Technophilia vs. Technophobia: A Preliminary Look at Why Second-Language Teachers Do or Do Not Use Technology in Their Classrooms
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.
Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it