Comparative study of the impact of information literacy, digital literacy and media literacy on employability between Indonesia and Malaysia
Bibliographic record
Abstract
The purpose of this research is to explore the relationships between information literacy, digital literacy, media literacy, Attitude toward use, and employability to examine the role of information and digital literacy in influencing employees' intentions to use technology in the workplace. The research sample for Indonesia was 250 respondents and for Malaysia there were 298 respondents. The data collection method uses Google Forms, distributed to respondents through purposive random sampling technique. The research results indicate that in Indonesia, Computer Literacy (CL) on Perceived Usefulness (PU), PU on Attitude towards Use (ATT), and ATT on Employability (EMP) have a big influence. On the other hand, Information Literacy (IL) and CL have a small influence on Employability. Likewise, Perceived Ease of Use (PEOU) has little influence on ATT. Malaysia, which has a big influence is Digital Literacy (DL) on Employability (EMP) and Perceived Ease of Use (PEOU). However, DL has a small influence on PU, as does IL on EMP, PEOU, and PU. Likewise, the influence of PEOU on PU is small.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| 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".