Towards a Situated View of Assessment Literacy for Higher Education
Bibliographic record
Abstract
The guiding purpose of this study was to explore how the term assessment literacy (AL) could be differently constructed in higher education (HE) settings as opposed to how it has been constructed for other settings. First, an empirical scoping review of 182 sources revealed AL for HE as more sophisticated than described with current AL models. Emergent themes of the scoping review were compared to existing AL conceptualizations and discussed with consideration to prior AL research. Using the scoping review results as a theoretical framework, a survey was developed to investigate how common assessment tasks in HE settings could be organized and labelled, and how such tasks may differently invoke speculated components of AL for HE. The thesis reports on survey development, item pool review, and various statistical analyses of data from a limited convenience sample of faculty from a Western Canadian HE institution. Survey findings revealed that assessment is implicated in a range of HE tasks that seem separable and which have not been considered in previous literature regarding AL. Further, different HE tasks were associated with varying strength to different arrangements of components of AL. As well, components of AL that were speculated from thematic analysis of a body of literature related to AL in HE were correlated to one another in various ways. Together, these findings indicated that AL may be explained by examining composite sub-concepts in relation to one another, and further that such a model for AL is related to different tasks in different ways. This underscores the idea that particular purposes for assessment in HE may be nested within a more general conceptualization of AL. Limitations and directions for future work on conceptualizing AL for HE are also discussed.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".