FACULTY READINESS FOR DIGITAL LEARNING ENVIRONMENTS: A RESEARCH ON ONLINE ATTENDANCE MANAGEMENT SYSTEMS

Abstract

Purpose- The purpose of this study is to investigate the readiness of the faculty towards digital learning management tools. Online attendance management systems are investigated as a part of the digitalized education environment. The statistical relations among technology readiness factors and technology acceptance variables are investigated.

Methodology- The study adopted a quantitative research method, and the survey is used as the data gathering tool. The survey consisted of items from the Technology Readiness Index (TRI) and Technology Acceptance Model (TAM). Across Turkey, 317 faculty from seven universities participated in the final survey.

Findings- The analysis reveals that there is a statistically significant yet weak relationship among technology readiness variables and acceptance of online attendance management systems. In addition, descriptive statistics presents some valuable insight regarding technology readiness situation of the faculty members.

Conclusion- Education environments are enhanced with technological tools and supported with online platforms. The most critical point is that the usage of these technological advancements is limited by technology acceptance, and this study reveals that technology readiness is a key component of technology acceptance.

Keywords

• Technology readiness,technology acceptance,educational technology,online attendance system,faculty members

References

1. Bhudke, P.A., Bhutekar, R.S., Horambe, V.V., and Naik, S. (2016). “VIVA-Tech SAM: Student Attendance Management System”. International Journal of Computer Applications Proceedings on National Conference on Role of Engineers in National Building 6(1): 10-14.
2. Davis, F.D. (1989). “Perceived Usefulness, Perceived Ease of Use, And User Acceptance”. MIS Quarterly. 13(3): 319-340.
3. Fabrigar, L.R., Wegener, D.T., MacCallum, R.C. and Strahan, E.J. (1999). “Evaluating the Use of Exploratory Factor Analysis in Psychological Research”. Psychological Methods. 4(3): 272-299.
4. Field, A. (2009). Discovering Statistics Using SPSS 3rd ed. Thousand Oaks, California: SAGE Pub.
5. Finney, J. (1970). Time and again. New York, NY: Simon and Schuster.
6. Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2010). Multivariate Data Analysis Seventh Edition. Essex: Prentice Hall.
7. Jacksi K. (2015). Design and Implementation of Online Submission and Peer Review System: A Case Study of E-Journal Of University Of Zakho. International Journal of Scientific & Technology Research, 4(8): 83-85.
8. Jacksi, K., Ibrahim, F. and Zebari, S. (2018). Student Attendance Management System. Scholars Journal of Engineering and Technology, 6(2): 49-53.

9. Ming‐Ling Lai, (2008). Technology Readiness, Internet Self‐Efficacy and Computing Experience of Professional Accounting Students. Campus-Wide Information Systems, 25(1): 18-29.
10. Norusis, M. J. (1993). SPSS for Windows: Professional Statics, Release 6.0, Chicago: SPSS Inc.
11. Nughoro, M.A and Fajar, M.A. (2017). Effects of Technology Readiness Towards Acceptance of Mandatory Web-Based Attendance System. Procedia Computer Science, 124: 319-328.
12. Nunnally, J. C. (1978). Psychometric Theory (2nd ed.), New York: McGraw-Hill.
13. Nwokeji, J.C., Olagunju, A., Apoorva, A., Frezza, S. and Tang, M.M. (2017). Requirements Model for an Integrated Attendance Monitoring System (IAMS). Future Technologies Conference (FTC), 29-30 November 2017, Vancouver, Canada.
14. Parasuraman, A. (2000). Technology Readiness Index (TRI): A Multiple-Item Scale to Measure Readiness to Embrace New Technologies. Journal of Service Research, 2(4): 307-320.
15. Patel, U.A. and Priya, S. R. (2014). Development of A Student Attendance Management System Using RFID and Face Recognition: A Review. International Journal of Advance Research inComputer Science and Management Studies, 2(8): 109-119.
16. Pires, P.J., Filho, B.A.C. and Cunha, J.C. (2011). Technology Readiness Index (TRI) Factors as Differentiating Elements between Users and Non Users of Internet Banking, and as Antecedents of the Technology Acceptance Model (TAM). in ENTERprise Information Systems International Conference Proceedings, Part II, CENTERIS 2011, Vilamoura, Portugal, October 5-7, 2011, pp. 215-229.
17. Taherdoost, H., Sahibuddin, S. and Jalaliyoon, N. (2014). Exploratory Factor Analysis; Concepts and Theory. Advances in Applied and Pure Mathematics, pp. 375-382
18. Yong, A.G. and Pearce, S. (2013). A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis. Tutorials in Quantitative Methods for Psychology, 9(2): 79-94.