Academic Dishonesty dan Variabel yang Memotivasinya: Studi Pada Pembelajaran Bermediasi TI

Sondang Aida Silalahi, Andri Zainal, Rini Heriliani, Gaffar Hafiz Sagala

Abstract


Pembelajaran bermediasi Teknologi Informasi (TI) menghasilkan tantangan tersendiri. Disamping memberikan kesempatan untuk meningkatkan kualitas pembelajaran, pembelajaran bermediasi TI juga membawa risiko academic dishonesty. Penelitian ini bertujuan untuk meneliti dishonesty academic dalam konteks pembelajaran bermediasi TI dan aspek-aspek yang memotivasinya. Subjek penelitian ini adalah mahasiswa Jurusan Akuntansi di Universitas Negeri Medan (Unimed) yang telah selesai melaksanakan pembelajaran etika profesi yang diselenggarakan secara blended. Data dikumpulkan dengan kuisioner elektronik dengan teknik penyampelan bertujuan. Peneliti berhasil mengumpulkan delapan puluh data yang selanjutnya dianalisis dengan Structural Equational Modelling (SEM) berbasis varians. Penelitian ini menemukan bahwa alasan akademik dan non-akademik menjadi motivator mahasiswa untuk melakukan tindakan academic dishonesty. Peneliti merekomendasikan dosen pendidikan tinggi untuk mengorientasi mahasiswa agar terkendali dari tindakan academic dishonesty dengan menyasar indikator akademik dan non-akademik yang kritikal bagi mahasiswa. Hal ini penting sebab tindakan academic dishonesty dapat berdampak destruktif jangka panjang pada perilaku belajar mahasiswa.


References


Aldosemani, T., Shepherd, C. E., & Bolliger, D. U. (2019). Perceptions of Instructors Teaching in Saudi Blended Learning Environments. TechTrends, 63(3), 341-352.

Ampuni, S., Kautsari, N., Maharani, M., Kuswardani, S., & Buwono, S. B. S. (2020). Academic dishonesty in Indonesian college students: An investigation from a moral psychology perspective. Journal of Academic Ethics, 18(4), 395-417.

Bobbitt, M. L. and Dabholkar, P. A. (2001), “Integrating Attitudinal Theories to Understand and Predict Use of Technology-Based Self-Service,” International Journal of Service Industry Management, 12 (5), 43-70.

Cheng, B., Wang, M., Mørch, A. I., Chen, N. S., & Spector, J. M. (2014). Research on e-learning in the workplace 2000–2012: a bibliometric analysis of the literature. Educational research review, 11, 56-72.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

Dowd, S. B. (1992). Academic integrity: A review and case study.

Field, A. (2013). Discovering statistics using IBM SPSS statistics. sage.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.

Geddes, K. A. (2011). Academic dishonesty among gifted and high-achieving students. Gifted child today, 34(2), 50-56.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long range planning, 46(1-2), 1-12.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24.

Jones, P., Skinner, H., Sloan, D., Porter, E., Robins, K., & McCourt, K. (2014). Using e-learning to support international students’ dissertation preparation. Education+ Training.

Kim, S., Haley, E., & Koo, G. Y. (2009). Comparison of the paths from consumer involvement types to ad responses between corporate advertising and product advertising. Journal of Advertising, 38(3), 67-80.

Lee, Y. H., Hsieh, Y. C., & Chen, Y. H. (2013). An investigation of employees' use of e-learning systems: applying the technology acceptance model. Behaviour & Information Technology, 32(2), 173-189.

Murdock, T. B., Beauchamp, A. S., & Hinton, A. M. (2008). Predictors of cheating and cheating attributions: Does classroom context influence cheating and blame for cheating?. European Journal of Psychology of Education, 23, 477-492.

Nisar, T. M. (2002). Organisational determinants of e‐learning. Industrial and Commercial training.

Putra, P. D., Zainal, A., & Thohiri, R. (2023). Dishonesty In Online Learning: Distance Learning Perspectives During Pandemic. Turkish Online Journal of Distance Education, 24(2), 108-119.

Rahimi, M. R., Ren, J., Liu, C. H., Vasilakos, A. V., & Venkatasubramanian, N. (2014). Mobile cloud computing: A survey, state of art and future directions. Mobile Networks and Applications, 19(2), 133-143.

Rettinger, D. A., & Kramer, Y. (2009). Situational and personal causes of student cheating. Research in higher education, 50, 293-313.

Sarabadani, J., Jafarzadeh, H., & ShamiZanjani, M. (2017). Towards Understanding the Determinants of Employees' E-Learning Adoption in Workplace: A Unified Theory of Acceptance and Use of Technology (UTAUT) View. International Journal of Enterprise Information Systems (IJEIS), 13(1), 38-49

Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. john wiley & sons.

Stahl, B. C. (2020). E-teaching-the economic threat to the ethical legitimacy of education?. Journal of Information Systems Education, 15(2), 6.

Yoo, S. J., Han, S. H., & Huang, W. (2012). The roles of intrinsic motivators and extrinsic motivators in promoting e-learning in the workplace: A case from South Korea. Computers in Human Behavior, 28(3), 942-950

Zainal, A., Sagala, G. A., & Silalahi, S. A. (2021). Do learning approaches matter on setting the time spent for pre-service teachers?. Cakrawala Pendidikan, 40(3), 613-623.




DOI: https://doi.org/10.30596/liabilities.v6i2.15742

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