AI and VR Integration for Communication and Problem-Solving in Higher Education (Behavioral Dataset)

This OSF project hosts the de-identified quantitative dataset and accompanying documentation for a clustered quasi-experimental study on the integration of artificial intelligence (AI)–driven formative feedback and virtual reality (VR) simulations into undergraduate courses at a private university in Mexico (academic year 2024–2025).

The dataset links the multi-level experimental structure of the study (time points nested within students, and students nested within classes) with detailed session-level “dose” indicators of AI and VR exposure (minutes of use, number of feedback events, number of completed scenarios and perceived presence). These exposure measures are connected to performance-based outcomes for two transversal competencies—oral communication and problem-solving—scored with analytic rubrics, as well as to short Likert-type scales that assess presence, perceived usefulness of feedback and self-efficacy.

The repository includes raw-like CSV files close to the original capture structure, processed analytic files ready for multilevel models and ANCOVA-style analyses, a machine-readable codebook, scoring guides for rubrics and scales, fidelity and safety checklists, and example scripts illustrating how to reproduce the main analyses.

The data are shared for non-commercial research and teaching purposes under a CC BY-NC 4.0 license and are intended to support reanalysis, methodological replication, cross-study comparisons and teaching activities in statistics, econometrics and research methods.