Teacher Candidates' Perceptions of Mixed Reality Simulations: Data and Analysis Filess

Principal Investigator(s):  View help for Principal Investigator(s) Kristyn Wilson, University of Virginia; Julie Cohen, University of Virginia; Steffen Erickson, University of Virginia

Version:  View help for Version V1

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Open_ICPSR.zip application/zip 41.4 KB 08/18/2025 05:43:AM

Project Citation: 

Wilson, Kristyn, Cohen, Julie, and Erickson, Steffen. Teacher Candidates’ Perceptions of Mixed Reality Simulations: Data and Analysis Filess. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-08-18. https://doi.org/10.3886/E237281V1

Project Description

Summary:  View help for Summary The data presented here includes 192 teacher candidates' responses to an online post-simulation survey. Each participant completed the survey immediately following the conclusion of a simulation session. The survey consisted of eight Likert questions that asked about candidates’ perceptions of the simulator, including their preparation, willingness to do it again or recommend it to a friend, and its relevance and utility. For each question, participants rated their response on a scale of one (strongly disagree) to five (strongly agree). Similar surveys have been used in prior research on candidates’ experiences of simulations (e.g., Bondie et al., 2023; Larson et al., 2020). We examined the scale’s validity for use for our sample and purpose of understanding experiences during simulated practice. Confirmatory factor analysis (CFA) models (Brown, 2015) were fitted using the questions on the survey (see Appendix Table C1 for additional details on the CFA models). Given the poor model fit and measurement invariance over tasks and years, we do not present a composite experience score. Instead, we completed the subsequent analyses on item-level responses. 

To understand participants’ perceptions of simulations across the full sample, we began by analyzing descriptive statistics for each item. Next, to tease out the influence of simulation features on candidates’ perceptions, we use a candidate random effects estimator to compare survey responses across different simulation conditions. The estimation strategy leverages variation in the features of simulation sessions within candidates and across cohorts to estimate the influence of task, support, and mode of delivery on candidates’ survey responses.
Funding Sources:  View help for Funding Sources Institute of Education Sciences, U.S. Department of Education (R305B140026); Institute of Education Sciences, U.S. Department of Education (R305D190043); National Academy of Education/Spencer Foundation (Post-doctoral fellowship); Jefferson Trust (DR02951); Bankard Fund (ER00562)

Scope of Project

Subject Terms:  View help for Subject Terms survey; teacher preparation; simulation; teacher learning; practice-based teacher preparation
Geographic Coverage:  View help for Geographic Coverage Southeastern United States
Time Period(s):  View help for Time Period(s) 2018 – 2020
Collection Date(s):  View help for Collection Date(s) 2018 – 2020
Universe:  View help for Universe Teacher candidates in a traditional graduate teacher preparation program in a Southern state in the United States
Data Type(s):  View help for Data Type(s) survey data
Collection Notes:  View help for Collection Notes
  1. The study includes data from a researcher created survey of teacher candidates' perceptions of mixed reality simulations. Similar surveys have been used in prior research of candidates perceptions of simulations.
  2. Data was collected using a Qualtrics form, which candidates completed immediately upon conclusion of a simulation session. 
  3. Data was collected for two cohorts of teacher candidates in a graduate teacher preparation program. Participants consented to have their data included in this study, but completion of simulations and surveys was a programmatic requirement. The first cohort completed simulations and post-simulation surveys in Fall 2018 and Spring 2019. The second cohort completed simulations and post-simulation surveys in Fall 2019 and Spring 2020.

Methodology

Data Source:  View help for Data Source Researcher created survey
Collection Mode(s):  View help for Collection Mode(s) web-based survey
Scales:  View help for Scales A Likert-type scale was used.
Unit(s) of Observation:  View help for Unit(s) of Observation Simulation session
Geographic Unit:  View help for Geographic Unit Region

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V1 [2025-08-18]

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