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Record W1644366169

A visualization of group cognition: semantic network analysis of a CSCL community

2010· article· en· W1644366169 on OpenAlex

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.

Bibliographic record

VenueThe HKU Scholars Hub (University of Hong Kong) · 2010
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFormative assessmentComputer scienceSocial network analysisVisualizationOnline discussionKey (lock)Collaborative learningSemantic networkDiscourse analysisCognitionSemantic analysis (machine learning)Data visualizationCollective intelligenceKnowledge managementNatural language processingWorld Wide WebArtificial intelligenceSocial mediaPsychologyMathematics educationLinguistics
DOInot available

Abstract

fetched live from OpenAlex

This paper reports our progress in using the Knowledge Space Visualizer (KSV) as a tool for formative assessment of online discourse. Whereas social network analysis has been used in research on computer-supported collaborative learning, it only examines the social structure of discourse participants, and does not provide information about the content of the discourse. We discuss two types of networks as they relate to online discourse: structural and semantic. The initial findings indicate that the KSV can be used to visualize a Knowledge Forum database, and can provide a fine-grained semantic analysis that may enable teachers and students to locate the key ideas around which collective learning may takes place.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.328
Teacher spread0.291 · 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