Investigating the role of multiple categorization tasks in a curriculum designed around mechanistic patterns and principles
Bibliographic record
Abstract
The goal of the present work is to extend an online reaction categorization task as a research instrument to a formative assessment tool of students’ knowledge organization for organic chemistry reactions. Herein, we report our findings from administering the task with undergraduate students in Organic Chemistry II, at a large, research intensive Canadian university, including the relationship between instrument and exam scores. The online categorization task uses 25 reaction cards that participants were asked to sort first into categories of their choosing ( i.e. , an open sort) then into the mechanistic categories defined in a Patterns of Mechanisms curriculum ( i.e. , a closed sort). We observed a small, significant correlation between how learners chose to organize their knowledge ( i.e. , open sort) and their cued ability ( i.e. , match with expert sort) at the beginning of the Organic Chemistry II course ( N = 65, r = 0.28, p = 0.026). We conducted a correlation analysis between students’ scores on the open and closed sort tasks and academic achievement. We found a strong relationship between the scores in the online categorization tasks and Organic Chemistry II exams, especially from the closed sort tasks ( N = 43, r = 0.70, p = 0.000). To date, no other discipline specific card-sort tasks have shown such a strong correlation with final assessment grades. We also found an increasing relationship between students’ choice and ability over time as students developed their expertise in the domain. This work also added evidence to the validity and reliability of the organic card-sort instrument, through multiple measures. Educators and students could use the card sort task as a self-assessment measure and as part of classroom activities related to mechanistic analysis. Future work is needed to investigate how card sort tasks of this type are connected with expertise in other settings.
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 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 | 0.015 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".