Ren Ce's dataset contains anonymized data from a three-round Delphi study to develop a framework for flipped lesson design in physical education. The data includes consolidated first-round responses, second-round item ratings, third-round priority rankings, and consensus statistics like Kendall’s coefficient of concordance. It was used to create the European Framework for Transformative Flipped Physical Education (EU-TFPE) and was last updated on June 5, 2026.
Use Cases
- Analyzing expert consensus on teacher competencies based on the three-round Delphi process.
- Training models to identify key dimensions for educational frameworks based on the Knowledge, Skills, and Attitudes and Values data.
- Studying methodological approaches for consensus-building in education based on the provided consensus statistics.
- Developing tools for teacher training in flipped learning based on the expert-informed framework items.
Strengths
- Data is structured around a three-round Delphi process, providing multiple stages of expert input.
- Includes consensus statistics such as Kendall’s coefficient of concordance for methodological rigor.
- Anonymized to protect participant identities, with experts represented by coded identifiers only.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Geographic coverage is limited to European experts, which may affect generalizability.
Provenance
- Source
- Harvard Dataverse, authored by Ren Ce.
- Collection Method
- Collected through a three-round Delphi process with a panel of European experts.
- Time Range
- null
- Freshness
- Last updated 2026-06-05 19:36:25; freshness should be verified.
- Geography
- European experts.