Self-Perception on Information Technology Skills of Pre-Service Teachers from the Point of View of Their Programs
Bibliographic record
Abstract
This article presents the initial results of a survey on the IT skills of prospective teachers of different teaching programs of the faculty of pedagogy of Dalat university (Vietnam). These students have no academic IT training in their curriculum, so the objectives of this survey were (1) to find out their self-perception about the skills IT they use almost every day but without a specific course, and (2) to identify specific profiles according to the different programs and to make a comparison between them. The survey has been conducted through the Internet, using Google Forms, and the responses were anonymous. The questions were focused on their self-perception on their skills regarding media processing (images, sounds, and videos) and website creation. 72 responses were received among which 70 were valid. The results show that there is not a significant difference between the student’s self-perception skills according to their programs whereas there are differences according to the kind of the media processing skills.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".