Developing pre-service O&M specialists’ reflective practices to improve problem-solving opportunities during instruction
Bibliographic record
Abstract
The ability of instructors to promote problem-solving abilities is an important pedagogical skill. Providing well-planned problem-solving opportunities is especially vital in orientation and mobility (O&M) lessons. During personnel preparation programs, pre-service O&M specialists would benefit from developing a keen awareness of how well they encourage problem-solving in their instruction. This mixed-methods study reports on a process in which nine pre-service O&M specialists engaged during their blindfold techniques course. Each participant taught two lessons to a peer in their course, engaging in a retroactive think-aloud after each lesson. The process focused participants on the types of questions they asked to promote thinking and engaged them in reflection on how well the lesson met their intended objectives. Results indicated qualitative benefits noted by the participants of engaging in the process and also highlighted a need for further work with pre-service O&M specialists on question asking and allowing problem-solving and thinking opportunities during basic lessons.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".