VOCATIONAL STUDENTS’ SATISFACTION OF THE SYNCHRONOUS ONLINE LEARNING IN LAO LANGUAGE COURSE
Keywords:
Lao Language, Asynchronous Online Learning, Students Satisfaction, Intrinsic Motivation, Perceived Interactivity, Perceived Ease of UseAbstract
Purpose: As the backdrop of this reaseach is online teaching via asynchronous online learning, this research examined the factors and effects of intrinsic motivation (IML), perceived interactivity (PI), attitude (AT), and perceived ease of use (PEU) on satisfaction with learning among students of Laotian language courses in vocational colleges. Design Data and Methodology: Employing a questionnaire survey, data were collected from 57 students majoring in Laotian language at a vocational and technical college in Yunnan Province— 16 males and 41 females. Multiple linear regression analysis was conducted to analyze the data. Results: The study revealed that student satisfaction was influenced by factors such as intrinsic motivation (IML), perceived interactivity (PI), and perceived ease of use (PEU). Specifically, perceived interactivity (PI) exerted the greatest influence on student satisfaction, explaining 65.9% of the variance (β=.659, p<.001), which was statistically significant. However, attitude (AT) did not significantly impact student satisfaction (β = -.543, p<.001). Conclusion: In conclusion, integrating students' perceived ease of use into the teaching process during online Laotian language instruction via asynchronous online learning could enhance student satisfaction. Such an online teaching mode could facilitate positive interactions between students and teachers as well as among students themselves.
References
Alturki, U., & Aldraiweesh, A. (2022). Students’ perceptions of the actual use of mobile learning during COVID-19 pandemic in higher education. Sustainability, 14(3), 1125.
Anderson, T. (2004). Teaching in an online learning context. Theory and practice of online learning, 273.
Astin, A. W. (1993). What matters in college? Four critical years revisited. Jossey-Bass.
Balbay, S., & Kilis, S. (2017). Students' Perceptions of the use of a YouTube channel specifically designed for an Academic Speaking Skills Course. Eurasian Journal of Applied Linguistics, 3(2), 235-251.
Bolliger, D. U., & Wasilik, O. (2009). Factors influencing faculty satisfaction with online teaching and learning in higher education. Distance education, 30(1), 103-116.
Brophy, J. E. (2013). Motivating Students to Learn. Routledge.
Camilleri, M. A., & Camilleri, A. C. (2022). The acceptance of learning management systems and video conferencing technologies: Lessons learned from COVID-19. Technology, Knowledge and Learning, 27(4), 1311-1333.
Carr, S. (2000). As distance education comes of age, the challenge is keeping the students. Chronicle of Higher Education, 46(23), A39-A41.
Chattaraman, V., Kwon, W. S., Gilbert, J. E., & Ross, K. (2019). Should AI-Based, conversational digital assistants employ social-or task-oriented interaction style? A task-competency and reciprocity perspective for older adults. Computers in Human Behavior, 90, 315-330.
Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers and Education, 59(3), 1054-1064.
Correia, A. P., Liu, C., & Xu, F. (2020). Evaluating videoconferencing systems for the quality of the educational experience. Distance Education, 41(4), 429-452.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340.
Froiland, J. M. (2014). Inspired childhood: Parents raising motivated, happy, and successful students from preschool to college. Amazon.
Froiland, J. M., & Oros, E. (2014). Intrinsic motivation, perceived competence and classroom engagement as longitudinal predictors of adolescent reading achievement. Educational Psychology, 34(2), 119-132.
Froiland, J. M., & Worrell, F. C. (2016). Intrinsic motivation, learning goals, engagement, and achievement in a diverse high school. Psychology in the Schools, 53(3), 321-336.
Froiland, J. M., Mayor, P., & Herlevi, M. (2015). Motives emanating from personality associated with achievement in a Finnish senior high school: Physical activity, curiosity, and family motives. School Psychology International, 36(2), 207-221.
Gangwar, H., Date, H., & Ramaswamy, R. (2015). Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. Journal of Enterprise Information Management, 28(1), 107-130.
Guichon, N. (2010). Preparatory study for the design of a desktop videoconferencing platform for synchronous language teaching. Computer Assisted Language Learning, 23(2), 169-182.
Guthrie, J. T., McRae, A., & Klauda, S. L. (2007). Contributions of concept-oriented reading instruction to knowledge about interventions for motivations in reading. Educational Psychologist, 42(4), 237-250.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Advanced diagnostics for multiple regression: A supplement to multivariate data analysis. Pearson.
Hampel, R., & Stickler, U. (2012). The use of videoconferencing to support multimodal interaction in an online language classroom. ReCALL, 24(2), 116-137.
Herguner, G., Son, S. B., Herguner Son, S., & Donmez, A. (2020). The Effect of Online Learning Attitudes of University Students on Their Online Learning Readiness. Turkish Online Journal of Educational Technology-TOJET, 19(4), 102-110.
Huang, F., Teo, T., & Scherer, R. (2022). Investigating the antecedents of university students’ perceived ease of using the Internet for learning. Interactive learning environments, 30(6), 1060-1076.
Kenny, J. (2003). Student perception of the use of online learning technology in their courses. Education, Computer Science
Kohnke, L., & Moorhouse, B. L. (2022). Facilitating synchronous online language learning through Zoom. Relc Journal, 53(1), 296-301.
Krutka, D. G., & Carano, K. T. (2016). Videoconferencing for global citizenship education: Wise practices for social studies educators. Journal of Social Studies Education Research, 7(2).
Liu, Y. (2003). Developing a scale to measure the interactivity of websites. Journal of advertising research, 43(2), 207-216.
Luo, R., Wang, J., & Wang, Y. (2023). Undergraduate students’ perceptions of using videoconferencing for EFL learning: Evidence from Tencent Meeting application. Heliyon, 9(12) , e22993.
Mohammadi, H. (2015). Investigating users’ perspectives on e-learning: An integration of TAM and IS success model. Computers in human behavior, 45, 359-374.
Moreno, V., Cavazotte, F., & Alves, I. (2017). Explaining university students’ effective use of e‐learning platforms. British Journal of Educational Technology, 48(4), 995-1009.
Muilenburg, L. Y., & Berge, Z. L. (2005). Student barriers to online learning: A factor analytic study. Distance education, 26(1), 29-48.
Nikou, S. A. (2021). Web-based videoconferencing for teaching online: Continuance intention to use in the post-COVID-19 period. Interaction Design and Architecture, 47, 123-143.
Nistor, N. (2013). Stability of attitudes and participation in online university courses: Gender and location effects. Computers & Education, 68, 284-292.
Oroujlou, N., & Vahedi, M. (2011). Motivation, attitude, and language learning. Procedia-Social and Behavioral Sciences, 29, 994-1000.
Rahayu, R. P., & Wirza, Y. (2020). Teachers’ perception of online learning during pandemic covid-19. Journal penelitian pendidikan, 20(3), 392-406.
Saadé, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Information & management, 42(2), 317-327.
Shin, W. S., & Kang, M. (2015). The use of a mobile learning management system at an online university and its effect on learning satisfaction and achievement. International Review of Research in Open and Distributed Learning, 16(3), 110-130.
Simanjuntak, U. S., Silalahi, D. E., Sihombing, P. S., & Purba, L. (2021). Students’ perceptions of using YouTube as English online learning media during Covid-19 pandemic. Journal of Languages and Language Teaching, 9(2), 150-159.
Skinner, E., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational dynamic?. Journal of educational psychology, 100(4), 765-781.
Su, B., Zhang, T., & Yan, L. (2021). Online medical teaching in China during the COVID-19 pandemic: tools, modalities, and challenges. Frontiers in Public Health, 9, 797694.
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 modeling approach. Computers & education, 57(2), 1645-1653.
Teo, T., Huang, F., & Hoi, C. K. W. (2018). Explicating the influences that explain intention to use technology among English teachers in China. Interactive Learning Environments, 26(4), 460-475.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research, 11(4), 342-365.
Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in human behavior, 67, 221-232.
Yu, L. T. (2022). The effect of videoconferencing on second-language learning: a meta-analysis. Behavioral Sciences, 12(6), 169.