This is an excerpt from one of my latest empirical papers.
How to Cite: Camilleri, A.C. & Camilleri, M.A. (2019). The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games at Home and at School. 13th Annual International Technology, Education and Development Conference. Valencia, Spain (10-13 March, 2019). International Academy of Technology, Education and Development (IATED). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3339163
This contribution has explored the primary school’s grade three students’ attitudes toward educational games. It relied on the technology acceptance model to investigate the students’ perceived usefulness and ease of use of the schools’ games (, , ). Moreover, the researchers have also included the measuring items that explored the students’ perceived enjoyment () as they investigated whether they experienced normative pressures to play the educational games (, , ). The findings from the Wilcoxon test reported that the students played the school games at home, more than they did at school. They indicated that the school’s games were easy to play. This study reported that the students recognized that the school’s games were useful and relevant as they were learning from them. Moreover, they indicated that the school’s educational games held their attention since they found them enjoyable and fun.
The vast majority of the children played the educational games, both at home and at school. The findings in this study are consistent with the argument that digital natives are increasingly immersing themselves in digital technologies (), including educational games (, ). However, the results have shown that there was no significant relationship between the perceived ease of the gameplay and the children’s enjoyment in them. Furthermore, the stepwise regression analysis revealed that there was no significant relationship between the normative expectations and the children’s engagement with the educational games; although it was evident (from the descriptive statistics) that the parents were encouraging their children to play the games at home and at school.
This research relied on previously tried and tested measures that were drawn from the educational technology literature in order to explore the hypothesized relationships. There is common tendency in academic literature to treat the validity and reliability of quantitative measures from highly cited empirical papers as given. In this case, the survey items in this study were designed and adapted for the primary school children who were in grade 3, in a small European state. Future studies may use different sampling frames, research designs and methodologies to explore this topic. To the best of our knowledge, there is no other empirical study that has validated the technology acceptance model within a primary school setting. Further work is needed to replicate the findings of this research in a similar context.
REFERENCES (this is a full list of references that appeared in the bibliography section of the paper)
 J. Bourgonjon, M. Valcke, R. Soetaert, and T. Schellens, “Students’ perceptions about the use of educational games in the classroom,” Computers & Education, vol. 54, no. 4, pp. 1145-1156, 2010.
 S. Bennett, K. Maton, and L. Kervin, “The ‘digital natives’ debate: A critical review of the evidence,” British Journal of Educational Technology, vol. 39, no. 5, pp. 775-786, 2008.
 M. Prensky, “Digital natives, digital immigrants part 1,” On the horizon, vol. 9, no. 5, pp. 1-6, 2001.
 W. Nadeem, D. Andreini, J. Salo, and T. Laukkanen, “Engaging consumers online through websites and social media: A gender study of Italian Generation Y clothing consumers.” International Journal of Information Management, vol. 35, no. 4, pp. 432- 442, 2015.
 H.J. So, H. Choi, W.Y. Lim, and Y. Xiong, “Little experience with ICT: Are they really the Net Generation student-teachers?”, Computers & Education, vol. 59, no. 4, pp. 1234- 1245, 2012.
 J.M. Twenge, “The evidence for generation me and against generation we.” Emerging Adulthood 1, no. 1, pp. 11-16, 2013.
 D. Oblinger, and J. Oblinger, “Is it age or IT: First steps toward understanding the net generation,” Educating the Net Generation, 2(1-2), 20, 2015.
 N. Howe, and W. Strauss, “Millennials go to college: Strategies for a new generation on campus,” American Association of Collegiate Registrars and Admissions Officers (AACRAO), 2003.
 K. Gregor, T. Judd, B. Dalgarno, and J. Waycott, “Beyond natives and immigrants: exploring types of net generation students,” Journal of Computer Assisted Learning, vol. 26, no. 5, pp.332-343, 2010.
 T. Teo, “Modelling technology acceptance in education: A study of pre-service teachers,” Computers & Education 52, no. 2 (2009): 302-312, 2009.
 M. Fishbein, and I. Ajzen, “Belief, attitude, intention and behavior: An introduction to theory and research,” 1975.
 F.D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, pp. 319-340, 1989.
 F.D. Davis, R.P. Bagozzi, and P.R. Warshaw, “User acceptance of computer technology: a comparison of two theoretical models,” Management Science, vol. 35, no. 8, pp. 982- 1003, 1989.
 I. Ajzen, “The theory of planned behavior,” Organizational Behavior and Human Decision Processes, vol. 50, no. 2, pp. 179-211, 1991.
 V. Venkatesh, M.G. Morris, G.B. Davis, and F.D. Davis, “User acceptance of information technology: Toward a unified view,” MIS Quarterly, pp. 425-478, 2003.
 V. Venkatesh, J.Y.L. Thong, and X. Xu, “Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology,” MIS Quarterly, pp. 157-178, 2012.
 S.Y. Park. “An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning,” Educational Technology & Society, vol. 12, no. 3, pp. 150-162, 2009.
 P. Legris, J. Ingham, and P. Collerette, “Why do people use information technology? A critical review of the technology acceptance model,” Information & Management, vol. 40, no. 3, pp. 191-204, 2003.
 H. Nysveen, P.E. Pedersen, and H. Thorbjørnsen, “Intentions to use mobile services: Antecedents and cross-service comparisons,” Journal of the Academy of Marketing Science, vol. 33, no. 3, pp. 330-346, 2005.
 L.M. Maruping, B. Hillol, V. Venkatesh, and S.A. Brown, “Going beyond intention Integrating behavioral expectation into the unified theory of acceptance and use of technology,” Journal of the Association for Information Science and Technology, vol. 68, no. 3, pp. 623-637, 2017.
 V. Venkatesh, and M.G. Morris, “Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior.” MIS Quarterly, pp. 115-139, 2000.
 M.A. Camilleri and A. Camilleri, “The Students’ Perceptions of Digital Game-Based Learning,” In M. Pivec and J. Grundler, 11th European Conference on Games Based Learning (October). Proceedings, University of Applied Sciences, Graz, Austria, pp 56- 62, 2017.
 T. Teo, and M. Zhou, “Explaining the intention to use technology among university students: a structural equation modeling approach,” Journal of Computing in Higher Education, vol. 26, no. 2, pp. 124-142, 2014.
 T. Doleck, P. Bazelais, and D.J. Lemay, “Examining the antecedents of social networking sites use among CEGEP students,” Education and Information Technologies, vol. 22, no. 5, pp. 2103-2123, 2017.
 B. Wu, and X. Chen, “Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model,” Computers in Human Behavior, vol. 67, pp. 221-232, 2017.
 C.T. Chang, J. Hajiyev, and C.R. Su, “Examining the students’ behavioral intention to use e-learning in Azerbaijan? The general extended technology acceptance model for elearning approach,” Computers & Education, vol. 111, pp. 128-143, 2017.
 I. Arpaci, K. Kilicer, and S. Bardakci, “Effects of security and privacy concerns on educational use of cloud services,” Computers in Human Behavior, vol. 45, pp. 93-98,
 A.F. Agudo-Peregrina, Á. Hernández-García, and F.J. Pascual-Miguel, “Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning,” Computers in Human Behavior, vol. 34,
pp. 301-314, 2014.
 F. Paraskeva, H. Bouta, and A. Papagianni. “Individual characteristics and computer self-efficacy in secondary education teachers to integrate technology in educational practice,” Computers & Education, vol. 50, no. 3, pp. 1084-1091, 2008.
 D.R. Compeau, and C.A. Higgins, “Computer self-efficacy: Development of a measure and initial test,” MIS Quarterly, pp. 189-211, 1995.
 S.A. Nikou, and A.A. Economides, “The impact of paper-based, computer-based and mobile-based self-assessment on students’ science motivation and achievement,” Computers in Human Behavior, vol. 55, pp. 1241-1248, 2016.
 L.A. Annetta, J. Minogue, S.Y. Holmes, and M.T. Cheng, “Investigating the impact of video games on high school students’ engagement and learning about genetics,” Computers & Education, vol. 53, no. 1, pp. 74-85, 2009.
 E.W.T. Ngai, J. K. L. Poon, and Y.H.C. Chan, “Empirical examination of the adoption of WebCT using TAM,” Computers & Education, vol. 48, no. 2, pp. 250-267, 2007.
 T.Teo, and C. Beng Lee, “Explaining the intention to use technology among student teachers: An application of the Theory of Planned Behavior (TPB),” Campus-Wide Information Systems, vol. 27, no. 2, pp. 60-67, 2010.
 T. Teo, and C. Beng Lee, C. Sing Chai, and S.L. Wong, “Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM),” Computers & Education, vol. 53, no. 3, pp. 1000-1009, 2009.
 J.Y.L. Thong, W. Hong, and K.Y. Tam, “Understanding user acceptance of digital libraries: what are the roles of interface characteristics, organizational context, and individual differences?” International journal of human-computer studies, vol. 57, no. 3, pp. 215-242, 2002.
 M.A. Camilleri, and A.C. Camilleri, “Digital learning resources and ubiquitous technologies in education,” Technology, Knowledge and Learning, vol. 22, no. 1, pp. 65- 82, 2017.
 D.Y. Lee, and M.R. Lehto, “User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model.” Computers & Education, vol. 61, pp. 193-208, 2013.
 T. Teo, and P. Van Schalk, “Understanding technology acceptance in pre-service teachers: A structural-equation modeling approach,” The Asia-Pacific Education Researcher, vol. 18, no. 1, pp. 47-66, 2009.
 C. Smarkola, “Technology acceptance predictors among student teachers and experienced classroom teachers,” Journal of Educational Computing Research, vol. 37, no. 1, pp. 65-82, 2007.
 M.A. Camilleri, and A.C. Camilleri, “Measuring The Educators’ Behavioural Intention, Perceived Use And Ease Of Use Of Mobile Technologies,” In Wood, G. (Ed) Reconnecting management research with the disciplines: Shaping the research agenda for the social sciences (University of Warwick, September). British Academy of Management, UK, 2017.
 M. Turner, B. Kitchenham, P. Brereton, S. Charters, and D. Budgen, “Does the technology acceptance model predict actual use? A systematic literature review,” Information and Software Technology, vol. 52, no. 5, pp. 463-479, 2010.
 R.P. Bagozzi, and Y. Youjae, “On the evaluation of structural equation models,” Journal of the Academy of Marketing Science, vol. 16, no. 1, pp.74-94, 1988.
 M.A. Camilleri, and A.C. Camilleri, “The Technology Acceptance of Mobile Applications in Education,” In Sánchez, I.A. and Isaias, P. (Eds) 13th International Conference on Mobile Learning (Budapest, 11th April). pp41-48. International Association for Development of the Information Society, 2017.
 A. Colbert, N. Yee, and G. George, “The digital workforce and the workplace of the future,” Academy of Management Journal, vol. 59, no. 3, pp. 731-739, 2016.