The Effect of Behaviour Intention on Academic Performance of Vocational Students in Blended Learning: A Case Study in Information Technology Courses

Sancoko Sancoko; Lydia Freyani Hawadi; Lin Yola; Deni Danial Kesa

doi:10.23960/jpp.v15i2.pp1088-1097

The Effect of Behaviour Intention on Academic Performance of Vocational Students in Blended Learning: A Case Study in Information Technology Courses

Sancoko Sancoko^(1,), Lydia Freyani Hawadi⁽²⁾, Lin Yola⁽³⁾, Deni Danial Kesa⁽⁴⁾

⁽¹⁾ Applied Administration and Business Department, Universitas Indonesia, Indonesia Doctoral Program (S3) School of Strategic and Global Studies, Universitas Indonesia, Indonesia, Indonesia
⁽²⁾ Doctoral Program (S3) School of Strategic and Global Studies, Universitas Indonesia, Indonesia,
⁽³⁾ Doctoral Program (S3) School of Strategic and Global Studies, Universitas Indonesia, Indonesia,
⁽⁴⁾ Applied Administration and Business Department, Universitas Indonesia, Indonesia, Indonesia

Corresponding Author

Article Metrics→

Indexing & Metadata Harvesting→

10.23960/jpp.v15i2.pp1088-1097

Download Full Text:

Abstract

There are three type of learning models, one of which is blended learning. Blended learning is learning that combines face-to-face instruction with e-learning. Program Vokasi Universitas Indonesia encourages lecturers to implement this model to enhance the quality of vocational students. Universitas Indonesia support for blended learning is shown through the Learning Management System: emas2.ui.ac.id. Behavioural intention in the context of blended learning is crucial, as reflect students readiness as learners to use technology. Studying academic performance is vital in the higher education, as it serves as the primary indicator of the success of the learning process and the achievement of educational goals. Objective: The study was conducted to asses the academic performance of vocational students in the blended learning model. Methods: This study uses the concept of behaviour intention derived from the Technology Acceptance Model (TAM). This study uses a quantitative approach for the analysis, an online survey was conducted to obtain data from 65 respondents, who have taken information technology courses. The collected data is then processed using SPSS using three stages: validity and reliability test, simple regression and moderation test. For the moderation test, subgroups based on gender and school origin were used. Findings: The result showed a significant effect behaviour intention on academic performance among vocational students. The moderation test revealed different results for the indicators: gender (male vs female) and school origin (public vs privat school). Significant result were found for the female and public school as moderation categories.

Keywords: behavior intention, academic performance, blended learning, vocational.

References

Aldoori, R. Z. K. (2023). The difference among blended learning, e-learning, and face-to-face learning. Humanitarian and Natural Sciences Journal. https://doi.org/10.53796/hnsj41014

Aldraiweesh, A., & Alturki, U. (2023). Exploring factors influencing the acceptance of e-learning and students’ cooperation skills in higher education. Sustainability (Switzerland), 15(12). https://doi.org/10.3390/su15129363

Andriani, D. S., Saputra, A., Husin, A., & Waty, E. R. K. (2022). Survei kepuasan mahasiswa program studi pendidikan masyarakat universitas sriwijaya terhadap pelaksanaan hybrid learning pasca covid 19. Sustainable Jurnal Kajian Mutu Pendidikan, 5(2), 374–384. https://doi.org/10.32923/kjmp.v5i2.2796

Asencios-Trujillo, L., Asencios-Trujillo, L., La-Rosa-Longobardi, C., & Gallegos-Espinoza, D. (2024). Study hours vs. exam results: academic success of students through performance prediction. International Journal of Engineering Trends and Technology, 72(7), 118–123. https://doi.org/10.14445/22315381/IJETT-V72I7P113

Darlis, A., Sinaga, A. I., Perkasyah, M. F., Sersanawawi, L., & Rahmah, I. (2022). Pendidikan berbasis merdeka belajar. Journal Analytica Islamica, 11(2), 393. https://doi.org/10.30829/jai.v11i2.14101

Durndell, A., & Haag, Z. (2002). Computer self efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample. www.elsevier.com/locate/comphumbeh

Farb, A. F., & Matjasko, J. L. (2012). Recent advances in research on school-based extracurricular activities and adolescent development. In Developmental Review (Vol. 32, Issue 1, pp. 1–48). https://doi.org/10.1016/j.dr.2011.10.001

Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of e-mail: An extension to the technology acceptance model. MIS Quarterly: Management Information Systems, 21(4), 389–400. https://doi.org/10.2307/249720

Hahn, S., Kim, T.-H., & Seo, B. (2014). Effects of public and private schools on academic achievement. Seoul Journal of Economics, 27.

Latifah, M., & Amelia, R. (2019). Predictors of adolescent academic achievement: the role of individual and family socioeconomic factors. In Journal of Family Sciences E (Vol. 04, Issue 02).

Lee, B. C., Yoon, J. O., & Lee, I. (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers and Education, 53(4), 1320–1329. https://doi.org/10.1016/j.compedu.2009.06.014

Liah, :, & Nasution, R. (2017). Self-concept and academic performance (Issue 2).

Linus, I. C. (2019). E-Learning and information and communication technology (ICT). World Applied Sciences Journal, 37(8), 634–640. https://doi.org/10.5829/idosi.wasj.2019.634.640

Mappadang, A., Khusaini, K., Sinaga, M., & Elizabeth, E. (2022). Academic interest determines the academic performance of undergraduate accounting students: Multinomial logit evidence. Cogent Business and Management, 9(1). https://doi.org/10.1080/23311975.2022.2101326

Olejarczuk, E. (2014). The e-learning component of a blended learning course. Teaching English with Technology, 14(3), 58–68. http://www.tewtjournal.org

Ong, C. S., & Lai, J. Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816–829. https://doi.org/10.1016/j.chb.2004.03.006

Osguthorpe, R. T., & Graham, C. R. (2003). Blended learning environments: definitions and directions. Quarterly Review of Distance Education, 4(3).

Rana, J., Gutierrez, P. L., & Oldroyd, J. C. (2021). Quantitative methods. In Global Encyclopedia of Public Administration, Public Policy, and Governance (pp. 1–6). Springer International Publishing. https://doi.org/10.1007/978-3-319-31816-5_460-1

Sam Howell. (2022). Importance of skills in human life. 104(1).

Shatta, D. N. (2023). The influence of behavioral intention to use e-learning system on academic performance in developing countries: tanzania context. The Barcelona Conference on Education 2023: Official Conference Proceedings, 953–967. https://doi.org/10.22492/issn.2435-9467.2023.75

Tahar, A., Riyadh, H. A., Sofyani, H., & Purnomo, W. E. (2020). Perceived ease of use, perceived usefulness, perceived security and intention to use e-filing: The role of technology readiness. Journal of Asian Finance, Economics and Business, 7(9), 537–547. https://doi.org/10.13106/JAFEB.2020.VOL7.NO9.537

Topping, K. J., Douglas, W., Robertson, D., & Ferguson, N. (2022). Effectiveness of online and blended learning from schools: A systematic review. Review of Education, 10(2). https://doi.org/10.1002/rev3.3353

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. https://doi.org/10.2307/30036540

Zuhdi, A., Firman, F., & Ahmad, R. (2021). The importance of education for humans. SCHOULID: Indonesian Journal of School Counseling, 6(1), 22. https://doi.org/10.23916/08742011

Refbacks

There are currently no refbacks.

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

View My Stats

Username
Password
Remember me