STUDENT-STUDENT ONLINE COACHING AS A RELATIONSHIP OF INQUIRY: AN EXPLORATIVE STUDY FROM THE COACH PERSPECTIVE
Bibliographic record
Abstract
There are comparatively few studies on one-to-one tutoring in online settings, even though it has been found to be an effective model. This paper explores student-student online coaching from the coach perspective. The empirical case is the project Math Coach, where K-12 students are coached by teacher students using instant messaging. This research is an adaptation of the community of inquiry model to an online coaching setting, which we refer to as a relationship of inquiry. The adapted model was used to gain a better understanding of the practice of online coaching by exploring the extent to which cognitive, social, and teaching presence exist in this case of online coaching. A relationship of inquiry survey was distributed to and answered by all active coaches (n=41). The adapted cognitive, social and teaching presence measures achieved an acceptable level of reliability. Differences between three presences, and their respective sub-categories, demonstrate a unique pattern of interaction between coaches and coachees in the online coaching environment. Findings suggest the online inquiry model fits as well for a relationship of inquiry as it does for a community of inquiry. The model provides valuable information for better understanding of online coaching.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".