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Record W1570879941 · doi:10.22329/celt.v1i0.3191

22. The Writing Development Initiative: A Pilot Project to Help Students Become Proficient Writers

2008· article· en· W1570879941 on OpenAlexaffvenueabout
Sherry Fukuzawa, Cleo Boyd

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGrading (engineering)PsychologyMedical educationTeaching assistantGrant writingPedagogyMathematics educationMedicineLibrary scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

In 2005, the undergraduate advisory committee at the University of Toronto Mississauga found that across all disciplines, writing proficiency was the skill weakness that generated the greatest concern. Students reported that they often found writing tasks intimidating, and suggested that effective feedback and guidance would improve their writing. In response to these findings, the Dean’s office created the writing development initiative. Thirteen departments participated with a wide range of strategies to improve student writing. One successful participant was a first-year undergraduate course in biological anthropology (n=255 students and 7 teaching assistants). We created a writing improvement model that involved defined objectives for teaching assistants and additional contact hours between teaching assistants and students. These measures significantly improved the students’ writing skills. In addition, the intensive training and monitoring of teaching assistants’ grading by the instructor and director of the Robert Gillespie Academic Skills Centre contributed to a reduction in grading disputes. The success of the pilot project led to an extension of the writing development initiative for the 2006-2007 academic year.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.066
GPT teacher head0.374
Teacher spread0.308 · 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 designObservational
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

Citations5
Published2008
Admission routes3
Has abstractyes

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