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Record W4237268742 · doi:10.28945/3299

Meaningful Learning in Discussion Forums: Towards Discourse Analysis

2009· article· en· W4237268742 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

VenueInforming Science and IT Education Conference · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsConcordia University
Fundersnot available
KeywordsReading (process)Discourse analysisQualitative analysisComputer scienceKnowledge managementCollaborative learningWork (physics)Knowledge buildingOnline discussionMathematics educationSociologyQualitative researchPsychologyWorld Wide WebPolitical scienceEngineering

Abstract

fetched live from OpenAlex

This document presents the analysis of a discussion forum used as a learning component in a ‘management information systems’ university course. By reporting on two macro level measures namely, participation and interaction, we seek to understand the occurrence of any collaborative knowledge-building activities/processes and at the same time work towards discourse analysis. Our analysis is based on the qualitative case study approach. Participation and interaction analysis from student usage of the discussion forum provide some insight into their learning and behavior in a virtual environment. Students spent time on reading forum discussions, reflecting and planning their contribution before posting it in the forum. Moreover, their participation behavior throughout the semester follows an s-curve, interestingly, typical in adoption theory studies.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.022
GPT teacher head0.382
Teacher spread0.360 · 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