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Record W2623789501 · doi:10.17161/iallt.v41i1.8487

Do Wikis Affect Grammatical Aspects of Second Language Writing

2011· article· en· W2623789501 on OpenAlexaff
Ulf Schuetze

Bibliographic record

VenueIALLT Journal of Language Learning Technologies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsGrammarClass (philosophy)GermanMathematics educationAffect (linguistics)Second language writingTask (project management)Computer scienceWord orderSyntaxTest (biology)PsychologyLinguisticsNatural language processingSecond languageArtificial intelligence

Abstract

fetched live from OpenAlex

This paper reports on a study that investigated the use of wikis in a first-year German as a second language class. The focus of the study was to analyze students’ use of grammar. Three classes of 24 students each participated in the study: one class using wikis and one class not using wikis to collaborate on two writing assignments; and one control group. Descriptive statistics as well as ANOVA were used to analyze the assignments as well as the writing components of two tests. Results showed the class using wikis benefited in their writing assignments regarding complex syntax (word order) but encountered problems with the same structures in a test. In addition, a short survey was carried out, asking students of the class using wikis about their experience, attitude and anxiety towards such a technology. Most students felt comfortable participating in a shared online writing task and thought that it helped their 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.

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)0.001
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.331
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueIALLT Journal of Language Learning TechnologiesSame topicWikis in Education and CollaborationFrench-language works237,207