From Wearables to AI Tutors: A Hands-on Tutorial on Physiological-Aware Learning Analytics

Tutorial Overview

This half-day tutorial introduces the Uedu platform and its Educational Omics framework, covering ClassroomGPT AI tutoring, the PALM physiological-aware language model, Garmin wearable HRV data integration, Uedu Brain multimodal biosensing, and the Trusted Educational Data Lake. Participants will gain hands-on experience integrating wearable sensor data with AI tutoring to build physiological-aware learning analytics research.

Highlight: In Session 2, participants will wear Garmin smartwatches to collect real-time HRV and stress data, then immediately analyze their own physiological data within the same session—experiencing the complete collect–analyze–interpret lifecycle firsthand.

Intended Learning Outcomes

By the end of this tutorial, participants will be able to:

1. Explain the Educational Omics framework and how its six dimensions map to data collection methods and research questions.
2. Collect real-time HRV and stress data using Garmin and UeduPAD, and interpret physiological metrics in an educational context.
3. Demonstrate how PALM adapts AI tutoring based on learner physiological states by manipulating inputs and observing responses.
4. Analyze pre-recorded EEG, fNIRS, and ECG data in Jupyter notebooks, identifying neural signatures across learning tasks.
5. Export datasets from the Uedu Lab Data Lake and evaluate their suitability for specific research designs.
6. Design an Educational Omics study by selecting data dimensions, devices, and methods for a self-defined research question.

Schedule

The half-day tutorial is organized into three thematic sessions with a coffee break in between.

What to Bring

• Laptop (macOS or Windows) with a modern web browser
• iPad (optional) for UeduPAD
• Garmin smartwatch owners are encouraged to bring theirs

No pre-installation needed—all analysis runs on Uedu Jupyter, our cloud-based notebook environment.

Organizers

Tutorial Materials