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Record W3217295046 · doi:10.37213/cjal.2021.31313

Does Prewriting Planning Positively Impact English L2 Students’ Integrated Writing Performance?

2021· article· en· W3217295046 on OpenAlex
Pakize Uludag, Kim McDonough, Caroline Payant

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Applied Linguistics · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversité du Québec à MontréalConcordia University
Fundersnot available
KeywordsPrewritingPsychologyMathematics educationPlan (archaeology)Multivariate analysis of varianceComputer scienceTeaching methodCooperative learning

Abstract

fetched live from OpenAlex

This study compared English L2 writers’ (N = 111) performance on an integrated writing task from the Canadian Academic English Language (CAEL) Assessment under three prewriting planning conditions: required self-timed planning required fixed time planning, and suggested (i.e., optional) planning. The participants’ integrated essays were scored according to the CAEL writing bands by raters at Paragon Testing Inc. The effect of planning condition on the participants' planning time, writing time, and integrated writing scores were analyzed using MANOVA. The student interviews were analyzed using thematic content analysis. The results indicated that planning time was the only variable impacted by planning condition, with students in the required self-timed planning condition taking more time to plan before beginning to write. Students’ perceptions about prewriting planning are discussed in terms of implications for the teaching and assessment of L2 integrated writing.

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.018
GPT teacher head0.259
Teacher spread0.240 · 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