Empirical Dataset Supporting the Validation of the PEPCII Pedagogical Design Model in TPR-Mediated Higher Education

This dataset supports the study “Validation of the PEPCII Pedagogical Design Model via Telepresence Robot Use in Higher Education.” It contains anonymised raw qualitative data and structured analytical materials generated during the empirical validation of the PEPCII pedagogical design model in synchronous hybrid higher education contexts involving telepresence robot (TPR)–mediated participation. The dataset includes materials from three stakeholder groups:(1) teachers delivering courses with TPR-mediated participation,(2) students participating remotely via telepresence robots, and(3) students physically present in the classroom. Data collection methods comprised focus group interviews and written end-of-course responses. The repository contains: anonymised interview transcripts (focus groups and written responses), pseudonymised participant identifiers, coded thematic matrices aligned with the PEPCII model components, category-level aggregation tables used in the validation analysis. The analytical structure follows a reflexive thematic analysis approach and maps empirical findings to the validated components of the PEPCII model. The dataset reflects validation in authentic instructional settings corresponding to Technology Readiness Levels (TRL) 7–9, focusing on operational demonstration, stakeholder-based validation, and sustained pedagogical applicability in synchronous hybrid environments. All data have been anonymised in accordance with the Estonian Personal Data Protection Act (2019) and the General Data Protection Regulation (EU 2016/679). Direct identifiers have been removed, indirect identifiers minimised, and quotations pseudonymised. The dataset is made available for research and academic purposes. This dataset enables transparency of the validation process, replication of the thematic coding logic, and further investigation of telepresence robot–mediated hybrid learning and pedagogical design models. Users of the dataset are responsible for ensuring that secondary use complies with applicable data protection and ethical standards.