Revisioning the potential of Freire’s principles of assessment: Influences on the art of assessment in open and online learning through blogging
Bibliographic record
Abstract
When the art of assessment in online and distributed learning is grounded in Freirean writings, instructors have the opportunity to craft a nuanced and layered learning environment where the potential for critical consciousness is enhanced through carefully codesigned assessment strategies. Patton (2017) summarized 10 pedagogical principles based on the writings of Freire, which he determined relevant as a result of their connection to critical pedagogy of evaluation. We explore a revisioning of those principles: using evaluative thinking to cultivate critical consciousness; learning resides in communities, not just individuals; critical pedagogy must be dialogical and interactive; assessment should integrate reflection, action, thinking, and emotion; and critical consciousness is co-intentional, focusing on process and product. We use them as a framework to describe what we call Freirean principles of assessment, through the application of student blogs within online and distributed assessment practices. Our intention is to share the potential of blogging, in connection with Freirean principles of assessment, when considering open assessment in higher education.
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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 | 0.052 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.040 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".