MétaCan
Menu
Back to cohort
Record W2345586933 · doi:10.1145/2910925.2910936

Engagement and Sustainability in a Data Structures Course in C for Non-Specialists

2016· article· en· W2345586933 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicTeaching and Learning Programming
Canadian institutionsUniversity of British Columbia
FundersU.S. Consumer Product Safety Commission
KeywordsSustainabilityVariety (cybernetics)Course (navigation)Engineering ethicsComputer scienceSustainability scienceEngineering managementKnowledge managementEngineeringSocial sustainabilityArtificial intelligence

Abstract

fetched live from OpenAlex

This paper is an experience report that deals with engagement and sustainability in a data structures course in C for non-specialists. The course is offered annually to about 200 engineering students who are not in the computer engineering option. We describe and justify a variety of engaging and sustainable practices, and provide benefits and caveats from the lessons we learned. These may be useful to instructors who are interested in either creating such a course or using some of its practices, while trying to achieve both high engagement and high sustainability when teaching non-specialists.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.166

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 communication0.0000.000
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 head0.043
GPT teacher head0.341
Teacher spread0.298 · 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

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicTeaching and Learning ProgrammingFrench-language works237,207