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Record W4383710805 · doi:10.1002/jgc4.1737

A novel online genomic counseling and variant interpretation certificate: Learning design, learning analytics, and evaluation

2023· article· en· W4383710805 on OpenAlexafffundabout
Leah P. Macfadyen, Jehannine Austin, Ping Cao, John Cheng, Carol Cremin, Linda Duong, Alison M. Elliott, Colleen Guimond, Shur Lim, Simone Race, Indhu‐Shree Rajan‐Babu, Anastasia Richardson, Tasha Wainstein, Farah Zahir, Patricia Birch

Bibliographic record

VenueJournal of Genetic Counseling · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsUniversity of British Columbia
FundersFaculty of Medicine, University of British ColumbiaNational Society of Genetic Counselors
KeywordsCertificateGenetic counselingMedical educationCurriculumAnalyticsAsynchronous learningMedicinePsychologyComputer sciencePedagogyData scienceTeaching methodSynchronous learningCooperative learning

Abstract

fetched live from OpenAlex

In this paper we describe the analysis, planning, design, development, implementation and evaluation of a new online Graduate Certificate in Genomic Counselling and Variant Interpretation (GCGCVI) at The University of British Columbia (UBC). Genetic counselling is now a prerequisite for diagnostic genomic testing in many countries, demanding that genetic counselling practitioners have up-to-the-moment genomic counselling skills and knowledge. Current practitioners reported a desire for more training in this rapidly developing field: our international survey revealed substantial interest in online continuing education addressing themes such as testing and clinical bioinformatics, applied variant interpretation, evidence-based genomic counselling, and other emerging genomic topics. However, our market analysis found no post-graduate program globally that offered such training. To fill this gap, our oversight team of genetic counsellors and geneticists therefore guided development of curriculum and materials, and online learning specialists developed rigorous interactive asynchronous online graduate courses through collaboration with subject matter experts, following best practices in online learning design. Since launch in September 2020, we have gathered learner feedback using surveys and focus groups, and we have used learning analytics to understand how learners engaged with each other and with course materials. Together, these have helped us understand learner behaviour and guide the continuous process of design improvement to support the learning goals of this audience of professional learners. Our courses have been reviewed and approved by the UBC Faculty of Medicine, UBC Senate, and the Province of British Columbia Ministries of Advanced Education and Health, and assessed by the National Society of Genetic Counselors (NSGC, USA) and the Canadian Association of Genetic Counsellors (CAGC) to enable learners to receive North American continuing education credits. To date, 151 individuals from 18 countries have succeeded in one or more course and 43 have completed the entire certificate.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.058
GPT teacher head0.322
Teacher spread0.265 · 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 designSimulation or modeling
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

Citations2
Published2023
Admission routes3
Has abstractyes

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