Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/3568739.3568781acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicdteConference Proceedingsconference-collections
research-article

Determinants of Foreign Language Teachers’ Intention to Adopt Online Teaching: An empirical study by the combined model of TAM and TTF

Published: 12 January 2023 Publication History

Abstract

The purpose of this study is to explore the factors that influence foreign language teachers’ intention to use (IU) the online platform by integrating Technology Acceptance Model (TAM) and Task Technology Fit (TTF). A sample of 358 foreign language teachers from Chinese universities were selected by distributing a questionnaire and the research hypotheses were tested by multiple regression analysis. The results showed that perceived usefulness (PU), perceived ease of use (PEOU) and TTF all significantly influenced teachers’ IU the online platform. What's more, TTF was an important mediator for teachers’ intention to utilize the virtual platform. In addition, we found the specific region and specialized foreign language also play a role in the teachers’ intention of using the technology. The results of our study helps to facilitate regional higher education development and to informalize foreign language education policies in Chinese universities.

References

[1]
Wendy Sutherland-Smith. 2002. Weaving the Literacy Web: Changes in Reading from Page to Screen. The Reading Teacher 55, 7 (April 2002), 662–669. https://doi.org/10.2307/20205116
[2]
Fred D. Davis. 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly 13, 3 (September 1989), 319–340. https://doi.org/10.2307/249008
[3]
Ronny Scherer, Fazilat Siddiq, and Jo Tondeur. 2019. The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education 128, (January 2019), 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
[4]
Dale L. Goodhue and Ronald L. Thompson. 1995. Task-Technology Fit and Individual Performance. MIS Quarterly 19, 2 (June 1995), 213. https://doi.org/10.2307/249689
[5]
Mark T Dishaw and Diane M Strong. 1999. Extending the technology acceptance model with task-technology fit constructs. Information & Management 36, 1 (July 1999), 9–21. https://doi.org/10.1016/s0378-7206(98)00101-3
[6]
Bing Wu and Xiaohui Chen. 2017. Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior 67, (February 2017), 221–232. https://doi.org/10.1016/j.chb.2016.10.028
[7]
George Koutromanos, Georgios Styliaras, and Sotiris Christodoulou. 2014. Student and in-service teachers’ acceptance of spatial hypermedia in their teaching: The case of HyperSea. Education and Information Technologies 20, 3 (January 2014), 559–578. https://doi.org/10.1007/s10639-013-9302-8
[8]
Ahmad Qasim Mohammad AlHamad. 2020. Acceptance of E-learning among university students in UAE: A practical study. International Journal of Electrical and Computer Engineering (IJECE) 10, 4 (August 2020), 3660. https://doi.org/10.11591/ijece.v10i4.pp3660-3671
[9]
Kung-Teck Wong, Timothy Teo, and Sharon Russo. 2012. Influence of gender and computer teaching efficacy on computer acceptance among Malaysian student teachers: An extended technology acceptance model. Australasian Journal of Educational Technology 28, 7 (August 2012). https://doi.org/10.14742/ajet.796
[10]
Mazen El-Masri and Ali Tarhini. 2017. Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Educational Technology Research and Development 65, 3 (January 2017), 743–763. https://doi.org/10.1007/s11423-016-9508-8
[11]
Sirkka L. Jarvenpaa. 1989. The Effect of Task Demands and Graphical Format on Information Processing Strategies. Management Science 35, 3 (March 1989), 285–303. https://doi.org/10.1287/mnsc.35.3.285
[12]
Yuanxin Ouyang, CUI Tang, Wenge Rong, Long Zhang, Chuantao Yin, and Zhang Xiong. 2017. Task-technology Fit Aware Expectation-confirmation Model towards Understanding of MOOCs Continued Usage Intention. Proceedings of the 50th Hawaii International Conference on System Sciences (2017). https://doi.org/10.24251/hicss.2017.020
[13]
David C. Yen, Chin-Shan Wu, Fei-Fei Cheng, and Yu-Wen Huang. 2010. Determinants of users’ intention to adopt wireless technology: An empirical study by integrating TTF with TAM. Computers in Human Behavior 26, 5 (September 2010), 906–915. https://doi.org/10.1016/j.chb.2010.02.005
[14]
Vanye Z. Vanduhe, Muesser Nat, and Hasan F.Hasan. 2020. Continuance intentions to use gamification for training in higher education: Integrating the technology acceptance model (TAM), social motivation and task technology fit (TTF). IEEE Access (2020), 1–1. https://doi.org/10.1109/access.2020.2966179
[15]
Jum C Nunnally. 1978. Psychometric theory : 2nd ed. Mcgraw-Hill, New York.
[16]
Henry F. Kaiser. 1974. An index of factorial simplicity. Psychometrika 39, 1 (March 1974), 31–36. https://doi.org/10.1007/bf02291575
[17]
Timothy Teo, Fang Huang, and Cathy Ka Weng Hoi. 2017. Explicating the influences that explain intention to use technology among English teachers in China. Interactive Learning Environments 26, 4 (June 2017), 460–475. https://doi.org/10.1080/10494820.2017.1341940

Index Terms

  1. Determinants of Foreign Language Teachers’ Intention to Adopt Online Teaching: An empirical study by the combined model of TAM and TTF

        Recommendations

        Comments

        Please enable JavaScript to view thecomments powered by Disqus.

        Information & Contributors

        Information

        Published In

        cover image ACM Other conferences
        ICDTE '22: Proceedings of the 6th International Conference on Digital Technology in Education
        September 2022
        440 pages
        ISBN:9781450398091
        DOI:10.1145/3568739
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 12 January 2023

        Permissions

        Request permissions for this article.

        Check for updates

        Author Tags

        1. Foreign language teacher
        2. Higher education in China
        3. Online teaching
        4. Task Technology Fit (TTF)
        5. Technology Acceptance Model (TAM)

        Qualifiers

        • Research-article
        • Research
        • Refereed limited

        Conference

        ICDTE 2022

        Contributors

        Other Metrics

        Bibliometrics & Citations

        Bibliometrics

        Article Metrics

        • 0
          Total Citations
        • 48
          Total Downloads
        • Downloads (Last 12 months)27
        • Downloads (Last 6 weeks)0
        Reflects downloads up to 19 Nov 2024

        Other Metrics

        Citations

        View Options

        Login options

        View options

        PDF

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        HTML Format

        View this article in HTML Format.

        HTML Format

        Media

        Figures

        Other

        Tables

        Share

        Share

        Share this Publication link

        Share on social media