Reflection and Readiness: Shared Benefits of Using an Oral Final Evaluation to Assess Counselor Competency
Bibliographic record
Abstract
The COVID-19 pandemic has impacted educational systems worldwide, shifting everything from pedagogy to learning environments. The emerging needs and complexities presented during this time has challenged long-standing practices, requiring creativity and innovation to adapt in the midst of uncertainty and accelerated change. This has been the reality within graduate counselling programs where coursework and internships were interrupted, and the counselling environment altered. In the face of such changes, the critical assessment and evaluation of pre-service counsellor competence remains a high priority of counsellor educators. This article outlines the practice of adopting an Oral Final Evaluation (OFE) of post-practicum graduate counselling students as a means of addressing the need to accurately assess counsellor competence in the changed landscape of the current pandemic. This article provides a rationale for integrating an OFE and space for reflection on its implementation, along with feedback from participating students, faculty, and site-supervisors.
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How this classification was reachedexpand
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 | 0.006 | 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".