Behavioral intention to use electronic resources by distance learners: An extension of the technology acceptance model

Abstract

This study aimed to discover the factors affecting behavioral intention to use electronic resources by distance learners of the Open University of Sri Lanka, and to develop a model explaining behavioral intention to use such resources. Using the Technology Acceptance Model (TAM) as the theoretical basis, this study explored the effect of five external factors on the behavioral intention of distance learners toward using e-resources. A quantitative research approach was used, and data were collected from a survey of 379 active undergraduates of the Open University of Sri Lanka. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was conducted to obtain the results of the study. The results of PLS-SEM reveal that the distance mode of learning and relevance of information are the two major external factors that affect behavioral intention to use e-resources. Computer self-efficacy and user satisfaction also have a significant influence on the dependent variable. Social influence, on the other hand, shows no significant impact. Of the TAM constructs, perceived usefulness, perceived ease of use, and user attitudes significantly affect e-resource utilization behavior.

Keywords

Behavioral intention distance learners e-resources structural equation modeling technology acceptance model

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References

Ahituv

(1980) A systematic approach toward assessing the value of an information system. MIS Quarterly 4(4): 61–75.

Ajzen

(1991) The theory of planned behavior. Organizational Behavior and Human Decision Processes 50(2): 179–211.

Al-Aulamie

(2013) Enhanced technology acceptance model to explain and predict learners’ behavioural intentions in learning management systems. PhD Thesis, University of Bedfordshire, Luton. Available at: https://uobrep.openrepository.com/handle/10547/323773 (accessed 22 January 2020).

Almarashdeh

Alsmadi

(2016) Investigating the acceptance of technology in distance learning program. In: 2016 IEEE and IFIP international conference in central Asia on information science and communications technologies ICISCT, Tashkent, Uzbekistan, 2–4 November 2016, pp.1–5. Tashkent: Tashkent University of Information Technologies.

Ankrah

Atuase

(2018) The use of electronic resources by postgraduate students of the University of Cape Coast. Library Philosophy and Practise. Epub ahead of print 07 February 2018. Available at: https://digitalcommons.unl.edu/libphilprac/1632/ (accessed 18 March 2020).

Bailey

Pearson

(1983) Development of a tool for measuring and analyzing computer user satisfaction. Management Science 29(5): 530–545.

Boadi

Letsolo

(2004) Information needs and information seeking behaviour of distance learners at the Institute of extra-mural studies in Lesotho. Information Development 20(3): 189–199.

Byrne

Bates

(2009) Use of the university library, elibrary, VLE, and other information sources by distance learning students in University College Dublin: Implications for academic librarianship. New Review of Academic Librarianship 15(1): 120–141.

Daramola

(2016) Perception and utilization of electronic resources by undergraduate students: The case of the Federal University of Technology Library, Akure. American Journal of Educational Research 4(5): 366–370.

10.

Dash

Paul

(2021) CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change 173(3): 121092.

11.

Davis

(1986) A technology acceptance model for empirically testing new end-user information systems: Theory and results. PhD Thesis, Massachusetts Institute of Technology, Cambridge.

12.

Davis

(1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3): 319–339.

13.

Davis

Bagozzi

Warshaw

(1989) User acceptance of computer technology: A comparison of two theoretical models. Management Science 35(8): 982–1003.

14.

DeLone

McLean

(1992) Information systems success: The quest for the dependent variable. Information Systems Research 3(1): 60–95.

15.

Dumpit

Fernandez

(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(1): 5–16.

16.

Farahat

(2012) Applying the technology acceptance model to online learning in the Egyptian universities. Procedia - Social and Behavioral Sciences 64: 95–104.

17.

Gunasekera

(2010) Usage of virtual resource centre of the Open University of Sri Lanka: distance learner experience. In: Katariya

Ambu

JPK

Ram

(eds) 2nd international symposium on Emerging technologies and change in dimension of libraries and information services ETTLIS, Waknaghat, India, 3–5 June 2010, pp.252–256. Waknaghat: Jaypee University of Information Technology.

18.

Gunasekera

(2012) An investigation on use of e-information resources by distance learners at CRC computer lab of the Open University of Sri Lanka. In: 3rd international symposium on emerging trends and technologies in libraries and information services ETTLIS, New Delhi, India, 26–27 October 2012, pp.569–578. Waknaghat: Jaypee University of Information Technology.

19.

Gunasekera

(2014) Use of online learning resources: Experiences explored by distance learners at Matara Regional Centre of the Open University of Sri Lanka. E-Library Science Research Journal 2(4): 1–12.

20.

Hair

Hult

GTM

Ringle

, et al. (2014) A Primer on Partial Least Squares Structural Equation Modeling. Thousand Oaks, CA: SAGE Publishing.

21.

Hanif

Jamal

Imran

(2018) Extending the technology acceptance model for use of e-learning systems by digital learners. IEEE Access 6: 73395–73404.

22.

Hill

(1998) What sample size is “enough” in internet survey research. Interpersonal Computing and Technology 6(3–4): 1–10.

23.

Hong

Thong

JYL

Wong

, et al. (2002) Determinants of user acceptance of digital libraries: An empirical examination of individual differences and system characteristics. Journal of Management Information Systems 18(3): 97–124.

24.

Izuagbe

Hamzat

Joseph

(2016) Electronic information resources (EIR) adoption in private university libraries: The moderating effect of productivity and relative advantage on perceived usefulness. Journal of Information Science Theory and Practice 4(1): 30–48.

25.

Karahanna

Straub

(1999) The psychological origins of perceived usefulness and ease-of-use. Information Management 35(4): 237–250.

26.

Karunarathna

(2015) Use of electronic resources by law degree students at Anuradhapura Regional Centre of the Open University of Sri Lanka. Journal of the University Librarians Association of Sri Lanka 18(2): 41–61.

27.

Katz

(2002) Attitudes affecting college students’ preferences for distance learning. Journal of Computer Assisted Learning 18(1): 2–9.

28.

Kelley

Orr

(2003) Trends in distant student use of electronic resources: A survey. College & Research Libraries 64(3): 176–191.

29.

Kher

Downey

Monk

(2013) A longitudinal examination of computer self-efficacy change trajectories during training. Computers in Human Behavior 29(4): 1816–1824.

30.

Kim

(2005) User acceptance of web-based subscription databases: extending the technology acceptance model. PhD Thesis, The Florida State University, Florida. Available at: https://diginole.lib.fsu.edu/islandora/object/fsu:181256/datastream/PDF/download (accessed 25 November 2019).

31.

Kripanont

(2007) Examining a technology acceptance model of internet usage by academics within Thai business schools. PhD Thesis, Victoria University, Australia. Available at: http://vuir.vu.edu.au/1512/1/Kripanont.pdf (accessed 22 January 2020).

32.

Lancaster

(2005) Research Methods in Management - A Concise Introduction to Research in Management and Business Consultancy. Oxford: Elsevier Butterworth-Heinemann.

33.

Lee

Lehto

(2013) User acceptance of YouTube for procedural learning: An extension of the technology acceptance model. Computers & Education 61(1): 193–208.

34.

Liaw

(2008) Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education 51(2): 864–873.

35.

Liu

Yang

( (2004) Factors influencing distance-education graduate students’ use of information sources: A user study. The Journal of Academic Librarianship 30(1): 24–35.

36.

Memon

Ramayah

Cheah

, et al. (2021) PLS-SEM statistical programs: A review. Journal of Applied Structural Equation Modeling 5(1): i–xiv.

37.

Parsons

(2010) Information provision for HE distance learners using mobile devices. The Electronic Library 28(2): 231–244.

38.

Saunders

MNK

Lewis

Thornhill

(2019) Research Methods for Business Students, 8th edn. New York, NY: Pearson.

39.

Setiawan

Setyohadi

(2018) Understanding customers’ intention to use social network sites as complaint channel: An analysis of young customers’ perspectives. E3S Web of Conferences 31: 1–7.

40.

Shih

(2004) Extended Technology Acceptance Model of internet utilization behavior. Information Management 41(6): 719–729.

41.

Szymanski

Hise

(2000) E-satisfaction: An initial examination. Journal of Retailing 76(3): 309–322.

42.

Tang

Tseng

(2013) Distance learners’ self-efficacy and information literacy skills. The Journal of Academic Librarianship 39(6): 517–521.

43.

Tao

(2009) Intention to use and actual use of electronic information resources: Further exploring Technology Acceptance Model (TAM). In: 2009 AMIA annual symposium, San Francisco, CA, 14–18 November 2009, pp.629–633. San Francisco, CA: AMIA Knowledge Center.

44.

Tarhini

Elyas

Akour

, et al. (2016) Technology, demographic characteristics and e-learning acceptance: A conceptual model based on extended technology acceptance model. Higher Education Studies 6(3): 72–89.

45.

Tekale

Dalve

(2012) E-Resources. Review of Research 1(4): 1–4.

46.

Tella

(2011) Predicting users’ acceptance of e-library from the perspective of Technology Acceptance Model. International Journal of Digital Library Systems 2(4): 34–44.

47.

The Open University of Sri Lanka (2019) Open and distance learning. Available at: https://ou.ac.lk/introduction-to-odl-system/ (accessed 25 March 2022).

48.

Thong

JYL

Hong

Tam

(2002) Understanding user acceptance of digital libraries: What are the roles of interface characteristics, organizational context, and individual differences? International Journal of Human-Computer Studies 57: 215–242.

49.

Tury

Robinson

Bawden

(2015) The information seeking behaviour of distance learners: A case study of the University of London international programmes. The Journal of Academic Librarianship 41(3): 312–321.