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Record W4392761600 · doi:10.1021/acs.jchemed.4c00040

A National Snapshot of Introductory Chemistry Instructors and Their Instructional Practices

2024· article· en· W4392761600 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.

Bibliographic record

VenueJournal of Chemical Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsToronto Metropolitan University
FundersDivision of Undergraduate EducationNational Science Foundation
KeywordsActive learning (machine learning)Mathematics educationMedical educationChemistryPsychologyMedicineComputer science

Abstract

fetched live from OpenAlex

The effectiveness of active learning on promoting students' academic outcomes and persistence has been established in the literature. However, despite the effort of purposeful change agents, the uptake of active learning in science, technology, engineering, and mathematics (STEM) is slow. While previous research from the chemistry education community has provided insights into the implementation of specific active learning strategies across the United States, the extent to which chemistry instructors leverage these strategies in general remains unknown. This article presents the results of a national survey aimed at exploring introductory chemistry instructors' knowledge and implementation of active learning, variations on this knowledge, and use across tenure statuses and institution types. This paper also aims to address the gap in the literature in our understanding of the characteristics of instructors of these courses. We thus provide a description of instructors' demographics, training, teaching experience, and teaching responsibilities. Our findings reveal that instructors in these courses are prominently males of European descent. Additionally, instructors come into their teaching position with minimal pedagogical training and participate mainly in short training once in their position. While the majority of instructors have knowledge of specific active learning strategies, their consistent implementation remains limited, with lecturing still being the instructional practice of choice. Variations were found between institution types and across tenure statuses within institutions in terms of pedagogical training, use of specific active learning strategies, and proportion of class time spent lecturing. The findings provide a baseline for future studies that aim to assess the effectiveness of interventions fostering the implementation of active learning in introductory chemistry courses and highlight the critical need for improved communication about teaching practices across institutions and tenure statuses.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.329
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.413
Teacher spread0.378 · 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