Subjective Norms and Academic Dishonesty: A Decision Tree Algorithm Analysis

Patriani Dewanti - Department of Accounting, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
Ida Purnama - Department,of Accounting, Universitas Pembangunan Nasional Veteran Yogyakarta, Yogyakarta, Indonesia
- Sukirno - Department of Accounting, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
Karthikeyan Parthasarathy - School of Management Studies, Kongu Engineering College, Erode, Tamilnadu, India


Citation Format:



DOI: http://dx.doi.org/10.30630/joiv.5.1.423

Abstract


Academic dishonesty becomes an exciting phenomenon to be examined. This research aimed to examine the effect of subjective norms on academic dishonesty. Data were collected from 426 accounting students from public and private universities in Yogyakarta, Indonesia. The data were analyzed with the J48 algorithm decision tree. The interest that happened in the low subjective norms node was divided into public universities and private universities. Based on the decision of tree visualization, male students with the more extended length of study in public universities tended to have lower subjective norms but higher academic dishonesty than their counterparts. The results were discussed, and recommendations were also provided to several relevant parties.

Keywords


Decision tree; academic cheating; subjective norms; student.

Full Text:

PDF

References


M. F. Nelson, M. S. L. James, A. Miles, D. L. Morrell, and S. Sledge, “Academic Integrity of Millennials: The Impact of Religion and Spirituality,” Ethics Behav., vol. 27, no. 5, pp. 385–400, 2017.

D. E. Morris and C. M. Kilian, “Do Accounting Students Cheat? A Study Examining Undergraduate Accounting Students’ Honesty and Perceptions of Dishonest Behavior,” SSRN Electron. J., 2011.

P. W. Grimes, “Dishonesty in academics and business: A cross-cultural evaluation of student attitudes,” J. Bus. Ethics, vol. 49, no. 3, pp. 273–290, 2004.

S. Park, “Goal contents as predictors of academic cheating in college students,” Ethics Behav., vol. 8422, 2019.

B. Winrow, “Do perceptions of the utility of ethics affect academic cheating?,” J. Account. Educ., vol. 37, pp. 1–12, 2016.

P. Šprajc, M. Urh, J. Jerebic, D. Trivan, and E. Jereb, “Reasons for plagiarism in higher education,” Organizacija, vol. 50, no. 1, pp. 33–45, 2017.

S. Babatunde Adeyemi and S. O. Adelaja, “Deterrent Measures and Cheating Behaviour of Accounting Undergraduates in Tertiary Institutions in Lagos Nigeria,” Int. J. Bus. Manag., vol. 6, no. 12, pp. 195–204, 2011.

C. H. Hsiao and C. Yang, “The impact of professional unethical beliefs on cheating intention,” Ethics Behav., vol. 21, no. 4, pp. 301–316, 2011.

D. L. McCabe, T. Feghali, and H. Abdallah, “Academic dishonesty in the Middle East: Individual and contextual factors,” Res. High. Educ., vol. 49, no. 5, pp. 451–467, 2008.

N. E. Day, D. Hudson, P. R. Dobies, and R. Waris, “Student or situation? Personality and classroom context as predictors of attitudes about business school cheating,” Soc. Psychol. Educ., vol. 14, no. 2, pp. 261–282, 2011.

B. E. Whitley, “Factors associated with cheating among college students: A review,” Res. High. Educ., vol. 39, no. 3, pp. 235–274, 1998.

N. T. Hendy and N. Montargot, “Understanding Academic dishonesty among business school students in France using the theory of planned behavior,” Int. J. Manag. Educ., vol. 17, no. 1, pp. 85–93, 2019.

T. H. Stone, I. M. Jawahar, and J. L. Kisamore, “Predicting academic misconduct intentions and behavior using the theory of planned behavior and personality,” Basic Appl. Soc. Psych., vol. 32, no. 1, pp. 35–45, 2010.

J. R. C. Kuntz and C. Butler, “Exploring Individual and Contextual Antecedents of Attitudes Toward the Acceptability of Cheating and Plagiarism,” Ethics Behav., vol. 24, no. 6, pp. 478–494, 2014.

T. P. Cronan, J. K. Mullins, and D. E. Douglas, “Further Understanding Factors that Explain Freshman Business Students’ Academic Integrity Intention and Behavior: Plagiarism and Sharing Homework,” J. Bus. Ethics, vol. 147, no. 1, pp. 197–220, 2018.

F. Jalilian, P. Moazami, M. Mirzaei-Alavijeh, A. M. Moazami, and C. Jalili, “Sensation seeking and the intention to cheating among college students: An application of the theory of planned behavior,” Res. J. Appl. Sci., vol. 11, no. 8, pp. 645–649, 2016.

H. Yu, P. L. Glanzer, R. Sriram, B. R. Johnson, and B. Moore, “What Contributes to College Students’ Cheating? A Study of Individual Factors,” Ethics Behav., vol. 27, no. 5, pp. 401–422, 2017.

I. Ajzen, “Theory of Planned Behavior,” Organ. Behav. Hum. Decis. Process., vol. 50, pp. 179–211, 1991.

C. H. Hsiao, “Impact of ethical and affective variables on cheating: comparison of undergraduate students with and without jobs,” High. Educ., vol. 69, no. 1, pp. 55–77, 2015.

E. Elijido-Ten, “Combining qualitative and quantitative methods in environmental accounting research,” 6th Australas. Conf. Soc. Environ. Account. Res., pp. 2–4, 2007.

U. Sekaran and R. Bougie, “Research methods for business : a skill-building approach,” John Wiley Sons, vol. Seventh ed, 2016.

J. Han, M. Kamber, and J. Pei, “Introduction,” in Data mining: concepts and techniques. Elsevier, 2011, pp. 1–38.

I. H. Witten, E. Frank, and M. a Hall, Data Mining: Practical Machine Learning Tools and Techniques (Google eBook). 2011.

S. Drazin, “Decision Tree Analysis using Weka,” Mach. Learn. II, Univ. Miami, pp. 1–3, 2010.

M. Kebede, D. T. Zegeye, and B. M. Zeleke, “Predicting CD4 count changes among patients on antiretroviral treatment: Application of data mining techniques,” Comput. Methods Programs Biomed., vol. 152, pp. 149–157, 2017.

R. Panigrahi and S. Borah, “Rank Allocation to J48 Group of Decision Tree Classifiers using Binary and Multiclass Intrusion Detection Datasets,” Procedia Comput. Sci., vol. 132, pp. 323–332, 2018.

S. Sridhar Raj and M. Nandhini, “Ensemble human movement sequence prediction model with Apriori based Probability Tree Classifier (APTC) and Bagged J48 on Machine learning,” J. King Saud Univ. - Comput. Inf. Sci., 2018.

S. B. Brown and P. Choong, “A Investigation of Academic Dishonesty among Business Students at Public and Private United States Universities,” Int. J. Manag., vol. 22, no. 2, pp. 201–2014, 2005.

K. Ahmed, “Student perceptions of academic dishonesty in a private middle eastern university,” High. Learn. Res. Commun., vol. 8, no. 1, pp. 16–29, 2018.

S. C. Yang, C. L. Huang, and A. S. Chen, “An investigation of college students’ perceptions of academic dishonesty, reasons for dishonesty, achievement goals, and willingness to report dishonest behavior,” Ethics Behav., vol. 23, no. 6, pp. 501–522, 2013.

L. Beck and I. Ajzen, “Predicting dishonest actions using the theory of planned behavior,” J. Res. Pers., vol. 25, no. 3, pp. 285–301, 1991.

E. Gentina, T. L. P. Tang, and Q. Gu, “Does Bad Company Corrupt Good Morals? Social Bonding and Academic Cheating among French and Chinese Teens,” J. Bus. Ethics, vol. 146, no. 3, pp. 639–667, 2017.

M. Bong, “Effects of parent - Child relationships and classroom goal structures on motivation, help-seeking avoidance, and cheating,” J. Exp. Educ., vol. 76, no. 2, pp. 191–217, 2008.




Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

__________________________________________________________________________
JOIV : International Journal on Informatics Visualization
ISSN 2549-9610  (print) | 2549-9904 (online)
Organized by Department of Information Technology - Politeknik Negeri Padang, and Institute of Visual Informatics - UKM and Soft Computing and Data Mining Centre - UTHM
Published by Department of Information Technology - Politeknik Negeri Padang
W : http://joiv.org
E : joiv@pnp.ac.id, hidra@pnp.ac.id, rahmat@pnp.ac.id

View JOIV Stats

Creative Commons License is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.