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Record W2806147561 · doi:10.33524/cjar.v18i3.355

WIKI’D TRANSGRESSIONS: SCAFFOLDING STILL NECESSARY TO SUPPORT ONLINE COLLABORATIVE LEARNING

2018· article· en· W2806147561 on OpenAlexaffvenue
Joshua P. DiPasquale

Bibliographic record

VenueThe Canadian Journal of Action Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsFacilitatorClass (philosophy)ImplementationStructuringCollaborative learningScaffoldComputer scienceCollaborative writingKnowledge managementPsychologyWorld Wide Web

Abstract

fetched live from OpenAlex

This paper is a reflection of my own individualistic participation in the EDUC 5001G: Principles of Learning (PoL) class wiki assignment. Specifically, I investigate the need for increased scaffolding strategies to facilitate direct collaboration among its participants. In order to do this, I first conducted a preliminary examination of the efficacy and suitability of wikis as tools for knowledge construction as well as some of the strategies that have been documented in their implementations. The examination revealed that although wikis have proven to be expedient tools to foster collaborative knowledge construction, the social aspects of the activity need to be reinforced in formal learning environments. Accordingly, an analysis of my own and other students’ behaviour, in different documented cases of wiki application, indicated that predispositions to work independently may be aggravating factors inhibiting the natural occurrence of collaborative events. Finally, my conclusions reiterated the critical role of the facilitator in scaffolding collaborative behaviour to overcome students’ inclinations to complete wiki assignments autonomously. Examples of scaffolding strategies discussed include: structuring wiki activities according to relevant theoretical frameworks, encouraging students to use existing avenues for communication and providing alternatives, and assigning students to specific and differentiated roles. This paper contributes to existing literature which has emphasized the need for an established framework to guide effective wiki implementation in formal education settings.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.191
GPT teacher head0.505
Teacher spread0.315 · 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 designNot applicable
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

Citations4
Published2018
Admission routes2
Has abstractyes

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