MétaCan
Menu
Back to cohort

Foundation Skills for Scientists: An Evolving Program

2010· article· en· W2095567284 on OpenAlex
Teresa Dawson, Sarah Fedko, Nancy Johnston, Elaine Khoo, Sarah King, Saira Rachel Mall, Mary M. Olaveson, Janice Patterson, Kamini Persaud, Frances Sardone, Zohreh Shahbazi, Allyson Skene, Martha Young, Clare A. Hasenkampf

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Journal for the Scholarship of Teaching and Learning · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsThe Scarborough HospitalUniversity of TorontoUniversity of Victoria
Fundersnot available
KeywordsSyllabusPsychologyPedagogyLibrary scienceMathematics educationComputer science

Abstract

fetched live from OpenAlex

We have undertaken an integrated and collaborative approach to developing foundational skills of students in a first year, Introductory Biology course. The course is a large lecture and laboratory course with enrollments ranging from 800-1000 per year. Teaching and Learning experts were brought into the course as weekly ‘Foundation Skills for Scientists’ sessions were created. The initial challenges were to have effective knowledge exchange between collaborators and create an integrated course syllabus. Once effective sessions were created, the next challenge was to improve student valuation of them. High value was only achieved when the skill sessions were tightly linked to course assignments and activities and was delivered ‘just in time’. Even then, the challenge has been to motivate students to realize that the sessions are directly relevant to them. Overall, student performance has improved since the program was initiated as measured by rate of retention in the course, overall course marks and quality of writing. Nous avons utilisé une approche intégrée et collaborative pour approfondir les compétences de base des étudiants de première année qui suivent un cours d’introduction à la biologie. Il s’agit d’un cours magistral et en laboratoire, auquel s’inscrivent entre 800 et 1000 étudiants par an. Ce cours a bénéficié de l’apport d’experts en enseignement et en apprentissage afin d’appuyer le développement de séances hebdomadaires portant sur les compétences de base en sciences. Les difficultés initiales étaient de susciter un échange de connaissances efficace entre les collaborateurs et de créer un plan de cours intégré. Une fois les séances organisées, la difficulté suivante a été de faire en sorte que les étudiants les apprécient davantage. Ces derniers les ont jugées très utiles uniquement lorsqu’elles étaient étroitement liées aux tâches et aux activités et lorsqu’elles étaient offertes au moment opportun. Même alors, le défi a consisté à motiver les étudiants afin qu’ils se rendent compte que les séances leur sont directement pertinentes. Dans l’ensemble, la performance des étudiants s’est améliorée depuis le début du programme comme l’indiquent les mesures du taux de persévérance dans le cours, les notes générales et la qualité de la rédaction.

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.

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)0.060
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0600.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0230.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.003
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 head0.057
GPT teacher head0.428
Teacher spread0.371 · 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