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Record W1495752035 · doi:10.22329/celt.v3i0.3238

8. Creativity and Writing: The Postcard Project

2010· article· en· W1495752035 on OpenAlexaffvenue
Mercedes Rowinsky-Geurts

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsCreativityFormative assessmentVocabularyClass (philosophy)Presentation (obstetrics)Mathematics educationPsychologyCreative writingExhibitionPedagogyComputer scienceVisual artsLinguisticsArtSocial psychology

Abstract

fetched live from OpenAlex

The purpose of the conference presentation upon which this paper is inspired was to present an innovative approach to motivate students to write in a second language during a first-year Spanish class. Usually, students comply with writing exercises that convey basic thoughts, due to constrained vocabulary and limited knowledge of grammatical concepts. The pieces they create are often simple repetitions of material already present in the textbook. In this case, the idea was to create a project that would be developed during the whole academic year. It consisted of creating a story of 100 words or less that would provoke the reader to think beyond the text and also motivate him/her to make connections between the title, the content, and the hidden message of the story. The format was a postcard, and the students had to add a creative piece of art on one side of the postcard and a story on the opposite side. The artwork was intended to add to the story. The objective of the project was for students to use their higher order cognitive abilities and subsequently realize higher levels of achievement (Burrowes, 2003; Railsback, 2002).The activity also aimed to encourage deeper student learning and self-regulated learning behaviours (Herington, 2008). The challenge was obvious: would students feel intimidated when presented with the project? How would they respond to the strict demands of the assignment? How would they deal with the creative aspect? How would they respond to formative feedback? How would they react to the public exhibition of their work? Throughout this article, responses to these queries are presented along with a discussion on how the activity could be applied across disciplines with similar end results. I hope this is the beginning of a productive dialogue.

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)0.004
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0400.015

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 head0.025
GPT teacher head0.390
Teacher spread0.365 · 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

Citations1
Published2010
Admission routes2
Has abstractyes

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