Real-Time Pedagogical Decision-Making of Simulation Specialists in Mixed Reality Teacher Education
Keywords:
mixed reality simulation, simulation specialists, real-time pedagogical decisions, pedagogical content knowledge, pre-service teacher education.Abstract
Pre-service teachers generally lack the skills, confidence, and professional judgement required to navigate the complexities of classroom practice (Loughran, 2019). This study examines how simulation specialists make real-time pedagogical decisions during Mixed Reality Simulation (MRS) sessions and how these decisions shape pre-service teachers’ pedagogical content knowledge (PCK) development. Guided by the Teacher Thoughts and Action Processes (TTAP) model and the Theory of Planned Behaviour (TPB), the study adopts a qualitative design involving eleven Simulation specialists. Data were generated through live observations of simulation sessions, stimulated recall interviews and focus group discussions. Thematic analysis revealed that simulation specialists’ real-time decisions are driven by four primary factors: (1) observable gaps in pre-service teachers’ PCK, particularly in content representation and instructional strategies; (2) minimal learner engagement within the simulation; (3) emerging classroom management difficulties; and (4) misalignment between instructional resources and lesson objectives. Specialists responded to these cues through immediate pedagogical adjustments, including scaffolding questioning techniques, redirecting instructional focus and modifying the level of challenge presented in the simulation. This study contributes to the field by providing empirically grounded insight into how simulation specialists interpret and respond to dynamic classroom interactions in real-time. These findings highlight the importance of targeted professional development that strengthens simulation specialists’ diagnostic and responsive decision-making to better support PCK development in simulation-based teacher education.
https://doi.org/10.26803/ijlter.25.9.36
References
Aguayo, C., & Eames, C. (2023). Using mixed reality (XR) immersive learning to enhance environmental education. The Journal of Environmental Education, 54(1), 58-71. https://doi.org/10.1080/00958964.2022.2152410
Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review 2of empirical research. Psychological bulletin, 84(5), 888. https://doi.org/10.1037/0033-2909.84.5.888
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control: From cognition to behavior (pp. 11-39). Springer.
Ajzen, I. (2020). The theory of planned behaviour: Frequently asked questions. Human behavior and emerging technologies, 2(4), 314-324. https://doi.org/10.1002/hbe2.195
Bautista, N. U., & Boone, W. J. (2015). Exploring the impact of TeachME™ lab virtual classroom teaching simulation on early childhood education majors’ self-efficacy beliefs. Journal of Science Teacher Education, 26(3), 237-262. https://doi.org/10.1007/s10972-014-9418-8
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative research in psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Cameron, R., Ginsburg, H., Westhoff, M., & Mendez, R. V. (2012). Ajzen’s theory of planned behavior and social media use by college students. American Journal of Psychological Research, 8(1), 1-20.
Creswell, J. W., Hanson, W. E., Clark Plano, V. L., & Morales, A. (2007). Qualitative research designs: Selection and implementation. The counseling psychologist, 35(2), 236-264. https://doi.org/10.1177/0011000006287390
Dalinger, T., Thomas, K. B., Stansberry, S., & Xiu, Y. (2020). A mixed reality simulation offers strategic practice for pre-service teachers. Computers & education, 144, 103696. https://doi.org/10.1016/j.compedu.2019.103696
Davis, A., Griffith, R., & Bauml, M. (2019). How preservice teachers use student knowledge for planning and in-the-moment teaching decisions during guided reading. Journal of Early Childhood Teacher Education, 40(2), 138-158. https://doi.org/10.1080/10901027.2018.1534161
Dawson, M. R., & Lignugaris Kraft, B. (2017). Meaningful practice: Generalizing foundation teaching skills fromTLE TeachLivE™ to the classroom. Teacher Education and Special Education, 40(1), 26–50. https://doi.org/10.1177/0888406416664184
Dempsey, N. P. (2010). Stimulated recall interviews in ethnography. Qualitative Sociology, 33, 349-367. https://doi.org/ 10.1007/s11133-010-9157-x
En Brok, P. (2001). Teaching and student outcomes. A study on teachers’ thoughts and actions from an interpersonal and a learning activities perspective. Utrecht: W.C.C
Deuchar, S., & Nodder, C. (2003). The impact of avatars and 3D virtual world creation on learning. The Proceedings of the 16th Annual NACCQ Conference. Palmerston North,
Dieker, L. A., Rodriguez, J. A., Lignugaris-Kraft, B., Hynes, M. C., & Hughes, C. E. (2014). The potential of simulated environments in teacher education: Current and future possibilities. Teacher Education and Special Education, 37(1), 21-33. https://10.1177/0888406413512683
Eggleston, J. (2018). Teacher decision-making in the classroom: A collection of papers. Routledge.
Ferguson, S. (2023). Developing and Implementing a Mixed-Reality Teaching Simulation to be Used with Preservice STEM Teachers. Journal of Educators Online, 20(4), n4.
Flick, U. (2018). Doing qualitative data collection–charting the routes. The SAGE handbook of qualitative data collection, 1-16. https://doi.org/10.4135/9781526416070.n1
Freeman, I. M., Lee, H., & Barsh, R. (2024). The Effect of Implementing Mixed-Reality Simulation (MRS) in an Educator Preparation Program. Journal of Educational Technology Systems, 53(2), 67-88. https://doi.org/10.1177/00472395241262731
Gravett, S., Van der Merwe, D., Ramsaroop, S., Tshabalala, P., Bremner, C., & Mello, P. (2023). Mixed-Reality Simulation to Support Practice Learning of Preservice Teachers. Education Sciences, 13(10), 1062. https://doi.org/10.3390/educsci13101062
Griffith, R. (2017). Undertaking research on people who lack decision-making capacity. British Journal of Community Nursing, 22(10), 511-513. https://doi.org/10.12968/bjcn.2017.22.10.511
Griffith, R., Bauml, M., & Barksdale, B. (2015). In-the-moment teaching decisions in primary grade reading: The role of context and teacher knowledge. Journal of Research in Childhood Education, 29(4), 444-457. https://doi.org/10.1080/02568543.2015.1073202
Hudson, M. E., Voytecki, K. S., Owens, T. L., & Zhang, G. (2019). Preservice teacher experiences implementing classroom management practices through mixed-reality simulations. Rural Special Education Quarterly, 38(2), 79-94. https://doi.org/10.1177/8756870519841421
Ireland, A. L. (2021). Mixed reality simulation in teacher preparation programs in the United States. University of California, Los Angeles.
Jasien, L., & Amick, L. (2022). Functional Concerns That Shape Teachers' In-the-Moment Decision-Making. North American Chapter of the International Group for the Psychology of Mathematics Education.
Kamhi-Stein, L. D., Lao, R. S., & Issagholian, N. (2020). The Future Is Now: Implementing Mixed-Reality Learning Environments as a Tool for Language Teacher Preparation. TESL-EJ, 24(3), 1-18.
Ke, F., & Xu, X. (2020). Virtual reality simulation?based learning of teaching with alternative perspectives taking. British Journal of Educational Technology, 51(6), 2544-2557. https://doi.org/10.1111/bjet.12936
Kelley, M. H., Qualls, L. W., Scott, S. N., & Hirsch, S. E. (2025). Mixed-reality simulation to prepare preservice teachers to use culturally responsive teaching strategies: A pilot study. Journal of Special Education Technology, 40(1), 65-78. https://doi.org/10.1177/01626434241262238
Kooloos, C., Oolbekkink-Marchand, H., van Boven, S., Kaenders, R., & Heckman, G. (2022a). Building on student mathematical thinking in whole-class discourse: exploring teachers’ in-the-moment decision-making, interpretation, and underlying conceptions. Journal of Mathematics Teacher Education, 25(4), 453-477. https://doi.org/10.1007/s10857-021-09499-z
Kooloos, C., Oolbekkink-Marchand, H., van Boven, S., Kaenders, R., & Heckman, G. (2022b). Making sense of student mathematical thinking: the role of teacher mathematical thinking. Educational Studies in Mathematics, 110(3), 503-524. https://doi.org/ 10.1007/s10649-021-10124-2
Kourti, S. K., & Potari, D. (2024). Teacher emotions and real-time decisions in the secondary mathematics classroom. The Journal of Mathematical Behavior, 74, 101152. https://doi.org/10.1016/j.jmathb.2024.101152
Larson, K. E., Hirsch, S. E., McGraw, J. P., & Bradshaw, C. P. (2020). Preparing preservice teachers to manage behavior problems in the classroom: The feasibility and acceptability of using a mixed-reality simulator. Journal of Special Education Technology, 35(2), 63-75. https://doi.org/10.1016/j.compedu.2016.01.001
Lindgren, R., Tscholl, M., Wang, S., & Johnson, E. (2016). Enhancing learning and engagement through embodied interaction within a mixed reality simulation. Computers & education, 95, 174-187. https://doi.org/10.1016/j.compedu.2016.01.001
Loughran, J. (2019). Pedagogical reasoning: The foundation of the professional knowledge of teaching. Teachers and Teaching, 25(5), 523-535. https://doi.org/10.1080/13540602.2019.1633294
Magnone, K. Q., & Yezierski, E. J. (2024). Beyond convenience: A case and method for purposive sampling in chemistry teacher professional development research. Journal of Chemical Education, 101(3), 718-726.https://doi.org/ 10.1021/acs.jchemed.3c00217
Maguire, K. R. (2023). Pre-service teachers’ reflections on content knowledge through microteaching. Reflective Practice, 24(2), 153-167. https://doi.org/10.1080/14623943.2022.2146082
McPherson, R., Tyler-Wood, T., Ellison, A. M., & Peak, P. (2011). Using a computerized classroom simulation to prepare pre-service teachers. Journal of Technology and Teacher Education, 19(1), 93-110.
Mendelson, E. J. (2022). Pre-Service Teachers’ Perceptions of an Affective, Formative, and Data-Driven Feedback Intervention in Response to Mixed-Reality Simulations. (Doctoral dissertation, Western Connecticut State University).
Mohebi, L. (2021). Theoretical models of integration of interactive learning technologies into teaching: A systematic literature review. International Journal of Learning, Teaching and Educational Research, 20(12), 232-254. https://doi.org/10.26803/ijlter.20.12.14
Morelli, M., Casagrande, M., & Forte, G. (2022). Decision making: A theoretical review. Integrative Psychological and Behavioral Science, 56(3), 609-629. https://doi.org/10.1007/s12124-021-09669-x
Mursion, Inc. (2019b). Virtual reality simulations for elevating educator performance. https://scheduling.mursion.com/download/14017-education-brochure-r2.pdf
Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International journal of qualitative methods, 16(1), 1609406917733847. https://doi.org/10.1177/1609406917733847
Nygren, T., Samuelsson, M., Hansson, P. O., Efimova, E., & Bachelder, S. (2024). Potentials and Challenges of AI-Generated Feedback in Mixed Reality Simulations about Controversial Issues: A Human versus Artificial Expertise Comparison. https://doi.org/10.31219/osf.io/m49dr
Nzuza, S. T. (2025). Preparing Pre-Service Teachers for Equitable Technology-Enhanced Learning (TEL) in Diverse Classroom Settings. In Empowering Pre-Service Teachers to Enhance Inclusive Education Through Technology (pp. 127-154). IGI Global Scientific Publishing.
Peterson, P. L., & Clark, C. M. (1978). Teachers’ reports of their cognitive processes during teaching. American Educational Research Journal, 15(4), 555-565. https://doi.org/10.3102/0002831201500455
Peterson, A. J., & Clark, A. W. (1986). Using group decision to reduce adolescent girls' smoking. Psychological Reports, 58(1), 179-185. https://doi.org/10.2466/pr0.1986.58.1.179
Peterson, R. A. (2005). Problems in comparative research: The example of omnivorousness. poetics, 33(5-6), 257-282. https://doi.org/10.1016/j.poetic.2005.10.002
Rokhsaritalemi, S., Sadeghi-Niaraki, A., & Choi, S.-M. (2020). A review on mixed reality: Current trends, challenges and prospects. Applied Sciences, 10(2), 636. https://doi.org/10.3390/app10020636
Rosati-Peterson, G. L., Piro, J. S., Straub, C., & O’Callaghan, C. (2021). A nonverbal immediacy treatment with pre-service teachers using mixed reality simulations. Cogent Education, 8(1), 1882114. https://doi.org/10.1080/2331186X.2021.1882114
Skae, V. A., Brown, B. J., & Wilmot, P. D. (2020). Teachers' engagement with students in inclusive foundation phase classrooms. South African Journal of Childhood Education, 10(1), 1-11. https://doi.org/10.4102/sajce.v10i1.873
Soeharto, S., & Csapó, B. (2022). Exploring Indonesian student misconceptions in science concepts. Heliyon, 8(9). https://doi.org/10.1016/j.heliyon.2022.e10720
Solheim, K., Ertesvåg, S. K., & Dalhaug Berg, G. (2018). How teachers can improve their classroom interaction with students: New findings from teachers themselves. Journal of Educational Change, 19(4), 511-538.https://doi.org/ 10.1007/s10833-018-9333-4
Sullamo, A. E., Mekonnen, E. A., & Mihirete, D. M. (2023). Teacher Educators' Views Vis-à-Vis Their Practices on Facilitating Learning to Teach. Pedagogical Research, 8(4). https://doi.org/10.29333/pr/13477
Trabelsi, Z., Alnajjar, F., Parambil, M. M. A., Gochoo, M., & Ali, L. (2023). Real-time attention monitoring system for classroom: A deep learning approach for student’s behavior recognition. Big Data and Cognitive Computing, 7(1), 48. https://doi.org/10.3390/bdcc7010048
Wernick, A. M. (2023). Exploring The Use of Mixed-Reality Simulations As a Tool In Teacher Training To Support Language for Academic Purposes.
Wilhelmsson, B. (2012). Teachers' intention for outdoor education: conceptualizing learning in different domains (Doctoral dissertation, Umeå universitet).
Yin, R. K. (2009). Case study research: Design and methods (Vol. 5). SAGE
Zhang, Z., Zhang, S., Wu, R., Zuo, W., Timofte, R., Xing, X., ... & Wu, P. (2024). NTIRE 2024 challenge on bracketing image restoration and enhancement: Datasets methods and results. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 6153-6166).
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Patrick Thabo Makhubalo, Jacqueline Batchelor, Nadine Petersen
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All articles published by IJLTER are licensed under a Creative Commons Attribution Non-Commercial No-Derivatives 4.0 International License (CCBY-NC-ND4.0).
