Playful Telepresence Robots with School Children
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 offer potential enhancements to real-time classroom participation and social interaction for remotely located children. This mixed-method study, including observation and questionnaires, examines the safety and effectiveness of these technologies in an educational environment, with 22 children aged 9-11 using GoBe mobile telepresence robots. Participants were divided into eight groups. They engaged in activities designed to simulate driving experiences, including navigating an obstacle course, participating in a treasure hunt, and parking the robot. Through thematic analysis of observation notes and statistical analysis of task performance measurements, we identified challenges such as initial connection issues, navigation difficulties in tight spaces, and inconsistent docking. These underscore the need for improvements in network compatibility, user interface, and automation. Our findings indicate that children are capable of safely operating the robots and collaborating effectively. Further, our data indicates that there may be gender differences affecting confidence and adjustment to driving tasks. This study suggests enhancements in robot design and instructional practices to better integrate telepresence robots into educational settings, ensuring their safety and utility for children.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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