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Record W4390475483 · doi:10.31958/jt.v26i2.8527

Development of Teaching Materials in the Form of Daras Books Student Management Courses

2023· article· en· W4390475483 on OpenAlexaff
Herma Yulis Syam, Vicky Rizki Febrian, Wilma Rahmah Hidayati

Bibliographic record

VenueTa dib · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsValidatorADDIE ModelComputer scienceQuality (philosophy)Presentation (obstetrics)Mathematics educationMultimediaPsychologyPedagogyWorld Wide WebCurriculumMedicine

Abstract

fetched live from OpenAlex

This study aims to develop teaching materials in the Student Management Study Program to determine the feasibility of teaching materials in improving the quality of classroom learning. This research was development research adapted from the ADDIE model. There are five stages of this research, namely: 1. Analysis 2. Design, 3. Development, 4. Implementation, and 5. Evaluation. Validation was carried out by material experts, media experts, linguists, and practicality assessments from MPI students at UIN Mahmud Yunus Batusangkar. Based on the assessment of validators, the first material expert scored aspects of the material presentation 3.4 (85%), and the second material expert scored 3.6 (90%) of the maximum score of 4.0. The results from the first material expert validator in the aspects of content eligibility were 3.4 (85%), and from the second material expert aspects of content feasibility were 3.2 (80%) of the maximum value of 4.0. The validation results from the first media expert validator were 3.4 (85% and the second media expert was 3.4 (85%) from a maximum value of 4.0, namely in the aspect of language feasibility; all aspects of the validator regarding the textbook of student management have been suitable to use as learning media for student management courses in improving the quality of learning.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.142

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.056
GPT teacher head0.415
Teacher spread0.359 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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