Dear fellow educators and researchers, 

K-12 STEM teachers are now eager to empower their students with AI tools for data analysis and scientific inquiry (SI), while also fostering data and AI literacy. To address this, we have developed an accessible tool for teachers to apply machine learning (ML) to analyze subject-related data (e.g., a dataset of field sites from different ecosystems) and create ML-supported scientific inquiry (SI) activities using data visualizations. We invite teachers to use the tool and share feedback to enhance its design.

Compensation: $75/hour will be compensated for your participation.

How to Participate: If you are a middle- or high-school STEM and are interested in trying out the tool and providing feedback via Zoom, please take five minutes to fill out this form https://forms.gle/NdMqE1vzYF2318CaA. A researcher will reach out shortly to schedule a time for the study. There is no requirement for prior experience in CS or AI.

Any Questions or concerns? Feel free to reach out to Xiaofei Zhou at xxxxxx@ur.rochester.edu or Dr. Zhen Bai at xxxxxx@rochester.edu. More Details can be found below:
  • Call for Participation: We are looking for middle-school and high-school STEM teachers to participate in an online study to try out the system and provide us feedback for future improvements. There is no requirement for prior experience in CS or AI.
  • Research Team: This study is conducted by Dr. Zhen Bai (PI) and Ms. Xiaofei Zhou (PhD candidate) at the Department of Computer Science, University of Rochester, and Dr. Michael Daley (Co-PI), at the Warner School of Education, University of Rochester.
  • Overview: There will be 3 sessions in total. Each session will last for 1-1.5 hours. You will first learn how to use the tool and then participate in designing ML-supported scientific inquiry learning activities for your chosen subject, in collaboration with a data science expert.
  • Setting: Remote via Zoom.
  • Ideal day spread: 3 sessions in 5 days (1-1.5 hr daily) 
  • Total time: 3-4.5 hours
  • Dates: Jun 17 - July 3, July 15 - Aug 4
  • Funding Information: This work is supported by the National Science Foundation (RETTL program award No. 2225227).

Best regards, 
Xiaoefei Zhou
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Computer Science, University of Rochester