Navigating the Cyborg Classroom: Telepresence Robots, Accessibility Challenges, and Inclusivity in the Classroom
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
Telepresence robots, designed to bridge physical distances, have unique capabilities and inherent limitations when deployed in classroom environments. This study examines these aspects, focusing on how telepresence robots facilitate or hinder classroom accessibility and inclusivity. Based on field study results from participatory observations, surveys and interviews with 22 participants, we present and catalogue the operational capabilities of telepresence robots, such as mobility and interaction potential, alongside their limitations in areas like sensory perception and social presence. Our findings reveal a nuanced landscape where telepresence robots act as both enablers and barriers in the classroom. This duality raises the question of whether these robots can be considered “disabled” in certain contexts and how this perceived disability impacts remote students’ inclusion in classroom dynamics. Finally, we present use recommendations to improve classroom experience and telepresence design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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