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Record W4210798822 · doi:10.1039/d1rp00267h

Investigating the role of multiple categorization tasks in a curriculum designed around mechanistic patterns and principles

2022· article· en· W4210798822 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueChemistry Education Research and Practice · 2022
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordssortCategorizationCard sortingFormative assessmentTask (project management)CurriculumPsychologyMathematics educationComputer scienceCognitive psychologyChemistryArtificial intelligenceInformation retrievalPedagogyEngineering

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.357
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it