Zelma

What is Zelma?

Who created Zelma?

Zelma was created as an AI-powered research assistant specializing in U.S. school testing data. It was launched on December 7, 2023. Developed at Brown University, Zelma Education integrates data across state-, district-, and school- levels, disaggregated by subject, grade level, and student subgroups. The project received financial support from the Walton Family Foundation and collaboration from entities like ParentData and OpenAI. Zelma is designed to provide easy access to comprehensive educational data and promote data-driven decision-making in the education sector.

What is Zelma used for?

• Compare scores between different states and school districts
• Analyze testing score trends over time
• Discern patterns based on demographic identifiers like race/ethnicity
• Visualize data with graphs or tables
• Aid in data-driven decision-making
• Understand U.S. school testing data
• Support educational policy research
• Convert a question into data
• Beneficial tool for educational data analysis
• Trend analysis capabilities
• Discern patterns based on demographic identifiers like race or ethnicity
• Visualize data through graphs and tables
• Share insights on social media or embed results on web platforms
• Support data dissemination for educational purposes
• Convert questions into data-driven answers
• Field a wide variety of questions related to U.S school testing data
• Analyzing testing score trends over time
• Discerning patterns based on demographic identifiers like race/ethnicity
• Graphing science scores by grade level
• Identifying top-performing districts in specific subjects or states
• Comparing charter districts to non-charter districts in specific subjects or states
• Tracking ELA scores over time in various locations
• Comparing math scores by English language status
• Understanding variations in math scores by race/ethnicity
• Supporting educational policy research
• Aiding in data-driven decision-making
• Fielding questions related to U.S school testing data
• Understanding U.S school testing data
• Converting questions into data-driven answers
• Analyzing scores comparisons between states or districts
• Analyzing scores trends over time
• Discerning patterns based on demographic identifiers
• Visualizing data with graphs or tables
• Supporting data communication in the educational field

Who is Zelma for?

• Educators
• Policymakers
• Researchers
• Data Analysts

How to use Zelma?

To use Zelma, follow these steps:

1. Start by inputting plain English questions related to U.S. school testing data into Zelma's interface.
2. Zelma's AI-powered engine interprets and analyzes these queries to understand the context and data parameters.
3. The tool retrieves relevant data from its U.S. school testing dataset and processes it into data-driven insights.
4. Ask a wide range of educational data inquiries such as comparing scores between states and school districts, analyzing scores over time, and identifying patterns based on demographic identifiers like race and ethnicity.
5. Visualize the data with generated graphs or tables to organize and comprehend the statistical information effectively.
6. Zelma's user-friendly interface simplifies the process, allowing easy text input of questions and presenting answers in various forms like descriptions, tables, or graphs.
7. No advanced technical skills are needed to utilize Zelma as it converts plain English questions into easily understandable data-driven insights.
8. Share your insights through tweet links or embed results, graphs, and tables into blogs or websites to disseminate educational data effectively.
9. Utilize Zelma's data-sharing capabilities to promote wider discussion and data-driven dialogues among educators, policymakers, researchers, and the public.
10. Leverage Zelma for data-driven decision-making by exploring and understanding educational datasets, identifying trends, and making informed decisions based on precise insights.

Zelma is a beneficial tool for educational data analysis, supporting policy research, trend analysis, data communication, and fostering a better understanding of U.S. school testing data .