Towards a Mixed Reality Agent to Support Multi-Modal Interactive Mini-Lessons That Help Users Learn Educational Concepts in Context
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The discipline of education and training is in a state of transformation currently and is shifting toward more online learning environments as such, researchers are beginning to explore and apply new emerging technologies for online education. However, the current online learning platforms face new challenges in presenting learning content. There is a need for ways to support self-directed learning using new technological resources to create personally meaningful curiosity-driven learning experiences. In this work, an architectural framework for a mixed reality learning system is designed and presented to address this need. This is presented as an approach toward building tools for future educators to enable them to create multi-modal interactive mini-lessons in mixed reality that students can experience when they are within the appropriate learning contexts. Two proof-of-concept use case scenarios are presented using this framework. Together, this provides a step toward future multi-modal interactive educational agents that help users learn educational concepts in mixed reality.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it