Predictors of Cheating among Early Adolescents: Academic and Social Motivations

Contemporary Educational Psychology 26, 96–115 (2001) doi:10.1006/ceps.2000.1046, available online at http://www.idealibrary.com on

Predictors of Cheating among Early Adolescents: Academic and Social Motivations Tamera B. Murdock, Natalie M. Hale, and Mary Jo Weber University of Missouri—Kansas City This study examined the relations between middle school students’ self-reported cheating and several indicators of academic and social motivation. It was hypothesized that students’ academic self-efficacy and personal and classroom goal orientations would predict cheating. Social motivations were presumed to predict cheating above and beyond achievement motivation. Four dimensions of relationships within schools were measured: participation structure, teacher commitment and competence, teacher respect, and sense of school belonging. Logistic regression analyses were used to predict classification as a cheater or noncheater. Although academic motivation variables predicted cheating, the addition of the relationship variables significantly improved the classification rates. The final model included grade in school, academic self-efficacy, extrinsic goal orientation, participation structure, teacher commitment, and teacher respect.  2001 Academic Press

Much attention has been given to understanding individual and contextual variables associated with students’ declining motivation and achievement as they make the transition from elementary to middle school. Findings suggest that both the structure of classrooms and schools and the changing relationships between students and teachers underlie students’ diminished interest and performance in school (Anderman & Maehr, 1994; Eccles et al., 1993; Maehr & Midgley, 1991; Midgley, Anderman, & Hicks, 1995; Midgley, Feldhaufer, & Eccles, 1989). Specifically, middle school students’ achievement motivation appears to be negatively affected by an increasing focus on grades and performance, heightened competition among classmates, loss of involvement in decision-making, and impersonal relationships with teachers. A recent study of early adolescents suggests that some of the same factors Thanks are extended to Wendy Briggs and Valerie Tucker for their help with data collection and to Chris Brown for feedback on an earlier version of this manuscript. This research could not have been conducted without the support of the faculty, staff, and students of the participating middle school. Address correspondence and reprint requests to Tamera Murdock, Educational Research and Psychology, 5100 Rockhill Road, University of Missouri—Kansas City, Kansas City, MO 64110-2499. E-mail: [email protected]. 96 0361-476X/01 $35.00

Copyright  2001 by Academic Press All rights of reproduction in any form reserved.

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contributing to maladaptive motivation patterns may also be predictive of another negative academic outcome: cheating (Anderman, Griesinger, & Westerfield, 1998). Among the early adolescents in their study, the same motivational goal structures (e.g., performance goal orientations) that are often associated with decreased cognitive engagement were predictors of self-reported cheating. Given that cheating, like effort, is a means to increase one’s academic success, it seems reasonable that achievement motivational variables account for variation in cheating behavior. Cheating and effort are, however, qualitatively different behaviors in that the former represents a violation of the norms and standards of schooling. As such, achievement motives seem insufficient to explain students’ willingness to cheat (i.e., break the norms). Several psychologists suggest that people are more likely to adopt the goals and standards of others if they have positive relationships with them (Baumeister & Leary, 1995; Bronfenbrenner, 1986; Noddings, 1992). It therefore seems logical that students would be more apt to adhere to the schools’ values regarding cheating to the degree that they perceived their relationships with school officials, such as teachers, as characterized by mutual trust, respect, and caring. Accordingly, this study seeks to expand on Anderman et al.’s (1998) research on middle school students by examining whether social motivational variables add anything to the prediction of individual differences in cheating beyond what can be explained by achievement motivation variables. Cheating not only results in biased assignment of grades, it also interferes with teachers’ ability to use assessment as a mechanism for monitoring and modifying instruction. It is therefore important to identify classroom factors that might support students’ dishonesty. In addition, documenting relations between cheating and teacher–student relationships might provide further impetus for researchers to work to understand the factors affecting the decline in student–teacher relationships that accompany the transition to middle school (Midgley, Feldhaufer, & Eccles, 1989). PATTERNS AND PREVALENCE OF CHEATING IN ADOLESCENCE

Various studies attest to both the actual and perceived ubiquity of cheating among adolescents. Evans and Craig (1990a) found that 61% of middle school students and 71% of high school students perceived cheating to be a serious problem in their school. Steinberg (1996) reported that two-thirds of the adolescents in his studies cheated on a test in the past year, and 50% of high school students in a study by McLaughlin and Ross (1989) admitted to frequent cheating. Moreover, longitudinal data on middle and high school students suggest an increase in the prevalence of cheating over the past 20 years and a decrease in the perceived severity of dishonest behavior (Schab, 1980a, 1980b, 1991). Although college-bound students were more likely to

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cheat than non-college-bound students, and boys cheated more than girls, increases in all groups were apparent over 2 decades. Academic Motivation and Cheating in the Middle School Calabrese and Cochran (1990) suggest that pressure for performance may be a primary motivation underlying students’ decisions to cheat. Indeed, when asked why students cheat, male and female high school students listed ‘‘fear of failure’’ and ‘‘parental insistence on grades’’ as two of their top three reasons (Schab, 1980a, 1991). Similarly, Evans and Craig (1990b) found that middle and high school students and teachers believe that the students who are most likely to cheat have low academic self-concepts and fear of failure. Among college students, there is direct evidence that cheating is inversely related to one’s self-reported ability to insure a successful outcome. For example, Michaels and Miethe (1989) found a positive relation between cheating and fear of failure in a sample of undergraduate students. Accordingly, in this study, we examined the relations between cheating and students’ self-efficacy judgments, an indicator of perceived competence. Evaluations of self-efficacy in a particular domain reflect people’s appraisals of their ability to execute the skills necessary to accomplish a particular goal (Bandura, 1986). We hypothesized that self-efficacy beliefs would predict cheating. More specifically, lower academic self-efficacy was assumed to increase the odds that one would cheat. A recent study suggests that the likelihood of students’ cheating may also depend on their motivational goal orientation (Anderman et al., 1998). Goal theory distinguishes between students who are mastery or task focused and those who are performance focused (Ames & Archer, 1988; Dweck, 1986; Dweck & Legett, 1988). Mastery-oriented students engage in academic tasks for the purpose of learning; they also believe that effort is the primary determinant of performance (Ames & Archer, 1988). In contrast, performanceoriented students try to protect their sense of themselves as high in ability, seek recognition for their achievements, and see high effort as indicative of lower ability (Dweck, 1986). Some researchers divide performance goals into ability goals and extrinsic goals (Pintrich & Garcia, 1991), though in each case the emphasis is on the appraisals one receives, rather than one’s learning. Moreover, Middleton and Midgley (1997) have provided some evidence that ability goals can take two forms: a desire to appear intelligent, referred to as approach goals or a desire to avoid appearing incompetent (i.e., avoidance goals). Classrooms and schools have also been described as having goal structures that vary in their emphasis on mastery versus performance goals and that influence students’ own personal goal orientations (Ames, 1992; Maehr & Midgley, 1991). Although cheating seems antithetical to mastery goals, a focus on performance could augment cheating since it is a plausible strategy for both re-

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wards, recognition and favorable self-presentation of ability. Indeed, in a sample of undergraduate students, 20% said the reason they cheated was to get better grades (Newstead, Franklyn-Stokes, & Armstead, 1996). Moreover, the social comparative aspects of classrooms with performance goal structures might heighten students’ focus on self evaluation. Social psychologists Malcolm and Ng (1989) compared levels of cheating among college students under high and low self-awareness conditions. Self-awareness was manipulated by having students complete a task while facing a mirror. Twice as many subjects in the high self-awareness condition cheated when given the opportunity to, and they cheated two times as often as those in the low self-awareness condition. As noted earlier, Anderman and his colleagues (1998) found direct support for a relationship between goal orientations and cheating in their study of 285 middle school students. They found that cheating was inversely related to task goals and positively related to extrinsic goals at the individual, classroom, and school levels. Logistic regression analyses used to predict cheating versus not cheating revealed that classroom extrinsic and school performance goals were unique predictors of cheating once personal extrinsic goals, school worry, self-handicapping, and deep level strategy use were controlled for. In this study, we examined both individual- and classroom-level task and extrinsic goals. We hypothesized that task goals would be associated with less likelihood of cheating, whereas performance goals would increase the odds of reported cheating. Although it can be argued that both types of performance goals (extrinsic goals and ability goals) would be predictive of increased cheating, extrinsic goals were used in this study in keeping with Anderman et al.’s previous work (1998). Social Motivation and Cheating in Middle School Although pressure for academic attainment may provide some impetus to cheat, academic motives alone seem insufficient to explain students’ willingness to violate established school norms. Cheating, after all, is a form of deviant behavior: People use dishonest means to acquire a desired outcome (Michaels & Miethe, 1989). One sociological theory, social bond theory (Hirschi, 1969, cited in Michaels & Miethe, 1989) conceptualizes deviant behavior as stemming from inadequate bonds to the environment. Similarly, Calebrese and Cochran (1990) hypothesized that cheating stems from alienation, defined by Bronfenbrenner (1986) as a lack of support or lack of meaningful relationships with others in an environment. They found positive relations between students’ self-reported cheating, disliking of school, and views of teachers and schools as unfair in samples of students from both public and private high schools. In other words, they found that social motives had a relationship to cheating behavior. In recent years, numerous researchers have documented the power of so-

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cial relationships in facilitating students’ adaptation to school (Juvonen & Wentzel, 1996). For example, a study of early adolescents found that students who perceived more support from their teachers and felt a greater sense of psychological belonging in school also demonstrated comparatively higher levels of effort and achievement (Goodenow, 1993). Moreover, the dimension of teacher caring, rather than peer caring, was the best predictor of adaptive behavior. Roeser, Midgley, and Urdan (1996) also demonstrated the importance of supportive teacher relationships among middle school students. In their study, feelings of belongingness had both direct and indirect effects on achievement, through their relations to academic efficacy, selfconsciousness, and positive school affect. The quality of students’ perceived relationship with the teacher was the best predictor of feelings of school belonging. Other research suggests that favorable relationships with teachers are not only related to adaptive behaviors such as high effort, but may also deter students from violating the norms of appropriate behavior. Murdock (1999) found that 7th-grade students were apt to have higher levels of discipline problems to the degree they saw their teachers as disrespectful toward them. In contrast, high expectations and supportive behaviors were related to lower levels of behavior problems. These Grade 7 relational variables further predicted adjustment in Grade 9 (Murdock, Anderman, & Hodge, 2000). Wentzel (1997) has also investigated relations between students’ perceptions of their relationships with teachers and their pursuit of prosocial and responsibility goals as well as their level of academic effort. Perceived teacher caring was a significant predictor of 8th-grade students’ beliefs and behaviors even after controlling for their motivation and behavior in the 6th grade. Higher levels of reported caring by teachers were associated with the pursuit of behaviors such as sharing and helping in the classroom and efforts to follow established classroom rules. A subsequent study further confirmed that middle school students who perceived higher level of supportive behaviors on the part of their teachers were more apt to pursue social responsibility goals in the classroom and to express greater interest in school. In a qualitative component of her (1997) study, Wentzel sought to better understand the characteristics of positive student–teacher relationships by collecting open-ended data on students’ definitions of caring teachers. As seen by these adolescents, caring teachers differed from noncaring teachers in terms of their personal and instructional interactions. As instructors, caring teachers were seen as more democratic in their interaction patterns, more willing or able to insure that students learn, and were better models of good teaching. At a more personal level, the caring teachers were described as more fair, honest, and equitable than noncaring teachers and as demonstrating more concern for students’ nonacademic lives. In this study, we assessed

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the instructional aspects of pedagogical caring with two scales: One assessed the degree to which teachers were perceived as promoting democratic interaction, whereas the other focused on students’ perceived level of teachers’ commitment and competence. Both of these variables were assessed at the level of a particular classroom teacher. Our school-level variables focused on students’ perceptions of the degree to which their interactions with teachers were characterized by respect. Following Goodenow’s work on school belonging (1993), we also measured students’ general feelings of belonging within the school community. We hypothesized that higher scores on each of the four social motivational variables would be associated with decreased odds of academic cheating. Summary A large body of evidence suggests that students are more apt to internalize the attitudes and behaviors promoted by schools if their relationships within those institutions are positive. As such, we assert that academic motives are insufficient to explain students’ willingness to cheat and that students’ relationships within the social context of school provide an additional motive to either cheat or refrain from cheating. We sought to expand on the work by Anderman and his colleagues (1998) which demonstrated relations between achievement goal orientations and self-reported cheating behavior. We presumed that the four measured social motivational variables (i.e., democratic interaction style, teacher competence and commitment, teacher respect, and school belonging) would predict cheating above and beyond the five measured individual- and classroom-level achievement motivation variables (i.e., academic self-efficacy, personal and classroom extrinsic and task goal orientations). METHOD

Participants Participants in this study were 495 7th- and 8th-grade students from a middle school in the midwestern United States. The school was located at the border between a major city and the surrounding suburbs. Data were collected during the spring of 1998 as part of a larger evaluation study focused on the social and motivational climate of the school. Sixty-four students from the school who were not included in this study were either absent on each of five efforts at data collection, in full-time special education placements, denied parental permission, or declined to participate. There were approximately even numbers of males and females in the sample and most students were either African American (n ⫽ 198) or Caucasian (n ⫽ 280). These demographics are representative of the school population.

Procedures The data reported in this study are based on students’ self-reported survey data and official school records. All students in the school were members of an academic team comprising five teachers who taught the major subject areas: math, science, english, social studies, and reading.

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Student survey data were collected over 2 days during science and social studies classes. These classes were selected because they contained the highest percentage of the school’s mainstreamed special education population. A university faculty member or graduate student read each question aloud to students while they followed along in their survey booklet. On day 1, students were randomly assigned to focus on a particular academic class/subject area: math, science, social studies, english, or reading. Survey instruments used on day 1 had instructions on each page reminding students to focus on a specific subject area; research assistants read those instructions aloud as they read the items to the students. The questions on the 2nd day focused on students’ experiences at the school-wide level. Students’ questionnaires were coded with a random number that was matched to their names by a graduate student not directly involved in this research project.

Measures The student questionnaires include items developed specifically for this study as well as measures adapted from other researchers. Sample items for each of the scales are presented in the Appendix. Students were instructed to respond to all items using a 4-point Likert-type scale ranging from 1 ⫽ disagree to 4 ⫽ agree. Final scores were computed by averaging across items; higher score indicate stronger agreement with the construct. Cheating. The cheating measure used in this study was developed by Anderman et al. (1998) for their study of middle school cheating. Students answered the four cheating questions (α ⫽ .80) based on their behavior in one academic class: math, science, english, reading, or social studies. Recall that the specific subject they responded to was randomly assigned by the researchers. Academic motivation. Items to measure students’ academic efficacy, personal goal orientations, and classroom goal orientations were adapted for this study from the Patterns of Adaptive Learning Survey (PALS; Midgley et al., 1998). Students were told to answer all questions based on their experiences in the same randomly assigned subject area as indicated above. Six items each assessed students’ academic self-efficacy (α ⫽ .80), personal extrinsic goals (α ⫽ .65), and personal task goals (α ⫽ .77) orientations. Classroom goal structure was measured using five task goal (α ⫽ .71) items and four extrinsic goal (α ⫽. 65) items. Social motivation. Consistent with students’ definitions of teacher caring (Wentzel, 1997) two aspects of the social motivational climate of the classroom were assessed: participation structure and teacher competence/commitment. Participation structure was measured using 10 items (α ⫽ .78) of student influence developed by Roberts, Hom, and Battistich (1995) as part of an assessment of schools as caring communities. These items refer to students’ perceptions of their ability to have input into the managerial and learning environment of the classroom. The authors provide construct validity data based on factor analysis. We developed nine items to assess perceived teacher commitment/competence (α ⫽ .88) based on Wentzel’s (1997) qualitative data of what constitutes ‘‘pedagogical caring’’ among middle school students. These items assessed students’ perceptions of teachers’ willingness, preparedness, and competence to teach. Items from both of these scales were answered with respect to the teacher of the randomly assigned subject area. Two aspects of the social climate of the school were also assessed: perceived respect from teachers and overall sense of belonging within the school. These questions all referred to students’ experiences in school generally rather than a single subject area. Students responded to 14 questions about their perceptions of the level of respect shown to them by the teachers in their school. The items on this scale were drawn from Roberts et al.’s (1995) scale of fair teacher treatment, Murdock’s (1994) scale of teacher respect, and Goodenow’s teacher support subscale of the School Belonging Inventory (1993). Principal components factor analysis across the scales suggested that a majority of these items measured one construct. Accordingly, we collapsed 12 items into one measure which we named school-level teacher respect

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(α ⫽ .88). The remaining two items were excluded from these analyses. Six items from Goodenow’s (1993) School Belonging Inventory were used to assess students’ psychological sense of belonging in the school (α ⫽ .71). Whereas the respect items asked about students’ experiences of teachers’ treatment, the belonging items focused on how much students felt they were a part of their school. Demographic information. Data on students’ grade in school, gender and ethnicity were taken from official school records.

Results Students were classified as ‘‘cheaters’’ (25%) if their score was higher than 3 or 4 (i.e., mostly agree or agree) on any cheating item; otherwise they were classified as noncheaters (75%). This classification system is comparable to that used by Anderman et al. (1998) and resulted in similar rates of categorization. Although dichotomizing the cheating variable produced a loss of variance among people who cheat, this solution seemed most appropriate given the significantly skewed cheating variable (skewness ⫽ .756; z ⫽ 7.17; p ⬍ .001). Mean scores on the continuous scale were 2.80 for cheaters (SD ⫽ 0.49) and 1.37 for noncheaters (SD ⫽ 0.36). Comparisons between groups. Cheaters and noncheaters were first compared in terms of their demographic characteristics. We found no gender, λ2 (471) ⫽ 3.46, p ⬎ .05, or ethnic, λ2 (471) ⫽ 0.21, p ⬎ .05, differences between the two groups; however, 8th-graders were disproportionately more likely to report cheating than were 7th-grade students, λ 2 (471) ⫽ 15.95, p ⬍ .01. Whereas 43% of students in Grade 8 admitted to cheating, only 26% of the Grade 7 students did so. In addition, more students were apt to report cheating in science (39%) and social studies (43%) as compared to math (23%), english (30%), and reading (29%), λ 2 (471) ⫽ 12.02, p ⬍ .05. However, further examination suggested that these subject level differences were a function of the specific teacher of the course. As such, neither subject nor teacher was included as a predictor variable because the variables would presumably share a lot of variance with the dimensions of teaching that were the focus of this study (i.e., goal orientation, commitment, and participation structure). T tests were used to compare cheaters and noncheaters on all academic and social motivational variables. Means and standard deviations broken down by groups are presented in Table 1. Results were interpreted using a corrected alpha level based on the Bonferroni method of adjustment (α ⫽ .05/9 or .0055). When Levene’s test of equality of variances indicated that the scores from the two groups violated the homogeneity of variance assumption, the t test based on unequal variances was interpreted. Cheaters and noncheaters in this study differed in several ways. At a personal level, cheaters reported lower academic self-efficacy for the subject area as compared to noncheaters, t(486) ⫽ 6.53, p ⬍ .001, and being less mastery oriented than noncheaters, t(484) ⫽ 2.99, p ⬍ .003. Contrary to expectations,

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TABLE 1 Means and Standard Deviations for all Variables Broken Down by Cheating Group Cheating group Measure Academic self-efficacy* Personal mastery goals* Personal extrinsic goals Classroom mastery goals* Classroom performance goals Teacher commitment* Class participation structure School-wide teacher respect* School belonging

Noncheaters (n ⫽ 329) 3.30 2.53 3.26 2.87 2.25 3.07 1.73 2.55 2.59

(0.63) (0.71) (0.64) (0.72) (0.81) (0.70) (0.57) (0.67) (0.74)

Cheaters (n ⫽ 159) 2.89 2.31 3.37 2.48 2.24 2.52 1.86 2.19 2.45

(0.71) (0.78) (0.72) (0.70) (0.86) (0.73) (0.66) (0.65) (0.74)

Note. Bonferroni adjustment was used to control for inflation in type I error associated with multiple comparisons; α ⫽ .05/8 ⫽ .0062. * p ⬍ .006.

there were no group differences in personal extrinsic focus, t(484) ⫽ ⫺1.61, p ⬎ .0055. Cheaters viewed the goal structure of their classrooms as less mastery focused, t(486) ⫽ 5.67, p ⬍ .001, than did noncheaters. They also viewed the classroom teacher as less competent and committed to good teaching, t(486) ⫽ 8.06, p ⬍ .001, than did noncheaters. There were no significant differences between cheaters and noncheaters in reports of the extrinsic goal structure, t(486) ⫽ .14, p ⬎ .0055, or the participation structure of the classroom, t(486) ⫽ ⫺2.20, p ⬎ .0055. At the school level, students who reported cheating viewed the teachers in the school as more disrespectful of students than did noncheaters, t(486) ⫽ 5.67, p ⬍ .001. They did not report less of a psychological sense of school belonging than did the noncheaters, t(486) ⫽ 2.01, p ⬎ .0055. Predictors of cheating. To examine individual-, classroom-, and schoollevel predictors of students’ cheating, a series of logistic regression models were examined. Logistic regression is one of the preferred approaches when working with a dichotomous criterion variable (Norusis, 1994; Tabachnick & Fidell, 1989). Consistent with ecological models (Bronfenbrenner, 1979), variables were entered hierarchically, based on their assumed proximity to the criterion variable. That is, model 1 comprised individual achievement motivational variables, whereas models 2 and 3 added classroom-level variables, and model 4 included school-level variables. In order to determine whether social context variables predicted cheating above and beyond academic motivational context (i.e., goal structure), classroom variables were entered in two stages: academic goal structure variables were entered in

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model 2 followed by relational variables in model 3. Grade (7 versus 8) was included as a control variable throughout. Table 2 summarizes the bivariate correlations between all of the variables that were used in the regression analyses. Relations between cheating and the predictor variables were consistent with the t tests. Correlation coefficients among predictor variables revealed moderate to strong relations between classroom mastery goal structures and each of the four social motivational variables: teacher commitment (r ⫽ .70, p ⬍ .001), participation structure (r ⫽ .38, p ⬍ .001), teacher respect (r ⫽ .44, p ⬍ .001), and school belonging (r ⫽ .27, p ⬍ .001). However, there were also moderate relations between extrinsic classroom goal structures and each of these four social context variables: teacher commitment (r ⫽ .31, p ⬍ .001), participation structure (r ⫽ .41, p ⬍ .001), teacher respect (r ⫽ .25, p ⬍ .001), and school belonging (r ⫽ .14, p ⬍ .001). Whereas both personal and classroom mastery orientations were significantly related to self-reported cheating, extrinsic goals were not correlated with this behavior. Among the social context variables, perceived commitment by the classroom teacher and perceived respect from teachers throughout the school were both inversely related to reported cheating. Logistic regression results including logistic regression coefficients, standard errors, and odds ratios are presented for each model in Table 3. Odds ratios refer to the probability of change in group membership, in this case from cheating to noncheating, that is associated with a one-unit increase in the predictor variable (Norusis, 1994). For instance, in the final model, a change from a score of 2 to 3 on academic self-efficacy (one unit) decreases students’ odds of cheating by .59 times. In model 1, individual motivational and control variables resulted in a successful classification rate of 71.6% [λ 2 (4) ⫽ 60.73, p ⬍ .001]. The model successfully classified 92.0% of noncheaters but only 30.4% of cheaters. Higher grade level and lower academic self-efficacy were both unique predictors of increased odds for cheating. When classroom motivational goal structures were entered into the prediction equation in model 2, the classification rate improved to 73.1% [improvement λ 2 (2) ⫽ 13.22, p ⬍ .0012]; this model now correctly identified 38.0% of cheaters and 90.0% of noncheaters. Grade in school and academic efficacy continued to predict cheating group membership. In addition, cheating was associated with higher endorsement of personal extrinsic goals as well as seeing the class goal structure as less mastery oriented and more extrinsically focused. With the addition of the classroom level relationship variables in step 3, the classification rate improved to 75.8% [improvement λ 2 (2) ⫽ 32.39, p ⬍ .001]. Moreover, the model successfully identified 46.2% of the cheaters, with no loss in the classification of noncheaters (89.8%). Significant

Cheater Grade Academic self-efficacy Personal mastery Personal extrinsic Classroom mastery Classroom extrinsic Classroom teacher commitment Classroom participation structure Schoolwide teacher respect School belonging .19** ⫺.28** ⫺.13** .07 ⫺.25** .01 ⫺.34** .10 ⫺.25** ⫺.09

1

⫺.08 .03 .03 ⫺.16** .08 ⫺.08 .04 .00 ⫺.03

2

Note. Cheater is coded 1 ⫽ does not cheat, 2 ⫽ cheats. * p ⬍ .05. ** p ⬍ .01.

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

Measure

.28** .08 .37** .12* .48** .06 .29 .21**

3

⫺.10 .27** .13* .31** .11 .47** .30**

4

.04 .01 .04 ⫺.04 ⫺.04 .01

5

TABLE 2 Bivariate Correlations among All Variables

.41** .70** .38** .44** .27**

6

.31** .41** .25** .14*

7

.20** .47** .23**

8

.19** .16**

9

.56**

10

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* p ⬍ .05. ** p ⬍ .01.

Grade Academic self-efficacy Personal mastery Personal extrinsic Classroom mastery Classroom extrinsic Teacher commitment Participation structure Schoolwide teacher respect School belonging

Measure 0.78** ⫺0.88** ⫺0.18 0.30

b 0.21 0.16 0.15 0.16

SE

Step 1

2.18 0.42 0.83 1.35

Odds ratio 0.64** ⫺0.73** ⫺0.11 0.33* ⫺0.62** 0.30*

b 0.21 0.17 0.15 0.16 0.18 0.15

SE

Step 2

1.91 0.48 0.90 1.39 0.54 1.35

Odds ratio 0.69** ⫺0.51* ⫺0.06 0.40* ⫺0.31 0.17 ⫺0.86** 0.77**

b 0.22 0.18 0.16 0.17 0.23 0.16 0.21 0.21

SE

Step 3

TABLE 3 Hierarchical Logistic Regression Predicting Cheating Group Membership

2.00 0.60 0.94 1.49 0.73 1.18 0.42 2.14

Odds ratio

0.74** ⫺0.54** 0.08 0.38* ⫺0.25 0.19 ⫺0.75** 0.77** ⫺0.66* 0.29

b

0.23 0.18 0.17 0.17 0.23 0.16 0.22 0.21 0.23 0.18

SE

Step 4

2.10 0.59 1.08 1.46 0.77 1.21 0.47 2.16 0.52 1.33

Odds ratio

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unique predictors of membership in the cheaters group included grade, academic efficacy, and personal extrinsic goals as well as teacher commitment and classroom participation structure. Contrary to expectations, when the other variables were included in the model, a democratic participation structure was positively related to cheating. The motivational goal structures of the classroom no longer made significant independent contributions to the criterion variable. Finally, students’ perceptions of teachers’ respect and their sense of school belonging were entered on step 4, resulting in a final classification rate of 76.5% [improvement λ 2 (1) ⫽ 8.29, p ⬍ .02]. The full model improved the identification of cheaters to 47.5% with little change in the prediction rate of noncheaters (90.5%). In this final model, being a cheater versus a noncheater was associated with higher grade level, lower levels of self-efficacy, more personal extrinsic focus, less perceived commitment on the part of the classroom teacher, and more democratic interaction styles in the classroom. At the school level, increased respect from teachers was negatively associated with self-reported cheating. Students’ psychological sense of school belonging was not a unique predictor of cheating. Discussion Results of this study suggest that efforts to understand the classroom behavior of middle school students should continue to attend to both social and academic motivational variables. In addition, the data also raise some important issues about the relations between what have been termed social and academic motivational variables. Each of these points is discussed below. Cheating and academic motivation. Cheating in this study was associated with students’ self-evaluations as well as with specific motivational orientations. Having lower perceptions of one’s academic self-efficacy, holding personal extrinsic goals, and perceiving the class as less focused on mastery or task goals were all associated with increased likelihood of cheating, though classroom task goals were not uniquely predictive of cheating behavior. These results affirm the importance of the role that individuals’ assessments of competence and academic goals play in predicting adaptive classroom behavior. Although this study was designed to extend Anderman et al.’s work (1998) on cheating to include social and academic predictors of cheating, the two studies differed in a few important ways that need to be considered when comparing the regression results. Specifically, whereas Anderman and his colleagues measured goals at the personal, classroom, and school levels, we elected not to include school-level goals because of their moderate correlations with individual goals. In addition, because Anderman et al. was interested in demonstrating the unique power of achievement goals, above and beyond other academic motivational variables, they included school worry,

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self-handicapping, and deep-level strategy use as control variables. Because we included four indictors of social goals, we had to carefully select the academic constructs to include in our model. In contrast to Anderman et al.’s study (1998), we presumed that academic self-efficacy rather than school worry would be more closely related to cheating. We also did not include deep-level strategy use or academic self-handicapping as control variables. We eliminated deep-level strategy because it was strongly correlated with other predictor variables (i.e., personal goals) in the Anderman et al. (1998) study. We did not have a strong conceptual argument to include self-handicapping in our study. Academic efficacy was the strongest motivational predictor of cheating, which is consistent with students’ explanations for why adolescents cheat in school: fear of failure. Although Anderman et al. (1997) found no relations between cheating and academic worry, which is also seemingly related to fear of failure, worry and academic self-efficacy are distinct constructs. Whereas worry might interfere with high performance, it might not necessary lead to cheating. On the contrary, worry about performance could presumably motivate people to higher levels of effort. In contrast, low self-efficacy beliefs imply a lack of belief in being able to personally carry out the tasks necessary for high performance. Doubting one’s ability to bring about a desired result might lead to reliance on other strategies for success. Low selfefficacy has been associated with a variety of negative motivational outcomes, including the use of uncontrollable attributions, low persistence, and low risk taking (Schunk, 1991). For students in this study, having extrinsic orientations toward school work was also associated with increased levels of cheating. Extrinsic orientations toward school work are inversely related to persistence and engagement (Kasser & Ryan, 1996). By cheating, students are able to achieve a better outcome than they might have otherwise, but they do not need to do the work that leads to actual learning. When classroom goal structures were entered as predictors of cheating, task goals were found to be related to decreased odds of cheating. Perceived extrinsic goal structures were associated with an increased probability of reporting dishonest behavior, suggesting that the motivational environment of the classroom as well as the individuals own motivational orientations are possible determinant of cheating behavior. Anderman et al. (1998) note that their definition of extrinsic goals, which was also adopted in this study, might be equated with ‘‘work avoidance.’’ In other words, these items might be conceptualized as measuring students’ desire to ‘‘get by.’’ Findings from these and other studies (e.g., Meece, Blumenfeld, & Hoyle, 1988; Nicholls, Patashnick, & Nolen, 1985) suggest that more attention should be paid to work avoidance as an orientation toward school. Many of the high school students in Steinberg’s (1996) study of adolescents reported they were striving simply to graduate rather than to get

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good grades. For these students, the external reinforcement of a ‘‘B’’ versus a ‘‘C’’ had very little meaning to them. In addition, high school students say that one of the most important reasons for student cheating is to ‘‘get out of working’’ (Schab, 1991). Future studies of cheating might include specific measures of effort avoidance. Cheating and social variables. Data from this study provide continued support for the primacy of social relationships and social context in understanding students’ behavior (Battistich, Solomon, Watson, & Schaps, 1997; Baumeister & Leary, 1996; Bronfenbrenner, 1986; Goodenow, 1992; Juvonen & Wentzel, 1996) as social motivational variables emerged as the best unique predictors of cheating in this study and accounted for significantly more variance in cheating than did academic variables alone. At a classroom level, students said they were less apt to cheat if they perceived that their teacher was upholding his or her agreement to perform their job competently. These findings further validate Wentzel’s (1997) documented relations between the adoption of positive values and perceived pedagogical caring, and further support the idea that teachers’ commitment to competent teaching is an integral aspect of perceived caring. Many early adolescents have begun to recognize that fair relationships are ones characterized by reciprocity (Selman, 1980) and may not feel obligated to ‘‘play by the rules’’ for teachers who are breaking their contract of caring (see Noddings, 1992; Wentzel, 1997). Contrary to our expectations, perceived democratic interaction style was not correlated with cheating and was a positive rather than an inverse predictor of cheating, once the other variables were accounted for. There are several potential explanations for these findings. Some research suggests that early adolescents are not always clear about what constitutes cheating (Evans & Craig, 1990a). Given the documented relations between goal structures, relationships with teachers, and academic help seeking (Newman & Schwager, 1992; Ryan, Gheen, & Midgley, 1998; Ryan & Pintrich, 1998), it may be that students in classes with more democratic participation structures believe that ‘‘copying from a friend’’ and ‘‘help seeking’’ are much the same thing. Future studies might attempt to tease out whether definitions of cheating vary within task versus performance oriented classrooms and whether classroom goal structures moderate the factors that predict cheating. It is also possible that democratic participation structures in and of themselves do not necessarily promote ideal behavior. Although democratic participation structures were assumed to represent a caring environment, research on parenting styles suggests that although too much control over adolescents behavior is not the best choice, opportunities for decision making and individual control only facilitate adaptation when coupled with appropriate amounts of parental support and structure (Baumrind, 1991; Steinberg, 1996; Steinberg, Lamborn, Dornsbusch, & Darling, 1992). It may be that when democratic participation structure is added to a model which already

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includes various dimensions of a positive classroom environment, both academically and socially, its unique variance represents a level of autonomy and lack of monitoring exceeding that which can be effectively managed by students of this age. Indeed, one study reports that students are less likely to cheat if they believe their behavior is monitored by the teacher (Evans & Craig, 1990a). The data also imply that the academic climate and social climate of a classroom may not be independent of each other and raise some question about our conceptualization and measurement of these constructs. Recall that the unique contribution of achievement goal orientations to the prediction of cheating was significantly reduced in the measurement models that included social motivational variables. Once social variables were included, only personal mastery goals continued as a significant unique predictor of cheating. An examination of the correlations between the predictor variables provides some insight into these findings. To be specific, classroom mastery goals were highly correlated with perceived teacher competence and commitment, making it unlikely that both variables could account for significant amounts of variance in the criterion variable. This correlation intimates that task-focused classrooms may be interpreted by students as classrooms where teachers are doing their jobs (i.e., evidence of ‘‘pedagogical caring’’; see Wentzel, 1997). However, there was also a moderate correlation between perceived teacher commitment and extrinsic classroom goal structures, which are often seen as ‘‘bad’’ because of the relations to lowered intrinsic motivation (Kasser & Ryan, 1996). It may also be that if teachers exert effort to provide incentives for work completion, students also interpret these behaviors as evidence that teachers want students to do their work, or ‘‘care.’’ Theoretically, there may be classrooms that are neither task or performance oriented. Future studies might explore whether ‘‘work avoidant’’ can also be used to describe the goal structure of classrooms and schools (see Nicholls, Patashnick, & Nolen, 1985) and to delineate the types of student behaviors these such environments support. A major limitation of this research is the self-report nature of the data. Although students’ names were not used at any point in our study, participants were aware that they had been assigned an identification number to match their responses over the 2 days. Accordingly, it may be that the academic and social variables we used in this study are better predictors of who is willing to admit to cheating than of who cheats per se. If that is the case, these findings may overestimate the predictive utility of social and academic variables with respect to cheating because the subset of students who were willing to say they have cheated are probably among the most rejecting of school norms. Future studies using other methodologies, such as naturalistic observations of actual cheating and experiments that encourage cheating, will be needed to confirm the validity of cheating measures. Also recall that the cheating variable was dichotomized because of its significant positive

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skew, limiting our ability to determine the factors that predict variations in the level of student cheating. These results add to the growing body of literature that suggests cheating increases with grade in school (Schab, 1991). Teachers of middle school students need to be aware of the potential for cheating in their classrooms and work toward establishing social climates that emphasize mutual trust, respect, and caring. Moreover, the data intimate that structuring one’s classroom to emphasize mastery might help to foster the positive teacher–student relationships that seem linked to adaptive classroom behavior. Finally, the correlations among variables designed to measure pedagogical caring and indicators of classroom academic goal structures suggest the need for motivational researchers to conceptually and empirically clarify the distinctions between these constructs. APPENDIX Scale Sample Items Scale name Cheating Academic Efficacy

Personal Task Goals

Personal Extrinsic Goals

Classroom Task Goals

Classroom Extrinsic Goals

Participation Structure

Teacher Commitment/ Competence

School Level Teacher Respect School Belonging

Sample items I cheat on my work in this class. I copy off other students when I do my work for this class. I’m certain I can master the skills taught in this class this year. I can do almost all the work in this class if I don’t give up. An important reason I do my work is because I like to learn new things. I do my school work because I’m interested in it. I want to get the right answers, even if I don’t understand the work. The main reason I would do an extra project is to get a better grade. Our teacher wants us to understand our work, not just memorize it. Our teacher recognizes us for trying hard. If we do really well in this class we can get out of homework. Our teacher does not give us rewards or prizes for doing our work (reflected ). The teacher lets us do things our own way. In my class, the teacher and students plan what they will do together. My teacher is well prepared for most classes. When I get stuck, my teacher can find ways to explain things to me. My teacher presents things to me in a way that makes sense. The teachers here always try to be fair. My teachers do not respect me. (reflected) My teachers care if I come to school. I feel like I am a real part of XXX middle school. Sometimes I feel like I don’t belong here. (reflected)

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