INSTRUCTOR

Manuel S. González Canché, University of Pennsylvania

TEACHING ASSISTANT
Chelsea Zhang, University of Pennsylvania

What if researchers could use advanced data science and AI tools without coding, without expensive monthly fees, and without giving up control of sensitive data?

Too many researchers are currently being asked to make an impossible choice: either remain outside the world of advanced data science and AI, or enter it by learning programming, relying on expensive proprietary platforms, and uploading sensitive data to external servers. This course begins from a different premise: researchers should not have to choose between rigor, accessibility, privacy, and interpretive depth.

This hands-on course introduces an integrated methodological ecosystem for ethical and equity-fueled data science in qualitative and mixed-methods research. It is designed for scholars working with textual, relational, temporal, affective, spatial, and multimodal evidence who want access to rigorous data science and AI-supported analytic tools without needing to master programming, pay recurring fees, or surrender control of sensitive materials. Participants will be introduced to a fully local, no-code ecosystem of tools for analyzing complex evidence across multiple layers of inquiry, from language and structure to time, emotion, and context.

Special attention will be devoted to ISARI (Intelligent Systems for Academic Research Integration), a fully offline, open-source, multimodal brainstorming partner designed to support scholarly memoing, comparison, synthesis, and evidence-grounded writing. The course positions ISARI not as a substitute for interpretation, but as part of a broader local analytic ecosystem in which computational outputs remain accountable to researchers’ judgment and to participants’ original evidence.

This is not a course about replacing researchers with AI. It is a course about giving researchers ethical, equity-fueled access to advanced analytic tools that have too often remained restricted to those with programming expertise or privileged institutional support. If you want to expand your analytic toolkit without compromising ethics, privacy, transparency, or scholarly control, this course is for you.

The content of this course aligns with a forthcoming book titled “Data Science, Interactive Visualizations, and Generative AI Tools for the Analysis of Qualitative, Mixed-Methods, and Multimodal Evidence” See https://cutt.ly/RtZ1ZOfq for more details.