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Record W4319336382 · doi:10.31274/itaa.15898

Teaching Broccoli Courses: Best Practices for Research Methods in Fashion

2022· article· en· W4319336382 on OpenAlexaff
Sandra Tullio-Pow, Kirsten Schaefer, Shelley Haines, Tarah Burke-Harris

Bibliographic record

VenueInnovate to Elevate · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture, Art, Education
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFlexibility (engineering)Computer scienceKey (lock)Best practiceMultimediaMathematics educationPsychology

Abstract

fetched live from OpenAlex

Based on our experiences, some fashion students view research methods more like broccoli than ice cream. Research Methods in Fashion (FSN 707) is a required undergraduate course with 150+ students. Best practices implemented in this course during the pandemic are described. Initiatives included new approaches to empathy and learning flexibility. We developed a course outline based on a blended learning format. To facilitate communication, weekly lecture outlines with required readings, key terms and guiding questions were developed. Video lectures were offered asynchronously. We scaffolded learning activities in synchronously scheduled tutorial classes to help students learn how to develop a research proposal. We shared practical applications of research methods through faculty and grad spotlights. Future developments include emphasis on student engagement activities such as using games to demonstrate learning of key terms used in research. We advocate these flexible, diverse learning strategies as applicable post-pandemic and beyond. 

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.280
GPT teacher head0.508
Teacher spread0.228 · 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 designNot applicable
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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