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Record W2308382059

Preparing Students for Practical Exams: The Dreaded Anatomy Bell Ringer

2016· article· en· W2308382059 on OpenAlexaff
Leigh M. Vanderloo

Bibliographic record

VenueScholarship@Western (Western University) · 2016
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsWestern University
Fundersnot available
KeywordsMedical educationTest (biology)PsychologyMathematics educationMedicine
DOInot available

Abstract

fetched live from OpenAlex

Undergraduate students in the health sciences typically perform poorly on practical exams. For example, the bell ringer is a stressful part of anatomy courses. This poor performance may be due to the fact that students often struggle with ‘transferring’ content from lecture (i.e., classroom) to a clinical setting (i.e., lab; Bolander et al., 2008). Although students are provided with weekly lab periods to interact with anatomical models, this learning is typically quite passive. As no assessments occur before the bell ringer, students have no early opportunities to test their knowledge. Course teaching assistants (TAs) are uniquely positioned to prepare students for the exam and to ensure they are meeting required learning outcomes. Workshop participants will explore facilitation strategies to actively involve students in the lab, thus aiding students to deepen their understanding of human anatomy and motivating reflection on these lessons. Moreover, this workshop will highlight the importance and utility of practical exams in anatomy courses and will also help increase participants’ confidence in helping students apply and evaluate their lecture-based knowledge in lab.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.762

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 communication0.0000.001
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 head0.073
GPT teacher head0.345
Teacher spread0.272 · 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
Published2016
Admission routes1
Has abstractyes

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