Pengembangan Modul Literasi Digital Etika Informasi Untuk Menguatkan Kemampuan Berpikir Kritis Siswa SD
Bibliographic record
Abstract
This research was motivated by the unavailability of digital literacy modules for elementary students regarding information ethics which can strengthen critical thinking skills.The research objective is to develop a digital literacy module for elementary school students using a project based learning model regarding information ethics.The research method used is research and development (R&D) with the ADDIE stages.This research involved several teachers in Java and outside Java for needs analysis, five validators for expert judgment, and ten fifth grade elementary school students as research subjects for the implementation of the information ethics digital literacy module.The research uses qualitative and quantitative data analysis.Needs analysis uses non-participatory observation, structured interviews, closed questionnaires.Meanwhile, during implementation, participatory observation, structured interviews, closed questionnaires and tests were used.The research results show, 1) the development of a digital literacy module on information ethics for elementary school students using the ADDIE stages, namely Analyze, Design, Develop, Implement, Evaluate.2) the information ethics digital literacy module has "very good" quality with an average score of 3.63 on a scale (1)(2)(3)(4).The modules developed can be used and applied by elementary school students.3) the information ethics digital literacy module developed helps students understand material regarding information ethics.The results of the observations carried out had an average score of 3.36 in the "very good" category.The structured interviews conducted showed that students were able to understand the material and were able to use the module.The results of the closed questionnaire obtained an average score of 3.66 in the "very good" category.The results of the student project regarding information ethics, students were able to create information according to facts with an average score of 3.36 in the "very good" category.The results of the pre test and post test showed an increase of 62% and 48%.
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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) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.165 | 0.002 |
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; both teacher heads agree on what is shown here.
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".