Assessing the ability of students to self-evaluate their level of comprehension in a 1st year chemical engineering course
Bibliographic record
Abstract
Self-regulated learners have the ability to accurately assess their own level of learning, and to adjust their learning methods in order to master their learning. These types of learners generally show a strongpersistence, and are most likely to succeed in in theiracademic career.To help determine whether students already possessthe skill to identify their academic capabilities, a selfassessment and reflection method was employed after every lecture in a first year chemical engineering course.The students were also tested at the beginning of the next lecture to determine the accuracy of their self-assessment. To have an academic goal, students were asked at the beginning of the course to estimate their desired lowest mark.On average, students overestimated their ability 47%of the time, and student did not show an improvement on their level comprehension over the course of the semester.Also only 22% of the students obtained a mark that wasequal to or greater than their desired lowest mark.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".