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Record W4389941060 · doi:10.5539/jel.v13n1p111

The Implementation of Hybrid Learning at Islamic University of Nahdlatul Ulama (UNISNU) Jepara

2023· article· en· W4389941060 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Education and Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Curriculum and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsHybrid learningPreparednessIslamBlended learningComputer scienceMathematics educationMedical educationPsychologyEducational technologyGeographyManagement

Abstract

fetched live from OpenAlex

Islamic University of Nahdlatul Ulama (UNISNU) Jepara has been implementing hybrid learning which combines face-to-face and online learning for several years. This research investigated how hybrid learning is implemented in teaching and learning and how the facility is provided by institution to support the success of the hybrid learning implementation at UNISNU Jepara. Discriptive qualitative method is used in this reserch involving respondents of 18 head study programs and 180 students to collect data needed in this research. Survey, interview and FGD were used as instruments to collect the data. The result of the research revealed that the implementation of hybrid learning at all study programs at UNISNU Jepara has not run successfully and the factors causing this was the lack of preparedness of the lecturers and the support system provided by instution has not fully met the requirements as the success factors of hybrid learning implementation.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.380
Teacher spread0.360 · 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