본문 바로가기
KERD
논문KCI 등재

교사의 AR․VR 테크놀로지 활용 수업 인식에 대한 잠재프로파일 분석 및 영향변인 탐색

A Latent Profile Analysis of Teachers' AR and VR Integration

고유정|장재홍|신원석
한국교육정보미디어학회 (Korea Association for Educational Information and Media)|2020.06|교육정보미디어연구 (Journal of Korean Association for Educational Information and Media)|제26권 제2호|pp. 367-393|DOI http://dx.doi.org/10.15833/KAFEIAM.26.2.367

0

조회

0

다운로드

12

인용

0

참고문헌

키워드

가상현실증강현실잠재프로파일 분석Technology integrationLatent profile analysis (LPA)테크놀로지 활용Augmented technology (AR)Virtual technology (VR)
주제분류교육학

초록

본 연구는 교사의 AR․VR 테크놀로지 활용 수업에 대한 인식 및 영향변인 탐색을 통해 새로운 테크놀로지 수용을 위해 필요한 시사점을 제공하고자 하였다. 이를 위해 AR․VR 테크놀로지 수업 경험이 있는 서울 및 경기지역 초등학교 교사 376명을 대상으로 설문을 실시하여 최종 320명을 분석하였다. 연구방법으로 효능감, 유용성, 용이성, 사용의도 지표변인을 활용하여 잠재프로파일분석을 실시하였으며 분류된 잠재집단에 영향을 미치는 변인들을 확인하였다. 연구결과, 교사의 AR․VR 테크놀로지활용 수업 인식에 따른 잠재집단은 총 3개의 집단으로 분류되었으며, 효능감과 용이성 지표변인의 상대적 차이가 크게 나타났다. 영향변인 탐색 결과, 개인 혁신성, 구성주의적 신념은 상위수준 집단, 사회적 규범은 하위수준 집단 구분에 영향을 미쳤으며, TPACK은 모든 집단에 영향을 미쳤다. 하지만동기적 지원, 기술적 지원은 모든 집단에 영향을 미치지 않았다. 본 연구를 통해 다수의 교사들이 AR․VR 테크놀로지를 활용한 수업 진행에 대해 낮은 효능감과 용이성을 느낀다는 점이 확인되었다. 수업에서의 AR․VR 테크놀로지 활용을 위해서는 교사연수, 매뉴얼 배포 등을 통한 테크놀로지 활용에 대한 체계적인 안내, 편리한 활용을 위한 기술적 측면의 노력, AR․VR 테크놀로지 적용 수업 설계및 교수법 개발 등이 병행될 필요가 있다.

Abstract

More digital textbooks are being distributed in K-12 schools in Korea and numerous contents using augmented reality (AR) and virtual reality (VR) technology embedded in the digital textbooks are one of the advantages of using them. However, without teachers' acceptance of and intention to use the technology, it is less likely to be used in classrooms. The present study is to investigate teachers' acceptance and its influencing factors of AR and VR technology for teaching and learning activities using Latent Profile Analysis (LPA). 376 inservice teachers with prior teaching experience with AR and/or VR answered our survey and 320 of the responses were analyzed for the study. For the LPA, four variables―teacher self-efficacy (SE), perceived usefulness (PU), perceived ease of use (PEU), and behavioral intention (BI)―were served as indicator variables and how influencing factors (i.e., TPACK, belief, motivational and technological support, personal innovativeness, and subjective norm) impact each latent group were examined. Results indicated that 1) teachers can be categorized into three latent groups with significant differences in SE and PEU; 2) belief was contributed to differentiate 'upper level' and subjective norm 'lower level,' and TPACK all three latent groups; and 3) motivational and technological support had influence on none of the groups. The current study confirmed that many teachers have low SE and PEU in using AR and VR in teaching and learning, which warrants supports for teachers with professional development, technological advancement for easier use, and instructional design for AR and VR-based learning.

참고문헌 (80)

  1. 고유정, "교사들의 테크놀로지 활용 교육을 위한 학교의 지원 중요성 분석", 제주대학교 교육과학연구, 22(1), pp.21~42 (2020), 교육과학연구소[DOI]
  2. 교육부, "미래교육의 첫발, 디지털교과서와 소프트웨어교육 실시", 보도자료 2018. 04. 02, ~ (2018)
  3. 2018 교육정보화백서, "교육부", 한국교육학술정보원, ~ (2018)
  4. 2020 디지털교과서와 함께하는 우리학교, "교육부", 한국교육학술정보원, ~, pp.PM 2020-1 (2020)
  5. 남선혜, "국내 증강현실활용교육의 효과에 대한 메타분석", 교육정보미디어연구, 26(1), pp.129~156 (2020), 한국교육정보미디어학회[DOI]
  6. 엄미리, "테크놀로지 내용교수지식(TPACK) 역량에 대한 예비교사의 인식 분석", 한국교원교육연구, 28(4), pp.141~165 (2011), 한국교원교육학회[DOI]
  7. "디지털교과서 서비스 이용 안내" (2020), 에듀넷[URL]
  8. 유명현, "VR, AR, MR 기반 학습의 효과에 관한 메타분석", 교육정보미디어연구, 24(3), pp.459~488 (2018), 한국교육정보미디어학회[DOI]
  9. Ritu Agarwal, "A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology", Information Systems Research, 9(2), pp.204~215 (1998), Institute for Operations Research and the Management Sciences (INFORMS)[DOI]
  10. Ajzen, I., "The theory of planned behavior", Organizational Behavior and Human Decision Processes, 50, pp.179~211 (1991)
  11. Akaike, H., "A new look at the statistical model identification", IEEE Transactions on Automatic Control, 19, pp.716~723 (1974)
  12. Murat Akçayır, "Advantages and challenges associated with augmented reality for education: A systematic review of the literature", Educational Research Review, 20, pp.1~11 (2017), Elsevier BV[DOI]
  13. Salsabeel F. M. Alfalah, "Perceptions toward adopting virtual reality as a teaching aid in information technology", Education and Information Technologies, 23(6), pp.2633~2653 (2018), Springer Science and Business Media LLC[DOI]
  14. Wadee Alhalabi, "Virtual reality systems enhance students’ achievements in engineering education", Behaviour & Information Technology, 35(11), pp.919~925 (2016), Informa UK Limited[DOI]
  15. Ronald E. Anderson, "School Technology Leadership: An Empirical Investigation of Prevalence and Effect", Educational Administration Quarterly, 41(1), pp.49~82 (2016), SAGE Publications[DOI]
  16. Guy Assaker, "Age and gender differences in online travel reviews and user-generated-content (UGC) adoption: extending the technology acceptance model (TAM) with credibility theory", Journal of Hospitality Marketing & Management, 29(4), pp.428~449 (2020), Informa UK Limited[DOI]
  17. Chai, C. S., "Examining preservice teachers’ perceived knowledge of TPACK and cyberwellness through structural equation modeling", Australasian Journal of Educational Technology, 28(6), pp.1000~1019 (2012)
  18. Hong-Ren Chen, "Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan", Evaluation and Program Planning, 35(3), pp.398~406 (2012), Elsevier BV[DOI]
  19. Jongpil Cheon, "An investigation of mobile learning readiness in higher education based on the theory of planned behavior", Computers & Education, 59(3), pp.1054~1064 (2012), Elsevier BV[DOI]
  20. Collins, L. M., "Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences (Vol. 718)" (2009), John Wiley & Sons
  21. Cuban, L., "Oversold and underused" (2001), Harvard University Press
  22. Fred D. Davis, "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology", MIS Quarterly, 13(3), pp.319~340 (1989), JSTOR[DOI]
  23. S. Dexter, "Contributions of professional community to exemplary use of ICT", Journal of Computer Assisted Learning, 18(4), pp.489~497 (2002), Wiley[DOI]
  24. Vincent Dutot, "Applying the technology acceptance model in a three-countries study of smartwatch adoption", The Journal of High Technology Management Research, 30(1), pp.1~14 (2019), Elsevier BV[DOI]
  25. Peggy A. Ertmer, "Teacher pedagogical beliefs: The final frontier in our quest for technology integration?", Educational Technology Research and Development, 53(4), pp.25~39 (2005), Springer Science and Business Media LLC[DOI]
  26. Peggy A. Ertmer, "Teacher Technology Change", Journal of Research on Technology in Education, 42(3), pp.255~284 (2010), Informa UK Limited[DOI]
  27. Peggy A. Ertmer, "Teacher beliefs and technology integration practices: A critical relationship", Computers & Education, 59(2), pp.423~435 (2012), Elsevier BV[DOI]
  28. Göran Fransson, "The challenges of using head mounted virtual reality in K-12 schools from a teacher perspective", Education and Information Technologies, 25(4), pp.3383~3404 (2020), Springer Science and Business Media LLC[DOI]
  29. Christopher Heinlen, "Exploring genetic counselors’ perceptions of usefulness and intentions to use refined risk models in clinical care based on the Technology Acceptance Model (TAM)", Journal of Genetic Counseling, 28(3), pp.664~672 (2019), Wiley[DOI]
  30. Khe Foon Hew, "Integrating technology into K-12 teaching and learning: current knowledge gaps and recommendations for future research", Educational Technology Research and Development, 55(3), pp.223~252 (2007), Springer Science and Business Media LLC[DOI]
  31. Shihkuan Hsu, "The impact of multilevel factors on technology integration: the case of Taiwanese grade 1–9 teachers and schools", Educational Technology Research and Development, 61(1), pp.25~50 (2013), Springer Science and Business Media LLC[DOI]
  32. Hughes, J. E., "The role of teacher knowledge and learning experiences in forming technology-integrated pedagogy", Journal of Technology and Teacher Education, 13(2), pp.277~302 (2005)
  33. Hughes, J. E., "A case study of technology leadership in situ", Journal of School Leadership, 26(2), pp.283~313 (2016)
  34. Hughes, J. E., "Preservice teachers’ social networking use, concerns, and educational possibilities : Trends from 2008-2012", Journal of Technology and Teacher Education, 23(2), pp.185~212 (2015)
  35. Hendrik Drachsler, "Applying augmented reality to enhance learning: a study of different teaching materials", Journal of Computer Assisted Learning, 33(3), pp.252~266 (2017), Wiley[DOI]
  36. Fethi A. Inan, "Factors affecting technology integration in K-12 classrooms: a path model", Educational Technology Research and Development, 58(2), pp.137~154 (2010), Springer Science and Business Media LLC[DOI]
  37. Syh-Jong Jang, "Exploring the TPACK of Taiwanese elementary mathematics and science teachers with respect to use of interactive whiteboards", Computers & Education, 59(2), pp.327~338 (2012), Elsevier BV[DOI]
  38. Young Ju Joo, "Integrating user interface and personal innovativeness into the TAM for mobile learning in Cyber University", Journal of Computing in Higher Education, 26(2), pp.143~158 (2014), Springer Science and Business Media LLC[DOI]
  39. Joo, Y. J., "Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model", Journal of Educational Technology & Society, 21(3), pp.48~59 (2018)
  40. Jung, T., "An introduction to latent class growth analysis and growth mixture modeling", Social and Personality Psychology Compass, 2(1), pp.302~317 (2008)
  41. Yong Ju Jung, "Revisiting critical factors on teachers’ technology integration: the differences between elementary and secondary teachers", Asia Pacific Journal of Education, 39(4), pp.548~561 (2019), Informa UK Limited[DOI]
  42. Minseok Kang, "An Empirical Investigation of Student Acceptance of Synchronous E-Learning in an Online University", Journal of Educational Computing Research, 52(4), pp.475~495 (2015), SAGE Publications[DOI]
  43. Kavanagh, S., "A systematic review of virtual reality in education", Themes in Science and Technology Education, 10(2), pp.85~119 (2017)
  44. ChanMin Kim, "Teacher beliefs and technology integration", Teaching and Teacher Education, 29, pp.76~85 (2013), Elsevier BV[DOI]
  45. Yeong Gug Kim, "Consumer acceptance of a quick response (QR) code for the food traceability system: Application of an extended technology acceptance model (TAM)", Food Research International, 85, pp.266~272 (2016), Elsevier BV[DOI]
  46. Larsen, R., "Missing data imputation versus full information maximum likelihood with second-level dependencies", Structural Equation Modeling: A Multidisciplinary Journal, 18(4), pp.649~662 (2011)
  47. Kimberly A. Lawless, "Professional Development in Integrating Technology Into Teaching and Learning: Knowns, Unknowns, and Ways to Pursue Better Questions and Answers", Review of Educational Research, 77(4), pp.575~614 (2016), American Educational Research Association (AERA)[DOI]
  48. Li, L., "On inclusion of covariates for class enumeration of growth mixture models", Multivariate Behavioral Research, 46(2), pp.266~302 (2011)
  49. Min Liu, "Examining the Role of Professional Development in a Large School District's iPad Initiative", Journal of Research on Technology in Education, 50(1), pp.48~69 (2017), Informa UK Limited[DOI]
  50. Lo, Y., "Testing the number of components in a normal mixture", Biometrika, 88(3), pp.767~778 (2001)
  51. Lubke, G., "Performance of factor mixture models as a function of model size, covariate effects, and class󰠏specific parameters", Structural Equation Modeling, 14(1), pp.26~47 (2007)
  52. Abbey Lunney, "Wearable fitness technology: A structural investigation into acceptance and perceived fitness outcomes", Computers in Human Behavior, 65, pp.114~120 (2016), Elsevier BV[DOI]
  53. Magidson, J., "Latent class models for clustering : A comparison with K-means", Canadian Journal of Marketing Research, 20, pp.37~44 (2002)
  54. McLachlan, G., "Finite Mixture Models" (2000), Wiley
  55. Minshew, L., "Teacher self-efficacy in 1 : 1 iPad integration in middle school science and math classrooms", Contemporary Issues in Technology and Teacher Education, 15(3), pp.334~367 (2015)
  56. Mishra, P., "Technological pedagogical content knowledge : A framework for teacher knowledge", Teachers College Record, 108(6), pp.1017~1054 (2006)
  57. Muthén, B., "Beyond SEM : General latent variable modeling", Behaviormetrika, 29(1), pp.81~117 (2002)
  58. Muthén, B., "Latent variable analysis", The Sage handbook of quantitative methodology for the social sciences, 345(368), pp.106~109 (2004)
  59. Nguyen, V. T., "Creating Virtual Reality and Augmented Reality development in classroom: Is it a hype?", 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), pp.212~2125 (2019), IEEE
  60. Pan, S. C., "In-service teachers’ self-efficacy, professional development, and Web 2.0 tools for integration", New Horizons in Education, 59(3), pp.28~40 (2011)
  61. Papanastasiou, E. C., "Evaluating the use of ICT in education: Psychometric properties of the survey of factors affecting teachers teaching with technology (SFA-T 3)", Educational Technology and Society, 11(1), pp.69~86 (2008)
  62. Tiffani Pittman, "Technology integration in third, fourth and fifth grade classrooms in a Florida school district", Educational Technology Research and Development, 63(4), pp.539~554 (2015), Springer Science and Business Media LLC[DOI]
  63. Hamaad Rafique, "Investigating the Acceptance of Mobile Library Applications with an Extended Technology Acceptance Model (TAM)", Computers & Education, 145, pp.103732~ (2020), Elsevier BV[DOI]
  64. Ramaswamy, V., "An empirical pooling approach for estimating marketing mix elasticities with PIMS data", Marketing Science, 12(1), pp.103~124 (1993)
  65. Rogers, E. M., "Diffusion of Innovations" (2003), Free Press
  66. Ronny Scherer, "The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education", Computers & Education, 128, pp.13~35 (2019), Elsevier BV[DOI]
  67. Schwartz, G., "Estimating dimensions of a model", Annals of Statistics, 6, pp.461~464 (1978)
  68. Sclove, L., "Application of model-selection criteria to some problems in multivariate analysis", Psychometrika, 52, pp.333~343 (1987)
  69. 신원석, "ICT 활용 수업 이후 교사의 역할 변화에 영향을 미치는 요인 연구", 교육공학연구, 27(3), pp.625~652 (2011), 한국교육공학회
  70. Shin, W. S., "The use of a mobile learning management system at an online university and its effect on learning satisfaction and achievement", International Review of Research in Open and Distributed Learning, 16(3), pp.110~130 (2015)
  71. Lee S. Shulman, "Those Who Understand: Knowledge Growth in Teaching", Educational Researcher, 15(2), pp.4~14 (1986), American Educational Research Association (AERA)[DOI]
  72. Ali Tarhini, "Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: a structural equation modeling of an extended technology acceptance model", Interactive Learning Environments, 25(3), pp.306~328 (2016), Informa UK Limited[DOI]
  73. Timothy Teo, "A path analysis of pre-service teachers' attitudes to computer use: applying and extending the technology acceptance model in an educational context", Interactive Learning Environments, 18(1), pp.65~79 (2010), Informa UK Limited[DOI]
  74. Timothy Teo, "Factors influencing teachers’ intention to use technology: Model development and test", Computers & Education, 57(4), pp.2432~2440 (2011), Elsevier BV[DOI]
  75. Timothy Teo, "Modelling Facebook usage among university students in Thailand: the role of emotional attachment in an extended technology acceptance model", Interactive Learning Environments, 24(4), pp.745~757 (2014), Informa UK Limited[DOI]
  76. Teo, T., "Understanding pre-service teachers' computer attitudes: Applying and extending the technology acceptance model", Journal of Computer Assisted Learning, 24(2), pp.128~143 (2008)
  77. Jo Tondeur, "A comprehensive investigation of TPACK within pre-service teachers’ ICT profiles: Mind the gap!", Australasian Journal of Educational Technology, 33(3) (2017), Australasian Society for Computers in Learning in Tertiary Education[DOI]
  78. Malene Thisgaard, "Virtual Learning Simulations in High School: Effects on Cognitive and Non-cognitive Outcomes and Implications on the Development of STEM Academic and Career Choice", Frontiers in Psychology, 8, pp.1~13 (2017), Frontiers Media SA[DOI]
  79. Viswanath Venkatesh, "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies", Management Science, 46(2), pp.186~204 (2000), Institute for Operations Research and the Management Sciences (INFORMS)[DOI]
  80. Sandra L. Woolley, "Construct Validity of a Self-Report Measure of Teacher Beliefs Related to Constructivist and Traditional Approaches to Teaching and Learning", Educational and Psychological Measurement, 64(2), pp.319~331 (2016), SAGE Publications[DOI]

관련 논문AI추천

온라인매체 활용 교육과 가상⋅증강현실 활용 교육에 대한 교사의 TPACK 수준 비교고유정, 신원석한국교육방법학회 · 교육방법연구2020 · 제32권 제2호정보교사의 증강현실(Augmented Reality) 수용에 관한 선행요인 탐색: 기술준비도와 기술-교수내용 지식, 학교 지원, 지각된 유용성, 지각된 용이성을 중심으로박정민, 송지훈한국교육공학회 · 교육공학연구2024 · 제40권 제2호대학생의 VR 학습 수용 특성에 따른 잠재프로파일 분석권동진, 이상은한국교육공학회 · 교육공학연구2025 · 제41권 제4호교사의 디지털 기술 인식･활용 유형 및 예측요인 탐색 연구정설미, 정혜주한국교원교육학회 · 한국교원교육연구2024 · 제41권 제3호초등 과학 수업에서 가상현실과 증강현실 콘텐츠 활용을 위한 교사 교육 모델의 개발과 적용 사례가석현, 윤혜경, 차현정한국초등과학교육학회 · 초등과학교육2024 · 제43권 제3호실감기술(Reality Technology)에 대한 교사와 예비교사의 인식과 활용방안 연구박헌우한국생물교육학회 · 생물교육2023 · 제51권 제1호

이 간행물의 다른 논문 (4건)

교육용 3D 게임에 활용된 판타지 유형과 학습자들의 판타지경향성이 과학 학습과 학습 도구 사용에 미치는 효과이재진pp. 283-309대학의 미래 교육 혁신을 위한 ICT 융합 최신 기술의 교육적 활용 가능성 탐색임성태, 김은희pp. 311-3362018-2019 국가수준 초․중학생 디지털 리터러시 수준의 연도별 비교 분석이운지, 김수환, 김한성, 이현숙pp. 337-366학습자 대시보드의 사용성 평가: 상호작용 정보의 시각화에 대한 학습자 인식 탐색김혜준, 임규연, 김윤진, 최지수pp. 395-424
원문 보기