Minecraft Education Edition in foreign language education: Pre-service teachers’ reasons for acceptance and integration

Kristen Fung; Sara Smith; Enrico Gandolfi

doi:10.54475/jlt.2022.013

Authors

Kristen Fung University of South Florida https://orcid.org/0000-0002-4261-249X
Sara Smith University of South Florida https://orcid.org/0000-0002-9024-8178
Enrico Gandolfi Kent State University https://orcid.org/0000-0002-8918-1033

DOI:

https://doi.org/10.54475/jlt.2022.013

Keywords:

multimodal input, virtual reality, reading comprehension, cognitive load

Abstract

In this paper, I explored the reasons three pre-service teachers gave for why they accept and integrate Minecraft Education Edition into their growing practice. During a six-week online university course on technology in foreign language education, a group of twenty-one pre-service and in-service teachers created weekly Reflexive Digital Story (RDS) Journals to document their technology exploration along with lesson plans and projects that incorporated innovative technologies they wanted to integrate into their practice. Three of the pre-service teachers enrolled in this course became innovators and early adopters in comparison to their peers as they voluntarily integrated Minecraft Education Edition into their coursework. This allowed me to qualitatively analyze their coursework to identify the reasons they integrated the digital game into their developing practice. This work contributes to the field of digital game-based learning, technology acceptance and integration, and the study of teacher education by illuminating the factors that contribute to why pre-service teachers accept and use Virtual Worlds (VWs). I discovered the reasons these pre-service teachers gave for acceptance and use of VW technology embodied the recognition of a need for motivation and engagement in the classroom, beliefs about the social nature of culture and language, and perceptions of VWs as an opportunity to make the impossible possible.

Author Biographies

Kristen Fung, University of South Florida

Kristen E. Fung (Ph.D.) is a graduate from the Technology in Education and Second Language Acquisition (TESLA) doctoral program at the University of South Florida. She is a well-published artist, an experienced English Language Arts and ESOL teacher, and the Managing Editor at the Journal of Literacy Research and Practice Online. Her research interests revolve around new emerging technologies including digital and immersive virtual environments, Digital Game-Based Language Learning, Multiliteracies Pedagogy, and Arts-Based Research Methods.
Email: kristenfung@usf.edu
Sara Smith, University of South Florida

Sara A. Smith (Ph.D.) is an Assistant Professor in ESOL and Foreign Language Education and Faculty in the Technology in Education and Second Language Acquisition (TESLA) doctoral program at the University of South Florida. The broad aim of her research program is to gain a better understanding of the diversity of language experience and how linguistic diversity relates to language, cognition, speech, and literacy and academic achievement. Her research interests include: differences related to the individual and the language environment; vocabulary, literacy/biliteracy, and achievement outcomes; and technology enhanced language learning, including digital environments and immersive virtual environments.
Email: sarasmith3@usf.edu
Enrico Gandolfi, Kent State University

Enrico Gandolfi (Ph.D.) is assistant professor and Program Coordinator of the Educational Technology program at Kent State University. His research interests include games and simulations for learning, augmented and virtual reality in education, and online communities of inquiry. He is author of several journal articles (e.g., for Journal of Technology and Teacher Education, New Media and Society, Technology in Society, British Journal of Educational Technology) and book chapters (for publishers like Routledge, MIT Press, ETC Press) about these topics. He has been CO-PI and senior personnel for grants funded by the National Science Foundation and the National Endowment for Humanities.
Email: egandol1@kent.edu

References

Ain, N., Kaur, K., & Waheed, M. (2016). The influence of learning value on learning management system use: An extension of UTAUT2. Information Development, 32(5), 1306-1321.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T

Al-Qeisi, K. I. (2009). Analyzing the use of UTAUT model in explaining an online behaviour: Internet banking adoption [Doctoral dissertation, Brunel University Brunel Business School PhD Theses]. Brunel University Research Archive.

Alsolami, T., & Saaty, N. (2020). The links between technology and principles of language teaching and learning: theoretical and practical insights. Technium Social Science Journal, 14, 718-726.

Anderson, S. E., & Maninger, R. M. (2007). Preservice teachers' abilities, beliefs, and intentions regarding technology integration. Journal of Educational Computing Research, 37(2), 151-172. https://doi.org/10.2190/H1M8-562W-18J1-634P

Anfara Jr, V. A., & Mertz, N. T. (Eds.). (2014). Theoretical frameworks in qualitative research. Sage publications.

Balanskat, A., Blamire, R., & Kefala, S. (2006). The ICT impact report. European Schoolnet, 1, 1-71.

Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4(3), 359-373.

Baydas, O., & Goktas, Y. (2016). Influential factors on preservice teachers' intentions to use ICT in future lessons. Computers in Human Behavior, 56, 170-178.

Beavis, C., Rowan, L., Dezuanni, M., McGillivray, C., O’Mara, J., Prestridge, S., Stieler-Hunt, C., Thompson, R., & Zagami, J. (2014). Teachers’ Beliefs about the Possibilities and Limitations of Digital Games in Classrooms. E-Learning and Digital Media, 11(6), 569-581.

https://doi.org/10.2304/elea.2014.11.6.569

Bernert-Rehaber, S., & Schlemminger, G. (2013). Immersive 3D-Technologien optimieren das Fremdsprachenlernen: EVEIL-3D – Lernen in virtuellen welten, Babylonia, 3, 44-49.

Bharati, V. J., & Srikanth, R. (2018). Modified UTAUT2 model for m-learning among students in India. International Journal of Learning and Change, 10(1), 5-20. https://doi.org/10.1504/IJLC.2018.089532

Birks, M., Chapman, Y., & Francis, K. (2008). Memoing in qualitative research: Probing data and processes. Journal of Research in Nursing, 13(1), 68-75. https://doi.org/10.1177/1744987107081254

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa

Briggs, K. (2019). Reflection and reflexivity [web blog]. http://kathrynbriggs.weebly.com/blog/reflection-reflexivity

Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in Psychology, 10, 1652. https://doi.org/10.3389/fpsyg.2019.01652

Chapelle, C. A., & Sauro, S. (2017). Introduction to the handbook of technology and second language teaching and learning. The handbook of technology and second language teaching and learning, 1-9.

Clarke, V., & Braun, V. (2013). Teaching thematic analysis: Overcoming challenges and developing strategies for effective learning. The Psychologist, 26(2).

Clemson University. (2022, October 12). College of Education. https://www.clemson.edu/education/index.html

Coleman, T. E., & Money, A. G. (2020). Student-centered digital game–based learning: a conceptual framework and survey of the state of the art. Higher Education, 79(3), 415-457. https://doi.org/10.1007/s10734-019-00417-0

Creswell, John W. (2013). Steps in Conducting a Scholarly Mixed Methods Study. [Speaker Series]. DBER Speaker Series 48. https://digitalcommons.unl.edu/dberspeakers/48

Crouch, M., & McKenzie, H. (2006). The logic of small samples in interview-based qualitative research. Social Science Information, 45(4), 483-499. https://doi.org/10.1177/0539018406069584

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008

Deci, E. L. (1971). Effects of externally mediated rewards on intrinsic motivation. Journal of Personality and Social Psychology, 18(1), 105–115. https://doi.org/10.1037/h0030644

Egbert, J., & Borysenko, N. (2018). Virtual learning environments in CALL classrooms: Engaging English language learners with Minecraft. European Journal of Applied Linguistics and TEFL, 7(2), 103-120.

Egbert, J., & Borysenko, N. (2019). Standards, engagement, and Minecraft: Optimizing experiences in language teacher education. Teaching and Teacher Education, 85, 115-124.

Fang, S., Wu, X., & Lai, I. K. W. (2021). Factors affecting Macau undergraduate students’ acceptance of hospitality English app: Applicability of UTAUT model. International Journal of Innovation and Learning, 29(3), 250-266. https://doi.org/10.1504/IJIL.2021.114510

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research: Addison-Wesley Publishing Company.

Fisher, M., King, J., & Tague, G. (2001). Development of a self-directed learning readiness scale for nursing education. Nurse Education Today, 21(7), 516-525.

Florida Department of Education (FLDOE). (2022, March 16). Family educational rights and privacy act (FERPA). FLDOE.org. https://www.fldoe.org/core/fileparse.php/7674/urlt/0064538-ferpa.pdf

Gabriel, S. (2016). Why digital game based learning should be included in teacher education. Reflecting Education, 10(1), 26-36.

Guest, W., Wild, F., Vovk, A., Lefrere, P., Klemke, R., Fominykh, M., & Kuula, T. (2018). A technology acceptance model for augmented reality and wearable technologies. Journal of Universal Computer Science, 24(2), 192-219. https://doi.org/10.3217/jucs-024-02-0192

Harrison, C., Comber, C., Fisher, T., Haw, K., Lewin, C., Lunzer, E., ... & Watling, R. (2002). ImpaCT2: The impact of information and communication technologies on pupil learning and attainment. British Educational Communications and Technology Agency (BECTA).

Howland, R., Urano, S., & Hoshine, J. (2013). SanjigenJiten: Computer assisted language learning system within a 3D game environment, In A. Nijholt, T. Romão, & D. Reidsma (Eds.), Advances in computer entertainment, Proceedings of 9th International Conference, 3.-5. November (pp. 262-273), Kathmandu, Nepal.

Hung, C. M., Huang, I., & Hwang, G. J. (2014). Effects of digital game-based learning on students’ self-efficacy, motivation, anxiety, and achievements in learning mathematics. Journal of Computers in Education, 1(2), 151-166. https://doi.org/10.1007/s40692-014-0008-8

Hung, H. T., Yang, J. C., Hwang, G. J., Chu, H. C., & Wang, C. C. (2018). A scoping review of research on digital game-based language learning. Computers & Education, 126, 89-104. https://doi.org/10.1016/j.compedu.2018.07.001

Inan, F. A., & Lowther, D. L. (2010). Factors affecting technology integration in K-12classrooms: A path model. Educational Technology Research and Development, 58(2), 137-154. https://doi.org/10.1007/s11423-009-9132-y

Jantke, K. P., & Hume, T. (2015). Effective learning through meaning construction in digital role playing games. Retrieved from https://www.theminnits.com/wpcontent/uploads/2014/12/ICCE-2015__ JH__final__red_Size.pdf

Jowitt, T. (2016, June 9). Microsoft offers Minecraft education edition to schools and teachers. Silicon.co.uk. https://www.silicon.co.uk/cloud/cloud-management/minecraft-education-edition-193431

Keengwe, J., Kidd, T., & Kyei-Blankson, L. (2009). Faculty and technology: Implications for faculty training and technology leadership. Journal of Science Education and Technology, 18(1), 23-28. https://doi.org/10.1007/s10956-008-9126-2

Kocaman, O., & Kizilkaya-Cumaoglu, G. (2014). The effect of educational software (DENIS) and games on vocabulary learning strategies and achievement. Education and Science, 39(176), 305-316. https://doi.org/10.15390/EB.2014.3704

Krathwohl, D. R. (1998). Methods of educational and social science: An integrated approach.

Levy, R. M., & O’Brien, Mary G. (2006). A virtual world for teaching german, Loading 1(1), 1-17.

Lincenberg, J., & Eynon, R. (2021). Crafting worldly spaces: The role of the educator in shaping student agency in Minecraft. Review of Education, Pedagogy, and Cultural Studies, 1-23. https://doi.org/10.1080/10714413.2021.1970465

Lincoln, Y.S. & Guba, E.G. (1985). Naturalistic inquiry. Sage Publications.

Long, T. & Johnson, M. (2000). Rigour, reliability and validity in qualitative research. Clinical Effectiveness in Nursing, 4(30), 30-37.

Marangunić, N., & Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal access in the information society, 14(1), 81-95.

McMillan, J. H., & Schumacher, S. (1997). Research in education: A conceptual framework. New York: Longman.

Miles, M. B., Huberman, A. M., & Saldaña, J. (2018). Qualitative data analysis: A methods sourcebook. Sage publications.

Minecraft. (2022, March 16). University students learn to communicate, create, and collaborate with 3D gaming software. Education.Minecraft.net. https://education.minecraft.net/en-us/blog/university-students-learn-to-communicate–create--and-collaborate-with-3d-gaming-software

Moorthy, K., Yee, T. T., T'ing, L. C., & Kumaran, V. V. (2019). Habit and hedonic motivation are the strongest influences in mobile learning behaviours among higher education students in Malaysia. Australasian Journal of Educational Technology, 35(4).

Muller, A. (2012). Research-based design of a medical vocabulary videogame, International Journal of Pedagogies and Learning, 7(2), 122-134.

Nelson, J., Christopher, A., & Mims, C. (2009). TPACK and Web 2.0: Transformation of teaching and learning. TechTrends, 53(5), 80.

Neville, D., O., Shelton, B. E., & McInnis, Brian (2009). Cybertext redux: using digital game-based learning to teach L2 vocabulary, reading, and culture. Computer Assisted Language Learning, 22(5), 409-424. https://doi.org/10.1080/09588220903345168

Newbill, P., & Baum, L. (2013). Design Creativity!. Learning & Leading with Technology, 40(4), 16-19.

Nizar, N. N. M., Rahmat, M. K., Maaruf, S. Z., & Damio, S. M. (2019). Examining the use behaviour of augmented reality technology through MARLCardio: Adapting the UTAUT Model. Asian Journal of University Education, 15(3), 198-210.

Patton, M.Q. (2002). Qualitative research and evaluation methods. Sage Publications.

Peirce, N., & Wade, V. (2010). Personalised learning for casual games: The 'language trap' online language learning game, In, B. Meyer (Ed.), Personalised learning for casual games: The 'language trap' online language learning game, 4th European conference on game based learning (ECGBL), 21.-22. October (pp. 111), Copenhagen, Denmark.

Peterson, M. (2012). Learner interaction in a massively multiplayer online role playing game (MMORPG): A sociocultural discourse analysis, ReCALL, 24(3), 361-380. https://doi.org/10.1017/S0958344012000195

Pintrich, P. R. (2000). Multiple goals, multiple pathways: The role of goal orientation in learning and achievement. Journal of Educational Psychology, 92(3), 544-555. https://doi.org/10.1037/0022-0663.92.3.544

Polit, D. & Beck C. T. (2010). Generalization in quantitative and qualitative research: Myths and Strategies. International Journal of Nursing Studies, 47(10), 1451-1458.

Porter III, J., Boyer, M., & Robb, A. (2018, October). Guidelines on successfully porting non-immersive games to virtual reality: a case study in Minecraft. [Conference session]. 2018

Annual Symposium on Computer-Human Interaction in Play.

Prensky, M. (2009). H. sapiens digital: From digital immigrants and digital natives to digital wisdom. Innovate: journal of online education, 5(3).

Primeau, L. A. (2003). Reflections on self in qualitative research: Stories of family. The American journal of occupational therapy, 57(1), 9-16.

Richards, J. (2021). Coding, Categorizing, and Theming the Data: A Reflexive Search for Meaning. Analyzing and Interpreting Qualitative Research: After the Interview, 149.

Rolfe, G. (2006). Validity, trustworthiness, and rigour: Quality and the idea of qualitative research. Journal of Advanced Nursing, 53(3), 304-310.

Romero, M., & Barma, S. (2015). Teaching pre-service teachers to integrate serious games in the primary education curriculum. International Journal of Serious Games, 2(1), 45-54.

Roy, M., & Schlemminger, G. (2014). Immersion und Interaktion in virtuellen Realitäten: Der Faktor Präsenz zur Optimierung des geleiteten Sprachenlernens. Zeitschrift für Interkulturellen Fremdsprachenunterricht 19(2), 187-201.

Samsudeen, S. N., & Mohamed, R. (2019). University students’ intention to use e-learning systems: A study of higher educational institutions in Sri Lanka. Interactive Technology and Smart Education.

Sandelowski, M. (1993). Rigor or rigor mortis: The problem of rigor in qualitative research revisited. Advanced Nursing Science, 16(2). 1-8.

Silva, E. (2009). Measuring skills for 21st-century learning. Phi delta kappan, 90(9), 630-634.

Smith, E. E., Kahlke, R., & Judd, T. (2020). Not just digital natives: Integrating technologies in professional education contexts. Australasian Journal of Educational Technology, 36(3), 1-14.

Noble, H. & Smith, J. (2015). Issues of validity and reliability in qualitative research. Evidence-Based Nursing, 18(2), 34-35.

Snead, K. C., & Harrell, A. M. (1994). An application of expectancy theory to explain a manager's intention to use a decision support system. Decision Sciences, 25(4), 499-510.

Snoeyink, R., & Ertmer, P. A. (2001). Thrust into technology: How veteran teachers respond. Journal of educational technology systems, 30(1), 85-111.

Stewart, D. L. (2010). Researcher as instrument: Understanding" shifting" findings in constructivist research. Journal of Student Affairs Research and Practice, 47(3), 291-306.

Strauss, A. L. (1987). Qualitative analysis for social scientists. Cambridge university press.

Sullivan, M. S. (2012). A study of the relationship between personality types and the acceptance of technical knowledge management systems (TKMS) [Doctoral dissertation, Capella University].

Sung, H. N., Jeong, D. Y., Jeong, Y. S., & Shin, J. I. (2015). The relationship among self-efficacy, social influence, performance expectancy, effort expectancy, and behavioral intention in mobile learning service. International Journal of u-and e-Service, Science and Technology, 8(9), 197-206.

Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.

Tavinor, G. (2011). Video games as mass art. Contemporary Aesthetics (Journal Archive), 9(1), 9.

Teo, T., & Van Schaik, P. (2012). Understanding the intention to use technology by preservice teachers: An empirical test of competing theoretical models. International Journal of Human-Computer Interaction, 28(3), 178-188.

Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS quarterly, 125-143.

Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on engineering management, (1), 28-45.

Turgut, Y., & Irgin, P. (2010). Students’ experiences of computer games and ELL: From phenomenological perspective, In Proceedings of the 10th METU ELT Convention, 22.-23. May 2009, Ankara, Turkey Retrieved from https://dbe.metu.edu.tr/convention/proceedingsweb/Games.pdf

Vallerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation. In Advances in experimental social psychology (Vol. 29, pp. 271-360). Academic Press.

Valtonen, T., Hoang, N., Sointu, E., Näykki, P., Virtanen, A., Pöysä-Tarhonen, J., ... &

Kukkonen, J. (2021). How pre-service teachers perceive their 21st-century skills and dispositions: A longitudinal perspective. Computers in Human Behavior, 116, 106643.

Veletsianos, G. (2016). The defining characteristics of emerging technologies and emerging practices in digital education. Emergence and innovation in digital learning: Foundations and applications, 3-16.

Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision sciences, 27(3), 451-481.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.

Vygotsky, L.S. (1962). Thought and language. MIT Press.

Wachira, P., & Keengwe, J. (2011). Technology integration barriers: Urban school mathematics teachers’ perspectives. Journal of Science Education and Technology, 20(1), 17-25. https://doi.org/10.1007/s10956-010-9230-y

Wang, L., MacCann, C., Zhuang, X., Liu, O. L., & Roberts, R. D. (2009). Assessing teamwork and collaboration in high school students: A multimethod approach. Canadian Journal of School Psychology, 24(2), 108-124. https://doi.org/10.1177/0829573509335470

Weinstein, C. E., Husman, J., & Dierking, D. R. (2000). Self-regulation interventions with a focus on learning strategies. In Handbook of self-regulation (pp. 727-747). Academic Press.

Yildiz Durak, H. (2019). Examining the acceptance and use of online social networks by preservice teachers within the context of unified theory of acceptance and use of technology model. Journal of Computing in Higher Education, 31(1), 173-209. https://doi.org/10.1007/s12528-018-9200-6

Yurdakul- Kabakçı, I., Ursavaş, Ö. F., & İsçitürk, G. B. (2014). An integrated approach for preservice teachers’ acceptance and use of technology: UTAUT-PST Scale. Eurasian Journal of Education Research, 55, 21-36. https://dx.doi.org/10.14689/ejer.2014.55.2