Qualitative Methods

Beyond the Hype: How We Built AI Tools That Actually Support Learning

November 12, 2025
by Weiying Li. What does genuine partnership look like when building AI for education? Working with middle school teachers and computer scientists, we co-designed AI dialogs where teachers are valuable contributors to refine what the AI understands as valuable thinking. Through iterative refinement, teachers identified precursor ideas and observations that predicted future learning, and refined guidance design in the dialog. Our AI dialog sees learning the way teachers do, built through genuine collaboration where both model development, learning sciences theories, and teachers' classroom expertise work together from the start, not just at the end.

Umesh Singla

Consulting Drop-In Hours: By appointment only

Consulting Areas: Bash or Command Line, Bayesian Methods, Causal Inference, Data Visualization, Deep Learning, Diversity in Data, Git or GitHub, Hierarchical Models, High Dimensional Statistics, Machine Learning, Nonparametric Methods, Python, Qualitative Methods, Regression Analysis, Research Design

Quick-tip: the fastest way to speak to a consultant is to first ...

Yaxuan Huang

Consulting Drop-In Hours: By appointment only

Consulting Areas: Causal Inference, Git or GitHub, LaTeX, Machine Learning, Python, Qualitative Methods, R, Regression Analysis, RStudio

Quick-tip: the fastest way to speak to a consultant is to first submit a request and then ...

Sharazad Ali

Consulting Drop-In Hours: By appointment only

Consulting Areas: Cluster Analysis, Databases and SQL, Data Visualization, Diversity in Data, Excel, Experimental Design, Focus Groups and Interviews, Machine Learning, Means Tests, Python, Qualitative Methods, Qualtrics, R, Regression Analysis, RStudio Cloud, Software Output Interpretation, SQL, Time Series

Quick-tip: the fastest way to speak to a consultant is to first ...

Alyssa Heinze

Consulting Drop-In Hours: By appointment only

Consulting Areas: Causal Inference, Data Visualization, Experimental Design, Focus Groups and Interviews, Git or GitHub, LaTeX, Machine Learning, Meta-Analysis, Mixed Methods, Qualitative Methods, Qualtrics, R, Regression Analysis, Research Design, RStudio, STATA, Survey Design, Text Analysis

Quick-tip: the fastest way to speak to a consultant is to first ...

John Louis-Strakes Lopez

Postdoctoral Scholar
Berkeley School of Education

John Louis-Strakes Lopez is a Data Science Education postdoctoral scholar. He recently received his PhD in Education from University of Caifornia, Irvine. John’s work looks at student epistemological development within data science contexts. He is also interested in designing -and studying artificial intelligence and playful learning technologies for learning. John serves as a co-chair for the International Learning Sciences Student Association.

Beyond work, you will find John reading at a local coffee shop or eating a warm bowl of Pho.

Maksymilian Jasiak

Data Science & AI Fellow 2025-2026
Civil and Environmental Engineering

Maksymilian Jasiak is a PhD Student in GeoSystems Engineering at the University of California, Berkeley. His research focuses on Distributed Fiber Optic Sensing (DFOS) for lifeline infrastructure monitoring. His work aims to advance critical infrastructure security and resilience. He holds a MS in GeoSystems Engineering from the University of California, Berkeley and a BS in Civil Engineering from the University of Illinois Urbana-Champaign.

Sohail Khan

Senior Data Science Fellow 2025-2026, Data Science Fellow 2024-2025
School of Information

Hey everyone, I’m Sohail - a 1st years Master’s student studying Data Science at the I-School. I am interested in the intersection between Computer Science, Data Science, and Cognitive Psychology and using these tools to understand, discover, and drive the development of assistive technologies.

I have experience building with brain computer Interfaces, developing distributed data processing applications, and am currently working on a large scale archival project aimed at preserving the history and memory of resistance movements through an embedding based...

Sarah Daniel

Data Science & AI Fellow 2025-2026
Political Science

Sarah Daniel is a PhD candidate in Political Science, specializing in urban politics in Sub-Saharan Africa, with a particular focus on East Africa. Her research examines how neighborhood communities organize for collective action to improve service delivery, reduce inequality, and enhance political representation.