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Record W2991721144 · doi:10.52266/tadjid.v3i2.295

TINGKAT LITERASI DIGITAL MAHASISWA KEGURUAN DALAM MENGHADAPI ERA REVOLUSI INDUSTRI 4.0

2019· article· id· W2991721144 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTAJDID Jurnal Pemikiran Keislaman dan Kemanusiaan · 2019
Typearticle
Languageid
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPsychologyHumanitiesArt

Abstract

fetched live from OpenAlex

Literasi digital merupakan suatu kemampuan soft skill yang selayaknya dimiliki mahasiswa guna menghadapi era revolusi industri 4.0. Sehubungan dengan hal tersebut, penelitian ini bertujuan untuk mengidentifikasi tingkat literasi digital mahasiswa keguruan dilihat dari aspek persepsi terhadap literasi digital, keterpaparan terhadap penggunaan teknologi digital, dan harapan terhadap pengembangan literasi digital. Penelitian ini merupakan penelitian lapangan (field research) yang bersifat kuantitatif. Populasi dalam penelitian ini adalah seluruh mahasiswa keguruan pada Prodi PGMI Fakultas Tarbiyah Institut Agama Islam (IAI) Muhammadiyah Bima, berjumlah 128 orang. Sampel dipilih dengan menggunakan teknik stratified random sampling sehingga diperoleh 30 mahasiswa sebagai sampel penelitian. Hasil penelitian menunjukan bahwa tingkat literasi digital mahasiswa keguruan Prodi PGMI Fakultas Tarbiyah Institut Agama Islam (IAI) Muhammadiyah Bima dilihat dari aspek persepsi terhadap literasi digital berada pada kategori sedang (63%), aspek keterpaparan terhadap teknologi digital menempati kategori rendah (33%), dan untuk aspek harapan terhadap pengembangan literasi digital masuk pada kategori sedang (42%).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0040.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.020
GPT teacher head0.268
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it