efficacy in cognitive development andfunctioning. Educational Psychologist, 28, 117–148.

Bouffard, T., Boileau, L., & Vezeau, C. (2001). Students’ transition fromelementary to high school and changes of the relationship between mo-tivation and academic performance. European Journal of Psychology ofEducation, 16, 589–604.

Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and childdevelopment. Annual Review of Psychology, 53, 371–399.

Brattesani, K. A., Weinstein, R. S., & Marshall, H. H. (1984). Studentperceptions of differential teacher treatment as moderators of teacherexpectation effects. Journal of Educational Psychology, 76, 236–247.

Brophy, J. (1983). Conceptualizing students’ motivation. Educational Psy-chologist, 18, 200–215.

Caprara, G. V., Barbaranelli, C., Steca, P., & Malone, P. S. (2006). Teach-ers’ self-efficacy beliefs as determinants of job satisfaction and students’academic achievement: A study at the school level. Journal of SchoolPsychology, 44, 473–490.

Carr, M. (1996). Metacognitive, motivational, and social influences onmathematics strategy use. In M. Carr (Ed.), Motivation in mathematics(pp. 89–111). Cresskill, NJ: Hampton.

Chouinard, R., & Roy, N. (2008). Changes in high-school students’ compe-tence beliefs, utility value and achievement goals in mathematics. BritishJournal of Educational Psychology, 78, 31–50.

Connell, J. P., & Wellborn, J. G. (1991). Competence, autonomy, and re-latedness: A motivational analysis of self-system processes. Hillsdale, NJ:Erlbaum.

Creemers, B. P. M. (1994). The effective classroom. London, UK: Cassell.Deci, E. L., & Ryan, A. M. (1985). Intrinsic motivation and self-determination

in human behavior. New York, NY: Plenum.Desimone, L. M. (2009). Improving impact studies of teachers’ professional

development: Toward better conceptualizations and measures. Educa-tional Researcher, 38, 181–199.

Eccles, J. S. (1984). Sex differences in achievement patterns. In T. Son-deregger (Ed.), Nebraska symposium on motivation, 1983 (pp. 97–132).Lincoln: University of Nebraska Press.

Eccles, J. S., Adler, T. F., Futterman, R., Goff, S. B., Kaczala, C. M., Meece,J. L., et al. (1983). Expectancies, values, and academic behaviors. In J. T.Spence (Ed.), Achievement and achievement motivation (pp. 75–146). SanFrancisco, CA: Freeman.

Eccles, J. S., Midgley, C., Wigfield, A., Buchanan, C. M., Reuman, D.,Flanagan, C., et al. (1993). Development during adolescence: The impactof stage-environment fit on young adolescents’ experiences in schools andin families. American Psychologist, 48, 90–101.

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4

The Journal of Educational Research 327

Eccles, J. S., Wigfield, A., Harold, R. D., & Blumenfeld, P. (1993). Ageand gender differences in children’s self- and task perceptions duringelementary school. Child Development, 64, 830–847.

Eccles, J. S., Wigfield, A., Midgley, C., Reuman, D., Mac Iver, D., &Feldlaufer, H. (1993). Negative effects of traditional middle schools onstudents’ motivation. The Elementary School Journal, 93, 553–574.

Evans, L. (1998). The effects of senior management teams on teacher moraleand job satisfaction: a case study of Rockville County Primary School.Educational Management and Administration, 26, 417–428.

Feldlaufer, H., Midgley, C., & Eccles, J. S. (1988). Student, teacher, andobserver perceptions of the classroom environment before and after thetransition to junior high school. Journal of Early Adolescence, 8, 133–156.

Felner, R. D., Seitsinger, A. M., Brand, S., Burns, A., & Bolton, N. (2007).Creating small learning communities: Lessons from the project on high-performing learning communities about “what works” in creating pro-ductive, developmentally enhancing, learning contexts. Educational Psy-chologist, 42, 209–221.

Goddard, R. D., Tschannen-Moran, M., & Hoy, W. K. (2001). A multilevelexamination of the distribution and effects of teacher trust in studentsand parents in urban elementary schools. The Elementary School Journal,102, 3–17.

Gottfredson, D. C. (1986). An empirical test of school-based environmentaland individual interventions to reduce the risk of delinquent behavior.Criminology, 24, 705–731.

Harris, M. J., & Rosenthal, R. (1985). Mediation of interper-sonal expectancy effects: 31 meta-analyses. Psychological Bulletin, 97,363–386.

Hughes, J., & Kwok, O. (2007). Influence of student-teacher and parent-teacher relationships on lower achieving readers’ engagement andachievement in the primary grades. Journal of Educational Psychology,99, 39–51.

The Institute for Research and Reform in Education (IRRE). (2003). Firstthings first: A framework for successful school reform (4th ed.). Kansas City,MO: E. M. Kauffman Foundation.

Jacobs, J. E., Lanza, S., Osgood, D., Eccles, J. S., & Wigfield, A. (2002).Changes in children’s self-competence and values: Gender and domaindifferences across grades one though twelve. Child Development, 73,509–527.

Janosz, M., Archambault, I., Morizot, J., & Pagani, L. (2008). Schoolengagement trajectories and their differential predictive relations todropout. Journal of Social Issues, 64, 21–40.

Jussim, L., Eccles, J., & Madon, S. J. (1996). Social perception, socialstereotypes, and teacher expectations: Accuracy, and the quest for thepowerful self-fulfilling prophecy. Advances in Experimental Social Psychol-ogy, 29, 281–388.

Jussim, L., & Harber, K. D. (2005). Teacher expectations and self-fulfillingprophecies: Knowns and unknowns, resolved and unresolved controver-sies. Personality and Social Psychology Review, 9, 131–155.

Karabenick, S. A., & Maehr, M. L. (2008). MSP–Motivation assessmentprogram. Ann Arbor: University of Michigan.

Kyriakides, L., & Creemers, B. P. M. (2008). Using a multi-dimensionalapproach to measure the impact of classroom-level factors upon studentachievement: a study testing the validity of the dynamic model. SchoolEffectiveness and School Improvement, 19, 183–205.

Lau, S., & Nie, Y. (2008). Interplay between personal goals and classroomgoal structures in predicting student outcomes: A multilevel analysisof person-context interactions. Journal of Educational Psychology, 100,15–29.

Lee, V. E., & Loeb, S. (2000). School size in Chicago Elementary Schools:Effects on teachers’ attitudes and students’ achievements. American Ed-ucational Research Journal, 37, 3–31.

Ludtke, O., Robitzsch, A., Trautwein, U., & Kunter, M. (2009). Assess-ing the impact of learning environment: How to use student rating ofclassroom or school characteristics in multilevel modeling in multilevelmodeling. Contemporary Educational Psychology, 34, 120–131.

Marsh, H. W. (1989). Age and sex effects in multiple dimensions of self-concept: Preadolescence to early adulthood. Journal of Educational Psy-chology, 81, 417–430.

Marsh, H. W., Trautwein, U., Ludtke, O., Koller, O., & Baumert, J.(2005). Academic self-concept, interest, grades, and standardized testscores: Reciprocal effects models of causal ordering. Child Development,76, 397–416.

Midgley, C., Feldlaufer, H., & Eccles, J. S. (1988). The transition to juniorhigh school: Beliefs of pre- and posttransition teachers. Journal of Youthand Adolescence, 17, 543–562.

Midgley, C., Feldlaufer, H., & Eccles, J. S. (1989). Student/teacher relationsand attitudes toward mathematics before and after the transition to juniorhigh school. Child Development, 60, 981–992.

Miller, A. D., & Murdock, T. B. (2007). Modeling latent true scores todetermine the utility of aggregate student perceptions as classroom in-dicators in HLM: The case of classroom goal structures. ContemporaryEducational Psychology, 32, 83–104.

Muijs, R. D., & Reynolds, D. (2000). School effectiveness and teacher effec-tiveness: some preliminary findings from the evaluation of the Mathemat-ics Enhancement Program. School Effectiveness and School Improvement,11, 273–303.

Newmann, F. M., Rutter, R. A., & Smith, M. S. (1989). Organizationalfactors that affect school sense of efficacy, community and expectations.Sociology of Education, 62, 221–238.

Ntamakiliro, L., Monnard, I., & Gurtner, J. L. (2000). Mesure de la motiva-tion scolaire des adolescents: construction et validation de trois echellescomportementale [Measure of adolescents’ academic motivation: Devel-opment and validation of three behavioral scales] L’Orientation Scolaireet Professionnelle, 29, 673–693.

Pajares, F., & Graham, L. (1999). Self-efficacy, motivation constructs, andmathematics performance of entering middle school students. Contem-porary Educational Psychology, 24, 124–139.

Patrick, H., Turner, J. C., Meyer, D. K., & Midgley, C. (2003). How teach-ers establish psychological environments during the first days of school:Associations with avoidance in mathematics. Teachers College Record,105, 1521–1558.

Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulatedlearning components of classroom academic performance. Journal of Ed-ucational Psychology, 82, 33–40.

Pintrich, P. R., & Schunk, D. H. (1996). Motivation in education: Theory,research, and applications. Englewood Cliffs, NJ: Prentice Hall.

Podell, D. M., & Soodak, L. C. (1993). Teacher efficacy and bias in specialeducation referrals. The Journal of Educational Research, 86, 247–253.

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Appli-cations and data analysis methods (2nd ed.). Thousand Oaks: CA: Sage.

Raudenbush, S. W., & Kasim, R. M. (1998). Cognitive skill and economicinequality: Findings from the National Adult Literacy Survey. HarvardEducational Review, 68, 33–79.

Reeve, J., Bolt, E., & Cai, Y. (1999). Autonomy-supportive teachers: Howthey teach and motivate students. Journal of Educational Psychology, 91,537–548.

Rosenthal, R., & Jacobson, L. (1968). Pygmalion in the classroom. New York,NY: Holt, Rinehart & Winston.

Ross, J. A. (1992). Teacher efficacy and the effect of coaching on studentachievement. Canadian Journal of Education, 17, 51–56.

Ross, J. A. (1998). The antecedents and consequences of teacher efficacy.In J. Brophy (Ed.), Advances in research on teaching: Vol. 7. Expectationsin the classroom (pp. 49–74). Greenwich, CT: JAI Press.

Ross, J. A., Hogaboam-Gray, A., & Hannay, L. (2001). Effects of teacherefficacy on computer skills and computer cognitions of K–3 students.Elementary School Journal, 102, 141–156.

Ryan, R. M., & Deci, E. L. (2002). Overview of self-determination theory: Anorganismic-dialectical perspective. Rochester, NY: University of RochesterPress.

Ryan, A. M., & Patrick, H. (2001). The classroom social environmentand changes in adolescents’ motivation and engagement during middleschool. American Educational Research Journal, 38, 437–460.

Sameroff, A. J., & Fiese, B. H. (1990). Transactional regulation and earlyintervention. In S. J. Meisels & J. P. Shonkoff (Eds.), Early intervention:A handbook of theory, practice, and analysis (pp. 119–149). New York, NY:Cambridge University Press.

Stipek, D., & Daniels, D. (1988). Declining perceptions of competence: Aconsequence of changes in the child or in the educational environment?Journal of Educational Measurement Psychology, 80, 352–356.

Tschannen-Moran, M., & Hoy, A. W. (2001). Teacher efficacy: Capturingan elusive construct. Teaching and Teacher Education, 17, 783–805.

Tschannen-Moran, M., Woolfolk Hoy, A., & Hoy, W. K. (1998). Teacherefficacy: Its meaning and measure. Review of Educational Research, 68,202–248.

Turner, J. C., Meyer, D. K., Cox, K. E., Logan, C., DiCintio, M., & Thomas,C. T. (1998). Creating contexts for involvement in mathematics. Journalof Educational Psychology, 90, 730–745.

Van de Gaer, E., De Fraine, B., Pustjens, H., Van Damme, J., De Munter, A.,& Onghena, P. (2009). School effects on the development of motivationtoward learning tasks and the development of academic self-concept

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4

328 The Journal of Educational Research

in secondary education: A multivariate latent growth curve approach.School Effectiveness and School Improvement: An International Journal ofResearch, Policy and Practice, 20, 235–253.

Wigfield, A., Eccles, J. S., Schiefele, U., Roeser, R. W., & Davis-Kean, P.(2006). Development of achievement motivation. Hoboken, NJ: Wiley.

Wubbels, T., Brekelmans, M., & Hooymayers, H. P. (1992). Do teacherideals distort the self-reports of their interpersonal behavior? Teachingand Teacher Education, 8, 47–58.

AUTHORS NOTE

Isabelle Archambault is Professor at the School of Psy-choeducation, Universite de Montreal, and member of theSchool Environment Research Group. Her research in-

terests focus upon developmental pathways of schooling,educational engagement/ disengagement processes, schooldropout, and the influences of teachers and classroom goalstructure on student motivation.

Michel Janosz is Director of the School EnvironmentResearch Group and Professor at the School of Psycho-Education, Universite de Montreal. He is pursuing researchon the development of student engagement and schooldropout, on school violence and on the efficacy of large-scale interventions to prevent school failure.

Roch Chouinard is full Professor of Educational Psychol-ogy at Universite de Montreal. His research interests areachievement motivation and classroom management.

Dow

nloa

ded

by [

Lau

rent

ian

Uni

vers

ity]

at 0

8:27

11

Oct

ober

201

4