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Record W6903592271 · doi:10.11575/ajer.v69i3.75299

The Growth of Computer Science Education in Alberta: An Analysis of High School Course Completion Trends

2022· article· en· W6903592271 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversity of Calgary · 2022
Typearticle
Languageen
FieldComputer Science
TopicTeaching and Learning Programming
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipCurriculumCourse (navigation)Science educationCurriculum development

Abstract

fetched live from OpenAlex

Computer Science (CS) education is an emergent growth area in schools worldwide. This paper explores how CS education has evolved at the high school level (grades 10–12) in the Canadian province of Alberta over the past decade after a reorganization and curriculum redesign of its Computing Science Education (CSE) program. In partnership with Alberta Education, a complete list of course records was obtained for high school students who had taken CSE course credits between 2009 and 2019. These course completions were analyzed for overall growth trends and then further examined with respect to course level, urbanicity, and gender. We found that growth in course credit completion has been consistent over the 10-year study period (annual average growth rate of 33.5%). Advanced course credits have grown faster than introductory course credits, urban areas have grown faster than rural areas, and gender growth rates have been similar for males and females. Understanding the growth rates of CSE course enrollments at the high school level will contribute to identifying some of the challenges encountered during the implementation of the CSE program of studies in Alberta. Keywords: High School Computer Science Education; Gender Participation. L'enseignement de l'informatique est un domaine de croissance émergent dans les écoles du monde entier. Cet article explore l'évolution de l'enseignement de l'informatique au niveau secondaire (10e à 12e année) dans la province canadienne de l'Alberta au cours de la dernière décennie, après une réorganisation et une refonte du programme d'études de l'informatique. En partenariat avec le ministère de l'éducation de l'Alberta, on a obtenu une liste complète des dossiers de cours pour les élèves du secondaire qui ont reçu des crédits pour des cours d’informatique entre 2009 et 2019. Ces cours ont été analysés pour déterminer les tendances générales de croissance, puis examinés plus en détail en fonction du niveau de cours, de l'urbanité et du sexe. Nous avons constaté que la croissance de l'obtention de crédits de cours a été constante au cours de la période d'étude de 10 ans (taux de croissance annuel moyen de 33,5 %). Les crédits de cours avancés ont augmenté plus rapidement que les crédits de cours d'introduction, les zones urbaines ont augmenté plus rapidement que les zones rurales, et les taux de croissance ont été similaires pour les hommes et les femmes. La compréhension des taux de croissance des inscriptions aux cours d'informatique au niveau secondaire contribuera à identifier certains des défis rencontrés lors de la mise en œuvre du programme d'études en informatique en Alberta. Mots clés : Enseignement de l'informatique au niveau secondaire ; participation des hommes et des femmes.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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