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Record W7045806583

Case Study: A Collaborative Approach to Rapid Course Development for Postsecondary Programs

2024· article· en· W7045806583 on OpenAlexaboutno aff

Bibliographic record

VenueSOURCE Sheridan's Institutional Repository (Sheridan College) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumProcess (computing)Curriculum developmentConstructiveSubject matterDegree programCollaborative learningCourse (navigation)
DOInot available

Abstract

fetched live from OpenAlex

This case study explores the rapid development of post-secondary course outlines for a new four-year honours bachelor’s degree program at an Ontario college. The six-week process was structured around a collaborative approach to curriculum development, integrating principles of constructive alignment and backward design. Subject Matter Experts (SMEs), with varying levels of experience in curriculum design, participated in flipped learning and workshops that focused on crafting measurable learning outcomes, aligning assessments, and designing cohesive module topics. Key strategies included the use of a program map to visually identify overlaps and gaps across courses, collaborative feedback sessions to refine course components, and tailored support to build SME capacity. The result was a comprehensive, scaffolded curriculum that aligned program and course-level learning outcomes, ensuring balanced and intentional student evaluations through an evaluation matrix. Insights from this initiative highlight the importance of alignment, visual planning tools, and differentiated support in achieving curriculum coherence. The study offers valuable guidance for curriculum developers and higher education institutions navigating similar challenges.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0050.001
Scholarly communication0.0010.001
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 head0.033
GPT teacher head0.338
Teacher spread0.304 · 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.

Study designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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