Available online at www.sciencedirect.com ScienceDirect Procedia - Social and Behavioral Sciences 205 ( 2015 ) 480 484 6th World conference on Psychology Counseling and Guidance, 14-16 May 2015 Reasons for missing classes in college; the role of personality traits Majda Rijavec a *,Dubravka Miljkovic a a University of Zagreb, Faculty of Teacher Education, Savska 77, 10000 Zagreb, Croatia Abstract The aim of this study was to investigate the reasons for missing classes as well as the relationship between students personality traits and tendency to miss classes for different reasons. The first part of the study describes the development of a self-report measure of reasons for missing classes in college. Reasons included not being in the mood, personal issues, health issues, lecture issues and no negative consequences. Results showed that personality traits, especially conscientiousness, play significant role in students tendency to skip classes. Since previous research have shown positive relationship between class attendance and college grades, policies aimed at increasing attendance might be worth considering. 2015 Published The Authors. by Elsevier Published Ltd. by This Elsevier is an open Ltd. access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Keywords: class attendance, college, missing classes, personality traits, student behaviour 1. Introduction When saying that 80% of success is showing up, Woody Allen probably did not consider showing up at classes but nevertheless, he was right. Research investigating the relationship between class attendance and college grades suggest that class attendance is an important determinant of grades (e.g. Aden, Yahye, and Dahir, 2013; Clump, Bauer and Whiteleather 2003). This relationship has been found across a number of subject areas, such as: Psychology (Chenneville and Jordan, 2008; Launius 1997), Sociology (Day 1994), Economics (Cohn and Johnson 2006; Durden and Ellis, 1995), Biology (Gatherer and Manning 1998) and Business (Rodgers, 2002). A metaanalysis of the relationship between class attendance and college grades (Crede, Roch and Kieszczynka, 2010) * Majda Rijavec. Tel.: +385 98410100 E-mail address:majda.rijavec@ufzg.hr 1877-0428 2015 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). doi:10.1016/j.sbspro.2015.09.046
Majda Rijavec and Dubravka Miljkovic / Procedia - Social and Behavioral Sciences 205 ( 2015 ) 480 484 481 revealed that class attendance is better predictor of college grades than any other known predictor of academic performance, including scores on standardized admissions tests such as the SAT, high school GPA, study habits, and study skills. Even more, class attendances is likely to be beneficial for learning irrespective of the specific teaching methods and strategies (Bligh,1998). In spite of the importance of attending class, students do miss them often and for a variety of reasons. It seems that the most frequently reason cited by students was boredom or general lack of interest in attending class (Launius, 1997; Van Blerkom, 1992). Boredom is followed by illness, and interference with other course work or social life, including family emergencies and other unavoidable circumstances. Some students believe that since they pay for classes, they should be the ones to decide whether or not to attend classes, and should not be penalized for failing to show up (Maizel, 2006). Some students even suggest that they can learn more from not going to class (Schoenbrum, 2007). They believe that instead of wasting time being bored and distracted in classes, they can sit down on their own, focus, and learn the material. Lot of students believe that the importance of attendance to academic success should be linked to receiving credit for attending class and their attendance rates drop if they do not receive some credit (Moore, 2003). However, establishing causality between lecture attendance and grades is difficult. Ryan, Delaney and Harmon (2010) suggest that empirical models of higher-education outcomes may be biased if they do not include measures of individual differences. They find that higher levels of future-orientation and conscientiousness, are important determinants of lecture attendance and study time (measured as hours of study) in fact the impact of these measures on the outcomes are often more significant than other variables such as course or institutional choice, or parental background (p. 15). The aim of this study was to investigate the reasons for missing classes as well as the relationship between students personality traits and tendency to miss classes for different reasons. The more we know about the causes of absenteeism, the more we will be able to prevent them. 2. Method 2.1. The first study Development of Reasons for missing classes scale The first stage in developing the Reasons for missing classes scale was to create a list of items that represented a wide range of possible reasons. College students (N=50) were asked to write down their answers to the following question: "Why would you skip class?" In the initial stage over 70 items were collected covering a variety of reasons. Some of these items were identical or had very similar meaning and could be replaced by a single item. The research team shortened the list to 30 items. The 30 items were administered to 258 college students at University of Zagreb. Participants rated each item on 4 point scale (1 will come for sure to 4 will not come for sure). They participated voluntarily and anonymously during the regular course in psychology. Items were factor analysed, using principal-components analysis with oblimin rotation. The analysis yielded 7 factors with eigenvalues exceeding 1, accounting for 62.4% of the total variance. Following the Scree test criterion (Cattell, 1978) and interpretability of factors, the factor analysis for the first five factors was repeated. Items with loadings lower than.35 on these factors, or with loading on several factors, were discarded. A second principal components analysis with oblimin rotation was then performed for a total of 21 items. The final solution included five factors accounting for 58.9 % of the total variance. After inspection of item contents factors were named as follows: not being in the mood (39.8% of total variance), no negative consequences (7.95%), personal issues (7.28 %), health issues (5.73%) and boring lecture (5.11%). Cronbach s alpha coefficients of reliability were 0.75, 0.79, 0.74, 0.70 and 0.78 respectively. Table 1 presents the rotated factor loadings and the percentage of the total variance accounted for by these five factors for all participants.
482 Majda Rijavec and Dubravka Miljkovic / Procedia - Social and Behavioral Sciences 205 ( 2015 ) 480 484 Table 1. Items and factor loadings for the Reasons for missing classes scale Factors and items Factor loadings Not being in the mood Interesting company waiting for me..71 Nice weather..65 Bad weather..58 I don t feel like it..54 I feel sleepy. 52 Personal issues Friend has a problem and wants to talk with me..77 Family duties..67 Something more important happened..62 I could not come on time..54 I have a part time job..49 Health issues I don t feel well.. 80 I have high temperature..80 I stayed late previous night..51 I am stressed..40 Lecture issues Lecture doesn t interest me..77 Teacher is boring..68 I am afraid of the teacher..66 The lecture is useless for my future work.57 No negative consequences Teacher does not keep evidence..84 Colleague will cover for me..83 There are no consequences..81 2.2. The second study Participants and procedure Sample comprised 213 college students at University of Zagreb. They participated voluntarily and anonymously during the regular courses. Instruments a. Reasons for missing classes scale instrument developed in the first part of this study. b. IPIP 50 - International Personality Item Pool scale (Mlacic and Goldberg, 2007, Croatian version). 3. Results and discussion 3.1. Descriptive statistics
Majda Rijavec and Dubravka Miljkovic / Procedia - Social and Behavioral Sciences 205 ( 2015 ) 480 484 483 Descriptive statistics and inter-correlations of all measured variables are presented in Table 2. Inspection of mean values of students reasons for missing classes showed that having no consequences has the highest rating. Contrary to that, not being in the mood is the least probable reason for skipping classes. The associations between various reasons for missing classes were all moderately positive (with range from.36 to.56). Table 2. Means, standard deviations and correlations of reasons for missing classes and personality traits Pearson s correlation coefficients 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. not being in the mood 1.41 **.55 **.56 **.36 ** -.13 -.40 ** -.39 ** -.04 -.21 ** 2. personal issues 1.55 **.48 **.31 ** -.01 -.19 ** -.21 ** -.09 -.15 * 3. health issues 1.54 **.37 ** -.11 -.17 * -.20 ** -.02 -.19 ** 4. lecture issues 1.40 ** -.10 -.27 ** -.29 ** -.02 -.12 5. no negative consequences 1.08 -.08 -.15 *.01 -.18 ** 6. extraversion 1.30 **.18 ** -.24 **.41 ** 7. agreeableness 1.33 ** -.01.45 ** 8. conscientiousness 1 -.15 *.16 * 9. emotional stability 1 -.01 10. intellect 1 Descriptive statistics M 1.62 2.33 2.39 2.01 2.75 3.44 3.93 3.54 2.76 3.62 SD.48.57.60.58.76.56.47.58,73,49 Note. * p< 0.05; ** p < 0.001 3.2. Reasons for missing classes and personality traits In order to test whether personality traits are related to students perceptions of their reasons for missing classes, five linear regression analyses were performed. Personality traits were predictor variables and reasons for missing classes were criteria variables. The results are presented in Table 3. The multiple regression analyses showed that age and gender were not significant predictors except for missing classes for not being in the mood. Older students tend more to skip classes because of that reason. On the other hand, personality traits were significant predictors in all five regressions accounting for 6% to 18% of reasons for missing classes variance. For four reasons (not being in the mood, personal issues, health issues, lecture issues) the only significant predictor was conscientiousness. More conscientious participants reported to be less likely to miss classes for any of aforementioned reasons. For no negative consequences as the reason for missing class, additional significant predictors were extraversion and intellect. The more extraverted students, the more they tend to skip class because there are no negative consequences. Contrary to that, the higher the intellect as personality trait the less are student prone to miss class for this reason. Table 3. Summary of hierarchical regression analyses for demographic characteristics and personality traits predicting reasons for missing classes not being in the personal lecture no negative health issues mood issues issues consequences β β β β β 1 Demograph. ch. gender.074 -.088 -.033 -.067.003 age.329 **.129.131.110 -.097 R² Change.146 **.039 *.024.026.010 2 personality traits gender.016 -.053.028.000.044 age.338 **.125.151.117 -.098 extraversion.054.088 -.018.009.202 * agreeableness -,131 -.024 -.012 -.118 -.069 conscientiousness -.357 ** -.193 * -.186 * -.250 * -.151 *
484 Majda Rijavec and Dubravka Miljkovic / Procedia - Social and Behavioral Sciences 205 ( 2015 ) 480 484 emotional stability -.013 -.082 -.015.016 -.033 intellect -.076 -.10 -.125 -.001 -.230 * R² Change.179 **.059 *.060 *.092 **.096 * R.570.313.289.344.324 R 2.325.098.084.119.105 Adj. R 2.300.065.050.086.073 F 10.189 ** 2.495 * 2.500 * 4.019 * 4.100 * Note. * p< 0.05; ** p < 0.001 This study confirms that personality characteristics (especially conscientiousness) play significant (although not very strong) role in students self perceptions of reasons for missing classes. This is in line with previous studies (Crede et al., 2010). Since the most frequent reason for missing classes is the fact that there are no negative consequences it seems that at least certain students could benefit from mandatory attendance policy. References Aden, A. A., Yahye, Z. A., & Dahir, A. M. (2013). The Effect of Student s Attendance on Academic Performance: A Case Study at Simad University Mogadishu. Academic Research International, 4 (6), 409-417. Bligh, D. (1998). What s the use of lectures? (5th ed.). San Francisco: Jossey-Bass. Brocato, J. (1989). How much does coming to class matter? Some evidence of class attendance and grade performance. Educational Research Quarterly, 13, 2 6. Cattell, R. B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York: Plenum. Chenneville, T., & Jordan, C. (2008). Impact of attendance policies on course attendance among college students. Journal of the Scholarship of Teaching and Learning, 8 (3), 29-35. Clump, M. A., Bauer, H., & Whiteleather, A. (2003). To attend or not to attend: Is that a good question? Journal of Instructional Psychology, 30, 220-224. Cohn, E., & Johnson, E., 2006. Class attendance and performance in principles of economics. Education Economics, 14 (2), 211-233. Crede, M., Roch, S. G., & Kieszczynka, U. M. (2010). Class Attendance in College: A Meta-Analytic Review of the Relationship of Class AttendanceWith Grades and Student Characteristics.Review of Educational Research, 80 (2), 272 295. Day, S., 1994. Learning in large sociology classes: Journals and attendance. Teaching Sociology, 22 (2), 151-165. Douglas, S., & Sulock, J., 1995. Estimating educational production functions with correction for drops. Journal of Economic Education, 26 (2), 101-112. Durden, G. C., & Ellis, L. V. (1995). The effects of attendance on student learning in principles of economics. The American Economic Review, 85 (2), 343-346. Gatherer, D., & Manning, F. C. R., 1998. Correlation of examination performance with lecture attendance: a comparative study of first-year biological sciences undergraduates. Biochemical Education, 26 (2), 121-123. Launius, M. H. (1997). College student attendance: Attitudes and academic performance. College Student Journal, 31, 86-92. Maizel, M. (2006). Mandatory class attendance. The Diamondback via University Wire, December 12, LexisNexis (http://web.lexisnexis.com/universe/document? _m=45c95d34351 a68771a721fbf6833495d) (25/03/ Mlacic, B., & Goldberg, L. R. (2007). An Analysis of a Cross-Cultural Personality Inventory: the IPIP Big-Five Factor Markers in Croatia, Journal of Personality Assessment, 88 (2), 168 177. Moore, R. (2003) Helping students succeed in introductory biology classes: Does improving students attendance also improve their grades? Bioscience, 29, 17-25. Rocca, A. K. (2003). Student Attendance: A Comprehensive Literature Review. Journal on Excellence in College Teaching, 14, 85-107. Rodgers, J. R. (2002). Encouraging tutorial attendance at university did not improve performance. Australian Economic Papers, 41(3), 255-266. Ryan, M., Delaney, L., & Harmon, C. (2010). Micro-Level Determinants of Lecture Attendance and Additional Study-Hours. Dublin: UCD School of Economics, University College Dublin Schoenbrum, D. (2007) Give me one good reason to go to class. Daily Pennsylvanian via UWire, April 3, LexisNexis (http://web.lexisnexis.com/universe/document? _m=45c95d34351a68771a721fbf6833495d) S Van Blerkom, M. L. (1992). Class attendance in undergraduate courses. The Journal of Psychology, 126, 487-494.