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Record W2943544114 · doi:10.1145/3300115.3309511

Experience Report

2019· article· en· W2943544114 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 Toronto
FundersOffice of Naval Research
KeywordsNoveltyPerspective (graphical)Relevance (law)Intervention (counseling)Diversity (politics)PsychologyComputer scienceMedical educationVideoconferencingKnowledge managementPedagogyMultimediaSocial psychologySociologyMedicine

Abstract

fetched live from OpenAlex

This paper details the experience of bringing an industry perspective to an introductory programming course, via "mini" interviews conducted during lectures using video conferencing. The novelty of this intervention comes from the frequency, duration and diversity of the industrial involvement. The use of video conferencing lowers the participation barrier for industry professionals and enables a broad range of volunteers to contribute. Our primary goal is to communicate the practical relevance of the materials we teach, and to motivate students to learn and practice course material. We discuss student feedback regarding these interviews collected via an optional, post-facto survey. While there was no quantitative evidence of improved learning outcomes, there was suggestive evidence that students found the interviews motivational, and appreciated learning more about available career paths. We conclude with recommendations to instructors who wish to adopt the intervention.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.552

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)0.0000.000

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 head0.011
GPT teacher head0.263
Teacher spread0.252 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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