AI acceptance model; AI adoption; AI in education; mixed methods; secondary education; teachers; technology acceptance model; vignettes; Acceptance models; Artificial intelligence acceptance model; Artificial intelligence adoption; Artificial intelligence in education; Mixed method; Secondary education; Teachers'; Technology acceptance model; Theory and practice; Vignette; Artificial Intelligence; Computer Vision and Pattern Recognition; Human-Computer Interaction; Media Technology; Education
Abstract :
[en] This PhD project critically examines the integration of artificial intelligence (AI) in secondary education in Luxembourg from a unique psycho-socio-technological perspective, focusing on teacher acceptance and adoption. Through a carefully designed mixed-methods approach, the study initiates with qualitative interviews to capture the nuances of teachers' experiences and attitudes towards AI. These findings will guide a systematic literature review to assess the applicability of traditional technology acceptance models to AI in education. The project innovates with a 'mise en situation' approach, using vignettes in a subsequent quantitative survey to assess acceptance in realistic teaching and learning contexts. This methodology bridges the gap between theoretical constructs and practical application, offering significant contributions to academic and educational practice. By developing a nuanced model of AI acceptance, the research aims to inform policy-making, curriculum development and professional development strategies. The anticipated findings promise to advance the discourse on AI integration in education, highlighting the complex interplay of factors influencing teacher acceptance and facilitating more effective adoption of AI technologies in educational settings.
Disciplines :
Education & instruction
Author, co-author :
Hau, Daniela; Department of Education and Social Work, University of Luxembourg, Esch-Belval, Luxembourg
REUTER, Robert A.P. ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Education and Social Work (DESW) > Teaching and Learning
Drews, Olga Marmo; Department of System and Computer, Universidad de los Andes, Bogotá, Colombia
HOUSSEMAND, Claude ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Education and Social Work (DESW) > Lifelong Learning and Guidance
External co-authors :
yes
Language :
English
Title :
Bridging theory and practice: A comprehensive model for AI acceptance among secondary school teachers
Publication date :
2024
Event name :
2024 IEEE International Conference on Advanced Learning Technologies (ICALT)
Event place :
Hybrid, Nicosia, Cyp
Event date :
01-07-2024 => 04-07-2024
Audience :
International
Main work title :
Proceedings - 2024 IEEE International Conference on Advanced Learning Technologies, ICALT 2024
Editor :
Altinay, Zehra
Publisher :
Institute of Electrical and Electronics Engineers Inc.
H. Lin, "Influences of artificial intelligence in education on teaching effectiveness," in International Journal of Emerging Technologies in Learning (iJET), vol. 17, no. 24, pp. 144-156, 2022. https://doi.org/10.3991/ijet.vl7i24.36037
O. Zawacki-Richter, V. I. Marin, M. Bond, and F. Gouverneur, "Systematic review of research on artificial intelligence applications in higher education - where are the educators?," in International Journal of Educational Technology in Higher Education, vol. 16, no. 1, 2019. https://doi.org/10.1186/s41239-019-0171-0
Y. Miao, M. S. Jong, and Y. Dai, "Pedagogical design of k-12 artificial intelligence education: a systematic review," in Sustainability, vol. 14, no. 23, 15620, 2022. https://doi.org/10.3390/sul42315620
H. Zhang, I. Lee, S. Ali, D. DiPaola, Y. Cheng, and C. Breazeal, "Integrating ethics and career futures with technical learning to promote ai literacy for middle school students: an exploratory study," in International Journal of Artificial Intelligence in Education, vol. 33, no. 2, pp. 290-324, 2022. https://doi.org/10.1007/s40593-022-00293-3
S. Popenici and S. Kerr, "Exploring the impact of artificial intelligence on teaching and learning in higher education," in Research and Practice in Technology Enhanced Learning, vol. 12, no. 1, 2017. https://doi.org/10.1186/s41039-017-0062-8
T. K F. Chiu, H. Meng, C. S. Chai, I. King, S. W. Wong, and Y. Yam, "Creation and evaluation of a pretertiary artificial intelligence (ai) curriculum," in IEEE Transactions on Education, vol. 65, no. 1, pp. 30-39, 2022. https://doi.org/10.1109/TE.2021.3085878
S. Polak, G. Schiavo, and M. Zancanaro, "Teachers' perspective on artificial intelligence education: an initial investigation," CHI Conference on Human Factors in Computing Systems Extended Abstracts, 2022. https://doi.org/10.1145/3491101.3519866
S. Attuquayefio and H. Addo, "Using the UTAUT model to analyze students' ICT adoption," in International Journal of Education and Development using Information and Communication Technology, vol. 10, pp. 75-86,2014.
M. Radovan and N. Kristl, "Acceptance of technology and its impact on teacher's activities in virtual classroom: Integrating UTAUT and Col into a combined model," in Turkish Online Journal of Educational Technology, vol. 16, pp. 11-22, 2017.
R. Scherer and T. Teo, "Unpacking Teachers' Intentions to Integrate Technology: A Meta-Analysis," in Educational Research Review, vol. 27, 2019. https://doi.Org/10.1016/j.edurev.2019.03.001
M. Liu, Y. Wang, W. Xu, and L. Liu, "Automated Scoring of Chinese Engineering Students' English Essays," in Int. J. Distance Educ. Technol., vol. 15, pp. 52-68, 2017.
K. Sohn and O. Kwon, "Technology Acceptance Theories and Factors Influencing Artificial Intelligence-based Intelligent Products," in Telematics and Informatics, 2020. https://doi.Org/10.1016/j.tele.2020.101324
O. Gansser and C. Reich, "A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application," in Technology in Society, Elsevier, vol. 65(C), 2021. https://doi.Org/10.1016/j.techsoc.2021.101587
S. Doroudi, "The intertwined histories of artificial intelligence and education," in International Journal of Artificial Intelligence in Education, vol. 33, no. 4, pp. 885-928, 2022. https://doi.org/10.1007/s40593-022-00313-2
A. Tlili, B. Shehata, M. A. Adarkwah, A. Bozkurt, D. T. Hickey, R. Huang, and B. Agyemang, "What if the devil is my guardian angel: chatgpt as a case study of using chatbots in education," in Smart Learning Environments, vol. 10, no. 1, 2023. https://doi.org/10.1186/s40561-023-00237-x
I. Tuomi, "Artificial intelligence, 21st-century competences, and socioemotional learning in education: more than high-risk?," in European Journal of Education, vol. 57, no. 4, pp. 601-619, 2022. https://doi.org/10.1111/ejed.12531
C.S. Chai, X. Wang & C. Xu (2020). An extended theory of planned behavior for the modelling of chínese secondary school students' intention to learn artificial intelligence. Mathematics, 8(11), 2089. https://doi.org/10.3390/math8112089
T. Nazaretsky, M. Cukurova & G. Alexandron (2022). An instrument for measuring teachers' trust in ai-based educational technology. LAK22: 12th International Learning Analytics and Knowledge Conference. https://doi.org/10.1145/3506860.3506866
U. Kuckartz, Qualitative Inhaltsanalyse: Methoden, Praxis, Computerunterstützung.Weinheim: Beltz Juventa, 2012.
A. Majumdar, "Thematic analysis in qualitative research" in Advances in Business Information Systems and Analytics, pp. 197-220, 2019. https://doi.org/10.4018/978-l-5225-5366-3.ch009
C. Helfferich (2009). Die Qualität qualitativer Daten. https://doi.org/10.1007/978-3-531-91858-7
D. Moher, A. Liberati., J. Tetzlaff and D. G. Altman, "Preferred reporting items for systematic reviews and meta-analyses: the prisma statement", in International Journal of Surgery, 8(5), pp. 336-341, 2010. https://doi.Org/10.1016/j.ijsu.2010.02.007
A.C. Tricco, E. Lillie, W. Zarin, K.K O'Brien, H. Colquhoun, D. Levac, and S.E. Straus, "Prisma extension for scoping reviews (prisma-scr): checklist and explanation," in Annals of Internal Medicine, 169(7), pp. 467-473, 2018. https://doi.org/10.7326/ml8-0850
J. Finch, "The Vignette Technique in Survey Research," in Sociology, 21(1), pp. 105-114, 1987. https://doi.org/10.1177/0038038587021001008
K. Skilling, and G. J. Stylianides, "Using Vignettes in Educational Research: A Framework for Vignette Construction," in International journal of research & method in education, 43.5, pp. 541-556, 2020.