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Record W2332363821 · doi:10.20360/g21p46

Revision and Participation Patterns in Grades 5 and 6 Wiki Writing

2016· article· en· W2332363821 on OpenAlexaffvenue
Christine Portier, Shelley Stagg Peterson

Bibliographic record

VenueLanguage and Literacy · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsParagraphSentencePsychologyMathematics educationWorkloadAction (physics)Quality (philosophy)LiteracyCollaborative writingPedagogyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Our study examined middle grade students’ participation in wikis during their two-month social studies unit co-taught by two teachers as part of a larger action research project. Using an analysis of 42 grades 5 and 6 students working together in eight wiki writing groups, we report on the frequency and types of revisions they made to collaboratively-written essays, and the distribution of the workload across group members in each of the wiki groups. Discussion data with 16 students from these wiki groups helps contextualize our analysis.Our findings suggest that given their extended time to write, students revised frequently, making replacements more often than they deleted, added or moved content. Students indicated a willingness to change others’ contributions and to have their own contributions revised by others in order to improve the quality of the essays. The majority of their revisions were at the word level, rather than at sentence, paragraph, and whole-text levels. One student in each group contributed significantly more frequently than any other group member. There were no gender or grade patterns in the frequencies or types of contributions that students made to the wikis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.643
Threshold uncertainty score0.105

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)0.0000.000

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 head0.013
GPT teacher head0.363
Teacher spread0.350 · 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.

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

Citations0
Published2016
Admission routes2
Has abstractyes

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