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An extended CCtalk technology acceptance model in EFL education

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Abstract

Numerous scholars are devoted to investigating the technology acceptance model (TAM) and its extensions, but a comprehensive TAM is still under investigation. This study aims to formulate a relatively comprehensive model by including personal investment and identify factors that influence students’ adoption of CCtalk-aided English as a foreign language (EFL) courses. This study tests the proposed model based on data collected from 771 participants in China using CCtalk to acquire EFL. Confirmatory factor analysis and exploratory factor analysis are conducted to identify the designed model measurement. Coefficients of determination and path analyses are adopted to access the model fit index and path hypotheses. This study reveals the following results: (1) Perceived ease of use (β = 0.033, P < .001) and perceived usefulness (β = 0.04, P < .001) of CCtalk-aided EFL courses significantly influence attitudes towards using CCtalk-aided EFL courses; (2) Attitude towards using (β = 0.028, P < .001), perceived ease of use(β = 0.019, P < .01),and personal investment (β = 0.04, P < .001) in the use of CCtalk-aided EFL courses significantly influence behavioral intention to use CCtalk-aided EFL courses; (3) Self-efficacy (β = 0.061, P < .001), and relevance (β = 0.08, P < .001) of CCtalk-aided EFL courses significantly influence perceived ease of use of CCtalk-aided EFL courses; (4) Social influence (β = 0.046, P < .001), personal investment (β = 0.074, P < .01), relevance (β = 0.069, P < .001), and perceived ease of use (β = 0.035, P < .001) of CCtalk-aided EFL courses significantly influence the perceived usefulness of CCtalk-based EFL courses. This research may provide enlightenment to the future research of a comprehensive TAM.

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References

  • Alvi, I. (2021). College students’ reception of social networking tools for learning in India: An extended UTAUT model. Smart Learning Environments, 8(1). https://doi.org/10.1186/s40561-021-00164-9

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411

    Article  Google Scholar 

  • Arpaci, I. (2017). The role of self-efficacy in predicting use of distance education tools and learning management systems. Turkish Online Journal of Distance Education, 18(1), 52–62. https://doi.org/10.17718/tojde.285715

    Article  Google Scholar 

  • Atif, A., Richards, D., Busch, P., & Bilgin, A. (2015). Assuring graduate competency: A technology acceptance model for course guide tools. Journal of Computing in Higher Education, 27(2), 94–113. https://doi.org/10.1007/s12528-015-9095-4

    Article  Google Scholar 

  • Balapour, A., Nikkhah, H. R., & Sabherwal, R. (2020). Mobile application security: Role of perceived privacy as the predictor of security perceptions. International Journal of Information Management, 52. https://doi.org/10.1016/j.ijinfomgt.2019.102063

  • Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295x.84.2.191

    Article  Google Scholar 

  • Cangur, S., & Ercan, I. (2015). Comparison of model fit indices used in structural equation modeling under multivariate normality. Journal of Modern Applied Statistical Methods, 14(1), 152–167. https://doi.org/10.22237/jmasm/1430453580

    Article  Google Scholar 

  • Chen, C. F., Xu, X. J., & Arpan, L. (2017a). Between the technology acceptance model and sustainable energy technology acceptance model: Investigating smart meter acceptance in the United States. Energy Research & Social Science, 93–104. https://doi.org/10.1016/j.erss.2016.12.011

  • Chen, H., Jun, S., Huang, Y. M., & Wu, W. C. V. (2017b). Technological acceptance of LINE in flipped EFL oral training. Computers in Human Behavior, 178–190. https://doi.org/10.1016/j.chb.2016.12.066

  • Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Computers & Education, 63, 160–175. https://doi.org/10.1016/j.compedu.2012.12.003

    Article  Google Scholar 

  • Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336.

  • Cui, X. (2016). The Status Quo and Characteristics of Internet Japanese Teaching in Recent Years--Taking Hujiang CCtalk as an Example. Ability and Wisdom, 21, 94.

    Google Scholar 

  • Dai, H. M., Teo, T., Rappa, N. A., & Huang, F. (2020). Explaining Chinese university students’ continuance learning intention in the MOOC setting: A modified expectation confirmation model perspective. Computers & Education, 150. https://doi.org/10.1016/j.compedu.2020.103850

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

    Article  Google Scholar 

  • Deng, Z. C. (2014). Analysis of affordances of online chatting Community for Oral English Autonomous Learning. Hunan University.

    Google Scholar 

  • Doo, M. Y., & Bonk, C. J. (2021). Cognitive instrumental processes of flipped learners: Effects of relevance for learning, quality of learning outcomes, and result demonstrability. Journal of Educational Computing Research, 59(6), 1093–1113. https://doi.org/10.1177/0735633121989128

    Article  Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

    Article  Google Scholar 

  • Hansen, K., & Henderson, M. (2019). Does academic self-concept drive academic achievement? Oxford Review of Education, 1–16. https://doi.org/10.1080/03054985.2019.1594748

  • Hao, S. X. (2019). The application of the internet-based scaffolding instruction in college English Reading teaching. Inner Mongolia Normal University.

    Google Scholar 

  • Hsu, H. T., & Lin, C. C. (2021). Extending the technology acceptance model of college learners’ mobile-assisted language learning by incorporating psychological constructs. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13165

  • Huang, F., Teo, T., & Zhou, M. M. (2017). Factors affecting Chinese English as a foreign language teachers’ technology acceptance: A qualitative study. Journal of Educational Computing Research. https://doi.org/10.1177/0735633117746168

  • Jiao, H. J. (2020). Research of physics classroom teaching based on CCtalk. Scientific Consulting, Education and Research, 03, 182.

    Google Scholar 

  • Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544–564. https://doi.org/10.1016/j.dss.2007.07.001

    Article  Google Scholar 

  • King, R. B., Sze Yeung, S. S., & Cai, Y. (2019). Personal investment theory: A multi-faceted framework to understand second and foreign language motivation. System. https://doi.org/10.1016/j.system.2019.102123

  • Kripanont, N. (2007). Examining a technology acceptance model of internet usage by academics within ThaiBusiness schools. Ph.D., School of Information Systems. Faculty of Business and Law, Victoria University.

    Google Scholar 

  • Liu, S. H., Liao, H. L., & Pratt, J. A. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52(3), 599–607. https://doi.org/10.1016/j.compedu.2008.11.002

    Article  Google Scholar 

  • McInerney, D. M. (2008). Personal investment, culture and learning: Insights into school achievement across Anglo, aboriginal, Asian and Lebanese students in Australia. International Journal of Psychology, 43(5), 870–879. https://doi.org/10.1080/00207590701836364

    Article  Google Scholar 

  • McInerney, D. M., Dowson, M., & Yeung, A. (2005). Facilitating conditions for school motivation: Construct validity and applicability. Educational and Psychological Measurement, 65(6), 1046–1066. https://doi.org/10.1177/0013164405278561

    Article  MathSciNet  Google Scholar 

  • Ming, J. R. (2013). Users’ acceptance of mobile library. Ph.D. thesis, 1–279. School of Information Management, Wuhan University.

  • Moses, P., Wong, S. L., Abu Bakar, K., & Mahmud, R. (2013). Perceived usefulness and perceived ease of use: Antecedents of attitude towards laptop use among science and mathematics teachers in Malaysia. The Asia-Pacific Education Researcher, 22(3), 293–299. https://doi.org/10.1007/s40299-012-0054-9

    Article  Google Scholar 

  • Nguyen, H. T. H., Pham, H. V., Vu, N. H., & Hoang, H. T. (2020). Factors influencing students’ intention to use E-learning system. International Journal of Emerging Technologies in Learning, 15(18), 165–182. https://doi.org/10.3991/ijet.v15i18.15441

    Article  Google Scholar 

  • Raaij, E. M., & Schepers, J. J. L. (2008). The acceptance and use of a virtual learning environment in China. Computers & Education, 50(3), 838–852. https://doi.org/10.1016/j.compedu.2006.09.001

    Article  Google Scholar 

  • Rahmiati, Yunita, E., & Rani, R. E. P. (2019). The influence of trust, perceived usefulness, and perceived ease of using intensity of E-money with attitude toward using intervening variable in Padang City. Advances in Economics, Business and Management Research, 97, 696–701. https://doi.org/10.2991/piceeba-19.2019.75

    Article  Google Scholar 

  • Raza, S. A., Qazi, W., Khan, K. A., & Salam, J. (2020). Social isolation and acceptance of the learning management system (LMS) in the time of COVID-19 pandemic: An expansion of the UTAUT model. Journal of Educational Computing Research, 1-26. https://doi.org/10.1177/0735633120960421

  • Salloum, S. A., AlHamad, A. Q. M., Al-Emran, M., Monem, A. A., & Shaalan, K. (2019). Exploring students’ acceptance of E-learning through the development of a comprehensive technology acceptance model. IEEE Access, 1–21. https://doi.org/10.1109/ACCESS.2019.2939467

  • Sanchez-Franco, M. J. (2010). WebCT – The quasimoderating effect of perceived affective quality on an extending technology acceptance model. Computers & Education, 54(1), 0–46. DOI:https://doi.org/10.1016/j.compedu.2009.07.005.

  • Sejin, H., & Leslie, S. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565–571. https://doi.org/10.1016/j.jbusres.2008.06.016

    Article  Google Scholar 

  • Siriparp, T. (2015). Examining self-efficacy and achievement in an educational research course. Procedia - Social and Behavioral Sciences, 171, 1360–1364. https://doi.org/10.1016/j.sbspro.2015.01.254

    Article  Google Scholar 

  • Sultan, H. A. (2020). The influence of technical support, perceived self-efficacy, and instructional design on students’ use of learning management systems. Turkish Online Journal of Distance Education, 21(3), 112–141. https://doi.org/10.17718/tojde.762034

    Article  Google Scholar 

  • Sun, P. P., & Mei, B. (2020). Modeling preservice Chinese-as-a-second/foreign-language teachers’ adoption of educational technology: A technology acceptance perspective. Computer Assisted Language Learning, 1–24. https://doi.org/10.1080/09588221.2020.1750430

  • Van Mol, C. (2021). Exploring explanations for the gender gap in study abroad: A case study of the Netherlands. Higher Education. https://doi.org/10.1007/s10734-020-00671-7

  • Venkatesh, D., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–231.

    Article  Google Scholar 

  • Venkatesh, V., & Davis, F. D. A. (2000). Theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.2307/2634758

    Article  Google Scholar 

  • Venkatesh, V., Morris, M. G., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

    Article  Google Scholar 

  • Venkatesh, V., Thong, J. I. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412

    Article  Google Scholar 

  • Viswanath, V., & Hillol, B. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.xPriscilla

    Article  Google Scholar 

  • Wang, L., Wang, Z., Wang, X., & Zhao, Y. (2021). Explaining consumer implementation intentions in mobile shopping with SEM and fsQCA: Roles of visual and technical perceptions. Electronic Commerce Research and Applications, 49. https://doi.org/10.1016/j.elerap.2021.101080

  • Wang, X. C., Fan, Z. Q., & Du, A. Y. (2018). Applying CCtalk to promote the application of "flipped classroom" in rural elementary school mathematics teaching. Modern Educational Science, 04, 90–94.

    Google Scholar 

  • Wixom, B., & Watson, H. (2001). An empirical investigation of the factors affecting data warehousing success. MIS Quarterly, 25, 17–29.

    Article  Google Scholar 

  • Wu, B., & Chen, X. H. (2016). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. https://doi.org/10.1016/j.chb.2016.10.028

    Article  Google Scholar 

  • Wu, X. Y., Wu, L. X., & Zhang, L. D. (2019). Application effect of standardized patient teaching model based on CCtalk in health assessment inquiry teaching. Guangxi Medical Journal, 41(24), 3223–3224.

    Google Scholar 

  • Yu, Z. G. (2020). Extending the learning technology acceptance model of WeChat by adding new psychological constructs. Journal of Educational Computing Research, 58(6), 1121–1143. https://doi.org/10.1177/0735633120923772

    Article  Google Scholar 

  • Yu, Z. G., & Yu, X. Z. (2019). An extended technology acceptance model of a mobile learning technology. Computer Applications in Engineering Education, 27(3), 721–732. https://doi.org/10.1002/cae.22111

    Article  Google Scholar 

  • Zhai, X. T., & Han, J. (2016). Research on the Design of English Phonetic Network Classroom Based on flipped class. Curriculum Education Research, 24, 81–83.

    Google Scholar 

  • Zheng, J., & Li, S. (2020). What drives students’ intention to use tablet computers: An extended technology acceptance model. International Journal of Educational Research, 102. https://doi.org/10.1016/j.ijer.2020.1

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Funding

This work is supported by 2019 MOOC of Beijing Language and Culture University (MOOC201902) (Important) “Introduction to Linguistics”; “Introduction to Linguistics” of online and offline mixed courses in Beijing Language and Culture University in 2020; Special fund of Beijing Co-construction Project-Research and reform of the “Undergraduate Teaching Reform and Innovation Project” of Beijing higher education in 2020-innovative “multilingual +” excellent talent training system (202010032003); The research project of Graduate Students of Beijing Language and Culture University “Xi Jinping: The Governance of China” (SJTS202108).

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Authors and Affiliations

  1. Department of English Studies, Faculty of Foreign Studies, Beijing Language and Culture University, 15 Xueyuan Road, Haidian District, Beijing, 100083, China

    Yong Wang & Zhonggen Yu

  2. School of Electronic Engineering, Jiangsu Ocean University, 59 Cangwu Road, Haizhou District, Lianyungang City, 222005, Jiangsu Province, China

    Liheng Yu

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  1. Yong Wang
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Contributions

Wang Yong: Methodology, Investigation, Editing, and Writing-Original Draft.

Liheng Yu: Editing and proof-reading.

Zhonggen Yu: Conceptualization and Funding acquisition.

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Correspondence to Zhonggen Yu.

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Highlights

• Personal investment can be integrated as a new construct to extend the technology acceptance model (TAM).

• Personal investment has positive and significant influence on perceived usefulness and behavioral intention to use CCtalk-aided English courses.

• Self-efficacy, relevance, personal investment, social influence, perceived ease of use, perceived usefulness and attitude towards using are strong predictors of behavioral intention to use CCtalk-aided English courses.

• Perceived security could not have significant influence on behavioral intention to use CCtalk-aided English courses.

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Wang, Y., Yu, L. & Yu, Z. An extended CCtalk technology acceptance model in EFL education. Educ Inf Technol 27, 6621–6640 (2022). https://doi.org/10.1007/s10639-022-10909-9

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