Students’ Adoption of ICT Tools for Learning English Based on Unified Theory of Acceptance and Use of Technology

Limin He

School of Foreign Languages, Zhaoqing University, Zhaoqing, Guangdong, China.

Chunming Li *

School of Foreign Languages, Zhaoqing University, Zhaoqing, Guangdong, China.

*Author to whom correspondence should be addressed.


Information and communication technology (ICT) has advanced significantly over the past few decades, and students now frequently use ICT tools that enable them to learn anywhere and at any time. This study explored the influencing factors of the adoption of ICT tools among Chinese college students to learn English based on the unified theory of acceptance and use of technology (UTAUT). Structural equation modelling was applied to analyse sample data collected from 223 students in Zhaoqing University and Guangdong University of Finance in China. The results revealed that effort expectancy, performance expectancy and social influence exerted significant effect on behavioural intention. In addition, facilitating conditions and behavioural intention are positively and significantly related to use behaviour. The five variables, namely, effort expectancy, performance expectancy, social influence, facilitating conditions and behavioural intention explained 93.4% of the total variance in the ICT tools use behaviour to learn English by Chinese college students, confirming the validity of UTAUT in Chinese higher education context. Finally, some implications were provided to boost the adoption of ICT tools for promoting students’ learning performance.

Keywords: Adoption, ICT tools, English learning, the unified theory of acceptance and use of technology, structural equation modelling

How to Cite

He, Limin, and Chunming Li. 2023. “Students’ Adoption of ICT Tools for Learning English Based on Unified Theory of Acceptance and Use of Technology”. Asian Journal of Education and Social Studies 44 (3):26-38.


Download data is not yet available.


Chau KG. The effect of ICT on learners’ speaking skills development. Int J TESOL Educ. 2021;1(1):22-9.

Tran TML, Nguyen TTH. The impacts of technology-based communication on EFL students’ writing. AsiaCALL Online Journal. 2021;24(5):54-76.

Al-Busaidi KA. An empirical investigation linking learners’ adoption of blended learning to their intention of full e-learning. Behav Inf Technol. 2013;32(11):1168-76.

Suleiman MM, Yahya AT, Tukur M. Effective utilization of ICT tools in higher education. Development. 2020;2:5.

Nguyen HT, Chu QP. Estimating university students’ acceptance of technological tools for studying English through the UTAUT model. Int J TESOL Educ. 2021;1(3): 209-34.

Chu, Q.P. trainee National Conference on Linguistic Studies and Applied Linguistics Translators' Use of Website Resources: What does It Mean for Us at the University of Finance -Marketing?. Hue City: Hue University Publisher. 2016; 459-70.

Abbad MMM. Using the UTAUT model to understand students’ usage of e-learning systems in developing countries. Educ Inf Technol (Dordr). 2021;26(6):7205-24.

Schulz R, Isabwe GM, Reichert F. Investigating teachers motivation to use ICT tools in higher education. In: Internet technologies and applications (ITA). IEEE Publications. 2015;62-7.

Castro Sánchez JJ, Chirino Alemán E. Sanchez. Comput Educ. 2011;56(3):911-5.

Alkamel MAA, Chouthaiwale SS. The use of ICT tools in English language teaching and learning: A literature review. Veda’s J Engl Lang Lit (JOELL). 2018;5(2):29-33.Available: resources/tte/.

Puentedura, R; 2006. Transformation, Technology, and Education [blog post] [cited Nov 12 2022].


Dang, X.T. ICT use in foreign language teaching in an Innovative University in Vietnam: current practices and factors affecting ICT use [la Trobe University PhD thesis]; 2013.

Tan PJB. Applying the UTAUT to understand factors affecting the use of English e-learning websites in Taiwan. Sage Open. 2013;3(4): 215824401-3503837;.

Venkatesh V, Morris M, Davis G, Davis F. User acceptance of information technology: toward a unified view. MIS Q. 2003;27(3):425-78.

Palau-Saumell R, Forgas-Coll S, Sánchez-García J, Robres E. User acceptance of mobile apps for restaurants: an expanded and extended UTAUT-2. Sustainability. 2019;11(4):1210.

Williams ML, Saunderson IP, Dhoest A. Students’ perceptions of the adoption and use of social media in academic libraries: a UTAUT study. Communicatio. 2021;47(1): 76-94.

Venkatesh V. Adoption and use of AI tools: a research agenda grounded in UTAUT. Ann Oper Res. 2022;308(1-2):1-12.

Zuiderwijk A, Janssen M, Dwivedi YK. Acceptance and use predictors of open data technologies: drawing upon the unified theory of acceptance and use of technology. Gov Inf Q. 2015;32(4):429-40.

Ayaz A, Yanartaş M. An analysis on the unified theory of acceptance and use of technology theory (UTAUT): acceptance of electronic document management system (EDMS). Comput Hum Behav Rep. 2020;2:100032.

Duyck P, Pynoo B, Devolder P, Voet T, Adang L, Vercruysse J. User acceptance of a picture archiving and communication system. Applying the unified theory of acceptance and use of technology in a radiological setting. Methods Inf Med. 2008; 47(2):149-56.

Wan, Xie L, S, Shu A. Toward an understanding of university students’ continued intention to use MOOCs: when UTAUT model meets TTF model. Sage Open. 2020;10(3):2158244020941858;.

Nillos, B. E. Performance Expectancy, Effort Expectancy, Social Influence and Facilitating Conditions are Factors that Influence Rural Health Workers in the Use of Wireless Access for Health and Perception of Behavior of their Pregnant Patients. JPAIR Multidisciplinary Research. 2016;24(1):16-31.

Baishya K, Samalia HV. Extending unified theory of acceptance and use of technology with perceived monetary value for smartphone adoption at the bottom of the pyramid. Int J Inf Manag. 2020;51:102036.

Purwanto, E, & loisa, J. The intention and use behaviour of the mobile banking system in Indonesia: UTAUT Model. Technol Rep Kansai Univ. 2020;62(06): 2757-67.

Chen PY, Hwang GJ. An empirical examination of the effect of self-regulation and the Unified Theory of Acceptance and Use of Technology (UTAUT) factors on the online learning behavioural intention of college students. Asia Pac J Educ. 2019: 1-17.

Hariguna T, Hariguna T, Nurfaizah. Understanding of public behavioral intent to use e-government service: an extended of unified theory of acceptance use of technology and information system quality. Procedia Comput Sci. 2017;124:585-92.

Chao CM. Factors determining the behavioral intention to use mobile learning: an application and extension of the UTAUT model. Front Psychol. 2019;10:1652.

Limna P, Siripipatthanakul S, Siripipattanakul S, Woodeson K, Auttawechasakoon P. Applying the UTAUT to Explain Factors Affecting English Learning Intention via Netflix (English Subtitle) among Thai people. Asia Pac Rev Res Educ. 2022;1(1):1-19.

Phetnoi N, Siripipatthanakul S, Phayaphrom B. Factors affecting purchase intention via online shopping sites and apps during COVID-19 in Thailand. Journal of Management in Businesss. Health Care Educ. 2021;1(1):1-17.

Li C, He L, Wong IA. Determinants predicting undergraduates’ intention to adopt e-learning for studying English in Chinese higher education context: A structural equation modelling approach. Educ Inf Technol. 2021;26(4):4221-39.

Yıldız Durak, H. What would you do without your smartphone? Adolescents’ social media usage, locus of control,and loneliness as a predictor of nomophobia. Addicta: The Turkish Journal on Addictions.2018;5(2),1-15.

Assaker G, Hallak R, El-Haddad R. Consumer usage of online travel reviews: expanding the unified theory of acceptance and use of technology 2 model. J Vacation Mark. 2020;26(2):149-65.

Escobar-Rodríguez T, Carvajal-Trujillo E. Online purchasing tickets for low cost carriers: an application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Manag. 2014; 43:70-88.

Sun Y, Gao F34. An investigation of the influence of intrinsic motivation on students’ intention to use mobile devices in language learning. Educ Technol Res Dev. 2020;68(3):1181-98.

Venkatesh V, Davis FD35. F.D.A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci. 2000;46(2):186-204.

Wei J, Vinnikova A, Lu L, Xu J. Understanding and predicting the adoption of fitness mobile apps: evidence from China. Health Commun. 2021;36(8):950-61.

Williams MD, Rana NP, Dwivedi YK. The unified theory of acceptance and use of technology (UTAUT): a literature review. J Enterpr Inf Manag. 2015;28(3):443-88.

Lallmahomed MZI, Lallmahomed N, Lallmahomed GM38. Factors influencing the adoption of e-Government services in Mauritius. Telemat Inform. 2017;34(4):57-72.

Venkatesh V, Thong JYL, Chan FKY, Hu PJH. Managing citizens’ uncertainty in e-government services: the mediating and moderating roles of transparency and trust. Inf Syst Res. 2016;27(1):87-111.

Handoko, B. L., & Prianto, J. A. The influence of UTAUT on ERP systems in start-up business. Int J Manag. 2020;11(4):262-71.

Rozmi ANA, Bakar MIA, Abdul Hadi AR, Imran Nordin A. Investigating the intentions to adopt ICT in Malaysian SMEs using the UTAUT model. In: Advances in visual. Informatics: 6th International Visual Informatics Conference, IVIC 2019, Bangi, Malaysia, Nov 19-21, 2019, Proceedings. Springer International Publishing. 2019;6: 477-87.

Bawack RE, Kala Kamdjoug JR42. Adequacy of UTAUT in clinician adoption of health information systems in developing countries: the case of Cameroon. Int J Med Inform. 2018;109: 15-22.

Dwivedi RK, Kumar R, Buyya R. A novel machine learning-based approach for outlier detection in smart healthcare sensor clouds. Int J Healthc Inf Syst Inform. 2021;16(4):1-26.

Gullslett MK, Zeleke AA, Tilahun B, Tebeje T, Tilahun B, Tebeje T et al.. Healthcare providers’ acceptance of telemedicine and preference of modalities during COVID-19 pandemics in a low-resource setting: an extended UTAUT model. PLOS ONE. 2021;16(4):e0250220.

Han, Xiong H, J, Zhao K. Digital inclusion in social media marketing adoption: the role of product suitability in the agriculture sector. Inf Syst e-Business Manag. 2022; 20(4):657-83.

Nayal K, Raut RD, Narkhede BE, Priyadarshinee P, Panchal GB, Gedam VV. Antecedents for blockchain technology-enabled sustainable agriculture supply chain. Ann Oper Res. 2021:1-45.

Raffaghelli JE, Rodríguez ME, Guerrero-Roldán AE, Bañeres D. Applying the UTAUT model to explain the students’ acceptance of an early warning system in Higher Education. Comput Educ. 2022;182:104468.

Altalhi M. Toward a model for acceptance of MOOCs in higher education: the modified UTAUT model for Saudi Arabia. Educ Inf Technol. 2021;26(2):1589-605.

Almaiah MA, Alamri MM, Al-Rahmi W. Applying the UTAUT model to explain the students’ acceptance of mobile learning system in higher education. IEEE Access. 2019;7:174673-86.

Hu, Laxman S, K, Lee K. Exploring factors affecting academics’ adoption of emerging mobile technologies—an extended UTAUT perspective. Educ Inf Technol. 2020;25(5): 4615-35.

Reinartz W, Haenlein M, Henseler J. An empirical comparison of the efficacy of covariance-based and variance-based SEM. Int J Res Mark. 2009;26(4):332-44.

Cronbach LJ, Warrington WG52. J. Coefficient alpha and the internal structure of tests. Time-limit tests: estimating their reliability and degree of speeding. Psychometrika. 1951;16(3):297-334.

Hair. J Mark Theor Pract, C. M., & Sarstedt, M. PLS-SEM: Indeed a silver bullet. 2011:19(2):139-52.

Chen. C.F., & Tsai, D. How Destination Image Evaluative Factors Affect Behav Intentions? Tourism Management. 2007; 28(4):1115-22.

Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39-50.

Hair J, Black W, Babin B, Anderson R, Tatham R. Multivariate data analysis. 6th ed. Uppersaddle River, N.J. Pearson Prentice Hall; 2006.

Lai HJ. Investigating older adults’ decisions to use mobile devices for learning, based on the unified theory of acceptance and use of technology. Interact Learn Environ. 2020; 28(7):890-901.