The Role of Technology in English Language Learning in Online Classes at Tertiary Level
DOI:
https://doi.org/10.54183/jssr.v3i2.215Keywords:
Language Learning, Attitudes, Online Applications, TAM, GenderAbstract
The primary objective of the study is to investigate the relationship between the TAM (Technology Acceptance Model) factors and online applications usage for language learning. Additionally, the influence of gender and prior technology use practice have been investigated by the study. In order to comprehend the user's responses to the technology used for language learning, this study used a quantitative approach and a TAM questionnaire to collect data. The study's participants are one hundred undergraduate English as a second language students who took online courses during the COVID-19 pandemic. Students' behavioral intentions, attitudes, and app use were found to be significantly positively correlated in the research results. Besides, a positive affiliation exists between the factors; seen usability, perceived use, genuine use, and behavior. In addition, the experience has been found to be positively correlated with TAM factors, whereas gender does not appear to be associated with any TAM factors. The study suggested using technology in the classroom to make learning a second language more fun for students.
References
Abbasi, I. (2022). An Investigation of the Factors Contributing to Inadequate Listening Comprehension in Non-Elite Private Secondary Schools, Punjab, Pakistan. Pakistan Languages and Humanities Review, 6(II). https://doi.org/10.47205/plhr.2022(6-ii)55
Action control: From cognition to behavior (pp. 11–39). New York: Springer.
Agudo-Peregrina, Á. F., Hernández-García, Á., & Pascual-Miguel, F. J. (2014). Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning. Computers in Human Behavior, 34, 301–314. https://doi.org/10.1016/j.chb.2013.10.035
Ahmed, M., Shahid, C., Ali, A., Akmal, F., & Arif, M. (2022). Assessment Of Knowledge Of Instructional Planning And Strategies Of Prospective Teachers. PalArch's Journal of Archaeology of Egypt/Egyptology, 19(4), 439-448. https://archives.palarch.nl/index.php/jae/article/view/11475
Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior. Springer eBooks, 11–39. https://doi.org/10.1007/978-3-642-69746-3_2
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. New Jersey: Pretice-Hall.
Akmal, F., Shahid, C., & Abbasi, I., A., (2022). Globalization in the Educational Culture of Punjab Public Secondary Schools. Global Sociological Review, 7(1), 203-209. https://doi.org/10.31703/gsr.2022(VII-I).20
Akmal, F., Shahid, C., & Ahmed, M. (2022). Knowledge-related Attained Learning Outcomes Gaps Detection and Resolution of BS Graduates. Global Educational Studies Review, VII(II), 533–544. https://doi.org/10.31703/gesr.2022(vii-ii).50
Al Fadda, H. A. (2020). Determining how social media affects learning English: An investigation of mobile applications instagram and snap chat in TESOL classroom. Arab World English Journal, 11(1), 3–11. https://doi.org/10.2139/ssrn.3581296
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
Ariff, M. S. (2012). The effect of computer self-efficacy and technology acceptance model on behavioral intention in internet banking system. Social and Behavioral Sciences, 57(2012), 448–452. https://doi.org/10.1016/j.sbspro.2012.09.1210
Braak, J. (2004). Domains and determinants of university students’ self-perceived computer competence. Computers & Education, 43(3), 299-312. https://doi.org/10.1016/j.compedu.2003.09.006.
Castañeda, J. A., Muñoz-Leiva, F., & Luque, T. (2007). Web Acceptance Model (WAM): Moderating effects of user experience. Information & Management, 44(4), 384–396. https://doi.org/10.1016/j.im.2007.02.003
Chen, R. (2010). Investigating models for pre-service teachers’ use of technology to support student-centered learning. Computer & Education, 55, 32–42. https://doi.org/10.1016/j.compedu.2009.11.015
Chou, Ch., Wu, H Ch., & Chen, Ch H. (2011). Re-visiting college students’ attitudes toward the Internet- based on a 6-T model: Gender and grade level difference. Computers & Education, 56(4), 939–947. https://doi.org/10.1016/j.compedu.2010.11.004
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. https://doi.org/10.2307/249688
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. Management Information Systems Quarterly, 13(3), 319. https://doi.org/10.2307/249008
Dharma, H. R. C., Asmarani, D., & Dewi, U. P. (2017). Basic Japanese Grammar and Conversation e-learning through Skype and Zoom Online Application. Procedia Computer Science, 116, 267–273. https://doi.org/10.1016/j.procs.2017.10.055
Enoch, Y., & Soker, Z. (2006). Age, gender, ethnicity and the digital divide: university students’ use of web‐based instruction. Open Learning: The Journal of Open and Distance Learning, 21(2), 99–110. https://doi.org/10.1080/02680510600713045
Ferns, S., Cappon, A., Duff, A., Marshall, A., Ryan, B., Thompson, B., & Gray, G. (2020). Technology tools for teaching in higher education, the practical handbook series.
Fitzpatrick, B., Berends, M., Ferrare, J. J., & Waddington, R. J. (2020, June 2). Virtual charter schools and online learning during COVID-19. The Brookings Institute.
González-Gómez, F., Guardiola, J., Martín-Rodríguez, O., & Montero-Alonso, M. A. (2012). Gender dif- ferences in e-learning satisfaction. Computers & Education, 58(1), 283–290. https://doi.org/10.1016/j.compedu.2011.08.017
Gurmani, M. T. A., LATIFF, A. A., Shahid, C., Abbasi, I. A., & Bhutto, A. A. (2022). Whatsapp And An Academic Wordlist (Awl) Have A Synergistic Impact On L2 Vocabulary Learners. Webology
Gurmani, M. T. A., Yusoff, Z. S., & Shahid, C. (2021). An Evaluation of Vocabulary Of English Textbooks of Pakistan and Saudi Arabia Through Cefr. PalArch's Journal of Archaeology of Egypt/Egyptology, 18(10), 3375-3387. https://archives.palarch.nl/index.php/jae/article/view/10381
Gurmani, M. T., Latiff, A, A., Abbasi, I. A., & Jatoi, Z, A., Shahid, C. (2023). Examining Vocabulary Usage Ratios of CEFR Vocabulary and AWL vocabulary in Comparison to CEFR Proficiency Levels among Pakistani EFL Writers and Offering Instructional Recommendations for Vocabulary Items. Central European Management Journal, 31(1), 266-274. https://doi.org/10.57030/23364890.cemj.31.1.28
Gurmani, M. T., Salmani, F. C., Shahid, C., Abbasi, I. A., & Ali, A. (2022). The effect of the British National Corpus' Frequency Lists What’s App Group Discussion on L2 Learners' Receptive Vocabulary Size. Central European Management Journal, 30(4), 1004-1014. https://doi.org/10.57030/23364890.cemj.30.4.101
Holden, H., & Rada, R. (2011). Understanding the influence of perceived usability and technology self- efficacy on teachers’ technology acceptance. Journal of Research on Technology in Education, 43(4), 343–367. https://doi.org/10.1080/15391523.2011.10782576
Hsu, C. L., & Lu, H. P. (2004). Why do people play online games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853–868. https://doi.org/10.1016/j.im.2003.08.014
Hung, M., Chou, C., Chen, C., & Own, Z. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090. https://doi.org/10.1016/j.compedu.2010.05.004
Istifci, I. (2017). Perceptions of Turkish EFL students on online language learning platforms and blended language learning. Journal of Education and Learning, 6(1), 113–121. https://doi.org/10.5539/jel.v6n1p113
Khan, T. and Khan, N. (2016) Obstacles in Learning English as a Second Language among Intermediate Students of Districts Mianwali and Bhakkar, Pakistan. Open Journal of Social Sciences, 4, 154-162. https://doi.org/10.4236/jss.2016.42021
Koohang, A. (2004). Students’ perceptions toward the use of the digital library in weekly web-based dis- tance learning assignments portion of a hybrid program. British Journal of Educational Technology, 35(5), 617–626.
Landry, B. J., Griffeth, R., & Hartman, S. (2006). Measuring student perceptions of blackboard using the technology acceptance model. Decision Sciences Journal of Innovative Education, 4(1), 87–99. https://doi.org/10.1111/j.1540-4609.2006.00103.x
Lee, D. Y., & Lehto, M. R. (2013). User acceptance of YouTube for procedural learning: An extension of the technology acceptance model. Computers & Education, 61, 193–208. https://doi.org/10.1016/j.compedu.2012.10.001
Lin, K. (2011). E-Learning continuance intention: Moderating effects of user E-learning experience. Com- puter & Education, 56(2), 515–526. https://doi.org/10.1016/j.compedu.2010.09.017
Liu, I. F., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C. H. (2010). Extending the TAM model to explore the factors that affect intention to use an online learning community. Computers & Education, 54(2), 600–610. https://doi.org/10.1016/j.compedu.2009.09.009
Liu, X. (2010). Empirical testing of a theoretical extension of the technology acceptance model: An exploratory study of educational wikis. Communication Education, 59(1), 52–69. https://doi.org/10.1080/03634520903431745
Lowenthal, P., Borup, J., West, R., & Archambault, L. (2020). Thinking beyond Online applications: Using asynchronous video to maintain connection and engagement during the COVID-19 pandemic. Journal of Technology and Teacher Education, 28(2), 383–391.
McClendon, C., Neugebauer, R. M., & King, A. (2017). Grit, growth mindset, and deliberate practice in online learning. Journal of Instructional Research, 8, 8–17. https://doi.org/10.9743/JIR.2017
Moore, J. L., Dickson-Deane, C., & Galyen, K. (2011). E-Learning, online learning, and distance learning environments: Are they the same? The Internet and Higher Education, 14(2), 129–135. https://doi.org/10.1016/j.iheduc.2010.10.001
Moran, M., Hawkes, M., & Gayar, O. E. (2011). Tablet personal computer integration in higher education: Applying the unified theory of acceptance and technology model to understands supporting factors. Journals of Education Computing Research., 42(1), 79–101. https://doi.org/10.2190/EC.42.1.d
Nikou, S. A., & Economides, A. A. (2017). Mobile-based assessment: Investigating the factors that influ- ence behavioral intention to use. Computers & Education, 109, 56–73. https://doi.org/10.1016/j.compedu.2017.02.005
Online applications Video Communications. (2020). Online applications for education. https://online applications.us/education
Padilla-MeléNdez, A., Del Aguila-Obra, A. R., & Garrido-Moreno, A. (2013). Perceived playfulness, gen- der differences and technology acceptance model in a blended learning scenario. Computers & Educa- tion, 63, 306–317. https://doi.org/10.1016/j.compedu.2012.12.014
Pallant, J. (2011). Survival manual. In A step-by-step guide to data analysis using SPSS.
Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. Educational Technology & Society, 12(3), 150–162. https://doi.org/10.1109/IIAI-AAI.2014.14.
Pynoo, B., Devolder, P., Tondeur, J., Braak, J., Duyck, W., & Dyck, P. (2011). Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study. Computers in Human Behavior, 27(2), 568–575. https://doi.org/10.1016/j.chb.2010.10.005
Rahayu, D. (2020). Students’ e-learning experience through a synchronous online applications web conference system. Journal of ELT Research: The Academic Journal of Studies in English Language Teaching and Learning, 5(1), 68–79.
Reid, M., & Levy, R. (2008). Integrating trust and computer self-efficacy with TAM: An empirical assessment of costumer acceptance of banking information system (BIS) in Jamaica. Journal of Internet Banking and Commerce., 12(3), 1–18.
Sayem, A. S. M., Taylor, B., McClanachan, M., & Mumtahina, U. (2017). Effective use of online applications technol- ogy and instructional videos to improve engagement and success of distance students in engineering. In 28th annual conference of the Australasian association for engineering education (AAEE 2017) (p. 926). Australasian Association for Engineering Education.
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in educa- tion. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
Schumacher, P., & Morahan-Martin, J. (2001). Gender, Internet and computer attitudes and experiences. Computers in Human Behavior, 17(1), 95–110. https://doi.org/10.1016/S0747-5632(00)00032-7
Shahid, C., Abbasi, I. A., & Asif, S. (2022). Factors Affecting Secondary Level Students’ Goal Achievement Performance and Self-Worth in L2 Learning in Pakistan. Global Language Review, VII(I), 310–324. https://doi.org/10.31703/glr.2022(vii-i).25
Shahid, C. ., Abbasi, I. A. ., & Bhutto, S. (2022). Improving Communicative Competence through CLT Approach in Second Language Learning at the Undergraduate Level. Pakistan Journal of Humanities and Social Sciences, 10(4), 1472–1486. https://doi.org/10.52131/pjhss.2022.1004.0305
Shahid, C., Abbasi, I. A. ., & Gurmani, M. T. . (2022). English as a Second Language Teachers and Students Beliefs about Learner Autonomy at Tertiary Level in Pakistan. Pakistan Journal of Humanities and Social Sciences, 10(1), 149–161. https://doi.org/10.52131/pjhss.2022.1001.0182
Shahid, C., Asif, S., & Muhammad, R. (2022). Pedagogies and Challenges in English Language Learning in Undergraduate Programs in Pakistan: A Review. Global Language Review, VII(II), 479-488. https://doi.org/10.31703/glr.2022(VII-II).39
Shahid, C., Muhammed, G. A., Abbasi, I. A., Gurmani, M. T., & ur Rahman, S. (2022). Attitudes of Undergraduates and Teachers Towards Evolving Autonomous Learning L2 In Higher Education. Journal of Positive School Psychology, 6(11), 527-544.
Shahid, C., Tek, O. E., Teck, M. W. K., & Perveen, A. (2019). EFL Learners Communicative Competence in Undergraduate Programmes in Pakistan: A Case of Two Universities in Pakistan. The International Journal of Advance Science and Technology, 28(20), 248-260.
Sheldon, P. (2016). Facebook friend request: Applying the theory of reasoned action to student-teacher relationships on Facebook. Journal of Broadcasting & Electronic Media, 60(2), 269–285. https://doi.org/10.1080/08838151.2016.1164167
Shih, H. F., Chen, S. H. E., Chen, S. C., & Wey, S. C. (2013). The relationship among tertiary level EFL students’ personality, online learning motivation and online learning satisfaction. Procedia-Social and Behavioral Sciences, 103, 1152–1160. https://doi.org/10.1016/j.sbspro.2013.10.442
Sumak, B., Hericko, M., Pusnik, M., & Polancic, (2011). Factors affecting acceptance and use of Moo- dle: An empirical study based on TAM. Slovenian Society Informatika, 35(1), 91–100. https://doi.org/10.4018/IJICTE.2017010102
Tai, H. C. (2016). Effects of collaborative online learning on EFL learners’ writing performance and self- efficacy. English Language Teaching, 9(5), 119–133. https://doi.org/10.5539/elt.v9n5p119
Tarhini, A., Hone, K., & Liu, X. (2014). Measuring the moderating effect of gender and age on e-learning acceptance in England: A structural equation modeling approach for an extended technology accept- ance model. Educational Computing Research, 51(2), 163–184. https://doi.org/10.2190/ec.51.2.b
Taylor, R. (1990). Interpretation of the correlation coefficient: A basic review. Journal of diagnostic medical sonography, 6(1), 35–39. https://doi.org/10.1177/875647939000600106
Teo, T. (2009). The impact of subjective norm and facilitating conditions on pre-service teachers’ attitude toward computer use: a structural equation modelling of an extended technology acceptance model. Journal Education Computing Research, 40(1), 89–109. https://doi.org/10.2190/EC.40.1.d
Teo, T., & Noyes, J. (2011). An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modelling approach. Computer & Technology, 57(2), 1645–1653. https://doi.org/10.1016/j.compedu.2011.03.002
Terzis, V., & Economides, A. A. (2011). Computer based assessment: gender differences in perceptions and acceptance. Computers in Human Behavior, 27(6), 2108–2122. https://doi.org/10.1016/j.chb.2011.06.005
Tondeur, J., Valcke, M., & van Braak, J. (2008). A multidimensional approach to determinants of computer use in primary education: Teacher and school characteristics. Journal of Computer Assisted learning, 24(6), 494–506.
Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010). Does the technology accept- ance model predict actual use? A systematic literature review. Information and Software Technology, 52(5), 463–479. https://doi.org/10.1016/j.infsof.2009.11.005
Venkatesh, V. (2000). Determinants of perceived ease of use integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 1194, 342–365. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of technology acceptance model: Four longitudinal field studies. Management Science, 46, 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. B. (2003). User acceptance of information technology: Toward a Unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.5555/2017197.2017202
Weng, C., & Tsai, C. (2015). Social support as a neglected e-learning motivator affecting trainee’s decisions of continuous intentions of usage. Australasian Journal of Educational Technology, 31(2), 177–192. https://doi.org/10.14742/ajet.1311.
Whitley, B. E. (1997). Gender differences in computer-related attitudes and behavior: A meta-analysis. Women in Management Review, 11(8), 18–26. https://doi.org/10.1108/09649429610148746
Wong, K. T., Goh, S. C., Fahri, Hafizul, & Osman, Rosma. (2010). Computer attitudes and use among novice teachers; The moderating effects of school environment. Malaysian Journal of Learning and Instruction, 7, 93–112.
Wu, W. C. V., Hsieh, J. S. C., & Yang, J. C. (2017). Creating an online learning community in a flipped classroom to enhance EFL learners’ oral proficiency. Journal of Educational Technology & Society, 20(2), 142–157.
Wu, W. C. V., Yen, L. L., & Marek, M. (2011). Using online EFL interaction to increase confidence, moti- vation, and ability. Journal of Educational Technology & Society, 14(3), 118–129.
Yang, Y., & Wang, X. (2019). Modeling the intention to use machine translation for student translators: An extension of Technology Acceptance Model. Computers & Education, 133, 116–126. https://doi.org/10.1016/j.compedu.2019.01.015
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Copyright in the Journal of Social Sciences Review is retained by the author(s). Authors also grant any third party the right to use the article freely as long as its integrity is maintained and its original authors, citation details and publisher are identified.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
SSR's Editorial Board shares the vision of providing free access to information, education, and science for everyone, thus promoting its content through an OPEN ACCESS POLICY, fulfilling the DOAJ definition of open access. The JSSR adheres to an Open Access and Copyright Licensing Policy based on the belief that making research freely accessible to the public promotes greater global knowledge sharing.
The JSSR uses the Creative Commons Attribution-NonCommercial 4.0 International License. The authors who apply and publish in JSSR consent to abide by the copyright policy set out in the Creative Commons 4.0 license (Attribution-NonCommercial 4.0 International license).
- Copyright in the Journal of Social Sciences Review is retained by the author(s).
- Authors also grant any third party the right to use the article freely as long as its integrity is maintained and its original authors, citation details and publisher are identified.
While "By 'open access' to this literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself."
