An Approach To Developing Students' Skill In Self Assessment
Bibliographic record
Abstract
Self and peer assessment can be vital parts to any team assessment.The assessment can be of the overall team or of the performance of team members.Assessment is a judgment as to the degree to which a goal has been achieved.In student self assessment, the judgment is made by the student.In this paper the five principles of assessment are summarized.Assessment is about performance not worth; is based on evidence not intuition; is done in a defined situation and for a purpose; is done in the context of published goals, measurable criteria and agreedupon forms of evidence; and is based on multiple forms of evidence.A rationale is given for why this skill is important.Self assessment is an important skill because it provides an element of ownership of the learning, is needed in professional life, helps to develop self confidence and provides a way to give prompt feedback.Self assessment is a valued skill because it seems to be related to self image and self confidence which, in turn, are related to exam anxiety, and propensity to procrastinate.We used five components to develop and apply skill in self assessment: a 4 to 6 hour workshop, resume writing, reflective journal writing, a personal enrichment project and a personal interview to determine the final grade in courses.Details are given.We have used this approach since 1982 as part of the McMaster Problem Solving program.Marks from self assessment agree within ∀ 5% with marks from faculty based on term work and exam performance for over 3/4 of the students.This compares with data from other researchers who found that marks from self assessment agree within ∀ 10% with the teacher=s marks for over 3/4 of the students.Anecdotal testimonies from our alumni identify the importance of this skill development.
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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 | 0.031 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".