Bibliographic record
Abstract
Several faculty members including the author were involved in exploring the implementation and effectiveness of research-based assessment strategies in their undergraduate teacher education courses at a Canadian university. The paper describes the process and the results of their ongoing improvement efforts and implications for teacher education and higher education in general. After attending several assessment workshops lead by the author, 12 faculty members implemented new assessment strategies in their own courses to enhance student learning. As the 12 faculty members reflected on their efforts to enhance assessment, a number of themes emerged. These included assessment as authentic performance, establishing clear learning targets, collaboration and community, and integrated assessment and instruction. Our results support the claim that current ideas about K-12 assessment are applicable to post-secondary education and can improve student learning outcomes. Developing balanced and integrated assessment systems is perhaps the most significant innovation we engaged in and we conclude that it has the potential to fundamentally change what occurs in university classrooms. Plusieurs professeurs, y compris l’auteur, ont exploré la mise en oeuvre et l’efficacité de stratégies d’évaluation basées sur la recherche dans le cadre de leurs cours de formation pour les enseignants. L’article décrit le processus et les résultats de leurs efforts pour améliorer la formation des enseignants et plus généralement l’enseignement, ainsi que les implications de cette approche. Après avoir participé à plusieurs ateliers sur l’évaluation dirigés par l’auteur, 12 professeurs ont mis en oeuvre de nouvelles stratégies d’évaluation dans leurs propres cours pour améliorer l’apprentissage des étudiants. Quand les 12 professeurs ont réfléchi sur leurs efforts pour améliorer l’évaluation, un certain nombre de thèmes sont apparus, entre autres : l’évaluation en tant que performance authentique, l’établissement d’objectifs d’apprentissage clairs, la collaboration et la communauté, l’intégration de l’évaluation et de l’instruction. Nos résultats étayent l’affirmation selon laquelle les théories actuelles sur l’évaluation dans les écoles (K-12) sont applicables en enseignement post-secondaire et peuvent améliorer l’apprentissage des étudiants. Le développement de systèmes d’évaluation équilibrés et intégrés est peut-être l’innovation la plus importante dans laquelle nous nous engageons et nous en concluons que cette pratique a le potentiel de changer radicalement ce qui se passe dans les salles de classe des universités.
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 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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".