Bibliographic record
Abstract
The purpose of this paper is to explore the principles of Assessment for Learning (AFL) in light of John Dewey’s writing about the purpose and possibility of education. In this paper, we compare Dewey’s ideas to the goals of assessment for learning (AFL)–a practice emerging globally and, more locally, moved forward by the Alberta Initiative for School Improvement (AISI) program. We believe the principles behind Dewey’s educational philosophy are congruent with fundamental principles of AFL. In this paper, we attempt to explicate key intersections between Dewey’s teachings and AFL. We review AFL strategies and the foundational philosophy of AFL in an attempt to reveal its connection points to Dewey’s educational philosophy. Specifically, we will outline seven AFL strategies and compare these to insights put forth in Dewey’s work. Although there is far from adequate space to consider all the matches of Dewey’s philosophy and the core principles of Assessment for Learning, we hope our quest for initial commonality might provide curriculum insight for those now working these new pedagogical activities. We are like people looking for something they have in their hands all the time; we're looking in all directions except at the thing we want, which is probably why we haven't found it. (Plato, 380BC) As the 21st century unfolds, societal changes affect communication, demographics, personal values, and the labour market. Today’s schools and learners can no longer be satisfied with specific career training from the past, because it is difficult to imagine what careers will even exist in the future. Furthermore, past pedagogies that called for an uncritical acceptance of hierarchy, order, and tradition seem to fold in the shifting winds of transformation. Knowledge is the driver in the global economy and, ultimately, educational institutions must ensure that students have the skills needed to
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.208 | 0.124 |
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".