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Optional online quizzes increase student success on exams in an undergraduate human anatomy course

2016· article· en· W4389024491 on OpenAlexaff
Nicolette Richardson

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsYork University
Fundersnot available
KeywordsDissection (medical)Human anatomyMedical educationTest (biology)Gross anatomyPsychologyMathematics educationMedicineAnatomy

Abstract

fetched live from OpenAlex

Background Repeated testing of material through online quizzing has been shown to improve student test scores in medical school human anatomy courses, however this has not been examined in undergraduate students. Since many undergraduate human anatomy programs do not have access to cadaveric material for learning/assessment, virtual dissection and related testing could be a successful alternative. Objective The present study examined student success on a midterm and final exam following two optional online quizzes covering similar material as the exams in an upper level undergraduate regional human anatomy course. Quiz questions were developed from virtual dissection labs which all students completed. We hypothesized that students who chose to complete the optional quizzes would be more successful on the exams, regardless of their level of success on the quizzes. Methods 113 kinesiology and physical therapy students, in their third or fourth year of undergraduate study, were enrolled in a Regional Human Anatomy course over the fall of 2014 or winter of 2015. All students wrote a midterm and final exam, and had the option to also complete two online quizzes, each worth 10% of the final grade and incorporating bell‐ringer style, timed, questions relating to a virtual dissection image. If students chose not to complete Quiz 1, that 10% would be applied to the midterm, and if they chose not to complete Quiz 2, that 10% would be applied to the final exam. The material covered in the quizzes was the same as that on the corresponding exams. Students were free to choose to do both quizzes, one quiz, or none. Results 56 students chose to complete at least one quiz, while 57 did not complete any quizzes. Students who completed Quiz 1 were more successful on the midterm (77.1 ± 13.4 compared to 72.4 ± 14.9%, p < 0.05) and students who completed Quiz 2 were more successful on the final exam (71.2 ± 16.9 compared to 60.9 ± 15.9%, p < 0.05, compared to those students who did not complete the respective quizzes. Conclusions Completion of optional online quizzes improves student success on exams covering similar material in an undergraduate human anatomy course. For undergraduate courses with or without a laboratory component, this may be a useful method to improve student retention and test scores. Support or Funding Information Supported by a Dean's Catalyst e‐Learning Grant, Faculty of Health, York University

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.003

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 head0.016
GPT teacher head0.307
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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