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Record W2039050144 · doi:10.4018/jwltt.2011040102

An Exploration of the Social Web Environment for Collaborative Software Engineering Education

2011· article· en· W2039050144 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

VenueInternational Journal of Web-Based Learning and Teaching Technologies · 2011
Typearticle
Languageen
FieldComputer Science
TopicE-Learning and Knowledge Management
Canadian institutionsConcordia University
Fundersnot available
KeywordsContext (archaeology)Social softwareSelection (genetic algorithm)Computer scienceWeb 2.0SoftwareWeb applicationSocial webWorld Wide WebEmerging technologiesEngineeringKnowledge managementEngineering ethicsWeb serviceSocial media

Abstract

fetched live from OpenAlex

The technological environment in which software engineering education (SEE) resides and thrives continues to evolve. In this paper, SW4CSE2, a methodology for collaborations in SEE based on the Social Web environment, is proposed. The impact of integrating Social Web technologies, and applications based on these technologies, in collaborative activities that commonly occur in the context of SEE are explored. In particular, teacher–student and student–student collaborations, both inside and outside the classroom, are highlighted. In doing so, the feasibility issues in selection and adoption of technologies/applications are emphasized, and the use of pedagogically-inclined patterns is made. The potential prospects of such an integration, and related concerns, are illustrated by practical examples.

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)0.001
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: none
Teacher disagreement score0.797
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.023
GPT teacher head0.271
Teacher spread0.248 · 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