Effects of Honor Codes and Classroom Justice on ... - Science Direct

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ScienceDirect Procedia - Social and Behavioral Sciences 112 (2014) 77 – 86

International Conference on Education and Educational Psychology (ICEEPSY 2013)

Effects of honor codes and classroom justice on students’ deviant behavior Kabiru Maitama Kura a

a,

a

a

*, Faridahwati Mohd. Shamsudin , Ajay Chauhan

Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia, Sintok, 06010 Sintok, Kedah, Malaysia

Abstract This study examined the influence of honor codes and classroom justice on students’ deviant behavior. One hundred and two final year undergraduate students studying in various higher institutions of learning in Nigeria participated in the study, i ncluding Bayero University, Kano, Ahmadu Bello University, Zaria, Federal Polytechnic, Kaura Namoda, Kano State Polytechnic and Federal College of Education, Zaria. Pearson correlation analysis, multiple linear regression analysis, independent sample t -test and one-way ANOVA analysis were conducted using Statistical Package for the Social Science s ( SP SS) to analyze the data. T he results of multiple regression analysis showed that Honor codes had a significant negetive effect on students’ deviant behavior. On the contrary, the results showed that classroom justice had no significant effect on students’ deviant behavior. Furthermore, the findings of the study revealed a significant difference in student deviant by gender, age categories and ethnicity. T he managerial implications for the school administrators, lecturers and educational policy makers a re discussed.

© 2012 2013Published The Authors. Published by Elsevier Ltd. © by Elsevier Ltd. Selection and/or peer-review under responsibility of Dr. Zafer Bekirogullari of Cognitive – Counselling, Selection&and peer-review under responsibility of Cognitive-counselling, research and conference services (c-crcs). Research Conference Services C-crcs. Keywords: Deviant behavior; honor codes; classroom justice; academic dishonesty

1. Introduction Deviant behavior among students of higher education institutions (i.e., universities, polytechnics and colleges of education) is prevalence and a major concern of organizational researchers, practitioners and the public at large (Aluede, Omoregie, & Osa-Edoh, 2006; Brimble & Stevenson-Clarke, 2005; Chapman & Lupton, 2004; Kidwell & Kent, 2008). For example, in a global survey on academic dishonesty, Lin and Wen (2007) reported that in Taiwan the prevalence rate for all types of deviant behaviors among university students was 61.72%. They further reported that some of the most practiced forms of deviant behaviors among university students in Taiwan include writing assignments for other students and giving prohibited help to others on their assignment among others. In Nigeria,

T el.: +601 6489 6138; Fax: +604 928 5220. E-mail address: [email protected] His research interests are deviant behavior in organizations; leadership; human resource practices.

1

1877-0428 © 2013 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of Cognitive-counselling, research and conference services (c-crcs). doi:10.1016/j.sbspro.2014.01.1141

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Kabiru Maitama Kura et al. / Procedia - Social and Behavioral Sciences 112 (2014) 77 – 86

deviant behaviors among students of higher education institutions have been frequently reported in the news media. Some of these behaviors include academic plagiarism, examination misconduct, forgery of certificates, fighting, indecent dressing, late coming, sexual harassment and cult-related offences among others (Adeniyi & Taiwo, 2011; Bello, 2012; Ibok, 2012; Omede, 2011; Osogbo, 2012). In an attempt to better explain why students engage in deviant acts in the universities and colleges, scholars in the field of educational psychology, criminology and sociology have advocated the use of honor codes (e.g., Gertz & Gould, 1995; Imran & Ayobami, 2011; McCabe & Trevino, 1993; 1997; Molnar & Kletke, 2012; Passow, Mayhew, Finelli, Harding, & Carpenter, 2006). Honor codes has been defined by Pauli, Arthur and Price (2002) as “a policy statement of an institution's position regarding student conduct as it relates to academic integrity” (p.3). From theoretical perspective, the use of honor codes in explaining students’ deviant behavior is grounded in the social cognitive theory of moral thought and action (Bandura, 1991). Social cognitive theory of moral thought and action (Bandura, 1991) suggests that students’ deviant behavior is a function of environmental factors, including honor codes, social norms, moral thought/development and classroom justice. In particular, if students perceived that the honor codes instituted by the university or college are being enforced properly, they are less likely to engage in deviant acts than if they perceived that such honor codes are fully enforced (Lau, Caracciolo, Roddenberry, & Scroggins, 2011). Furthermore, if a student experience injustice in the course of relating with other students and faculty members he or she is more likely to engage in deviant acts, thereby seeking to restore justice (Aquino, Tripp, & Bies, 2006; Chory-Assad & Paulsel, 2004; Morris, 2010). While Bandura’s (1991) social cognitive theory of moral thought and action suggested honor codes and classroom justice among the significant predictors of students’ deviant behavior, however there is a paucity of studies combining the two factors to predict students’ deviant behavior. The purpose of the present study is to contribute to the existing body of knowledge concerning social cognitive theory of moral thought and action. Specifically, the objective of this study was to investigate the effects of honor codes and classroom justice on students’ deviant behavior among undergraduate students from various higher institutions of learning in Nigeria. In so doing, remainder of this paper is organized as follows. In the next section we review previous stud ies on the relationship between students’ deviant behavior, honor codes, classroom justice and individual characteristics. Next, we then describe the method used in the present study, followed by presentation of the results. The final section captured discussion and conclusion. 2. Literature review 2.1 Relationship between honor codes and student deviant behavior Previous studies have examined the effect of honor codes on students’ deviant behavior (Arnold, Martin, & Bigby, 2007; Cole & McCabe, 1996; Konheim-Kalkstein, Stellmack, & Shilkey, 2008; McCabe, 1993; McCabe & Trevino, 1993; McCabe, Trevino, & Butterfield, 2002). For example, McCabe and Trevino (1993) conducted a study to examine the influence of perceived formal controls (i.e., honor codes or set of rules and regulations governing student conduct) on deviant behavior (e.g., copying other student’s work during a test, helping other students to cheat during a test and cooking or fabricating data) among 6,096 students from thirty -one colleges and universities in the United States. Multiple regression results revealed a significant negative relationship between honor codes and students’ deviant behavior, suggesting that perception of formal control reduces students’ predispositions to engage in deviant acts. In a similar study, McCabe, et al. (2002) included students from 21 colleges and universities in the United States to examined the effects of modified honor codes, defined as an alternative to traditional honor codes that place responsibility for maintaining academic honesty faculty and/or administrators rather than on students) on students’ academic dishonesty. The findings of the study showed a significant negative relationship between modified honor codes and students’ deviant behavior, suggesting that modified honor codes are far more significant in reducing students’ tendency to engage in deviant acts than traditional honor codes. Thus, drawing from foregoing literature, the following hypotheses were formulated: Hypothesis 1: Honor codes will be negatively related to student deviant behavior.


2.2 Relationship between classroom justice and student deviant behavior Classroom justice is defined by Chory-Assad and Paulsel (2004) as “ perceptions of fairness regarding outcomes or processes that occur in the instructional context” (p. 254). T hree dim ensions of classroom justice have been identified in the organizational justice literature: distributive justice, procedural justice and interactional justice. Distributive justice, which refers to the perception about the extent to which the outcomes of given transaction are equitable (Niehoff & Moorman, 1993). Procedural justice, which refers to perceptions of fairness of the manner in which policies and procedures are implemented (Bakhshi, Kum ar, & Rani, 2009; Folger & Konovsky, 1989). Interactional just ice refers to the quality of interpersonal treatment received by individuals in the course of implementation of organizational policies and procedures (Bies & Moag, 1986). Extant empirical studies have demonstrated that classroom justice is the one of the major concerns of college students (Horan & Myers, 2009). The effects of classroom justice on students’ deviant behavior have also been examined by many scholars in the field of educational psychology (Chory-Assad, 2002; Chory-Assad & Paulsel, 2004; Kennedy, Homant, & Homant, 2004; Morris, 2010). However, the findings of these studies have reported conflicting results. In particular, Chory -Assad and Paulsel (2004) conducted a study to investigate the influence of procedural justice on aggressive behavior (defined as hostility and resistance of instructors' requests) among 154 college students. The results of the multiple regression analyses revealed that perceptions of procedural justice, defined as perceptions of fairness of the manner in which policies and procedures are implemented (Folger & Konovsky, 1989) had significant and negative relationship with students’ aggressive behavior. However, the results also showed that distributive justice was not have significantly related with students’ aggressive behavior. In a similar vein, Kennedy, Homant and Homant (2004) conducted a study to investigate the relationship between perceptions of injustice and aggressive behaviors among 139 undergraduate students. The findings of the study showed a quite significant correlation between perceived injustice and aggressive behaviors. Therefore, on the basis of the foregoing literature review and discussion, the following hypotheses were formulated:

Hypothesis 2: classroom justice will be negatively related to student deviant behavior. 2.3 Individual differences in students’ deviant behavior Individual differences refer to the variations from one person to another on variables such as gender, age, marital status, education and race, among others (Berger, 2008). Individual differences in students’ deviant behavior have been investigated by many scholars in the field of educational psychology (Ameen, Guffey, & McMillan, 1996; Arnold, et al., 2007; McCabe & Trevino, 1996; Newstead, Franklyn-Stokes, & Armstead, 1996; Tibbetts, 1999; Whitley, Nelson, & Jones, 1999). However, there are no consistent findings relating to individual differences in students’ deviant behavior. In particular, some studies investigating individual differences in students’ deviant behaviors have found significant differences in academic misconduct by gender, while some studies could not establish any difference. Whitley, Nelson and Jones (1999) conducted a meta-analysis of 34 studies to examine gender differences in academic dishonesty. The findings of their analysis of gender differences in academic dishonesty showed that men would report more cheating behavior compared to their women counterparts. In a similar study, Newstead, Franklyn-Stoke and Armstead (1996) included 943 students at a large English university in United Kingdom (study 1) to examine gender differences in cheating behaviors. The results of the study showed a significant difference in cheating behaviors by gender of the student, suggesting that men were more likely to cheat than their women counterparts. On the contrary, Jordan (2001) examined individual characteristics differences in cheating behaviors among 175 college students. In particular, the study established no statistically significant difference in cheating behaviors by students’ gender, suggesting that female students were significantly more likely to engage in cheating behaviors than their male counterparts. Furthermore, this finding was confirmed by more recent studies conducted by Gesinde, Adejumo and Odusanya (2011) and Walton (2011), which showed that female students were more to engage in academic cheating than their male counterparts. Nevertheless, extant empirical studies have consistently found age differences in students’ deviant behavior (Newstead, et al., 1996; Nonis & Swift, 2001; Rakovski & Levy, 2007; Vandehey, Diekhoff, & LaBeff, 2007). In particular, Rakovski and Levy (2007) conducted a study to investigated age differences in academic dishonesty among 1,255 business students at the North-eastern business college. The results of the analysis showed that junior students were more likely to engage in dishonest behavior at the college than their senior students counterparts. Similarly, conducted a multicampus investigation to examine age differences in academic dishonesty among 1,051 graduate and undergraduate business students from 6 different campuses in the South and Midwest, United States. The results of the one-way ANOVA analysis revealed a significant difference in academic dishonesty by age,

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suggesting that academic dishonesty occurred more frequently among younger students than their olde r counterparts. On the basis of the foregoing literature review and discussion, two hypotheses were formulated: Hypothesis 3: There is a significant difference in student deviant behavior by gender. Hypothesis 4: There is a significant difference in student deviant behavior by age categories. Hypothesis 5: There is a significant difference in student deviant behavior by ethnicity.

Honor codes Student deviant behavior Classroom justice

Fig. 1 Research framework 3. Method 3.1 Participants Participants were 102 final year undergraduate students studying in various higher institutions of learning in Nigeria, including Bayero University, Kano, Ahmadu Bello University, Zaria, Federal Poly technic, Kaura Namoda, Kano State Polytechnic and Federal College of Education, Zaria. Of these 102 participants, 3 (2.9%) were between 20 and 25, 53(52.0%) between 26 to 30, 36 (35.3%) between 31 to 35, 6 (5.9%) between 36 to 40, and 4 (3.9%) 41 years old. Majority of the participants, 66 (64.7%) were male and the remaining 36 (35.3%) were female. Of the participants, 38 (37.3%) were Yoruba by tribe, 48 (47.1%) were Hausas, 3 (2.9%) Igbos and 13(12.7%) were the minority tribes. The Educational level of the participants were 56 (54.9%) holders of Senior School Certificates (SSC), 1 (1.0%) was Advanced level certificate holder, 26 (25.5%) Diploma holders, 16 (15.7%) previously hold either a Bachelor degree or Higher National Diploma and the remaining 3 (2.9%) previously hold Postgraduate qualification. Lecturers from the four selected institutions distributed 180 questionnaires to students who were offering management related courses. Participants were given the assurance that their identities would never be known to anybody. One hundred and two participants returned the completed questionnaires directly to the lecturers, representing 56.7% response rate. 3.2 Measures The present study adapted the measurement scales from past studies to measure all the four constructs depicted in the research framework. We also make some minor changes in wording in order to suit the context of the study. The measurement scales were also pre-tested by an expert in methodology for clarity and understanding of the scale items. All the response options were indicated on a 5-point Likert scale, ranging from 1 = strongly disagree to 5 = strongly agree. Student deviant behavior. Student deviant behavior was measured using workplace deviance scale developed by Aquino, Lewis and Bradfield (1999). In order to reduce response bias, participants were asked to indicate whether they know any of their coursemate or classmate engages in deviant behaviors in their present school. This method is called projective vignettes (Robertson & Anderson, 1993) and has been found to be reliable. Examples of items are: “Intentionally arriving late for lecture”; “making unauthorized use of school property”. Classroom justice. Classroom justice was assessed with a 7-item scale (Niehoff & Moorman 1993), which assess the students’ perception of fairness of the policies and procedures used to allocate their school resources. Example of an item is “procedures in the class and the school are designed to collect accurate information from students for making decisions” This scale was used in the previous studies and it has been found to be reliable (Lambert, Hogan & Griffin, 2007; Paré & Tremblay, 2007).

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Honor codes. Hollinger and Clack’s (1982) formal control scale was adapted to measure the perception of students on the reaction of the person in authority when a student engages in the b ehavior in their present school. Example of items is “what would be the most common reaction of the person in authority when a coursemate or schoolmate called in sick when he was not really sick”. 4. Data analysis In this study, several statistical analyses were performed using SPSS version 18 to analyze the data, including reliability analysis, Pearson correlation analysis and multiple linear regression analysis. In particular, multiple linear regression analysis was carried out to determine the influence of influence of Honor codes and procedural justice on students’ deviant behavior. 4.1 Results 4.1.2 Reliability analysis To assess the reliability of the measures used in this study, Cronbach alpha co-efficient were calculated. Table 1 shows that the Cronbach alpha co-efficient for student deviant behavior, classroom justice and Honor codes. The Cronbach's alpha coefficient ranged from 0.78 to 0.88. According to Nunnally, (1978), a Cronbach’s alpha coefficient greater than 0.70 is considered to be acceptable. Hence, we conclude that all the instruments adapted in this study are reliable since the Cronbach alpha for each variable is greater than 0.70. Table 1 Reliability coefficient Number of

Cronbach's

Items

Alpha

13

.836

7

.781

14

.882

Construct Student Deviant Honor codes Classroom justice

*Cut-off Criteria

Remark

≥ .70 for accepta nc e

Acceptable


Acceptable


Acceptable

* (Nunnally, 1978). 4.1.2 Hypotheses testing Table 2 shows the correlations between the study variables. It can be seen that honor codes was positively related to student deviant behavior (r = 0.64, p < 0.01), positively related to gender (r = 0.27, p < 0.01) and negatively related to education (r = -0.22, p < 0.05). On the contrary, honor codes were not related to classroom justice. Table 3 shows the results of multiple regression analysis. Honor codes had a significant negative effect 2 on students’ deviant behavior (β = -0.748, t = 8.500, p < 0.000). Table 3 also shows that the R value for the research model is 0.422, indicating that 42.20% of the variation in student deviant behavior (dependent variable) can be explained by honor codes and classroom justice (independent variables). Table 2 Correlations among the research variables (N = 102) Mean Student deviant

2.8045

SD .71991

1 -

2

3

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Honor codes Classroom justice

2.9477

.62709

3.7759

.55765

.646**

-

0.015

-0.084

-

**. Correlation is significant at the 0.01 level (2tailed). *. Correlation is significant at the 0.05 level (2-tailed).

Table 3 Regression results Model Summary

b

Model

1

R .650

ANOV A Model 1

Adjusted R Square .410

R Square .422

b

Regression

Sum of Squares 22.092

df 2

Mean Square 11.046

Residual

30.253

99

.306

Total

52.345

101 Coefficie nts

Model

F 36.146

Sig. .000

a

Standa rdiz ed

Unstanda rdiz ed Coefficients 1

Std. Error of the Estimate .55280

Coefficients

(Constant)

B .261

Std. Error .476

Honor codes

-.748

.088

Classroom justice

.089

.099

Beta

t .549

Sig. .584

-.652

-8.500

.000

.069

.904

.368

Note: N = 102; * p < 0.05, ** p < 0.01 Existence of honor codes lower deviant behaviors among students. Hence, hypothesis 1 was supported. On the contrary, the results showed that classroom justice had no significant effect on students’ deviant behavior (β = 0.089, t = 0.904, ns). Thus, hypothesis 2 is not supported. Table 4 Independent sample t-test for comparing the male and female’s student deviant scores Gender Std.

Error

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Overall deviant

student Male Female

N 66

Mean 2.6629

Std. Deviation .77568

Mean .09548

36

3.0641

.52058

.08676

df 100

t -2.778

Hypothesis 3 predicted that there is a significant difference in student deviant behavior by gender. This hypothesis was tested using independent sample t-test and the results were shown in table 4. As depicted in table 4, subjects were divided into two groups according to their gender (Group 1: Male; Group 2: Female). Table 4 shows that there is a significant difference in student deviant by gender (t = -2.778, p< 0.05). Thus, hypothesis 3 is greater than the mean score of male student (Mean = 2.6629). This implies that female students exhibit more deviant behavior as compared to the male students. Table 5 Mean Differences in Student Deviant by age Age groups Variable Younger Older M SD M SD Student Deviant 2.82 .47 2.17 .61 Note. *p < .05.

F 2.882*

df1 4

df2 97

Sig. .027

Our hypothesis (H4) predicted that there is a significant difference in student deviant behavior by age categories. This hypothesis was tested using one-way ANOVA analysis as shown in table 5. Subjects were divided into two groups according to their age (Group 1: Younger, whose age falls between under 20 years and 30 years; Group 2: Older, their age between 31 years and 40 years). There was a statistically significant difference at the p < .05 level in student deviant scores for the two age groups: F (4, 97) = 2.88, p = .027. Hence, as predicted, hypothesis 4 is supported. Post-hoc comparisons was conducted using the Tukey HSD test indicated that the mean score for Group 1 (M = 2.82, SD = .47) was significantly different from Group 2 (M = 2.17, SD = .61). The means scores revealed that deviant behaviors were predominant among the younger students compared to the older students. Table 6 Mean differences in student deviant behaviors by ethnicity Ethnic groups Variable Yoruba Hausa Igbo M SD M SD M SD Student deviant 2.82 .72 2.82 .80 3.10 .18 Note. * p < .05.

Minority M SD 2.63 .45

F 4.161*

df1 3

df2 98

Sig. .008

Our hypothesis (H5) predicted that there is a significant difference in student deviant behavior by ethnicity. This hypothesis was tested using one-way ANOVA analysis as shown in table 6. Subjects were divided into four groups according to their ethnicity (Group 1: Yoruba; Group 2: Hausa; Group 3: Igbo; Group 4: Minority). There was a statistically significant difference at the p < .05 level in student deviant scores for the four ethnic groups: F (3, 98) = 4.16, p = .008. Hence, as predicted, hypothesis 5 is supported. Post-hoc comparisons was conducted using the Tukey HSD test indicated that the mean score for Group 3 (M = 3.10, SD = .18) was significantly different from Group 1 (M = 2.82, SD = .72), Group 2 (M = 2.82, SD = .80) and Group 4 (M = 2.63, SD =.45). The means scores revealed that Igbos students reported more deviant behaviors compared to their Hausa, Yoruba and Minority counterparts. 5. Discussion and conclusion The present study investigated the influence of honor codes organisational formal control and classroom

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justice on students’ deviant behavior. Specifically we found that honor codes, as measured by organizational formal control were negatively related to student deviant behavior (Hypothesis 1). Classroom justice was negatively related to student deviant behavior (Hypothesis 2); that there was a significant difference in student deviant by gender (Hypothesis 3); that there was a statistically significant difference in student deviant by age groups (Hypothesis 4) and there was a statistically significant difference in student deviant by ethnicity (Hypothesis 5). Our result for Hypothesis 1 is not surprising because it appears to be in line with the previous studies conducted by McCabe and Trevino (1993) and McCabe, Trevino and Butterfield (2002), who found a significant negative relationship between honor codes and students’ deviant behavior, suggesting that perception of honor codes reduce students’ tendency to engage in deviant acts. Furthermore, our result for Hypothesis 2 showed that classroom justice was not significantly related with students’ deviant behavior. However, this finding is also not surprising because it is in line with the previous research conducted by Chory-Assad and Paulsel (2004) who found that distributive justice was not a significant predictor of students’ aggressive behavior. Meanwhile, in trying to know who engages in deviant acts, the study has demonstrated that almost all students who participated in this study in one way or the other engage in deviant behavior, but differently. In particular, our result for Hypothesis 3 appears to be in line with the previous studies conducted by Walton (2011) and Jordan (2001), who found that female students exhibit more deviant behavior as compared to their male counterparts. A possible explanation for this finding is different contexts within which the study is carried out. Thus, the effects of classroom justice on students’ deviant behavior depend upon the context of the study. Furthermore, the findings of the present study are in line with those reported by Rakovski and Levy (2007) and Nonis and Swift (2001) who found that younger students exhibit more deviant behaviors as compared to the older students (Hypothesis 4). Thus the age differences in students’ deviant behavior could be explained linking mental ability to age. May and Loyd (1993) and Budner (1987) have suggested that in general older individuals have been conditioned morally and culturally to abides by the rules and regulations as compared to the younger individuals. Hence this cognitive resource makes older individuals to refrain from getting into unethical behavior. Our result for the last hypothesis is not surprising because it appears to be consistent with the studies conducted by Shamsudin, Subramaniam, & Ibrahim (2011), who found a significant difference in wrongful behaviors by ethnicity. On the basis of the above findings and discussion, there are few managerial implications for the school administrators, lecturers and educational policy makers that need to be discussed. First, the significant negative relationship between honor codes and students’ deviant behavior suggest that environmental factors are important fin enhancing reducing the tendency of student to engage in deviant behaviour deviance, as suggested by social cognitive theory of moral thought and action (1991). Therefore, universities and colleges ought to strengthen and enforce instituted honor codes so that students’ deviant behavior could be minimized. In addition ethical issues should be inculcated in the curriculum to that student will develop moral attitudes. Furthermore, the present study has several limitations that need to be noted. First, this study only confined to 102 undergraduate students from only three higher institutions of learning to represent the entire population of students in the Nigerian universities, colleges of education and polytechnics. While the sample size has met the minimum criteria for conducting a regression analysis as recommended by Knofczynski and Mundfrom (2008) and Sawyer (1984), the results obtained cannot represent the entire population of students in the Nigerian higher institutions of learning. Therefore, future study should to draw a larger sample size by including more students from other universities, colleges of education and polytechnics to generate a sample that can be relied upon as a representative of the entire students of higher institutions of learning in Nigeria. Second, this study was a cross -sectional, in which data about students’ deviant behavior were collected within a timeframe. Hence, conclusions rega rding the causal nature of the research model cannot be made using a cross -sectional design. Therefore, there is a need to confirm the findings of this study using longitudinal study in future studies. Third, this study only considered final year undergraduate students; future studies should include other undergraduate students and also the graduate students in their sample because deviant behaviors are also common among graduate students (Love & Simmons, 1998). Finally, in this study self-ratings, which involves asking students directly to rate their attitude or behaviour through the use of questionnaire was employed (Barker, Pistrang, & Elliott, 2003). However, because of fear of punishment, when students are asked to report on their deviant acts themselves, problems such as social desirability or common method bias method bias will arise that could lead to contamination of the substantive results. Therefore, future study should use superior-ratings to assess students’ deviant behaviors by their teachers because teachers have been working closely together, interacting frequently, and had the opportunity to observe students’ attitudes and


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