The role of student‐generated analogies in promoting conceptual understanding for undergraduate chemistry students
Bibliographic record
Abstract
This article reports on the value of using student‐generated analogies with undergraduate science students as a strategy for promoting conceptual understanding. A quantitative study was undertaken involving students in four sections of an introductory chemistry course for prospective science majors attending a four year college in British Columbia, Canada. Students in one section of the course developed, performed and discussed analogies representing a conceptually difficult chemistry topic. Students in three other sections received instruction on the same topic via a teacher‐generated analogy combined with in‐class discussion. To assess the impact of student‐generated analogies, students’ performance on a final exam question was compared across the four sections and their answers were analyzed for evidence of depth of conceptual understanding. Students who generated their own analogies performed significantly better in the exam and demonstrated a greater level of conceptual understanding than students who were presented with a teacher‐derived analogy. It is particularly noteworthy that lower‐achieving students who devised and enacted analogies for their peers significantly out‐performed their counterparts who received more traditional instruction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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; both teacher heads agree on what is shown here.
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".