An investigation of the relationship between Students’ Approaches to Learning and Individual and Collaborative Academic Dishonest Behavior

Author(s):

Xin Guo(presenting / submitting)Joan Ballantine Patricia Larres

Conference:

ECER 2014

Network:

22. Research in Higher Education

Format:

Paper

Session Information

22 SES 13 A, Teaching, Learning and Assessment in Higher Education

Paper Session

Time:

2014-09-05

11:00-12:30

Room:

B020 Anfiteatro

Chair:

Mariana Gaio Alves

Contribution

The objective of the current study was to investigate if individual and collaborative forms of academic dishonesty among UK undergraduate business related students could be predicted by students’ approaches to learning, age and gender. The study addresses Marsden et al.’s (2005) concern about the poor internal reliability of the instrument they used to measure academic orientation and adopts Tait et al’s (1998) short form Approaches and Study Skills Inventory for Students (ASSIST) as the appropriate construct to measure students’ learning approaches. Additionally, it focuses on an under-researched classification of cheating behavior which reflects our modern collaborative society, namely a collectivist–individualist dichotomy. Data were collected for 1,033 UK business undergraduate students. Confirmatory factor analysis was used to test the fit of the data. Findings suggest that students’ approaches to learning are a determinant of academic misconduct, both of an individual and collaborative nature.

Method

Data were collected for 1,033 UK business undergraduate students. The participants in the study (n=1,033) were undergraduate students enrolled on first (26%), second (37.1%) and final year (36.9%) degree programmes at two business schools based at two medium sized UK universities. A total of 482 students were male (46.7%) and the remaining 551 (53.3%) were female. While the age of the respondents ranged from 18 to 36, the mean age was 20.9 years. Students’ approaches to learning were measured using the 18-item short form of the Approaches and Study Skills Inventory for Students (ASSIST) (Tait, Entwistle and McCune, 1998). Academic dishonest behaviors were measured using a 29 item self-report inventory derived from a comprehensive review of items reported in previous studies of academic dishonesty (e.g. Franklyn-Stokes and Newstead, 1995; Newstead et al., 1996; Allmon et al (2002); McCabe et al., 2001; Bennett, 2005; Brimble and Stevenson-Clarke, 2005; Roig and Marks, 2006; Kidwell and Kent, 2008; de Jager and Brown, 2010; Payan et al, 2010; Jurdi et al, 2012). Data analysis proceeded in three parts using SPSS 21 and AMOS 21. First, Cronbach’s alpha coefficients were calculated for scores yielded by the three students’ approaches to learning and individual and collaborative acts of academic dishonesty. Secondly, correlation coefficients were used to explore relationships between students’ approaches to learning, individual and collaborative acts of academic dishonesty and the control variables of age and gender. Thirdly, the hypothesized conceptual model was tested by structural equation modelling (SEM), ‘an advanced multivariate form of regression analysis that allows studying complex relationships among variables’ (Abi-Habib & Luyten, 2013, p. 922). To evaluate the fit of the hypothesized model, Tucker-Lewis Index (TLI), comparative fit index (CFI) and the root mean square error of approximation (RMSEA) were used in tandem with the standardized root mean square residual (SRMR) (Hu & Bentler, 1999; MacCallum & Austin, 2000). Statistical significance testing was undertaken (α = 0.05).

Expected Outcomes

Findings suggest that students’ approaches to learning are a determinant of academic misconduct, both of an individual and collaborative nature. First, as expected, a surface approach to learning was found to be positively associated with both individual and collaborative forms of academic dishonesty. Second, evidence was found to support the prediction that students who adopt a deep approach to learning are less likely to engage in individual acts of academic dishonesty. Finally, a negative relationship between a strategic learning approach and collaborative acts of academic dishonesty only were found. With respect to the control variables, gender was found to be a strong and consistent determinant for both individual and collaborative acts of academic dishonesty, with males more likely to engage in such behaviors as opposed to females. Age was also a predictor of collaborative but not individual acts of academic dishonesty with younger students more likely to engage in such behavior when compared to their older counterparts, again confirming earlier studies (e.g.Marsden et al., 2005). The findings for both control variables confirm to some extent earlier studies reported in the literature (e.g. Davis et al., 1992; Marsden et al., 2005). In conclusion, the findings of the current study provide evidence regarding the determinants of academic dishonest behaviour, both of an individual and collaborative nature. The findings of the study also provide insights into the collectivism-individualism construct of academic dishonest behaviour among Generation Y business related students. It is hoped that the findings might support academics identify the characteristics of business related undergraduate students who are most likely to engage in academic dishonest behaviors which in turn might facilitate the design of appropriate and targeted interventions to curb the growing rise in inappropriate academic behaviour.

References

Allmon, D. E., Page, D., & Robert, R. (2000). Determinants of Perceptions of Cheating: Ethical Orientation, Personality and Demographics. Journal of Business Ethics, 23(4), 411-422. Bennett, R. (2005). Factors associated with student plagiarism in a post-1992 university. Assessment and Evaluation in Higher Education, 30(2), 137-167. Biggs, K., Workman, J.P., & York, A.S. (2013). Collaborating to cheat: a game theoretic exploration of academic dishonesty in teams. Academy of Management Learning & Education, 12, 4-17. Davis, S. F., Grover, C. A., Becker, A. H., and McGregor, L. N. (1992). Academic dishonesty: Prevalence, determinants, techniques, and punishments, Teaching of Psychology, 19 (1), 119-121. Duff, A., Boyle, E., Dunleavy, K., & Ferguson, J. (2004). The relationship between personality, approach to learning and academic performance. Personality and Individual Differences, 36, 1907-1920. Entwistle, N.J. & Ramsden, P. (1983). Understanding Student Learning. London: Croom Helm. Franklyn-Stokes, A. and Newstead, S. E. (1995). Undergraduate Cheating: who does what and why? Studies in Higher Education, 20(2), 159-172. Gray, R., Bebbington, J., & McPhail, K. (1994). Teaching ethics in accounting and the ethics of accounting teaching: educating immorality and a possible case for social and environmental accounting education. Accounting Education: An International Journal, 3, 51-75. Haines, V.J., Diekhoff, G.M., LaBeff, E.E., & Clark, R.E. (1986). College cheating: Immaturity, lack of commitment and the neutralizing attitude. Research in Higher Education, 25, 342-354. Marsden, H., Carroll, M., & Neill, J.T. (2005). Who cheats at university? A self-report study of dishonest academic behaviours in a sample of Australian university students. Australian Journal of Psychology, 5, 1-10. Marton, F., & Saljo, R. (1976). On qualitative differences in learning-I: outcomes and processes. British Journal of Educational Psychology, 46, 4-11. McCabe, D. L., & Treviño, L. K. (1995). Cheating among business students: A challenge for business leaders and educators. Journal of Management Education, 19, 205-218. Newstead, S.E., Franklyn-Stokes, A., & Armstead, P. (1996). Individual differences in student cheating. Journal of Educational Psychology, 88(2), 229-241. Tait, H., Entwistle, N. J., & McCune, V. (1998). ASSIST: A reconceptualization of the approaches to study inventory. In C. Rust (Ed.), Improving student learning (pp.262-270). The Oxford Centre for Staff and Learning Development, Oxford Brookes University. Zhu, C. Valcke, M. & Schellens, T. (2008). A cross-cultural study of Chinese and Flemish university students: Do they differ in learning conceptions and approaches to learning. Learning and Individual Differences, 18, 120-127.

Author Information

Xin Guo (presenting / submitting)

University of the West of Scotland

Glasgow

Joan Ballantine

University of Ulster

Patricia Larres

Queen’s University, Belfast

Search the ECER Programme

Search for keywords and phrases in "Text Search"
Restrict in which part of the abstracts to search in "Where to search"
Search for authors and in the respective field.
For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.