Abstract
Drawing on the technology acceptance model, the theory of reasoned action, and the expectation-confirmation model, an integrated model was proposed to explore teenagers’ learning management system (LMS) acceptance and continuance. Based on the data collected from a longitudinal survey of 1182 junior secondary students in Hong Kong, the results of structural equation modelling (SEM) supported the hypothesised model. Key findings were peer and teacher influences and perceived ease of use demonstrated significant effects; whereas parental influence and perceived usefulness had no effect, on behavioural intention over time. Multi-group SEM was used to test whether the paths in the hypothesized model varied across teenagers with different immigrant backgrounds. The sample was classified into three cultural groups: 203 first-generation immigrant students (FG), 354 second-generation immigrant students (FG), and 521 non-immigrant student (Native). The results showed that cultural divides existed in the relations of the proposed model across the FG, SG, and Native groups. The FG group, who were Mainland China born immigrants, were significantly different from the Native group in terms of the effects of perceptions, use experience, parental influence, and peer influence on their learning satisfaction and behavioural intention. The SG and Native groups, students who were born in Hong Kong, were the least noticeable in significant path differences. To highlight, peer influence demonstrated significantly stronger relationships with the FG group’s intention at the initial use stage, and peer influence only had a significant relationship with satisfaction for the FG and SG group. Discussion and implications of the findings are presented.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Change history
25 July 2019
In the abstract, the second “FG” in the sentence below should be “SG”:
The sample was classified into three cultural groups: 203 first-generation immigrant students (FG), 354 second-generation immigrant students (FG), and 521 non-immigrant student (Native).
Thus, the original sentence should be corrected as follows:
The sample was classified into three cultural groups: 203 first-generation immigrant students (FG), 354 second-generation immigrant students (SG), and 521 non-immigrant student (Native).
References
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
Al-Emran, M., Mezhuyev, V., & Kamaludin, A. (2018). Technology acceptance model in m-learning context: A systematic review. Computers & Education,125, 389–412.
Alhirz, H., & Sajeev, A. (2015). Do cultural dimensions differentiate ERP acceptance? A study in the context of Saudi Arabia. Information Technology & People,28(1), 163–194.
Arbuckle, J. L. (2014). Amos 23.0 user’s guide. Chicago: IBM SPSS.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
Bentler, P., & Appelbaum, Mark I. (1990). Comparative fit indexes in structural models. Psychological Bulletin,107(2), 238–246.
Berry, J. (1997). Immigration, acculturation, and adaptation. Applied Psychology,46(1), 5–34.
Bhattacherjee, A. (2001a). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems,32(2), 201–214.
Bhattacherjee, A. (2001b). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly,25(3), 351–370.
Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly,28(2), 229–254.
Bourgonjon, J., Valcke, M., Soetaert, R., & Schellens, T. (2010). Students’ perceptions about the use of video games in the classroom. Computers & Education,54(4), 1145–1156.
Census and Statistics Department. (2011). Babies born in Hong Kong to Mainland Women. Hong Kong: Census and Statistics Department.
Chan, R., (2002). Acculturation of young new arrivals from mainland China to Hong Kong. (Doctoral dissertation, The Chinese University of Hong Kong).
Cheng, M., & Yuen, A. H. K. (2018). Student continuance of learning management system use: A longitudinal exploration. Computers & Education,120, 241–253.
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.
Chong, S. (2004). A critical perspective of culturally diverse children in the changing school population in Hong Kong. (Doctoral dissertation, University of Toronto).
Chou, S., & Liu, C. (2005). Learning effectiveness in a Web-based virtual learning environment: A learner control perspective. Journal of Computer Assisted Learning,21(1), 65–76.
d’Addio, A. C. (2007). Intergenerational transmission of disadvantage: Mobility or immobility across generations? OECD Social, Employment, and Migration Working Papers (p. 52).
Dağhan, G., & Akkoyunlu, B. (2016). Modeling the continuance usage intention of online learning environments. Computers in Human Behavior,60, 198–211.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems. (Doctoral dissertation, Massachusetts Institute of Technology).
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly,13(3), 319–340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science,35(8), 982–1003.
Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems,19(4), 9–30.
EDB. (2009). Main report: Working group on textbooks and e-Learning resources development. Hong Kong: Education Bureau, Government of the Hong Kong Special Administrative Region.
EDB. (2012). Report on the review surveys of the THIRD strategy on information technology in education. Hong Kong: Education Bureau, Government of the Hong Kong Special Administrative Region.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Fornell, C., & Larker, D. (1981). Structural equation modeling and regression: Guidelines for research practice. Journal of Marketing Research,18(1), 39–50.
Friedrich, H. F., & Hron, A. (2010). Factors influencing pupils’ acceptance of an e-learning system for secondary schools. Journal of Educational Computing Research,42(1), 63–78.
Gil-Aluja, J. (2004). Fuzzy sets in the management of uncertainty. Berlin, New York: Springer.
Greener, S. (2017). Cultural diversity and learning technology. Interactive Learning Environments,25(8), 947–948.
Gu, M. M. (2011). ‘I am not qualified to be a Honkongese because of my accented Cantonese’: Mainland Chinese immigrant students in Hong Kong. Journal of Multilingual and Multicultural Development,32(6), 515–529.
Hatcher, L., & O’Rourke, N. (2013). A step-by-step approach to using SAS for factor analysis and structural equation modeling. Cary, NC: SAS Institute.
Ho, K. (2006). Stories of marriage migration: Identity negotiation of Chinese immigrant women in Hong Kong. (Doctoral dissertation, The University of Hong Kong).
Home Affairs Department & Immigration Department. (2006). Statistics on new arrivals from the Mainland (Fourth quarter of 2006). Hong Kong: Home Affairs Department & Immigration Department.
Home Affairs Department & Immigration Department. (2012). Statistics on new arrivals from the Mainland (Fourth quarter of 2012). Hong Kong: Home Affairs Department & Immigration Department.
Home Affairs Department & Immigration Department. (2016). Statistics on new arrivals from the Mainland (Fourth quarter of 2016). Hong Kong: Home Affairs Department & Immigration Department.
Hong Kong Government. (2013a), LCQ2: One way permit scheme. Retrieved from http://www.info.gov.hk/gia/general/201303/20/P201303200372.htm.
Hong Kong Government. (2013b), LCQ12: Immigration policy. Retrieved from http://www.info.gov.hk/gia/general/201303/20/P201303200372.htm.
Hofstede, G. (2013). Values survey module 2013 questionnaire Chinese (Hong Kong) version. Retrieved from https://geerthofstede.com/wpcontent/uploads/2017/10/VSM2013_HongKongVersion.pdf.
Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and organizations: Software of the mind (Rev. and expanded (3rd ed.). New York: McGraw-Hill.
Hofstede, G., & Minkov, M. (2013). Values survey module 2013 manual. Retrieved from https://geerthofstede.com/wp-content/uploads/2016/07/Manual-VSM-2013.pdf.
Hossain, L., & Silva, A. D. (2009). Exploring user acceptance of technology using social networks. The Journal of High Technology Management Research,20(1), 1–18.
Islam, A. N. (2013). Investigating e-learning system usage outcomes in the university context. Computers & Education,69, 387–399.
Islam, A. N., & Azad, N. (2015). Satisfaction and continuance with a learning management system: Comparing perceptions of educators and students. The International Journal of Information and Learning Technology,32(2), 109–123.
Kline, R. B. (2005). Principles and practice of structural equation modeling. Methodology in the social sciences (2nd ed.). New York: Guilford Press.
Lau, G. K. (2014). Digital divide in education: A shift to ethical usage. (Doctoral dissertation, The University of Hong Kong).
Lau, W. W., & Yuen, A. H. K. (2014). Internet ethics of adolescents: Understanding demographic differences. Computers & Education,72, 378–385.
Law, K.-Y., & Lee, K.-M. (2006). Citizenship, economy and social exclusion of mainland Chinese immigrants in Hong Kong. Journal of Contemporary Asia,36(2), 217–242.
Lee, M. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers & Education,54(2), 506–516.
Lee, S.-G., Trimi, S., & Kim, C. (2013). The impact of cultural differences on technology adoption. Journal of World Business,48(1), 20–29.
Leidner, D. E., & Kayworth, T. (2006). Review: A review of culture in information systems research: Toward a theory of information technology culture conflict. MIS Quarterly,30(2), 357–399.
Limayem, M., & Cheung, C. M. K. (2008). Understanding information systems continuance: The case of Internet-based learning technologies. Information & Management,45(4), 227–232.
Limayem, M., & Cheung, C. M. K. (2011). Predicting the continued use of Internet-based learning technologies: The role of habit. Behaviour & Information Technology,30(1), 91–99.
Lin, X., & Hatano, G. (2003). Technology, culture, and adaptive minds: An introduction. Mind, Culture, and Activity,10(1), 3–8.
Lin, C. S., Wu, S., & Tsai, R. J. (2005). Integrating perceived playfulness into expectation-confirmation model for web portal context. Information & Management,42(5), 683–693.
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.
Ma, W. K., & Yuen, H. K. (2011). e-Learning system acceptance and usage pattern. In T. Teo (Ed.), Technology acceptance in education: Research and issues (pp. 201–216). Rotterdam: Sense Publishers.
Marks, G. N. (2005). Accounting for immigrant non-immigrant differences in reading and mathematics in twenty countries. Ethnic and Racial Studies,28(5), 925–946.
McGill, T., Hobbs, V., & Klobas, J. E. (2003). User developed applications and information systems success: A test of DeLone and McLean’s model. Information Resources Management Journal,16(1), 24–45.
Metallo, C., & Agrifoglio, R. (2015). The effects of generational differences on use continuance of Twitter: An investigation of digital natives and digital immigrants. Behaviour & Information Technology,34(9), 869–881.
OECD. (2004). Learning for tomorrow’s world: First results from PISA 2003. Paris and Washington, DC: Organisation for Economic Co-operation and Development.
OECD. (2007). PISA 2006: Science competencies for tomorrow’s world. Paris and Washington, DC: Organisation for Economic Co-operation and Development.
OECD. (2012). Untapped skills: Realising the potential of immigrant students. Paris and Washington, DC: Organisation for Economic Co-operation and Development.
OECD. (2015). Helping immigrant students to succeed at school—and beyond. Paris and Washington, DC: Organisation for Economic Co-operation and Development.
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research,17(4), 460–469.
Pelgrum, W. (2008). School practices and conditions for pedagogy and ICT. In N. Law, W. J. Pelgrum, & T. Plomp (Eds.), Pedagogy and ICT use (pp. 67–120). Dordrecht: Springer.
Phillion, J. (2008). Multicultural and cross-cultural narrative inquiry into understanding immigrant students’ educational experience in Hong Kong. Compare: A Journal of Comparative and International Education,38(3), 281–293.
Pong, S.-L. (2009). Grade level and achievement of immigrants’ children: Academic redshirting in Hong Kong. Educational Research and Evaluation,15(4), 405–425.
Schleicher, A. (2006). Where immigrant students succeed: A comparative review of performance and engagement in PISA 2003. Intercultural Education,17(5), 507–516.
Shiue, Y. M., & Hsu, Y. C. (2017). Understanding factors that affecting continuance usage intention of game-based learning in the context of collaborative learning. Eurasia Journal of Mathematics Science and Technology Education,13(10), 6445–6455.
Srite, M., & Karahanna, E. (2006). The role of espoused national cultural values in technology acceptance. MIS Quarterly,30(3), 679–704.
Straub, D. W. (1994). The effect of culture on IT diffusion: E-Mail and FAX in Japan and the US. Information Systems Research,5(1), 23–47.
Straub, D. W., Keil, M., & Brenner, W. (1997). Testing the technology acceptance model across cultures: A three country study. Information & Management,33(1), 1–11.
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research,6(2), 144–176.
Teo, T., & Noyes, J. (2014). Explaining the intention to use technology among pre-service teachers: A multi-group analysis of the unified theory of acceptance and use of technology. Interactive Learning Environments,22(1), 51–66.
Teo, A. C., Tan, G. W. H., Cheah, C. M., Ooi, K. B., & Yew, K. T. (2012). Can the demographic and subjective norms influence the adoption of mobile banking? International Journal of Mobile Communications,10(6), 578–597.
Teo, T., Wong, S. L., & Chai, C. S. (2008). A cross-cultural examination of the intention to use technology between Singaporean and Malaysian pre-service teachers: An application of the Technology Acceptance Model (TAM). Journal of Educational Technology & Society,11(4), 265–280.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences,39(2), 273–315.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science,46(2), 186–204.
Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly,24(1), 115–139.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly,27(3), 425–478.
Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision Sciences,33(2), 297–316.
Venkatesh, V., Thong, J. Y., & 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.
Venkatesh, V., & Zhang, X. (2010). Unified theory of acceptance and use of technology: US vs China. Journal of Global Information Technology Management,13(1), 5–27.
Wong, Y.-C. (2011). The challenges for educational achievements of young Mainland Chinese migrants in Hong Kong. Asia Pacific Journal of Education,31(3), 277–291.
Wu, J.-H., Tennyson, R. D., & Hsia, T.-L. (2010). A study of student satisfaction in a blended e-learning system environment. Computers & Education,55(1), 155–164.
Yuen, A. H. K., Law, N. W., Lee, M. W., & Lee, Y. (2010). The changing face of education in Hong Kong: Transition into the 21st century. Hong Kong: Centre for Information Technology in Education, The University of Hong Kong.
Zhang, J. (2007). A cultural look at information and communication technologies in eastern education. Educational Technology Research and Development,55(3), 301–331.
Zhou, Z., Fang, Y., Vogel, D. R., Jin, X.-L., & Zhang, X. (2012). Attracted to or locked in? Predicting continuance intention in social virtual world services. Journal of Management Information Systems,29(1), 273–306.
Zhu, Y., & Leung, F. K. (2011). Mathematics achievement of mainland immigrant students in Hong Kong. Asia Pacific Journal of Education,31(4), 471–485.
Funding
This study was funded by the Research Grants Council of the Hong Kong Special Administrative Region (Project No.: 17411414).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Cheng, M., Yuen, A.H.K. Cultural divides in acceptance and continuance of learning management system use: a longitudinal study of teenagers. Education Tech Research Dev 67, 1613–1637 (2019). https://doi.org/10.1007/s11423-019-09680-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11423-019-09680-5