Comparison of Digital Technology Competencies among Mexican and Spanish Secondary Education Students
Bibliographic record
Abstract
<p class="apa">Information and Communication Technologies (ICT) are tools to be used to support educational processes and students have access to them more and more every day. However this does not assure the appropriate use of these tools. That is why the objective of the present study is to identify the level of competency in the use of ICT of students in secondary schools in Obregon City, Sonora, Mexico, in the opinions of the students themselves and of their teachers and to compare this with the level of digital competencies of students in some regions of Spain, using an investigation carried out earlier. Two questionnaires with 51 questions were used, one for 949 students and the other for 49 teachers. The results show that students claim to have between moderately and very high levels of competence in ICT skills while their teachers say the students have high levels of competence in some technological skills such as producing a written documents with a word processor. In the study in Spain, students and teachers voiced similar averages in the highest level of competencies, but differed in the competencies with the lowest averages.</p>
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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 | 0.000 | 0.001 |
| 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 | 0.002 |
| Open science | 0.001 | 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".