Digital Literacy and Autonomous Learning in High School Students in Mexico
Bibliographic record
Abstract
The present study tested the relationship between digital literacy skills and autonomous learning strategies in high school students in southern Sonora to see their impact on the training processes implied by the digital age. A quantitative, non-experimental, cross-sectional study of correlational scope was conducted with 365 secondary school students, selected through a non-probabilistic sampling for convenience. The responses to the instrument were processed using Pearson’s correlation tests, scales, and reliability and validity analysis. According to the results, all the dimensions of the variables are significantly correlated with each other, with low, medium, and high positive forces. The levels of both variables were analyzed, thus giving medium and high levels. The findings suggest a significant relationship between digital literacy skills and autonomous learning strategies in students, specifically, those who demonstrated a high level of digital literacy also showed a greater ability to manage their learning autonomously. This suggests that digital skills facilitate access to information and enhance students’ ability to organize, plan, and evaluate their learning process.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".