The Educational Omics Framework
Six dimensions of the Theory layer · see the full Uedu Educational Omics Research Stack
Cognomics
Cognitive processes traced through AI dialogue, Bloom's Taxonomy assessment, and learning trajectory analysis.
PhysioNeuromics
Physiological and neural time-series — beat-to-beat intervals, heart rate variability, sleep, EEG, fNIRS — analyzed as correlates of learning states with validated, transparent algorithms.
Sociomics
Social interaction patterns including discussion engagement, collaborative learning, and peer assessment.
Environomics
The learning exposome — the totality of environmental exposures and contextual conditions a learner experiences during a learning event — across four sub-layers: indoor environmental quality (light, temperature, humidity, noise, CO₂, air), spatial and equipment conditions, temporal and activity context, and external environmental context.
Linguomics
Language expression analysis — complexity, semantic structure, voice features — from speech and text.
Ethicomics
Ethical governance — IRB approval, informed consent, privacy protection, AI bias detection.
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Funding
Our research is supported by governmental agencies and institutional partners
| Project | Agency | Period | Role |
|---|---|---|---|
|
A Study on the Learning Transfer Effectiveness of Digital Scaffolding Teaching Methods Based on Generative AI in the "Introduction to Generative Artificial Intelligence" Course for the College of Liberal Arts
MOE-114-TPREE-0008-019Y1 |
教育部 Ministry of Education (MOE) |
Aug 2025 – Jul 2026 | PI |
|
Exploring Learning Effectiveness of Matrix Immersive Problem Oriented Project-Based Learning (POPjBL) in Capstone Project Course
MOE-113-TPREE-0008-007Y1 |
教育部 Ministry of Education (MOE) |
Aug 2024 – Jul 2025 | PI |
|
Self-regulation and Transfer Learning on AI-based Adaptive Guidance System
PEE1122848 |
教育部 Ministry of Education (MOE) |
Dec 2023 – Jan 2025 | PI |
| IoT Project | 國防部 Ministry of National Defense (MND) |
2023 – 2025 | Co-PI |
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