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Record W6940849362 · doi:10.11575/ajer.v57i4.55527

An Analysis of Large-Scale Writing Assessments in Canada (Grades 5-8)

2012· article· en· W6940849362 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsWriting assessmentComposition (language)Professional writingPortfolioWriting processProcess (computing)Authentic assessmentAcademic writing

Abstract

fetched live from OpenAlex

This paper reports on an analysis of large-scale assessments of Grades 5-8 students’ writing across 10 provinces and 2 territories in Canada. Theory, classroom practice, and the contributions and constraints of large-scale writing assessment are brought together with a focus on Grades 5-8 writing in order to provide both a broad view of Canada-wide assessments and specific recommendations for enhancing the validity of provincial and territorial writing assessment in Canada. We deductively analyzed the primary assessment administration documents found on the provincial and territorial education websites using the categories of (a) design (e.g., grades at which the tests are written, the goals of the tests, the number and types of written compositions that are gathered, (b) administration (e.g., time of year, length of time provided to students to write, and pre-writing activities), and (c) the scoring of the assessments. We also used tenets of effective writing assessment from a process writing approach and from a multiliteracies approach to analyze the assessment procedures. Our analysis shows that process writing approaches have influenced the administration procedures in terms of the provision of time to talk with peers before writing and the recognition of various composition and thinking processes. However, composing processes are directed to be less idiosyncratic and recursive than composition theorists and noted teachers of writing would recommend. The assessments do not yet reflect an awareness of multiliteracies theory, as there is little use of digital technology to write and portfolio assessments and the collaborative writing of Web 2.0 practices are non-existent. Cet article fait état d’une analyse d’évaluations à grande échelle de rédactions d’élèves de la 5e à la 8e année dans 10 provinces et 2 territoires au Canada. Se penchant sur les rédactions écrites par des élèves de la 5e à la 8e année, nous réunissons la théorie, la pratique en salle de classe et les avantages et les contraintes liés aux évaluations à grande échelle pour élaborer un aperçu général des évaluations pancanadiennes et des recommandations spécifiques visant l’augmentation de la validité des évaluations de l’écriture dans les provinces et les territoires du Canada. Nous avons analysé par déduction les documents administratifs de l’évaluation principale tirés des sites Web d’éducation des provinces et des territoires. Notre analyse reposait sur les trois catégories suivantes : (a) conception (p. ex. niveau scolaire auquel on écrit les examens, objectifs des examens, nombre et type de rédactions exigées), (b) administration (p.ex. période de l’année, temps de rédaction accordée aux élèves, activités de pré-écriture et (c) évaluation des examens. Nous nous sommes également appuyés sur les principes de l’évaluation efficace des rédactions selon une approche processus et une approche axée sur la multilittératie pour analyser les procédures d’évaluation. Notre analyse démontre que les approches processus à l’écriture ont influencé les procédures administratives quant au temps accordé à la discussion avec les pairs avant l’écriture et quant à la reconnaissance de divers processus de rédaction et de réflexion. Toutefois, les processus d’écriture imposés sont moins idiosyncratiques et récursifs que des théoriciens de l’écriture et des enseignants éminents de la rédaction recommanderaient. Les évaluations ne reflètent pas encore une prise de conscience de la théorie de la multilittératie, l’emploi de la technologie numérique pour écrire étant très limité, et les évaluations de portfolios et l’écriture coopérative qui découle des pratiques de Web 2.0 étant inexistantes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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