Oral Assessment as a Culminating Activity for Faculty Development
Bibliographic record
Abstract
This paper describes the oral assessment activity we designed and used as a culminating activity for faculty participants in a professional academic development program. The program offers multiple certificates, and the goal of each certificate is to enhance participants’ abilities to design and deliver exceptional student learning experiences. We describe the unique nature of the assessment activity and provide details on the process of implementing oral assessment. The process enabled faculty to demonstrate achievement of the program learning outcomes and consider next steps in their professional development. Three key ideas discussed in this paper are: oral assessment, folio thinking, and dialogic curriculum. Dans cet article, nous présentons l’activité d’évaluation orale que nous avons conçue comme le point culminant d’un programme de perfectionnement professionnel universitaire pour les enseignants. Ce programme comprend plusieurs certificats visant chacun à renforcer la capacité des participants à créer des expériences d’apprentissage exceptionnelles pour les étudiants. Nous montrons en quoi l’évaluation orale est unique et nous fournissons des précisions au sujet du processus de mise en œuvre de cette activité. Grâce à l’évaluation, les enseignants ont été à même de montrer qu’ils avaient atteint les objectifs d’apprentissage du programme et d’envisager la suite de leur perfectionnement professionnel. Voici en somme les trois idées clés dont traite cet article : l’évaluation orale, la pensée organisée sous forme de dossier (folio thinking) et le programme d’étude dialogique.
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.
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 | 0.028 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".