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Record W4393410566 · doi:10.1002/ase.2415

Anatomy beyond the pandemic: A Q‐methodology study exploring student perceptions toward a hybrid curriculum

2024· article· en· W4393410566 on OpenAlexafffund
Sai Gayathri Metla, Noori Akhtar‐Danesh, Jessica Saini, Ilana Bayer, Yasmeen Mezil, Danielle Brewer‐Deluce, Bruce Wainman

Bibliographic record

VenueAnatomical Sciences Education · 2024
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMcMaster UniversityHamilton Health Sciences
FundersMcMaster University
KeywordsCurriculumPreferencePerceptionPsychologyMedical educationCohortMathematics educationPedagogyMedicinePathology

Abstract

fetched live from OpenAlex

As a result of the COVID-19 pandemic, anatomy education was forced to adopt online modes of delivery. Previous research on student views revealed areas of strong preference (asynchronous lectures) and strong dislike (virtual specimens) in online anatomy courses. The current study seeks to compare the views of a single cohort of students experiencing both online and in-person undergraduate introductory anatomy and physiology courses. This comparison can highlight what students consider beneficial to their education and can inform future hybrid course offerings. Q-methodology was used to assess the opinions of students. Students sorted 41 statements on anatomy education in a quasi-normally distributed grid based on their degree of agreement with the statements. The rankings underwent a by-person factor analysis which categorized students with shared perceptions into groups. Data were collected from 246 students in the primarily online fall semester and 191 students in the primarily in-person winter semester. Analysis revealed three distinct factors (groups) in the cohort. Factor one (n = 113 (fall), n = 93 (winter)), was satisfied overall with the course materials and delivery. Factor two (n = 52 (fall), n = 18 (winter)) had a deep dislike of online learning, and factor three (n = 37 (fall), n = 49 (winter)) had a strong preference for online learning. While many students were comfortable in both online and in-person learning environments, this was not the case for all learners. The strengths and weaknesses of each teaching modality suggest the opportunity to explore hybrid learning as an option for future course offerings and specifically highlight valuable aspects to incorporate from each environment.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.075
GPT teacher head0.384
Teacher spread0.309 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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