MétaCan
Menu
Back to cohort
Record W1973469398 · doi:10.1145/2512276.2512291

Computing is not a rock band

2013· article· en· W1973469398 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 institutionsMount Royal University
Fundersnot available
KeywordsVariety (cybernetics)Computer scienceInstitutionData scienceInformation technologyMathematics educationArtificial intelligencePsychologySocial scienceSociology

Abstract

fetched live from OpenAlex

This paper reports the initial findings of a multi-year study that is surveying major and non-major students' understanding of the different computing disciplines. This study is based on work originally conducted by Courte and Bishop-Clark from 2009 [7] and then repeated by Battig and Shariq in 2011 [3], but which uses a broadened study instrument that provided additional forms of analysis. Data was collected from 199 students from a single institution who were computer science, information systems/information technology and non-major students taking a variety of introductory computing courses. Results show that undergraduate computing students are more likely to rate tasks as being better fits to computer disciplines than are their non-major (NM) peers. Uncertainty among respondents did play a large role in the results and is discussed alongside implications for teaching and further research.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicTeaching and Learning ProgrammingFrench-language works237,207