Self-assessment of digital competences of Croatian students from The Faculty of Humanities and Social Sciences and Canadian students from The Southern Alberta Institute of Technology
Bibliographic record
Abstract
Suvremeni čovjek živi u digitalnom društvu. U takvom društvu biti pismen ne podrazumijeva samo znati čitati, pisati i računati, već pored ostalih kompetencija i digitalnu kompetenciju. Digitalna se kompetencija prema Europskoj komisiji smatra jednom od osam ključnih kompetencija. Ona podrazumijeva sigurnu, kritičku i kreativnu uporabu informacijske i komunikacijske tehnologije za postizanje ciljeva vezanih za rad, zapošljavanje, učenje, slobodno vrijeme te za uključivanje i/ili sudjelovanje u društvu. Stoga cilj ovoga istraživanje bio je ispitati razlike u samoprocjeni vlastite razine digitalnih kompetencija kroz pet područja između hrvatskih studenata s Filozofskog fakulteta u Splitu i kanadskih studenata sa Southern Alberta Institute of Technology. Za provedbu istraživanja napravljen je upitnik za hrvatske i kanadske studente. Upitnik je proveden na uzorku od 89 studenta s Filozofskog fakulteta u Splitu i na uzorku od 36 studenata sa Southern Alberta Institute of Technology. Rezultati istraživanja pokazuju da hrvatski studenti s Filozofskog fakulteta u Splitu samoprocjenjuju vlastitu razinu digitalnih kompetencija za pet područje boljom od kanadskih studenata sa Southern Alberta Institute of Technology. Rezultati još pokazuju da studenti integriranog studija na Filozofskog fakulteta u Splitu samoprocjenjuju vlastitu razinu digitalnih kompetencija za pet područje boljom od studenata dvopredmetnih studija na Filozofskom fakultetu u Splitu. Razlog tomu može biti činjenica što se u istraživanju koristila samo samoprocjena, a ne objektiva procjena poput testa znanja.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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; 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".