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Record W2070847246 · doi:10.3138/cmlr.56.3.389

Technophilia vs. Technophobia: A Preliminary Look at Why Second-Language Teachers Do or Do Not Use Technology in Their Classrooms

2000· article· en· W2070847246 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicSubtitles and Audiovisual Media
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyResistance (ecology)Mathematics educationPedagogy

Abstract

fetched live from OpenAlex

Given the increasing pressure exerted by technological developments on education, it is important to understand the perceived ‘technophobia’ of teachers and to determine whether fear is the underlying factor behind their decisions regarding technology. Oral interviews were conducted with 10 L2 teachers and analyzed for their content in light of the following questions: (1) What are the reasons behind L2 teachers' decisions to use technology for teaching? (2) Why do some L2 teachers choose not to use computers in their teaching? (3) What factors influence these decisions? The main reasons are related to the teacher's personal belief in technology's benefits, or lack thereof, rather than to a resistance to technology. This finding suggests that teachers are not really ‘technophobic’ and that institutions are perhaps overly ‘technophilic’ in their rush to obtain the latest innovations without considering the needs of teachers and students.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.000

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 head0.019
GPT teacher head0.221
Teacher spread0.202 · 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