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Evaluating In‐person and Remote Delivery of Human Anatomy Laboratory Education Among Medicine and Dentistry Students

2021· article· en· W3169703579 on OpenAlexaffabout
Jobanpreet Dhillon, Mayssa Moukarzel, George Laggis, Geoffroy Noël, Nicole M. Ventura, Sean McWatt

Bibliographic record

VenueThe FASEB Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsCurriculumMedical educationGross anatomyMedicineTeaching methodPsychologyAnatomyMathematics educationPedagogy

Abstract

fetched live from OpenAlex

As remote teaching has become the forefront of education during the COVID‐19 pandemic, anatomy curricula have been forced to adapt to provide quality education for core competencies. In particular, in‐person laboratory components have been largely reduced or removed from anatomy teaching to comply with social distancing guidelines. While this has compromised typical learning environments, it offers a unique opportunity to implement remote teaching practices in anatomy and assess their impact on students’ learning. The Faculty of Medicine and Health Sciences at McGill University has initiated a hybrid teaching strategy for the anatomy laboratory curriculum that combines limited hands‐on cadaveric dissection with remote laboratory‐adjacent activities using a 3‐D software application (Complete Anatomy 2021). During the Fall 2020 semester, first‐year medicine and dentistry students had the opportunity to experience both teaching formats while learning respiratory and cardiovascular anatomy. Our study aimed to evaluate the efficacy of this hybrid curriculum delivery format by comparing in‐person versus digital teaching approaches implemented within the same cohort on the following outcomes: (i) student and instructor experiences, (ii) students’ approach to learning (SAL) and performance, and (iii) faculty time, resources, and cost considerations. Given that hands‐on cadaver‐based learning is considered the gold standard in anatomy education, we hypothesized that the in‐person teaching format would be associated with higher deep and lower surface learning scores, higher grades, and higher resource requirements. The qualitative feedback revealed greater student preference for in‐person dissection learning. Comparisons of SAL between in‐person and remote delivery formats revealed no significant differences in students’ deep or surface approach scores between in‐person and remote delivery formats during the respiratory (deep: p = 0.63; surface: p = 0.84) or cardiovascular (deep: p = 0.18; surface: p = 0.22) anatomy laboratory sessions. Further, no significant differences were noted in mean grades on the laboratory exam when correlated with the respective in‐person vs. remote learning format for both respiratory (p = 0.65) and cardiovascular (p = 0.18) blocks. Together, these findings suggest that irrespective of the teaching method utilized, students adopted similar approaches to learning anatomy and performed equally well in summative assessments. Pending a thematic analysis of instructors’ experiences, resource use, and cost considerations, findings from this study will help guide educational policy revisions aimed at maintaining student‐centered learning during current and future disruptions to in‐person teaching.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.026
GPT teacher head0.344
Teacher spread0.318 · 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 designObservational
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
Published2021
Admission routes2
Has abstractyes

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