Keywords: mobile learning, technology acceptance model, ICT in education, mobile class record


Technology adoption is a process that is affected by many variables. To achieve innovative teaching and learning, mClassRecord, an Android-based class record application, was developed and tested. This paper is aimed at predicting the level of adoption of mClassRecord as experienced by the respondents using the Unified Theory of Acceptance and Use of Technology Model. Specifically, this article presents the qualitative analysis of mClassRecord adoption among the respondents in terms of performance expectancy, effort expectancy, attitudes toward using mClassRecord, social influence, facilitating conditions, self-efficacy, anxiety, and behavioral intention to use mClassRecord. The respondents of the study are the 17 teacher educators in higher education institutions in Central Visayas, Philippines. A semi-structured questionnaire was used, which was adapted from the model. Results show that mClassRecord is useful in the classroom. The interaction of teachers with mClassRecord is found to be clear and understandable. The positive comments from the respondents imply that the app is a good idea for teachers. Findings reveal that there is no clear indication that there is a direct influence or support from the school administration. It shows also that the teachers acquire dissimilar skills and even different levels of the same skills. The results indicate that majority of the teachers do not have fear and apprehension in using mClassRecord. Likewise, it implies that there is positive attitude and high degree of intention to use mClassRecord. The study concludes that adoption of mClassRecord is predicted at different stages. There is strong evidence that mClassRecord offers effective and efficient class recording and management. There is promising indication that the teaching tool offers an innovative contribution to teaching.


Download data is not yet available.

Author Biography

Dave E. Marcial, Silliman University

PhD in Education, Associate Professor, Director for Silliman Online University Learning



L. Robinson, “A summary of Diffusion of Innovations,” 2009. [Online]. Available:

D. W. Surry и J. D. Farquhar, “Diffusion Theory and Instructional Technology,” Journal of Instructional Science and Technology, vol. 2, no. 1, May 1997.

E. M. Rogers, “Diffusion of Innovations,” New York, N. Y. : The Free Press, 1983.

K. Renaud and J. van Biljon, “Predicting Technology Acceptance and Adoption by the Elderly: A Qualitative study,” SAICSIT 2008, Wilderness Beach Hotel, Wilderness, South Africa, 2008.

Bridges to Technology Corp., 2005. [Online]. Available: Accessed on: March 24, 2016.

Digital Marketing, The 5 Customer Segments of Technology Adoption, 2016. [Online]. Available: Accessed on: March 24, 2016.

V. Venkatesh, M. G. Morris, G. B. Davis и F. D. Davis, “User Acceptance of Information Technology: Toward A Unified View,” MIS Quarterly, vol. 27, no.3, pp. 425 - 478, September 2003.

S.-J. Tan, “Predicting Innovation Adoption: a Choice-Based Approach, AP - Asia Pacific Advances in Consumer Research,” vol. 1, pp. 72-78, 1994.

C. Liao and P. Palvia, “Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT),” International Journal of Information Management, vol. 29, no. 4, pp. 309–320, August 2009.

F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, vol. 13, no. 3, p. 319–340, 1989.

V. Venkatesh and F. D. Davis, “A theoretical extension of the technology acceptance model: Four longitudinal field studies,” Management Science, vol. 46, no. 2, pp. 186–204, 2000.

V. Venkatesh, “Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model,” Information systems research, vol. 11, no. 4, pp. 342–365, 2000.

V. Venkatesh and H. Bala, “Technology Acceptance Model 3 and a Research Agenda on Interventions,” Decision Sciences, vol. 39, no. 2, pp. 273–315, 2008.

W. Lee, A. Wong and C. Tong, “A Qualitative Study of the Software Adoption of Building Information Modelling Technology in the Hong Kong Construction Industry, Business and Economic Research,” vol. 4, no. 2, pp. 222-236, 2014.

Khan and Hall, New Economy Handbook, November 2002. [Online]. Available: Accessed on: March 24, 2016

E. Ekebom, “Adoption of smartphones: iPhone. Research of adopting a mobile phone innovation from private consumers' viewpoint,” 2012.

N. H. Abdullah, E. Wahab and A. Shamsuddin, “Exploring the Common Technology Adoption Enablers among Malaysian SMEs: Qualitative Findings,” Journal of Management and Sustainability, vol. 3, no. 4, pp. 78-91, 2013.

P. Tobbin, “Towards a model of adoption in mobile banking by the unbanked: a qualitative study, Info,” vol. 14, no. 5, pp. 74 - 88, 2012.

B. Doolin and I. Troshani, “Drivers and Inhibitors Impacting Technology Adoption: A Qualitative Investigation into the Australian Experience with XBRL,” 18th Bled eConference, Bled, Slovenia, 2005.

S. Llewellyn, R. Procter, G. Harvey, G. Maniatopoulos and A. Boyd, “Facilitating technology adoption in the NHS: negotiating the organisational and policy context – a qualitative study,” Health Services and Delivery Research, vol. 2, no. 23, July 2014.

P. Godoe and T. S. Johansen, “Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept,” Journal of European Psychology Students, vol. 3, no. 1, pp. 38–52, 2012.

S. C. Chan and E. W. Ngai, “A qualitative study of information technology adoption: how ten organizations adopted Web-based training,” Information Systems Journal, pp. 289–315, July 2007.

K. Ghalandari, “The Effect of Performance Expectancy, Effort Expectancy, Social Influence and Facilitating Conditions on Acceptance of E-Banking Services in Iran: the Moderating Role of Age and Gender,” Middle-East Journal of Scientific Research, vol. 12, no. 6, pp. 801-807, 2012.

J. Lee, F. A. Cerreto and J. Lee, “Theory of Planned Behavior and Teachers’ Decisions Regarding Use of Educational Technology,” Educational Technology & Society, vol. 13, no. 1, pp. 152–164, 2010.

P. Moses, K. Abu Bakar, R. Mahmud and S. L. Wong, “ICT Infrastructure, Technical and Administrative Support as Correlates of Teachers’ Laptop Use,” Procedia - Social and Behavioral Sciences, vol. 59, pp. 709–714, 17-20 December 2011.

L. Minshew and J. Anderson, “Teacher self-efficacy in 1:1 iPad integration in middle school science and math classrooms,” Contemporary Issues in Technology and Teacher Education, vol. 15, no. 3, 2015.

N. Nyembezi and A. Bayaga, “Performance Expectancy and Usage of Information Systems and Technology: Cloud Computing (PEUISTCC),” International Journal of Education Science, vol. 7, no. 3, pp. 579-586, 2014.

K. Vogelsang and M. Steinhüser, “A Qualitative Approach to Examine Technology Acceptance,” Thirty Fourth International Conference on Information Systems, Milan, 2013.

E. W. Ford, N. “Menachemi and M. Thad Phillips, Predicting the Adoption of Electronic Health Records by Physicians: When Will Health Care be Paperless?,” Journal of the American Medical Informatics Association, vol. 13, no. 1, pp. 106–112, Jan-Feb 2006.

N. Sanakulov and H. Karjaluoto, “Consumer adoption of mobile technologies: a literature review,” International Journal of Mobile Communications, vol. 13, no. 3, pp. 244-275, April 2015.

V. Venkatesh, C. Speier and M. G. Morris, “User acceptance enablers in individual decision making about technology: toward an integrated model,” Decision Sciences, vol. 33, nj. 3, pp. 297-316, 2002.

How to Cite
ICT and learning tools in the higher education establishments

Most read articles by the same author(s)