Evaluation of Technology-Based Learning on Effectiveness and Student Satisfaction: a Case Study at the Tax Center UNPAD

Authors

  • Retta Farah Pramesti Universitas Padjadjaran
  • Agus Puji Priyono Universitas Padjadjaran
  • Rosyani Muthya Universitas Padjadjaran
  • Aulia Baharudin

DOI:

https://doi.org/10.12928/joves.v9i1.12970

Keywords:

Blended Learning, Student Centered Learning, Tax Education, Digital Learning, Learning Effectiveness and Student Satisfaction

Abstract

This study aims to evaluates the effectiveness and satisfaction of technology-based instruction that combines Blended Learning and Student-Centered Learning (SCL) in Income Tax courses at the Tax Center, Universitas Padjadjaran (UNPAD). Using a mixed-methods design, survey data from 52 students were analyzed with multiple regression to test the effects of student involvement, student roles, and implementation challenges on learning effectiveness and satisfaction; interviews and document analysis enriched the interpretation. Quantitative results show that both student involvement and student roles are positively associated with learning effectiveness, whereas implementation challenges do not exert a meaningful impact on effectiveness in this context. In contrast, student satisfaction is shaped by all three factors, with challenges emerging as the strongest driver, indicating that even highly engaged, well-positioned learners may report lower satisfaction when facing technical or organizational barriers. Qualitative findings corroborate these patterns: students value flexibility, interactivity, and the ability to review recordings, yet cite connectivity issues, reduced hands-on practice, and concentration lapses during long online sessions. Students propose practical remedies such as on-camera policies, contingency plans for disruptions, and recording face-to-face sessions for later review. The study highlights the need to pair active, role-rich pedagogy with robust facilitation and infrastructure to sustain both effectiveness and satisfaction in vocational tax education.

References

Alqahtani, A. Y., & Rajkhan, A. A. (2020). E-learning critical success factors during the COVID-19 pandemic: A comprehensive analysis of e-learning managerial perspectives. Education Sciences, 10(9), 216. https://doi.org/10.3390/educsci10090216

Baber, H. (2020). Determinants of students’ perceived learning outcome and satisfaction in online learning during the pandemic of COVID-19. Journal of Education and E-Learning Research, 7(3), 285–292. https://doi.org/10.20448/journal.509.2020.73.285.292

Bada, D., & Olusegun, S. (n.d.). Constructivism learning theory: A paradigm for teaching and learning.

Badaruddin, M., Noni, N., Jabu, B., Basri, M., Ziska, I. Y., Agung, M., B., M., Malik, A., Hartoto, M., Larekeng, S. H., Nur, R., & Dangnga, M. S. (2019). Need analysis to design blended learning model: An instructional design to create a dynamic, engaging and student-centered learning environment. In Proceedings of the 1st International Conference on Advanced Multidisciplinary Research (ICAMR 2018). https://doi.org/10.2991/icamr-18.2019.19

Capone, R., & Lepore, M. (2022). From distance learning to integrated digital learning: A fuzzy cognitive analysis focused on engagement, motivation, and participation during COVID-19 pandemic. Technology, Knowledge and Learning, 27(4), 1259–1289. https://doi.org/10.1007/s10758-021-09571-w

Cubacub, P. D. C., & Jimenez, E. C. (2025). The role of blended learning in enhancing student engagement: Evidence from high schools in Micronesia. International Journal of Didactical Studies, 3. https://doi.org/10.33902/IJODS.202533074

De Bruijn-Smolders, M., & Prinsen, F. R. (2024). Effective student engagement with blended learning: A systematic review. Heliyon, 10(23), e39439. https://doi.org/10.1016/j.heliyon.2024.e39439

Distyasa, M. J. E., Winanti, E. T., Buditjahjanto, I. G. P. A., & Rijanto, T. (2021). The effect of project-based blended learning (PJB2L) learning model on students’ learning outcomes. International Journal for Educational and Vocational Studies, 3(4), 268. https://doi.org/10.29103/ijevs.v3i4.3959

Efgivia, M. G., Adora Rinanda, R. Y., Suriyani, Hidayat, A., Maulana, I., & Budiarjo, A. (2021). Analysis of constructivism learning theory. In 1st UMGESHIC International Seminar on Health, Social Science and Humanities (UMGESHIC-ISHSSH 2020). https://doi.org/10.2991/assehr.k.211020.032

Hein, G. E. (1991). Constructivist learning theory. Institute for Inquiry.

Howard Miller, A. (2018). Using unsupervised machine learning to model tax practice learning theory. International Journal of Engineering & Technology, 7(2.4), 109. https://doi.org/10.14419/ijet.v7i2.4.13019

Kuo, T.-Y., Chen, S.-K., & Lin, S. (2023). Exploring student engagement and teacher-student interaction patterns in collaborative STEM PBL courses through epistemic network analysis. In International Conference on Computers in Education. https://doi.org/10.58459/icce.2023.1398

Li, W., Gillies, R., He, M., Wu, C., Liu, S., Gong, Z., & Sun, H. (2021). Barriers and facilitators to online medical and nursing education during the COVID-19 pandemic: Perspectives from international students from low- and middle-income countries and their teaching staff. Human Resources for Health, 19(1), 64. https://doi.org/10.1186/s12960-021-00609-9

Martin, F., Wang, C., & Sadaf, A. (2018). Student perception of helpfulness of facilitation strategies that enhance instructor presence, connectedness, engagement and learning in online courses. The Internet and Higher Education, 37, 52–65. https://doi.org/10.1016/j.iheduc.2018.01.003

Mok, K. H., Xiong, W., & Bin Aedy Rahman, H. N. (2021). COVID-19 pandemic’s disruption on university teaching and learning and competence cultivation: Student evaluation of online learning experiences in Hong Kong. International Journal of Chinese Education, 10(1), 22125868211007011. https://doi.org/10.1177/22125868211007011

Moubayed, A., Injadat, M., Shami, A., & Lutfiyya, H. (2021). Student engagement level in e-learning environment: Clustering using K-means. SocArXiv. https://doi.org/10.31235/osf.io/ecg4x

Rapanta, C., Botturi, L., Goodyear, P., Guàrdia, L., & Koole, M. (2020). Online university teaching during and after the COVID-19 crisis: Refocusing teacher presence and learning activity. Postdigital Science and Education, 2(3), 923–945. https://doi.org/10.1007/s42438-020-00155-y

Setiyani, R., H., Lianingsih, S., & Susilowati, N. (2020). Using blended learning to enhance students’ engagement and learning experience in taxation. KnE Social Sciences. https://doi.org/10.18502/kss.v4i6.6615

Tondeur, J., Scherer, R., Baran, E., Siddiq, F., Valtonen, T., & Sointu, E. (2019). Teacher educators as gatekeepers: Preparing the next generation of teachers for technology integration in education. British Journal of Educational Technology, 50(3), 1189–1209. https://doi.org/10.1111/bjet.12748

Van Laerhoven, H., Van der Zaag-Loonen, H., & Derkx, B. (2004). A comparison of Likert scale and visual analogue scales as response options in children’s questionnaires. Acta Paediatrica, 93(6), 830–835. https://doi.org/10.1111/j.1651-2227.2004.tb03026.x

Weimer, M. (2013). Learner-centered teaching: Five key changes to practice (2nd ed.). Jossey-Bass.

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Published

2026-05-23

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