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Record W2115974590 · doi:10.5539/jel.v3n1p70

Reflecting the Process of Teaching and Listening in Two Different Approaches in Educational Philosophy

2014· article· en· W2115974590 on OpenAlexvenueno aff
Aminuddin Hassan, Norashikin Mohd Mokhtar, Norhasni Zainal Abiddin

Bibliographic record

VenueJournal of Education and Learning · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningPsychologyContext (archaeology)Process (computing)Mathematics educationPerspective (graphical)Quality (philosophy)Synchronous learningTeaching methodPedagogyExperiential learningCooperative learningComputer scienceEpistemologyArtificial intelligenceCommunication

Abstract

fetched live from OpenAlex

In the philosophical sense, learning should be enjoyable, fun, dynamic and engaging with access of a lot of sources. While philosophical perspective in the context of this writing is regarded as integral to reflecting the quality of learning in connection to the listening process, it is also an inclination of practice with deep understanding without limitation on the aspect of the learning process itself. The question of traditional classroom and online learning is important in the learning process. To produce high achievers in education, it is important to find out the best type of learning that we can provide for students. It differed on the type of strategy the higher learning institution students used but the frequency of applying the strategy between the groups of traditional classroom and of online learning are the same. The result showed that students that subscribed to traditional classroom performed better than those who subscribed to online learning. This could be due to the fact that less instruction was provided by the teacher in online learning consequently causing the inability within students to perform.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.013
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0030.040
Scholarly communication0.0130.009
Open science0.0010.007
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.001

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 head0.067
GPT teacher head0.406
Teacher spread0.339 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Quick stats

Citations2
Published2014
Admission routes1
Has abstractyes

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