West Chester University · UTAUT acceptance study

Measuring Undergraduate Nursing Students’ Acceptance of AI-Enabled Virtual Reality

Baccalaureate nursing students completed AI-generated virtual reality simulations, then rated their acceptance of the technology on the UTAUT instrument. Acceptance was above neutral overall, but not evenly: how easy the technology felt to use scored well clear of the midpoint, while social encouragement to use it did not.

19respondents
18UTAUT items
4constructs
1–5response scale

What was measured

UTAUT, the Unified Theory of Acceptance and Use of Technology, asks about four separate reasons a person might take up a technology. The eighteen items divide between them, and each is rated from 1, strongly disagree, to 5, strongly agree.

The four constructs, and what each one asks about.
ConstructItemsWhat it captures
PE Performance ExpectancyQ1–Q6Whether the technology helps you do the task better
SI Social InfluenceQ7–Q10Whether people who matter to you encourage it
EE Effort ExpectancyQ11–Q15Whether it feels easy to learn and use
FC Facilitating ConditionsQ16–Q18Whether support is there when something goes wrong

What was found

Each construct was compared against the scale midpoint of 3, the point at which a respondent neither agrees nor disagrees. Three of the four sit above it. One does not.

Acceptance by UTAUT construct Mean score with 95% confidence interval. The dashed line is the scale midpoint (3). 2.5 3 neutral 3.5 4 Performance Expectancy 3.43 Social Influence 3.08 Effort Expectancy 3.74 Facilitating Conditions 3.44 Mean response (1 to 5 scale)
Figure 1. Mean score per construct, with 95% confidence intervals.

Effort Expectancy is the clear result. At 3.74, with an interval of 3.45 to 4.03 and d = 1.23, students found the technology easy to use, and the interval is nowhere near the midpoint. Social Influence is the clear non-result. At 3.08, interval 2.62 to 3.54, p = .7215, it is indistinguishable from neutral: students did not report that people around them encouraged VR for learning. Performance Expectancy (3.43) and Facilitating Conditions (3.44) sit modestly above the midpoint.

With 19 respondents every interval is wide, and the gap between "above neutral" and "not above neutral" is narrower than it looks. Read the intervals, not the ranking.

Where to go next

The analysis

Every construct and item, with intervals, effect sizes, reliability and the assumption checks.

Live

The code

The SAS program, and a Colab notebook that reproduces the analysis in Python.

Live

The paper

Citation and DOI for the published article.

Live

Repository

The analysis code and the rebuild pipeline.

Open