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Record W2086687355 · doi:10.1145/2591062.2591160

Lessons learned managing distributed software engineering courses

2014· article· en· W2086687355 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsUniversity of AlbertaUniversity of TorontoUniversity of Waterloo
Fundersnot available
KeywordsCapstoneComputer scienceSoftware engineeringCapstone courseSoftware developmentEngineering managementSet (abstract data type)Distributed developmentSoftware peer reviewSocial software engineeringSoftwareOpen-source software developmentSoftware Engineering Process GroupSoftware development processKnowledge managementEngineeringSoftware construction

Abstract

fetched live from OpenAlex

We have run the Undergraduate Capstone Open Source Projects (UCOSP) program for ten terms over the past six years providing over 400 Canadian students from more than 30 schools the opportunity to be members of distributed software teams. UCOSP aims to provide students with real development experience enabling them to integrate lessons they have learned in the classroom with practical development experience while developing their technical communication skills. The UCOSP program has evolved over time as we have learned how to effectively manage a diverse set of students working on a large number of different projects. The goal of this paper is to provide an overview of the roles of the various stakeholders for distributed software engineering projects and the various lessons we have learned to make UCOSP an effective and positive learning experience.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.695
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.280
Teacher spread0.254 · 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