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Course Redesign: An Evidence-Based Approach

2014· article· en· W1964846286 on OpenAlexaffvenue
Kathy Nomme, Gülnur Bírol

Bibliographic record

VenueThe Canadian Journal for the Scholarship of Teaching and Learning · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHumanitiesCurriculumPsychologyPedagogyPhilosophy

Abstract

fetched live from OpenAlex

A first year non-majors biology course, with an enrollment of around 440 students, has been redesigned from a course of traditional content and teaching style to one that emphasizes biological concepts in current global issues and incorporates active learning strategies. We were informed by the education literature incorporating many aspects of established curriculum redesign principles and extended its application to a biology course. Systematic measurement of student attitudes and collection of student feedback through a series of surveys as well as focus group interviews proved to be invaluable in the course redesign process. The information gathered over a two-year period enabled us to fine-tune the course content and teaching strategies effectively to better meet the interests of students in the non-majors course as was documented by the evidence gathered in this research. Un cours de biologie de première année pour étudiants qui ne se spécialisent pas dans ce domaine, dans lequel étaient inscrits 440 étudiants, a été remanié. Ce cours, dont le contenu et le style d’enseignement étaient traditionnels, est devenu un cours où les concepts de biologie ont été mis en valeur dans le contexte des questions globales d’actualité, et des stratégies d’apprentissage actif y ont été incorporées. Nous avons puisé nos ressources dans les publications consacrées à l’éducation qui incorporent les principes établis de remaniement des programmes de cours et nous avons appliqué ces principes à un cours de biologie. La mesure systématique des attitudes des étudiants, les commentaires recueillis auprès des étudiants par le biais de plusieurs sondages, ainsi que les entrevues de groupes témoins, se sont avérés inestimables au cours du processus de remaniement du cours. Les renseignements recueillis pendant une période de deux ans nous ont permi d’affiner de façon efficace le contenu du cours ainsi que les stratégies d’enseignement afin de mieux répondre aux intérêts des étudiants dans des cours qui ne s’adressent pas à des spécialistes du sujet enseigné, tel que documenté par l’évidence recueillie au cours de cette recherche.

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)0.250
metaresearch head score (Gemma)0.597
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.250
Threshold uncertainty score0.924

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2500.597
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0260.020
Science and technology studies0.0030.004
Scholarly communication0.0120.010
Open science0.0120.008
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0110.001

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 head0.178
GPT teacher head0.416
Teacher spread0.237 · 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.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations17
Published2014
Admission routes2
Has abstractyes

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