MétaCan
Menu
Back to cohort
Record W2041741823 · doi:10.2298/csis111128019x

Exploring the use of contextual modules for understanding and supporting collaborative learning activities: An empirical study

2012· article· en· W2041741823 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

VenueComputer Science and Information Systems · 2012
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsWestern University
Fundersnot available
KeywordsWorkspaceComputer scienceCollaborative learningGroup workHuman–computer interactionComputer-supported collaborative learningCooperative learningKnowledge managementMathematics educationTeaching methodPsychologyArtificial intelligence

Abstract

fetched live from OpenAlex

We report three student groups? collaboration experiences in a semester-long classroom project. The project included both tasks that required completion in virtual group workspace and activities that could be carried out in the physical world environment. We observed different collaboration patterns among the groups with respect to building and maintaining social relationships, submitting individual work to the group, and scheduling group meetings. We use Bereiter?s two contextual modules, intentional learning and schoolwork, to help us understand the observed patterns and suggest that the group leader?s contextual module plays a significant role in all members? group learning experiences and outcomes. We propose design implications that are intended for encouraging learning-based (as opposed to work-based) practices in virtual group environments.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.008
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 head0.277
GPT teacher head0.376
Teacher spread0.099 · 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