Category Archives: digital games

October 3, 2019 · 4:42 pm

Key Terms in Education Technology Literature

This is an excerpt from one of my latest contributions, entitled: “The Use of Mobile Learning Technologies in Primary Education”.

edtech(The Image has been adapted from Buzzle.com)

 

  • The ‘Constructivist-Based learning’ is a learning theory claiming that individuals construct their knowledge and understandings through experiencing things.
  • The ‘Digital Learning Resources’ include digitally formatted, educational materials like; graphics, images or photos, audio and video, simulations and animation technologies, that are used to support students to achieve their learning outcomes.
  • The ‘Digital Games-Based Learning’ (DGBL) involves the use of educational video games that can be accessed through computer-based applications. DGBL are usually aimed to improve the students’ learning outcomes by balancing educational content and gameplay.
  • The ‘Discovery-Based Learning’ is a constructivist-based approach to education as students seek to learn through continuous inquiry and experience.
  • The ‘Learning Outcomes’ are assessment tools that measure the students’ achievement at the end of a course or program.
  • ‘Mobile Learning’ (M-Learning) is a term that describes how individuals learn through mobile, portable devices, including smart phones, laptops and/or tablets.
  • The ‘Serious Games’ refer to games that are used in industries like; education, health care, engineering, urban planning, politics and defence, among other areas. Such games are usually designed for training purpose other than pure entertainment.
  • The ‘Ubiquitous Technology’ involves the use of wireless sensor networks that disseminate information in real time, from virtually everywhere.

 

ADDITIONAL READING

  1. Bakker, M., van den Heuvel-Panhuizen, M., & Robitzsch, A. (2015). Effects of playing mathematics computer games on primary school students’ multiplicative reasoning ability. Contemporary Educational Psychology, 40, 55-71.
  2. Blatchford, P., Baines, E., & Pellegrini, A. (2003). The social context of school playground games: Sex and ethnic differences, and changes over time after entry to junior school. British Journal of Developmental Psychology, 21(4), 481-505.
  3. Bottino, R. M., Ferlino, L., Ott, M., & Tavella, M. (2007). Developing strategic and reasoning abilities with computer games at primary school level. Computers & Education, 49(4), 1272-1286.
  4. Camilleri, M.A. & Camilleri, A. (2017). The Students’ Perceptions of Digital Game-Based Learning. In Pivec, M. & Grundler, J. (Ed.)11th European Conference on Games Based Learning (October). Proceedings, pp. 52-62, H JOANNEUM University of Applied Science, Graz, Austria, pp 56-62. http://toc.proceedings.com/36738webtoc.pdf https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3087801
  5. Camilleri, A.C. & Camilleri, M.A. (2019). The Students Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games. In Shun-Wing N.G., Fun, T.S. & Shi, Y. (Eds.) 5th International Conference on Education and Training Technologies (ICETT 2019). Seoul, South Korea (May, 2019). International Economics Development and Research Center (IEDRC). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3339158
  6. 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 (March 2019). International Academy of Technology, Education and Development (IATED). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3339163
  7. Camilleri, M.A. & Camilleri, A.C. (2019). Student-Centred Learning through Serious Games. 13th Annual International Technology, Education and Development Conference. Valencia, Spain (March 2019). International Academy of Technology, Education and Development (IATED). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3339166
  8. De Aguilera, M., & Mendiz, A. (2003). Video games and education:(Education in the Face of a “Parallel School”). Computers in Entertainment (CIE), 1(1), 1-14.
  9. Hainey, T., Connolly, T. M., Boyle, E. A., Wilson, A., & Razak, A. (2016). A systematic literature review of games-based learning empirical evidence in primary education. Computers & Education, 102, 202-223.
  10. Hromek, R., & Roffey, S. (2009). Promoting Social and Emotional Learning With Games: “It’s Fun and We Learn Things”. Simulation & Gaming, 40(5), 626-644.
  11. Lim, C. P. (2008). Global citizenship education, school curriculum and games: Learning Mathematics, English and Science as a global citizen. Computers & Education, 51(3), 1073-1093.
  12. McFarlane, A., Sparrowhawk, A., & Heald, Y. (2002). Report on the educational use of games. TEEM (Teachers evaluating educational multimedia), Teem, Cambridge, UK. pp.1-26. http://consilr.info.uaic.ro/uploads_lt4el/resources/pdfengReport%20on%20the%20educational%20use%20of%20games.pdf
  13. Miller, D. J., & Robertson, D. P. (2010). Using a games console in the primary classroom: Effects of ‘Brain Training’programme on computation and self‐British Journal of Educational Technology, 41(2), 242-255.
  14. Pellegrini, A. D., Blatchford, P., Kato, K., & Baines, E. (2004). A short‐term longitudinal study of children’s playground games in primary school: Implications for adjustment to school and social adjustment in the USA and the UK. Social Development, 13(1), 107-123.
  15. Tüzün, H., Yılmaz-Soylu, M., Karakuş, T., İnal, Y., & Kızılkaya, G. (2009). The effects of computer games on primary school students’ achievement and motivation in geography learning. Computers & Education, 52(1), 68-77.

 

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May 28, 2019 · 9:22 pm

The Students Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games

An Excerpt from one of my latest papers, entitled; “The Students’ Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games”.

How to Cite: Camilleri, A.C. & Camilleri, M.A. (2019). The Students Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games. In Shun-Wing N.G., Fun, T.S. & Shi, Y. (Eds.) 5th International Conference on Education and Training Technologies (ICETT 2019). Seoul, South Korea (May, 2019).

This contribution has explored the primary school’s grade three  students’ intrinsic and extrinsic motivations toward the use of educational games. It relied on the technology acceptance model to investigate the students’ perceived usefulness and ease of use of the  schools’ games ([7], [8], [15]). Moreover, the researchers have also  included the measuring items that explored the students’ perceived  enjoyment ([12], [13], [20]) as they investigated whether they  experienced normative pressures to play the educational games ([14], [22], [23]). 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 ([2]), including educational games ([1], [4], [10], [11], [28]). 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.

ACKNOWLEDGEMENTS
We thank the department of education, the school’s principal and her members of staff who have provided their invaluable support during the data gathering process.

REFERENCES
[1] Ge, X., and Ifenthaler, D. 2018. Designing engaging
educational games and assessing engagement in game-based
learning” In Gamification in Education: Breakthroughs in
Research and Practice, IGI Global, Hershey, USA, 1-19,

[2] Bourgonjon, J., Valcke, M., Soetaert, R., and Schellens, T.
2010, Students’ perceptions about the use of educational
games in the classroom. Comp. & Educ. 54, 4, 1145-1156.

[3] Hwang, G.J., and Wu, P.H. 2012. Advancements and trends
in digital game‐based learning research: a review of
publications in selected journals from 2001 to 2010. Brit. J.
of Educ. Tech. 43, 1, E6-E10.

[4] Carvalho, M.B., Bellotti, F., Berta, R., De Gloria, A.,
Sedano, C.I., Hauge, H.B., Hu, J., and Rauterberg, M. 2015.
An activity theory-based model for serious games analysis
and conceptual design. Comp. & Educ. 87, 166-181.

[5] Connolly, T.M., Boyle, E.A., MacArthur, E. Hainey, T., and
Boyle, J.M. 2012. A systematic literature review of empirical
evidence on computer games and serious games. Comp. &
Educ. 59, 2, 661-686.

[6] Burguillo, J.C. 2010. Using game theory and competitionbased
learning to stimulate student motivation and
performance. Comp. & Educ. 55, 2, 566-575.

[7] Dickey, M.D. 2011. Murder on Grimm Isle: The impact of
game narrative design in an educational game‐based learning
environment. Brit. J. of Educ. Tech, 42, 3, 456-469.

[8] Huang, W.H., Huang, W.Y., and Tschopp, J. 2010.
Sustaining iterative game playing processes in DGBL: The
relationship between motivational processing and outcome
processing. Comp. & Educ. 55, 2, 789-97.

[9] Harris, J. Mishra, P., and Koehler, M. 2009. Teachers’
technological pedagogical content knowledge and learning
activity types: Curriculum-based technology integration
reframed. J. of Res. on Tech. in Educ. 41, 4, 393-416.

[10] Wouters, P., Van Nimwegen, C., Van Oostendorp, H., and
Van Der Spek, E.D. 2013. A meta-analysis of the cognitive
and motivational effects of serious games. J. of Educ. Psych.
105, 2, 249-266.

[11] Camilleri, M.A., and Camilleri, A. 2017. The Students’
Perceptions of Digital Game-Based Learning, In Pivec, M.
and Grundler, J. 11th European Conference on Games Based
Learning Proceedings (London, UK, October 04-05, 2017),
University of Applied Sciences, Graz, Austria, 56-62.

[12] Davis, F.D. 1989. Perceived usefulness, perceived ease of
use, and user acceptance of information technology. MIS
Quart. 319-340.

[13] Davis, F.D., Bagozzi, R.P., and Warshaw, P.R. 1989. User
acceptance of computer technology: a comparison of two
theoretical models. Mgt. Science, 35, 8, 982-1003.

[14] Ajzen, I. 1991. The theory of planned behavior. Org. Behav.
and Human Dec. Proc. 50, 2, 179-211.

[15] Lee, M. K., Cheung, C. M., and Chen, Z. 2005. Acceptance
of Internet-based learning medium: the role of extrinsic and
intrinsic motivation. Inf. & Mgt. 42, 8, 1095-1104.

[16] Chen, K. C. and Jang, S. J. 2010. Motivation in online
learning: Testing a model of self-determination theory.
Comp. in Human Behav. 26, 4, 741-752.

[17] Dunne, Á., Lawlor, M. A., and Rowley, J. 2010. Young
people’s use of online social networking sites–a uses and
gratifications perspective. Journal of Res. in Int. Mktg. 4, 1,
46-58.

[18] Li, H., Liu, Y., Xu, X., Heikkilä, J., and Van Der Heijden, H.
2015. Modeling hedonic is continuance through the uses and
gratifications theory: An empirical study in online games.
Comp. in Human Behav. 48, 261-272.

[19] Teo, T., Beng Lee, C., Sing Chai, C., and Wong, S.L. 2009.
Assessing the intention to use technology among pre-service
teachers in Singapore and Malaysia: A multigroup invariance
analysis of the Technology Acceptance Model (TAM).
Comp. & Educ. 53, 3, 1000-1009.

[20] Camilleri, M.A., and Camilleri, A.C. 2017. Digital learning
resources and ubiquitous technologies in education, Tech.,
Knowl. and Learng. 22, 1, 65-82.

[21] Park, S.Y. 2009. An analysis of the technology acceptance
model in understanding university students’ behavioral
intention to use e-learning, Educ. Tech. & Soc. 12, 3, 150-
162.

[22] Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D.
2003. User acceptance of information technology: Toward a
unified view. MIS Quart. 425-478.

[23] Venkatesh, V., Thong, Y.T.L., and Xu, X. 2012.Consumer
acceptance and use of information technology: extending the
unified theory of acceptance and use of technology. MIS
Quart. 157-178.

[24] Ryan, R. M., and Deci, E. L. 2000. Intrinsic and extrinsic
motivations: Classic definitions and new directions.
Contemp. Educ. Psych. 25, 1, 54-67.

[25] Cheon, J., Lee, S., Crooks, S. M. and Song, J. 2012. An
investigation of mobile learning readiness in higher
education based on the theory of planned behavior. Comp. &
Educ. 59, 3, 1054-1064.

[26] Chang, C.T., Hajiyev, J., and Su, C.R. 2017. Examining the
students’ behavioral intention to use e-learning in
Azerbaijan? The general extended technology acceptance
model for e-learning approach. Comp. & Educ. 111, 128-
143.

[27] Park, S. Y., Nam, M. W., and Cha, S. B. 2012. University
students’ behavioral intention to use mobile learning:
Evaluating the technology acceptance model. Brit. Journal of
Educ. Tech. 43, 4, 592-605.

[28] Camilleri, M.A. and Camilleri, A.C. 2017. The Technology
Acceptance of Mobile Applications in Education. In
Sánchez, I.A. and Isaias, P. (Eds) 13th
International Conference on Mobile Learning (London, UK,
10-11 April 2018). International Association for
Development of the Information Society Budapest, Hungary,
41-48.

Presentation is available at: https://www.slideshare.net/markanthonycamilleri/the-students-intrinsic-and-extrinsic-motivations-148006875

 

 

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March 22, 2019 · 12:02 pm

The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games

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

gamesThis 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 ([10], [12], [44]). Moreover, the researchers have also included the measuring items that explored the students’ perceived enjoyment ([19]) as they investigated whether they experienced normative pressures to play the educational games ([10], [14], [20]). 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 ([45]), including educational games ([1], [3]). 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)

 
[1] 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.

[2] 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.

[3] M. Prensky, “Digital natives, digital immigrants part 1,” On the horizon, vol. 9, no. 5, pp. 1-6, 2001.

[4] 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.

[5] 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.

[6] J.M. Twenge, “The evidence for generation me and against generation we.” Emerging Adulthood 1, no. 1, pp. 11-16, 2013.

[7] 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.

[8] 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.

[9] 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.

[10] T. Teo, “Modelling technology acceptance in education: A study of pre-service teachers,” Computers & Education 52, no. 2 (2009): 302-312, 2009.

[11] M. Fishbein, and I. Ajzen, “Belief, attitude, intention and behavior: An introduction to theory and research,” 1975.

[12] F.D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, pp. 319-340, 1989.

[13] 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.

[14] I. Ajzen, “The theory of planned behavior,” Organizational Behavior and Human Decision Processes, vol. 50, no. 2, pp. 179-211, 1991.

[15] 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.

[16] 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.

[17] 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.

[18] 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.

[19] 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.

[20] 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.

[21] 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.

[22] 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.

[23] 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.

[24] 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.

[25] 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.

[26] 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.

[27] 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,
2015.

[28] 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.

[29] 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.

[30] D.R. Compeau, and C.A. Higgins, “Computer self-efficacy: Development of a measure and initial test,” MIS Quarterly, pp. 189-211, 1995.

[31] 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.

[32] 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.

[33] 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.

[34] 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.

[35] 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.

[36] 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.

[37] 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.

[38] 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.

[39] 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.

[40] 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.

[41] 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.

[42] 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.

[43] 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.

[44] 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.

[45] 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.

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