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Record W7033075103

The Past, Present, and Future Direction of Computer Science Curriculum in K-12 Education

2022· article· en· W7033075103 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies in Central America
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumThematic analysisTransformative learningCurriculum mappingCurriculum theoryField (mathematics)Subject (documents)State (computer science)
DOInot available

Abstract

fetched live from OpenAlex

This integrated article thesis provides an analysis of the past, present, and potential future state of Computer Science (CS) in K-12 education. Once implemented in optional courses at the secondary level, CS concepts and skills are now being integrated into other subject areas such as mathematics, science, and technology and other grades including K-8. This new state of K-12 CS education is explored through an analysis of 1) related theory reflected in the literature, 2) historical secondary school CS curriculum, 3) enrolment data and important issues related to equity, diversity, and inclusion, and 4) K-8 CS-related curriculum approaches currently being implemented in educational jurisdictions across Canada. The four articles in this dissertation employ a qualitative approach to research, drawing on a constructivist epistemology. Thematic Analysis is used in the comparative analysis of historical curriculum documents from Ontario and Document Analysis is used in comparing the various K-8 curriculum documents from across Canada. Together, the chapters included in this integrated article thesis provide a comprehensive analysis of K-12 CS education that supports educators, policy makers, and researchers in the field during a transformative time.

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.

How this classification was reachedexpand

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.045
GPT teacher head0.272
Teacher spread0.227 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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