Development of a metacognition co-curriculum for a university course in introductory organic chemistry
Bibliographic record
Abstract
Metacognition is a fundamental skill that allows advanced learners to adapt to diverse learning environments. Metacognition, however, can be domain specific and students may fail to generalize metacognitive skills across domains. Thus, students in higher education may require specific training to acquire relevant metacognitive skills in differing domains or may need cueing to engage their metacognitive skills and knowledge in new domains. The present report describes the development of a co-curricular metacognitive program for chemistry students and suggests how this program could be adopted by other chemistry courses or adapted for other domains in higher education. Several supports were introduced in this program including self-assessment of competence with learning task inventories (LTIs; i.e., detailed lists of learning tasks), self-assessments of confidence regarding in-class content questions, and performance predictions and postdictions on tests. In general, exposure to these supports resulted in overall performance and confidence gains. However, individual differences were evident with some students demonstrating greater learning gains than others. Initial Dunning-Kruger effects associated with pre-and postdictions, with low-performing students overestimating grades and high-performing students underestimating grades, decreased over exposure. A summary of the evolution of this metacognitive co-curricular program, the educational literature that steered it, and the differential impact on students is explained.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".