RPPL builds tools alongside our research — and we share them. Below are open-source resources you can use to analyze implementation data, protect sensitive information, and study coaching practice. Explore each tool, access the code, and reach out with questions.
1) RPPL Insights is a web-based application that helps PL providers explore and analyze their HQIM and CBPL implementation. This current version offers an early preview of Insights’ capabilities using data from Version 1 of the ELA Shared Measures Toolkit.
- Use it to gather and reflect on shared measures data. You can use Insights to explore trends, generate visualizations, and support internal learning. An updated version aligned with the new Shared Measures Toolkit will launch early next year.
2) RPPL Redact is a toolkit that enables the secure de-identification of qualitative data (e.g., PL artifacts, coaching transcripts, classroom recording transcripts) leveraging locally hosted large language models (LLMs).
- Use it to remove personally identifiable information from transcripts or other sensitive files before sharing them for research, analysis, or collaboration. Whenever your organization needs to prepare materials that include student or educator data, use Redact to do so safely.
3) RPPL AI-enabled Coaching Moves Classifier is a tool that can analyze patterns in the moves coaches use from transcripts of coaching conversations, based on RPPL’s Coaching Moves Framework.
All required code is available on GitHub. Executing this code requires a foundational understanding of Python and access to high-performance computing power. RPPL research staff are currently working to create a more user-friendly version of the tool for less-technical audiences.
Use it to surface which coaching moves from the Framework show up in raw coaching-conversation transcripts.
Collaborators
Hannah Carter
Heather Hill
Maciej Pankiewicz
Zhanlan Wei
