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Record W1483614593 · doi:10.5430/jct.v4n1p122

Fostering Integrated Learning and Faculty Collaboration through Curriculum Design: A Case Study

2015· article· en· W1483614593 on OpenAlexvenueno aff
Robert L. Routhieaux

Bibliographic record

VenueJournal of Curriculum and Teaching · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Marketing Education
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumMetropolitan areaEngineeringCurriculum developmentEngineering managementFaculty developmentEngineering ethicsMedical educationProfessional developmentPedagogySociologyMedicine

Abstract

fetched live from OpenAlex

Designing and implementing innovative curricula can enhance student learning while simultaneously fosteringfaculty collaboration. However, innovative curricula can also surface numerous challenges for faculty, staff, students,and administration. This case study documents the design and implementation of an innovative Master of BusinessAdministration (MBA) program at a comprehensive university located in a metropolitan area in the MidwesternUnited States. It outlines the successes and challenges encountered along the way, and provides suggestionsregarding the development and implementation of innovative curricula.

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)0.024
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.003
Scholarly communication0.0050.003
Open science0.0040.007
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.057
GPT teacher head0.332
Teacher spread0.275 · 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 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

Citations6
Published2015
Admission routes1
Has abstractyes

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