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Record W2587082844 · doi:10.5539/elt.v10n3p54

Visual Learning: A Learner Centered Approach to Enhance English Language Teaching

2017· article· en· W2587082844 on OpenAlexvenueno aff
Andrew Philominraj, David Jeyabalan, Cristian Vidal-Silva

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyProcess (computing)Selection (genetic algorithm)Mathematics educationLanguage acquisitionEmpirical researchVisual learningTeaching methodExperiential learningPedagogyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This article presents an empirical study carried out among the students of higher secondary schools to find out how English language learning occurs naturally in an environment where learners are encouraged by an appropriate method such as visual learning. The primary data was collected from 504 students with different pretested questionnaires. A selection of a series of variables is taken into consideration in the survey, which is measured and information of each one is collected to describe what is researched. The results indicate that visual learning is an essential part of the overall experience that the learners gain towards their process of language learning. Also, it constitutes a vital process of ‘Input and Interaction’ for the learner ensuring that his needs, necessities and aspirations are taken into account and by making him involved, produce genuine 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)0.003
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.300
Teacher spread0.281 · 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.

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".

Quick stats

Citations39
Published2017
Admission routes1
Has abstractyes

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