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Record W3215260381 · doi:10.54583/apic.vol4.no1.68

Analisis Kelas Virtual Google Classroom Pada Pelatihan TIK Bagi Guru Madrasah Tsanawiyah Di Wilayah Kerja Kantor Kementerian Agama Kabupaten Labuhan Batu Selatan

2021· article· en· W3215260381 on OpenAlexaff
Gunarno Gunarno

Bibliographic record

VenueJurnal Analisa Pemikiran Insan Cendekia · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsChristian ministryClass (philosophy)Information and Communications TechnologyWork (physics)Medical educationPsychologyMathematics educationPedagogyLibrary scienceEngineeringComputer sciencePolitical scienceMedicineWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

Google Classroom Virtual Class Analysis on Information and Communication Technology (ICT) Training for Madrasah Tsanawiyah Teachers in the Work Area of ​​the Ministry of Religion, South Labuhan Batu Regency. This study aims to determine the description of the virtual google classroom that has been created by the trainee teachers in ICT Training for Madrasah Tsanawiyah Teachers in the Work Area of ​​the Ministry of Religion, Labuhan Batu Selatan Regency. The research subjects were participants in the ICT Training for Madrasah Tsanawiyah Teachers in the Work Area of ​​the Ministry of Religion, Labuhan Batu Selatan Regency, which was held from 11 until 16 January 2021 totaled 30 people, with 2 aspects observed, namely the general aspect and the accessibility aspect. This research method is descriptive research. Data was obtained through observation and then analyzed using mean analysis. The results of data analysis showed that 46.67% of the training participants had an eligibility value of the Google Classroom virtual class with the "Very Eligible" category, 53.33% of the training participants had a feasibility value in the "Eligible" category.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.308
Teacher spread0.282 · 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 designObservational
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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