Influence of onboarding length on PCS, TLX, UEQ and CAP

This dataset accompanies the empirical study titled "Closing the experience gap: Onboarding duration as an equaliser in VR-assisted learning". It contains anonymised experimental data collected from 45 university students enrolled in hydrology courses to assess the impact of pre-experimental virtual reality (VR) onboarding duration on the overall user experience and perceived learning outcomes. The primary objective of the study was to explore whether increased familiarisation time with VR mechanics could reduce extraneous cognitive load, thus negating the bias caused by participants' lack of prior VR experience. Participants were randomly assigned to a "Short" (5 minutes) or "Long" (up to 20 minutes) onboarding session using Google Earth VR. Following onboarding, participants completed a custom Unreal Engine VR learning application focused on flood-water management. The dataset includes self-reported background metrics, completion times, and responses to four standardized questionnaires evaluating competence, cognitive load, user experience, and perceived learning. Methodology & Study Design: Design: A 2×2 between-subjects experimental design. Factor 1 (Onboarding Duration): Short (5 min) vs. Long (5–20 min). Factor 2 (Institution): Mendel University in Brno (MENDELU, Czechia) vs. Turku University of Applied Sciences (TUAS, Finland). Participants: 45 adult university students across the two universities (MENDELU and TUAS), with cell sizes ranging from 10 to 14 participants per group. Apparatus: Google Earth VR (for onboarding familiarisation) and a custom VR application simulating water channel profiles and flood stages (for the learning task). Data Structure and Variables: The dataset includes the following key variables and instruments: Participant Background / Demographics: Self-reported prior VR experience. Self-reported gaming experience. Prior hydrology background knowledge. Time Measurements: Onboarding Time: Exact time (in minutes) spent in the Google Earth VR training application. Learning App Time: Exact time (in minutes) spent completing tasks within the flood-water management VR environment. Standardised Questionnaires: Perceived Competence Scale (PCS): Administered immediately after onboarding to gauge participants' subjective confidence in using VR before the learning task. NASA Task Load Index (NASA-TLX): Used to assess subjective mental workload across six dimensions (mental demand, physical demand, temporal demand, performance, effort, and frustration) using a raw seven-point Likert-like scale. User Experience Questionnaire (UEQ): Measured across 26 semantically differentiated items (on a seven-point scale) to evaluate factors such as Attractiveness, Perspicuity, Efficiency, Dependability, Stimulation, and Novelty. Cognitive, Affective, Psychomotor test (CAP): A self-reported questionnaire assessing the participants' perceived ability to apply course-related knowledge (evaluated on a six-point Likert-like scale). Ethics and Privacy: The study was non-interventional and posed minimal risk. All participants provided written informed consent prior to participating. The dataset is fully anonymised; no directly identifying data (such as names or contact information) were retained. The research was conducted in accordance with the principles of the Declaration of Helsinki. AI use: The authors used Large Language Models (Gemini and Claude) to assist in the processing the data using Python scripts. The authors critically reviewed and verified all results to ensure accuracy and technical integrity. The authors remain responsible for the final published content. Funding Acknowledgements: Data collection and analysis were supported by the project CZ.02.1.01/0.0/0.0/16_017/0002334 (Research Infrastructure for Young Scientists, co-financed by the Operational Programme Research, Development and Education) and grant No. IGA24-PEF-TP-003 (Using metaverse technologies for working with spatial data) from the Internal Grant Agency FBE MENDELU.