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Record W3006329369 · doi:10.1039/c9rp00203k

Essential learning outcomes for delocalization (resonance) concepts: How are they taught, practiced, and assessed in organic chemistry?

2020· article· en· W3006329369 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemistry Education Research and Practice · 2020
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDelocalized electronContext (archaeology)Set (abstract data type)Mathematics educationEpistemologyPsychologyChemistryComputer sciencePhilosophyOrganic chemistryHistory

Abstract

fetched live from OpenAlex

The concept of delocalization ( <italic>i.e.</italic> , resonance) is fundamental concept in organic chemistry but essential learning outcomes (LOs) have not previously been proposed nor has there been an analysis of how resonance is taught, despite indications in the literature that students have many non-canonical ideas about the concepts. To address this deficit, we first developed a set of ten learning outcomes believed to be essential to the concept of delocalization in organic chemistry, especially for students’ later success. Next, we analyzed how these learning outcomes are being taught, practiced and assessed in common textbooks and in a sample of exams. Five themes emerged from the analysis: (1) several of the essential intended LOs we identified are not represented in the textbooks’ teaching explanations, practice questions, or professors’ assessments; (2) the concepts related to delocalization are often taught, practiced, and assessed without associated justifications; (3) there is a large gap between when delocalization is taught and when it is used in context; (4) the link between delocalization and other concepts ( <italic>e.g.</italic> , reactivity) is not explicitly explained in most teaching materials; and (5) the language used around delocalization may be misleading ( <italic>e.g.</italic> , resonance, stability). Our analysis identified areas in which delocalization education could be improved, including with respect to teaching, practice opportunities, and assessing the concepts.

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)0.001
metaresearch head score (Gemma)0.045
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.410
Teacher spread0.353 · 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