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Record W2320224244 · doi:10.1177/1541344614538521

Connecting Critical Theory of Technology to Educational Studies

2013· article· en· W2320224244 on OpenAlex
Matthew Krüger-Ross

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

VenueJournal of Transformative Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTransformative learningInstrumentalismEducational technologySociologyEducation theoryCritical theoryLearning theorySituatedEpistemologyEducational researchPedagogyEngineering ethicsHigher educationComputer scienceEngineeringPolitical science

Abstract

fetched live from OpenAlex

In this article, I explore how transformative learning theory, an approach to educating drawn from adult education, can be used to provide access to the critical theory of technology for educators. Rather than focusing primarily on K–12 teachers and educational systems or higher education and other postsecondary instruction, I connect learning as a human capacity with the critical approach to technology. Beginning with a discussion of assumptions and how they structure our ability to make meaning within two common perspectives on technology, instrumentalism and substantivism, an overview of the basic framework of the critical theory of technology is shared and situated among the assumptions made by current perspectives toward technology. Transformative learning theory is then presented as a possible connective thread that could be used to assist educational researchers and practitioners embrace a more critical approach to technology in education.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.421
Teacher spread0.393 · 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