Investigating University Student’s Acceptance of Information and Communication Technology: Applying the Technology Acceptance Model
Building on the technology acceptance model (TAM), this study examines university student’s acceptance of information and communication technology (ICT) as a learning resource outside of the classroom. With the aim of looking more deeply into this subject, the study applied the technology acceptance model to recognize the effect of perceived usefulness on the student’s actual use of ICT with the existence of perceived usefulness as a moderator variable. Data were collected from 376 students from Duhok Polytechnic University in the Kurdistan Region of Iraq using a questionnaire survey consisting of 15 items developed based on the related literature. The results support that both perceived ease of use and perceived usefulness are key determinants of student’s actual use of ICT as a learning resource, and the relationship between perceived ease of use and actual use is moderated by perceived usefulness. Based on the findings, conclusions, implications, limitations, and an outlook for future studies were made. The originality of this study stems from the use of perceived usefulness as a moderator on the relationship between perceived ease of use and actual use of ICT among university students.
Akman, I., & Turban, C. (2017). User acceptance of social learning systems in higher education: An application of the extended technology acceptance model. Innovations in Education and Teaching International, 54, 229–237.
Al-Gahtani, S. (2016). ‘Empirical investigation of e-learning acceptance and assimilation: A structural equation model. Applied Computing and Informatics 12(1), 27–50.
Saroia A. & Gao S. (2019). Investigating university students’ intention to use mobile learning management systems in Sweden. Innovations in Education and Teaching International, 56(5), 569-580, doi: https://doi.org/10.1080/14703297.2018.1557068
Davis, D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. Management Information Systems Research Center, University of Minnesota (MIS Quarterly), 13(3), 319–340. doi: https://doi.org/10.2307/249008
Dumpit, D. & Fernandez, C. (2017). Analysis of the use of social media in Higher Education Institutions (HEIs) using the Technology Acceptance Model. International Journal of Educational Technology in Higher Education, 14(5), 1-16. doi: https://doi.org/10.1186/s41239-017-0045-2
Edmunds, R., Thorpe, M. & Conole, C. (2012) Student attitudes towards and use of ICT in course study, work and social activity: A technology acceptance model approach. British Journal of Educational Technology, 43(1), 71–84. doi: https://doi.org/10.1111/j.1467-8535.2010.01142.x
Egle, S. & B. Nijole (2015). University Students’ Attitudes Towards the Usage of Web 2.0 Tools for Learning Esp. A Preliminary Investigation. Socialinių mokslų studijos / Societal Studies, 7(2), 270–291.
Farahat, T. (2012). Applying the Technology Acceptance Model to Online Learning in the Egyptian Universities. Procedia - Social and Behavioral Sciences, 64, 95 – 104.
Fishbein, M. & Ajzen, I. (1975) Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading, MA, USA.
Hanif, A., Jamal, F. & Imran, M. (2018). Extending the Technology Acceptance Model for Use of e-Learning Systems by Digital Learners. IEEE Access, 6, 73395-73404. doi: 10.1109/ACCESS.2018.2881384
Hayes, A. (2018). Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation. Communication Monographs, 85(1), 4-40. doi: https://doi.org/10.1080/03637751.2017.1352100
Horton, P., Buck, T., Waterson, E., & Clegg, W. (2001). Explaining intranet use with the Technology Acceptance Model. Journal of Information Technology, 16(4), 237–249. https://doi. org/10.1080/02683960110102407
Iqbal, S. & Bhati, Z. (2015). An Investigation of University Students’ Readiness towards M-learning using Technology Acceptance Model. International Review of Research in Open and Distributed Learning, 16(4):83-102.
Ismael, H. & Abbas, S. (2019). Adapting Technology Acceptance Model to Predict Attitudes Toward Using E-Management Exploratory study of the views of the heads of the scientific departments at the University of Duhok. Academic Journal of Nawroz University (AJNU), 8(4), 393-404. doi: https://doi.org/10.25007/ajnu.v8n4a484
Joo, J., Kim, N. & Kim, H. (2016). Factors predicting online university students’ use of a mobile learning management system (m-LMS). Educational Technology Research and Development, 64, 611–630.
Kline, R. (2011). Principles and Practice of Structural Equation Modeling (3rd ed.). NY: Guilford Publications.
Koul, S. & Eydgahi, A. (2018). Utilizing technology acceptance model (TAM) for driverless car technology adoption. Journal of Technology Management & Innovation, 13(4), 37-46.
Masrom, M. (2007). Technology Acceptance Model and E-learning. 12th International Conference on Education, Sultan Hassanal Bolkiah Institute of Education, University Brunei Darussalam, 21-24 May. doi: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.554.6982&rep=rep1&type=pdf
Momani, A., Yafooz, W. & Jamous, M. (2017). The Evolution of Technology Acceptance Theories. International Journal of Contemporary Computer Research (IJCCR),.1 (1), 51-58.
Nazu, S. (2016). Evaluation of Students’ Attitude towards ICT for Learning Perceived usefulness: Case Study of EMU IT Students. Master theses in Information and Communication Technologies, Eastern Mediterranean University, Gazimağusa, North Cyprus, 2016.
Park, S., Nam, M. & Cha, S. (2012). University students' behavioral intention to use mobile learning: Evaluating the technology acceptance model. British Journal of Educational Technology, 43(4), 592-605.
Park, S. (2009). An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning. Educational Technology & Society, 12(3), 150–162.
Portz J., Bayliss, E., Bull, S., Boxer, R., Bekelman, D., Gleason, K. & Czaja, S. (2019). Using the Technology Acceptance Model to Explore User Experience, Intent to Use, and Use Behavior of a Patient Portal Among Older Adults with Multiple Chronic Conditions: Descriptive Qualitative Study. J Med Internet Res; 21(4): e11604. doi: 10.2196/11604
Roca, J. & Gagne, M. (2008). Understanding E-Learning Continuance Intention in The Workplace: A Self-Determination Theory Perspective. Computers in Human Behavior, 24, 1585–1604.
Sharma, S., Chandel, J., & Govindaluri, S. (2014) Students’ acceptance and satisfaction of learning through course websites. Education, Business and Society: Contemporary Middle Eastern Issues, 7, (2/3), 152–166.
Taherdoost, H. (2019). Importance of Technology Acceptance Assessment for Successful Implementation and Development of New Technologies. Global Journal of Engineering Sciences, 1(3): GJES.MS.ID.000511. doi: 10.33552/GJES.2019.01.000511.
Tingoy, O. & Gulluoglu, S. (2011). Informatics education in different disciplines at university level case study: A survey of attitude toward information technology. The Turkish Online Journal of Educational Technology, 10(4), 221-229.
Yea-Ru, T. (2015). Applying the Technology Acceptance Model (TAM) to explore the eﬀects of a Course Management System (CMS)-Assisted EFL Writing Instruction. CALICO Journal, 32(1), 153-171.
Zogheib, B., Rabaa, A., Zogheib, S. & El Saheli, A. (2015). University Students’ Acceptance of Technology in Math Classes: Does Gender Matter?. Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS), 6(4), 273- 287.
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