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Record W2625637360 · doi:10.5539/elt.v10n7p210

A Comparison of Students’ Performances Using Audio Only and Video Media Methods

2017· article· en· W2625637360 on OpenAlexvenueno aff
Norazean Sulaiman, Ahmad Mazli Muhammad, Nurul Nadiah Dewi Faizul Ganapathy, Zulaikha Khairuddin, Salwa Othman

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningPsychologyTest (biology)Mathematics educationAudio equipmentSample (material)MultimediaComputer scienceCommunication

Abstract

fetched live from OpenAlex

Listening is a very crucial skill to be learnt in second language classroom because it is essential for the development of spoken language proficiency (Hamouda, 2013). The aim of this study is to investigate the significant differences in terms of students’ performance when using traditional (audio-only) method and video media method. The data of this study were collected by giving students the same two sets of questions in pre-test and post-test. The data were then analysed with paired-sample t-test by using Statistical Package for the Social Sciences (SPSS). Based on the results attained, it was found that the majority of the students obtained higher marks when using video media method compared to audio only method. Hence, it is recognised that by using video as one of the assessment tools will help students to perform better due to the use of authentic, meaningful and real-life situation contexts and language. Therefore, instructors are advised to use more authentic texts and materials when it comes to teaching and assessing listening skills in second language (L2) classroom.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.071
GPT teacher head0.421
Teacher spread0.349 · 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 designNon-randomized trial
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

Citations9
Published2017
Admission routes1
Has abstractyes

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