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Record W3209393940 · doi:10.36312/jime.v7i4.2448

Pengaruh Pembelajaran Daring Mahasiswa Dimasa Covid 19 Dalam Tugas Mempelajari Dan Menghafal Ayat-Ayat Alquran

2021· article· id· W3209393940 on OpenAlexaff
Bashori Hasan, Muhammad Ahsanul Habib, Cindy Mutiara Utami, Devania Agelita Andani

Bibliographic record

VenueJurnal Ilmiah Mandala Education · 2021
Typearticle
Languageid
FieldSocial Sciences
TopicCOVID-19 Prevention and Impact
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsPolitical scienceMathematics educationArtPsychology

Abstract

fetched live from OpenAlex

Pandemi Covid 19 menyebar sejak akhir tahun 2019 hingga kini di beberapa wilayah dengan kasus yang berbeda, terhitung 193 negara berjuang dengan keras untuk melawan covid yang tidak pandang bulu. Wuhan adalah salah satu kota di China sebagai tempat pertama kali virus ditemukan, sebelum virus ini lalu berstatus pandemi. Tentu sangat berpengaruh terhadap sosial ekonomi, khususnya bidang pendidikan, pelaksanaan sistem pembelajaran pada satuan pendidikan mengalami perubahan bentuk operasional yaitu intruksi social distancing, hingga berujung pada himbauan lockdown , sehingga model pembelajaran hampir di seluruh Indonesia dengan Model daring mulai daari lembaga pendidikan hingga Instansi Pemerintah. Penelitian ini menggunakan metode diskrptif kualitatif karena jauh lebih subyektif dalam pembelajaran daring di Universitas Duta Bangsa Surakarta yang diputuskan pembeljaran dari rumah. Subyek terdiri dari 2 dosen dan 2 mahasiswa Universitas Duta Bangsa Surakarta. Dengan aplikasi E-Learning UDB, Zoom, Google Meet, Whatsap, vidio call email dll, walaupun terdapat beberapa kendala diantaranya, sinyal internet, kuota , serta tidak bisa bertanya kepada dosen dengan leluasa.

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.

How this classification was reachedexpand

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.040
GPT teacher head0.384
Teacher spread0.344 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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