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Record W4291178546 · doi:10.55849/jiltech.v1i2.82

Strategies for Parent Involvement During Distance Learning in Arabic Lessons in Elementary Schools

2022· article· en· W4291178546 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

VenueJournal International of Lingua and Technology · 2022
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsConcordia University
Fundersnot available
KeywordsActive listeningThe InternetProcess (computing)PsychologyDistance educationAsk priceData collectionMathematics educationMedical educationComputer scienceMedicineWorld Wide WebSociologyCommunicationBusiness

Abstract

fetched live from OpenAlex

This study aims to find various obstacles, describe, and provide strategies for parents when accompanying and providing direction to their children in distance learning. The method used in this research is the interview method. Interview, observation, listening, and note-taking techniques are data collection techniques used. The results of this study indicate that there are barriers for parents in distance learning. Among them are difficult internet signals, expensive internet quotas, and parents who are not able to fully guide and understand the material, so you have to ask your friends directly. The role of parents is very conducive to the academic success of a child. Always encourage and have innovations in child supervision so that children do not feel bored or even stressed in learning. There needs to be smooth coordination between parents and teachers. This assessment is needed to improve student learning outcomes. In the application of the home learning system, parents play an important role in the student learning process in the distance learning process at home today.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.034
GPT teacher head0.357
Teacher spread0.323 · 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