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Record W4393348882 · doi:10.51574/ijrer.v1i2.187

Problems of Learning Planning in The Time of The Covid Pandemic 19

2022· article· en· W4393348882 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

VenueETDC Indonesian Journal of Research and Educational Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Curriculum and Learning Methods
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VirologyGeographyMedicineInfectious disease (medical specialty)Outbreak

Abstract

fetched live from OpenAlex

This paper discusses learning planning during the COVID-19 pandemic. The purpose of this paper is to provide an overview of the solutions to the problems of learning planning during the COVID-19 pandemic and the ability of educators to formulate learning plans during the COVID-19 pandemic. The study's findings indicate that future learning and planning are crucial. The COVID-19 pandemic requires the ability of an educator to involve parents, pay attention to environmental conditions and the habits of students in their homes. Learning plans that involve parents as supervisors for each student in carrying out learning activities independently Likewise, with the environment and habits of students at home as a form of appreciation for the psychology of the development of students, learning planning can arouse interest and challenge the curiosity of every student towards 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.

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)0.027
metaresearch head score (Gemma)0.006
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 score0.606
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.163
GPT teacher head0.497
Teacher spread0.334 · 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