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Record W4244442687 · doi:10.32332/tapis.v2i1.1117

[no title]

2018· article· W4244442687 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

VenueTapis Jurnal Penelitian Ilmiah · 2018
Typearticle
Language
FieldSocial Sciences
TopicArabic Language Education Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsClass (philosophy)Mathematics educationArabicAction researchComputer scienceControl (management)PsychologyArtificial intelligenceLinguistics

Abstract

fetched live from OpenAlex

This study aimed to improve the memory of students of the Arabic Language Education Study Program at the Faculty of Education and Teacher Training in State Islamic University of Raden Fatah Palembang through Advance Organizer Learning Models based on concept maps. This experimental research employed 40 students consist of experimental and control class. According to Pre-survey data showed that students' average memory in the experimental class reached 4.59%, while the control class reached 4.45%. The target of this study was to improve the students’ memory until 81%. Data collection techniques was employed using action tests were then analyzed quantitatively. After being given a treatment using the Advance Organizer Learning Model based on Concept Maps, the memory of students in the experimental class was obtained 8.05%. Thus, it can be concluded that Advance Organizer Learning Model based on concept maps can improve student memory in Qowaid courses.

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)0.006
metaresearch head score (Gemma)0.004
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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0150.015
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.003

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 head0.033
GPT teacher head0.357
Teacher spread0.324 · 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