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Record W2744154447 · doi:10.5539/elt.v10n9p17

To Investigate ESL Students’ Instrumental and Integrative Motivation towards English Language Learning in a Chinese School in Penang: Case Study

2017· article· en· W2744154447 on OpenAlexvenueno aff
Yee Chee Hong, Malini Ganapathy

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyVocabularyContext (archaeology)Mathematics educationGrammarLanguage acquisitionPedagogyForeign languageQualitative researchLearner autonomyLanguage educationComprehension approachLinguisticsSociology

Abstract

fetched live from OpenAlex

Malaysians have long realised the importance of being competent in English as one of the success factors in attaining their future goals. However, English is taught as a second language in Malaysia, and it is not easy to teach under such a foreign context, because authentic input may not exist beyond the classroom, especially in Chinese private schools. In this scenario, English is learnt as a subject with 10 sessions per week, which is considered insufficient for students to master the language effectively. Past research highlights the significance of motivation in English language acquisition. Motivated students tend to put in more effort in their academic endeavours by showing more persistence in their learning process. The purpose of the study was to identify and analyse whether instrumental or integrative motivation plays a more important role in promoting Form Four ESL students’ English language learning. Furthermore, examine the areas of problems that affect ESL students’ motivation towards English language learning. This study was a qualitative case study that used focus group interviews to elicit data from 12 students in a secondary school in Penang. The findings of this research indicate that students are more instrumentally motivated than integratively motivated in ESL learning. Instrumental motivation is found to have a greater impact on students’ English language learning. This research also highlights that vocabulary and grammar are the biggest areas of problems that are encountered by students during their ESL learning process, which further influence their speaking and writing skills.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.350
Teacher spread0.333 · 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 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

Citations78
Published2017
Admission routes1
Has abstractyes

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