What question did this study set out to answer?

The research aims to explore the dynamics between instructors and students during extended VR use in neuroanatomy instruction, using relevant educational frameworks.

February 26, 2026Open Access

Understanding extended VR use in undergraduate STEM education: a focused ethnographic case study of neuroanatomy instruction

Key Points

The research aims to explore the dynamics between instructors and students during extended VR use in neuroanatomy instruction, using relevant educational frameworks.
Conducted focused ethnographic case study at a public university in California over a semester.
Collected data through seven classroom observations, a semi-structured instructor interview, and a student focus group.
Analyzed data using TPACK and EVT frameworks with coding and triangulation for reliability.
Instructor showed strong technological content knowledge but weak technological pedagogical knowledge, leading to implementation gaps.
Student experiences indicated low expectations and unclear perceived value of VR, overshadowing its intrinsic benefits.
Discrepancies between what instructors assumed about VR and students' values created ongoing friction throughout the semester.

Abstract

Background While virtual reality (VR) shows promise for enhancing STEM education, most research relies on short interventions with pre- and post-designs, limiting the understanding of how classroom integration of VR unfolds across extended instructional periods and excluding instructor behavior and perspectives from analysis. Objective This study examines instructor and student dynamics during semester-long VR integration in an undergraduate neuroanatomy lab instruction, applying the Technological Pedagogical Content Knowledge (TPACK) framework to analyze instructor knowledge profiles and the Expectancy-Value Theory (EVT) to examine student motivational responses. Methods A focused ethnographic case study was conducted at a public university in California during the Spring 2024 semester. Data included seven classroom observations across 16 weeks, a 60-min semi-structured instructor interview, and a 45-min student focus group (n = 6). Analysis employed theoretically grounded coding with TPACK and EVT constructs, triangulation across data sources, and inter-coder reliability procedures. Results Three key findings emerged: (1) The instructor’s TPACK profile revealed strong Technological Content Knowledge (TCK), i.e., understanding VR’s potential for neuroanatomical visualization, but underdeveloped Technological Pedagogical Knowledge (TPK), which created implementation gaps; (2) Student experiences reflected EVT dynamics where low expectancy beliefs, unclear utility value perceptions, and elevated cost of VR overshadowed intrinsic value; (3) Misalignment between instructor TPACK assumptions and student EVT profiles generated friction and discrepancy that both parties recognized but could not fully resolve during the semester. Conclusion This study demonstrates that effective VR integration requires alignment between the instructor’s knowledge, especially technological pedagogical knowledge, and the student’s motivational dynamics. A TPACK-EVT integration framework is proposed to connect instructor knowledge to student motivation, offering a theoretical contribution to VR education research and practical implications for faculty development.

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