Journal Screenshot

International Journal of Academic Research in Progressive Education and Development

Open Access Journal

ISSN: 2226-6348

Impact of Autonomous Motivation on College Students’ Continuous Intention to Use Chaoxing Platform toward Hybrid Learning Context: TAM-PCASS Model

Zheng Zheng, Wan Ahmad Jaafar Wan Yahaya, Zhao Xin, Jiao Fengming

http://dx.doi.org/10.6007/IJARPED/v13-i1/20688

Open access

Hybrid learning integrates online instruction with in-person interaction, and the Chaoxing platform serves as an indispensable intermediary in higher education in China. The efficacy of hybrid learning hinges upon the learner's active engagement in the mobile technology educational process. Hence, this study integrates the technology acceptance model (TAM) with the perceived choice and awareness of self scale (PCASS) to develop a comprehensive model for assessing learners' continuous intention to use Chaoxing. The study identifies five constructs: perceived choice (PC), self-awareness (SA), perceived usefulness (PU), perceived ease of use (PEOU), and continuous intention to use (CI). 320 valid responses were obtained from undergraduate students at Jitang College, North China University of Science and Technology. The model's path coefficients are computed using SPSS and AMOS software. The empirical findings demonstrate that the two factors of autonomous motivation, specifically perceived choice and self-awareness, exert a substantial impact on continuous intention to use Chaoxing. Nevertheless, the importance of the perceived ease of use in relation to the continuous intention to use Chaoxing that of the perceived usefulness. This suggests that learners prioritize the information offered by the course. These findings can offer efficient pedagogical approaches for administrators and educators who can facilitate hybrid instruction using Chaoxing as a medium.

Acheampong, E., & Agyemang, F. G. (2021). Enhancing academic library services provision in the distance learning environment with mobile technologies. Journal of Academic Librarianship, 47(1). https://doi.org/10.1016/j.acalib.2020.102279
Afandi, K., Rinaldi, A., Putra, F. G., Rionanda, L. S., Maharani, I. P., Mulyani, S., & Safitri, A. (2023). Factor analysis uses confirmatory factor analysis: The accuracy and suitability of the instrument indicators of anxiety, motivation, and learning independence. AIP Conference Proceedings, 2595. https://doi.org/10.1063/5.0141348
Ahmad Husairi, M., & Rossi, P. (2024). Delegation of purchasing tasks to AI: The role of perceived choice and decision autonomy. Decision Support Systems, 179. https://doi.org/10.1016/j.dss.2023.114166
Akritidi, D., Gallos, P., Koufi, V., & Malamateniou, F. (2022). Using an Extended Technology Acceptance Model to Evaluate Digital Health Services. In Studies in Health Technology and Informatics (Vol. 295). https://doi.org/10.3233/SHTI220782
Atmojo, S. E., Muhtarom, T., & Lukitoaji, B. D. (2020). The level of self-regulated learning and self-awareness in science learning in the covid-19 pandemic era. Jurnal Pendidikan IPA Indonesia, 9(4), 512–520. https://doi.org/10.15294/jpii.v9i4.25544
Bandara, U. C., & Amarasena, T. S. M. (2018). Impact of Relative Advantage, Perceived Behavioural Control and Perceived Ease of Use on Intention to Adopt with Solar Energy Technology in Sri Lanka. Proceedings of the Conference on the Industrial and Commercial Use of Energy, ICUE, 2018-Octob. https://doi.org/10.23919/ICUE-GESD.2018.8635706
Bujang, M. A., Omar, E. D., & Baharum, N. A. (2018). A review on sample size determination for cronbach’s alpha test: A simple guide for researchers. Malaysian Journal of Medical Sciences, 25(6), 85–99. https://doi.org/10.21315/mjms2018.25.6.9
Chen, Y. (2022). Exploration of Blended Teaching in Comprehensive English Course Based on Chaoxing Mobile Platform. 2022 IEEE 2nd International Conference on Educational Technology, ICET 2022, 66–70. https://doi.org/10.1109/ICET55642.2022.9944445
Chow, T. S., Hui, C. M., & Siu, T. S. U. (2022). “It Is My Choice to Control Myself!”: Testing the Mediating Roles of Expectancy and Value in the Association Between Perceived Choice and Self-Control Success. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.851964
Center for Self-determination Theory (Ed.) (2017). Perceived Choice and Awareness of Self Scale (PCASS). Center for Self-determination Theory. https://selfdeterminationtheory.org/perceived-choice-and-awareness-of-self-scale/
Deci, E. L., & Ryan, R. M. (1980). The empirical exploration of intrinsic motivational processes. In Advances in Experimental Social Psychology (Vol. 13, Issue C). https://doi.org/10.1016/S0065-2601(08)60130-6
Denneson, L. M., Ono, S. S., Trevino, A. Y., Kenyon, E., & Dobscha, S. K. (2020). The applicability of self-determination theory to health coaching: a qualitative analysis of patient experiences. Coaching, 13(2), 163–175. https://doi.org/10.1080/17521882.2019.1673457
Dirette, D. (2010). Self-awareness enhancement through learning and function (SELF): A theoretically based guideline for practice. British Journal of Occupational Therapy, 73(7), 309–318. https://doi.org/10.4276/030802210X12759925544344
Evans, P. (2015). Self-determination theory: An approach to motivation in music education. Musicae Scientiae, 19(1), 65–83. https://doi.org/10.1177/1029864914568044
Febrianda, & Indayani. (2022). The Effect of Perceived Ease of Use, Perceived Usefulness & Quality of Information on Interest in Transactions Using E-Commerce (Study on Generations Y & Z in Aceh Province). 2022 International Conference on Decision Aid Sciences and Applications, DASA 2022, 999–1003. https://doi.org/10.1109/DASA54658.2022.9765231
Fernando, G., & Sooriyarachchi, R. (2022). The development of a goodness-of-fit test for high level binary multilevel models. Communications in Statistics: Simulation and Computation, 51(5), 2710–2730. https://doi.org/10.1080/03610918.2019.1700275
Fierro-Suero, S., Almagro, B. J., Becker, E. S., & Sáenz-López, P. (2022). Basic Psychological Needs, Class-related Emotions and Satisfaction with Life in Spanish Teachers | Necesidades Psicológicas Básicas, Emociones en las Clases y Satisfacción con la Vida en Profesores Españoles. International Journal of Educational Psychology, 11(2), 153–181. https://doi.org/10.17583/ijep.9106
Fila, N. D., & Purzer, ?. (2017). Using self-determination theory to understand engineering student motivation during innovation projects. Proceedings - Frontiers in Education Conference, FIE, 2017-Octob, 1–8. https://doi.org/10.1109/FIE.2017.8190579
Galaige, J., Binnewies, S., Torrisi-Steele, G., & Wang, K. (2018). The effect of students’ technology readiness on technology acceptance. Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018.
Giannakopoulos, A., & Eybers, S. (2015). The adoption of mobile technologies in a higher education institution: A mixed methods study. In Communications in Computer and Information Science (Vol. 560). https://doi.org/10.1007/978-3-319-25684-9_21
Gupta, P., Prashar, S., Vijay, T. S., & Parsad, C. (2021). Examining the influence of antecedents of continuous intention to use an informational app: The role of perceived usefulness and perceived ease of use. International Journal of Business Information Systems, 36(2), 270–287. https://doi.org/10.1504/IJBIS.2021.112829
Hapsari, W. P., Saputri, H. S., & Haryanto. (2020). Engaging self-awareness to heutagogy approach of distance learning in primary education. ACM International Conference Proceeding Series. https://doi.org/10.1145/3452144.3453782
Hossain, R., & Mahmud, I. (2016a). Influence of cognitive style on mobile payment system adoption: An extended technology acceptance model. 2016 International Conference on Computer Communication and Informatics, ICCCI 2016. https://doi.org/10.1109/ICCCI.2016.7479973
Hossain, R., & Mahmud, I. (2016b). Influence of cognitive style on mobile payment system adoption: An extended technology acceptance model. 2016 International Conference on Computer Communication and Informatics, ICCCI 2016. https://doi.org/10.1109/ICCCI.2016.7479973
Iancu, I., & Iancu, B. (2023). Interacting with chatbots later in life: A technology acceptance perspective in COVID-19 pandemic situation. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1111003
Isard, J. L., & Szalma, J. L. (2015). The effect of perceived choice on performance, workload, and stress. Proceedings of the Human Factors and Ergonomics Society, 2015-Janua, 1037–1041. https://doi.org/10.1177/1541931215591293
Jamogha, E., Owoeye, J., & Godwin, L. S. (2022). Perceived usefulness and adoption of Koha integrated library systems by librarians in universities in Southern Nigeria. Digital Library Perspectives, 38(1), 55–68. https://doi.org/10.1108/DLP-12-2020-0130
Jellison, J. M., & Harvey, J. H. (1973). Determinants of perceived choice and the relationship between perceived choice and perceived competence. Journal of Personality and Social Psychology, 28(3), 376–382. https://doi.org/10.1037/h0035110
Jiao, S. (2021). Implementation of english digital evaluation model for higher vocational colleges based on chaoxing teaching platform. ACM International Conference Proceeding Series, 851–853. https://doi.org/10.1145/3482632.3483035
Johnston, C. A., Klein, G. B., Johnston, N., & Johnston, J. (2021). The Interactive Learning Model: A theory that assists the L2 learner in achieving self-awareness. Glottodidactica, 48(2), 21–41. https://doi.org/10.14746/gl.2021.48.2.02
Khemlani, S., & Trafton, J. G. (2014). Percentile analysis for goodness-of-fit comparisons of models to data. Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014, 737–742.
Kim-Soon, N., Ibrahim, M. A., Ahmad, A. R., & Xin Sirisa, N. M. (2016). Continuous intention to use m-learning among students of Malaysian technical university network universities. Advanced Science Letters, 22(12), 4116–4119. https://doi.org/10.1166/asl.2016.8188
Krauter, J. (2023). New Perspectives on Leaders’ Motivational and Emotional Experiences and the Role of Basic Psychological Needs Not to Fail Organizational Change in a Multi-Crisis Context—A Content Analysis. Open Journal of Leadership, 12(03), 258–310. https://doi.org/10.4236/ojl.2023.123014
Kumari, M., & Sharma, A. (2020). Examining three connected concepts: Social impairment and STEM; Broader autism phenotype; and convergence validity in autistic trait screening tools. International Journal of Engineering Trends and Technology, 68(12), 77–86. https://doi.org/10.14445/22315381/IJETT-V68I12P214
Kurdi, V., Fukuzumi, N., Ishii, R., Tamura, A., Nakazato, N., Ohtani, K., Ishikawa, S.-I., Suzuki, T., Sakaki, M., Murayama, K., Murayama, K., & Tanaka, A. (2024). Transmission of Basic Psychological Need Satisfaction Between Parents and Adolescents: The Critical Role of Parental Perceptions. Social Psychological and Personality Science, 15(2), 157–169. https://doi.org/10.1177/19485506231153012
Kulkarni, M. and Sommer, K. (2015), Language-Based Exclusion and Prosocial Behaviors in Organizations. Hum Resour Manage, 54: 637-652. https://doi.org/10.1002/hrm.21637
Luo, Y., Lin, J., & Yang, Y. (2021). Students’ motivation and continued intention with online self-regulated learning: A self-determination theory perspective. Zeitschrift Fur Erziehungswissenschaft, 24(6), 1379–1399. https://doi.org/10.1007/s11618-021-01042-3
Matumba, M., & Rajkoomar, M. (2023). Academic librarians’ perceptions of mobile technology’s usefulness in library service delivery at universities of technology in South Africa. Digital Library Perspectives. https://doi.org/10.1108/DLP-08-2023-0072
Mehdizadeh, K., Salehi, M. M., Moosavi, J., Mohebbi, B., Klok, F. A., Bikdeli, B., Shafe, O., Pouraliakbar, H., Alizadehasl, A., Farrashi, M., Bakhshandeh, H., & Sadeghipour, P. (2023). Cross-cultural validity of the Pulmonary Embolism Quality of Life questionnaire in the quality of life survey after pulmonary embolism: A Persian-speaking cohort. Research and Practice in Thrombosis and Haemostasis, 7(3). https://doi.org/10.1016/j.rpth.2023.100145
Mills, D. J., & Allen, J. J. (2020). Self-determination theory, internet gaming disorder, and the mediating role of self-control. Computers in Human Behavior, 105. https://doi.org/10.1016/j.chb.2019.106209
Ningsih, S. K., Suherdi, D., & Purnawarman, P. (2022). SECONDARY SCHOOL TEACHERS’ PERCEPTIONS OF MOBILE TECHNOLOGY ADOPTION IN ENGLISH AS A FOREIGN LANGUAGE LEARNING: TRENDS AND PRACTICES. International Journal of Education and Practice, 10(2), 160–170. https://doi.org/10.18488/61.v10i2.3004
Pan, X. (2022). Exploring the multidimensional relationships between educational situation perception, teacher support, online learning engagement, and academic self-efficacy in technology-based language learning. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1000069
Poile, C. (2017). Why would i help my coworker? Exploring asymmetric task dependence and the self-determination theory internalization process. Journal of Experimental Psychology: Applied, 23(3), 354–368. https://doi.org/10.1037/xap0000128
Qin, L., & Huang, N. (2022). Research on Blended Teaching Mode under the Background of “internet plus”: Application based on Chaoxing Learning Pass Platform. ACM International Conference Proceeding Series, 60–65. https://doi.org/10.1145/3569507.3569516
Ryan, R. M., Bradshaw, E. L., & Deci, E. L. (2019). Motivation. In The Cambridge Handbook of the Intellectual History of Psychology. https://doi.org/10.1017/9781108290876.016
Ryan, R. M., & Deci, E. L. (2020a). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61. https://doi.org/10.1016/j.cedpsych.2020.101860
Ryan, R. M., & Deci, E. L. (2020b). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61. https://doi.org/10.1016/j.cedpsych.2020.101860
Ryan, R. M., & Sapp, A. R. (2007). Basic psychological needs: A self-determination theory perspective on the promotion of wellness across development and cultures. In Wellbeing in Developing Countries: From Theory to Research. https://doi.org/10.1017/CBO9780511488986.004
Santana-Monagas, E., & Núñez, J. L. (2022). Predicting students’ basic psychological need profiles through motivational appeals: Relations with grit and well-being. Learning and Individual Differences, 97. https://doi.org/10.1016/j.lindif.2022.102162
Scherer, R., Siddiq, F., & Teo, T. (2015). Becoming more specific: Measuring and modeling teachers’ perceived usefulness of ICT in the context of teaching and learning. Computers and Education, 88, 202–214. https://doi.org/10.1016/j.compedu.2015.05.005
Shin, J. Y., Pohlig, R., & Habermann, B. (2023). Impacts of Perceived Choice on Physical Strain, Emotional Stress and Health among Caregivers. Western Journal of Nursing Research, 45(9), 826–832. https://doi.org/10.1177/01939459231186900
Stone, M., Laughren, T., Jones, M. L., Levenson, M., Holland, P. C., Hughes, A., Hammad, T. A., Temple, R., & Rochester, G. (2009). Risk of suicidality in clinical trials of antidepressants in adults: Analysis of proprietary data submitted to US Food and Drug Administration. BMJ (Online), 339(7718), 431–434. https://doi.org/10.1136/bmj.b2880
Susanti, L., & Alamsyah, D. P. (2022). Perceived Ease of Use as a Precursor of Mobile Payment E-Wallet. 2022 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2022, 123–127. https://doi.org/10.1109/ZINC55034.2022.9840646
Tang, D., & Chen, L. (2011). A review of the evolution of research on information Technology Acceptance Model. BMEI 2011 - Proceedings 2011 International Conference on Business Management and Electronic Information, 2, 588–591. https://doi.org/10.1109/ICBMEI.2011.5917980
Trendafilov, N. T., & Fontanella, S. (2019). Exploratory factor analysis of large data matrices. Statistical Analysis and Data Mining, 12(1), 5–11. https://doi.org/10.1002/sam.11393
Vrana, R. (2018). Acceptance of mobile technologies and m-learning in higher education learning: An explorative study at the Faculty of Humanities and Social Science at the University of Zagreb. 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2018 - Proceedings, 738–743. https://doi.org/10.23919/MIPRO.2018.8400137
Wang, J., & Li, Y. (2023). Hybrid Teaching Model of Internet Marketing Gold Course: Based on Chaoxing Information Technology. In Lecture Notes in Electrical Engineering: Vol. 1031 LNEE. https://doi.org/10.1007/978-981-99-1428-9_91
Wang, J., Zhang, X., & Zhang, L. J. (2022). Effects of Teacher Engagement on Students’ Achievement in an Online English as a Foreign Language Classroom: The Mediating Role of Autonomous Motivation and Positive Emotions. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.950652
Wang, S., Bao, J., Liu, Y., & Zhang, D. (2023). The impact of online learning engagement on college students’ academic performance: The serial mediating effect of inquiry learning and reflective learning. Innovations in Education and Teaching International. https://doi.org/10.1080/14703297.2023.2236085
Wong, E. Y.-C., Hui, R. T.-Y., & Kong, H. (2023). Perceived usefulness of, engagement with, and effectiveness of virtual reality environments in learning industrial operations: the moderating role of openness to experience. Virtual Reality, 27(3), 2149–2165. https://doi.org/10.1007/s10055-023-00793-0
Yang, Y.-Q., Wu, M., Lin, Y.-Q., & Hong, X. (2022). The influence of online learning readiness on online learning engagement of nursing students: the mediating role of online self-regulated learning. Chinese Journal of Nursing Education, 19(6), 535–538. https://doi.org/10.3761/j.issn.1672-9234.2022.06.011
Yao, Y., Wang, P., Jiang, Y., Li, Q., & Li, Y. (2022). Innovative online learning strategies for the successful construction of student self-awareness during the COVID-19 pandemic: Merging TAM with TPB. Journal of Innovation and Knowledge, 7(4). https://doi.org/10.1016/j.jik.2022.100252
Yu, R., & Cai, X. (2022). Impact of Immediacy of Feedback on Continuous Intentions to Use Online Learning From the Student Perspective. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.865680
Zhang, Y., Yu, X., Cai, N., & Li, Y. (2020). Analyzing the employees’ new media use in the energy industry: The role of creative self-efficacy, perceived usefulness and leaders’ use. Sustainability (Switzerland), 12(3). https://doi.org/10.3390/su12030967
Zhao, X. (2021). Research on College English Teaching Model Based on Chaoxing Platform and Dingding Live Broadcast. ACM International Conference Proceeding Series, 763–766. https://doi.org/10.1145/3452446.3452629
Zhu, F. (2022). Study on strategies to enhance the continuous use intention of Chaoxing among college students [Master differtation, Guizhou University of Finance and Economics]. Chinese National Knowledge Infrastructure. 10.27731/d.cnki.ggzcj.2022.000207

(Zheng et al., 2024)
Zheng, Z., Yahaya, W. A. J. W., Xin, Z., & Fengming, J. (2024). Impact of Autonomous Motivation on College Students’ Continuous Intention to Use Chaoxing Platform toward Hybrid Learning Context: TAM-PCASS Model. International Journal of Academic Research in Progressive Education and Development, 13(1), 1033–1052.