Exploring Technology Integration in Education: Lecturers Perspective on Outcomes-Based Education Platforms

Julianti Kasih - Maranatha Christian University, Bandung, 40164, Indonesia
Galih Wasis - Universitas Muhammadiyah Malang, Malang, 65144, Indonesia
Hendra Bunyamin - Maranatha Christian University, Bandung, 40164, Indonesia


Citation Format:



DOI: http://dx.doi.org/10.62527/joiv.8.2.2691

Abstract


Informatics education is evolving rapidly through the adoption of Outcome-Based Education (OBE), necessitating a rigorous investigation into the effectiveness of the implementation. This study was conducted using the advanced Unified Theory of Acceptance and Use of Technology (UTAUT)-3 model to assess the potential of OBE systems in enhancing teaching and learning processes. The study integrated a comprehensive set of nine variables to measure the acceptance level of OBE systems among lecturers at Maranatha Christian University Bandung and Universitas Muhammadiyah Malang. UTAUT-3 provides a more explicit understanding by incorporating Hedonic Motivation (H.M.), Habit (H), and Personal Innovativeness (P.I.). The Model also integrated the core constructs of Performance Expectancy (P.E.), Effort Expectancy (E.E.), Social Influence (S.I.), Facilitating Conditions (F.C.), Behavioral Intention (B.I.), and Users Behavior (U.B.). The result showed that B.I. was a central determinant of U.B., suggesting users' preparedness to engage with OBE systems.Furthermore, the routine use of technology as Habit (H) was closely related to Behavioral Intension (B.I.), showing that familiarity with technology facilitated the intention to adopt OBE systems. The result showed that UTAUT-3's comprehensive framework was superior in evaluating educational technology adoption due to its ability to account for users' engagement as Hedonic Motivation (H.M.), dispositional tendencies toward Personal Innovativeness (P.I.), and the critical role of established habits. Consumers' actual experiences and technological proficiency significantly influence adoption rather than individual characteristics. Therefore, UTAUT-3 was a more effective tool for predicting and understanding the Acceptance of OBE systems, guiding educational institutions toward successfully integrating information systems in learning environments.


Keywords


outcome-based; education; acceptance; use of technology.

Full Text:

PDF

References


S. Shaheen, “Theoretical perspectives and current challenges of OBE framework,” Int. J. Eng. Educ., vol. 1, no. 2, pp. 122–129, 2019, doi: 10.14710/IJEE.1.2.122-129.

M. S. Farooq and M. Radovic-Markovic, “Modeling entrepreneurial education and entrepreneurial skills as antecedents of intention towards entrepreneurial behaviour in single mothers: a PLS-SEM approach,” Entrep. Types, Curr. Trends Futur. Perspect., vol. 198, p. 216, 2016.

S. M. F. Azam, A. Khatibi, A. Gunasinghe, and J. Abd Hamid, “The Viability of UTAUT-3 in Understanding the Lecturers Acceptance and Use of Virtual Learning Environments,” Int. J. Technol. Enhanc. Learn., vol. 1, no. 1, p. 1, 2019, doi: 10.1504/ijtel.2019.10023751.

M. Tarhini, Ali; El-Masri, “Factors affecting the adoption of elearning systems in Qatar and USA: Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2),” Educ. Tech Res. Dev, vol. 12, no. 3, pp. 183–201, 2017, doi: :10.1007/s11423-016-9508-8.

A. Gunasinghe, J. A. Hamid, A. Khatibi, and S. M. F. Azam, “The adequacy of UTAUT-3 in interpreting academician’s adoption to e-Learning in higher education environments,” Interact. Technol. Smart Educ., vol. 17, no. 1, pp. 86–106, 2020, doi: 10.1108/ITSE-05-2019-0020.

J. Kim and K. S. S. Lee, “Conceptual model to predict Filipino teachers’ adoption of ICT-based instruction in class: using the UTAUT model,” Asia Pacific J. Educ., vol. 42, no. 4, pp. 699–713, 2022, doi: 10.1080/02188791.2020.1776213.

P. Utomo, F. Kurniasari, and P. Purnamaningsih, “The Effects of Performance Expectancy, Effort Expectancy, Facilitating Condition, and Habit on Behavior Intention in Using Mobile Healthcare Application,” Int. J. Community Serv. Engagem., vol. 2, no. 4, pp. 183–197, 2021, doi: 10.47747/ijcse.v2i4.529.

S. Asanprakit and P. Limna, “Understanding the Role of Social Influence in Consumers ’ Intention to Use Social Commerce,” no. September, 2023.

Y. K. Dwivedi, N. P. Rana, A. Jeyaraj, M. Clement, and M. D. Williams, “Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model,” Inf. Syst. Front., vol. 21, no. 3, pp. 719–734, 2019, doi: 10.1007/s10796-017-9774-y.

H. Chatti and S. Hadoussa, “Factors Affecting the Adoption of E-Learning Technology by Students during the COVID-19 Quarantine Period: The Application of the UTAUT Model,” Eng. Technol. Appl. Sci. Res., vol. 11, no. 2, pp. 6993–7000, 2021, doi: 10.48084/etasr.3985.

L. D. Kaczmarek, “Encyclopedia of Personality and Individual Differences,” Encycl. Personal. Individ. Differ., no. March 2017, 2016, doi: 10.1007/978-3-319-28099-8.

C. Gan, “Understanding WeChat users’ liking behavior: An empirical study in China,” Comput. Human Behav., vol. 68, pp. 30–39, 2017, doi: 10.1016/j.chb.2016.11.002.

Y. T. Wang and K. Y. Lin, “Understanding Continuance Usage of Mobile Learning Applications: The Moderating Role of Habit,” Front. Psychol., vol. 12, no. November, pp. 1–8, 2021, doi: 10.3389/fpsyg.2021.736051.

V. Venkatesh, J. Y. L. Thong, and X. Xu, “Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology,” MIS Q. Manag. Inf. Syst., vol. 36, no. 1, pp. 157–178, 2012, doi: 10.2307/41410412.

S. Santoso, Konsep Dasar dan Aplikasi SEM dengan Amos 22. Elex Media Komputindo, Edisi ke 2. Jakarta: PT Alex Media Komputindo,Kelompok Gramedia 2018, 2018.

A. Granić and N. Marangunić, “Technology acceptance model in educational context: A systematic literature review,” Br. J. Educ. Technol., vol. 50, no. 5, pp. 2572–2593, 2019, doi: 10.1111/bjet.12864.

S. Nandwani and S. Khan, “Teachers’ Intention towards the Usage of Technology: An Investigation Using UTAUT Model,” J. Educ. Soc. Sci., vol. 4, no. 2, pp. 95–111, 2016, doi: 10.20547/jess0421604202.

A. Šumak, B. and Šorgo, “The acceptance and use of interactive whiteboards among teachers: Differences in UTAUT determinants between pre-and post-adopters,” Comput. Human Behav., vol. 64, pp. 602–620, 2016, doi: https://doi.org/10.1016/j.chb.2016.07.037.

B. Bervell and I. N. Umar, “Validation of the UTAUT model: Re-considering non-linear relationships of exogeneous variables in higher education technology acceptance research,” Eurasia J. Math. Sci. Technol. Educ., vol. 13, no. 10, pp. 6471–6490, 2017, doi: 10.12973/ejmste/78076.

E. Abu-shanab and L. Ababneh, “Exploring Academicians Acceptance of E-Learning Using an Extended TAM : The Case of Yarmouk,” J. Netw. Commun. Emerg. Technol., vol. 1, no. 1, pp. 6–10, 2015, doi: https://doi.org/10.3390/su15129363.

A. H. (2018) Ugur, N.G. and Turan, “E-learning adoption of academicians: a proposal for an extended model,” Behav. Inf. Technol., vol. 37, no. 4, pp. 393–405, 2018, doi: https:/http://dx.doi.org/10.1080/0144929X.2018.1437219.

T. Machimbidza and S. Mutula, “Factors influencing the behaviour of academics towards peer-reviewed electronic journals in Zimbabwean state universities,” South African J. Libr. Inf. Sci., vol. 83, no. 2, pp. 42–51, 2018, doi: 10.7553/83-2-1688.

S. Abrahim, B. A. Mir, H. Suhara, F. A. Mohamed, and M. Sato, “Structural equation modeling and confirmatory factor analysis of social media use and education,” Int. J. Educ. Technol. High. Educ., vol. 16, no. 1, 2019, doi: 10.1186/s41239-019-0157-y.

N. U. Ain, K. Kaur, and M. Waheed, “The influence of learning value on learning management system use: An extension of UTAUT2,” Inf. Dev., vol. 32, no. 5, pp. 1306–1321, 2016, doi: 10.1177/0266666915597546.

A. Gunasinghe, J. A. Hamid, A. Khatibi, and S. F. Azam, “Academicians’ Acceptance of Online Learning Environments: A Review of Information System Theories and Models,” Glob. J. Comput. Sci. Technol., vol. 19, no. 1, pp. 31–39, 2019, doi: 10.34257/gjcsthvol19is1pg31.

N. Rizkalla, H. Tannady, and R. Bernando, “Analysis of the influence of performance expectancy, effort expectancy, social influence, and attitude toward behavior on intention to adopt live.on,” Multidiscip. Rev., vol. 6, no. Special Issue, 2023, doi: 10.31893/multirev.2023spe017.

S. . Shen, C.M. and Shariff, “Apply UTAUT model for understanding the teacher perceptions using frog VLE”,” in Paper presented at the Postgraduate Annual Research On Informatics Seminar, Paris., 2016.

C. Technology, “Using the UTAUT model to analyze students ’ ICT adoption Samuel NiiBoi Attuquayefio Methodist University College , Ghana Hillar Addo University of Professional Studies , Ghana,” vol. 10, no. 3, pp. 75–86, 2014.

A. S. Ahmed and H. Ali Salah, “Modeling, Implementing and Evaluation a Decision Support System Used for Choosing the Best HVAC System in The Buildings, Case Study in Iraq,” JOIV Int. J. Informatics Vis., vol. 8, no. 1, pp. 289–298, 2024, doi: 10.62527/joiv.8.1.1947.

B. G. (4) Seypullaev Jumabek (1), Kurbanbaev Tuwelbay (2), Arziev Allabay (3), “Current Trends in The Formation of Mathematical Terminology on An Online Platform,” IJASCE, vol. 6, no. 1, 2024, doi: https://doi.org/10.62527/ijasce.6.1.150.

J. X. T. [5 Hyo-Jeong So [3], Kyung-sim Yeon [1], Seong-hye Yoon [1], Positioning ICT in education to achieve the Education 2030 Agenda in Asia and the Pacific: recommendations for a regional strategy Corporate author : UNESCO Office Bangkok and Regional Bureau for Education in Asia and the Pacific [1118] Person as author : Bangkok: UNESCO UNESCO Office Bangkok and Regional Bureau for Education in Asia and the Pacific, 2018.

S. Huff and N. Zealand, “THE ROLE OF CONTINUOUS TRUST,” J. Comput. Inf. Syst., no. July, 2015.