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Record W2148674593 · doi:10.5539/ies.v7n2p10

Oral Academic Discourse Socialisation: Challenges Faced by International Undergraduate Students in a Malaysian Public University

2014· article· en· W2148674593 on OpenAlexvenueno aff
Omer Hassan Ali Mahfoodh

Bibliographic record

VenueInternational Education Studies · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
FundersUniversiti Sains Malaysia
KeywordsPresentation (obstetrics)Content analysisPsychologyQualitative researchPedagogySemi-structured interviewPublic speakingFace (sociological concept)SocializationMedical educationSociologyMathematics educationMedicinePolitical scienceSocial scienceDevelopmental psychology

Abstract

fetched live from OpenAlex

This paper reports a qualitative study which examines the challenges faced by six international undergraduate students in their socialisation of oral academic discourse in a Malaysian public university. Data were collected employing interviews. Students’ presentations were also collected. Semi-structured interviews were transcribed verbatim and qualitative content analysis was employed to examine the challenges faced by international undergraduate students in their socialisation of oral academic discourse. The results reveal that the major difficulties international undergraduate students face in their oral academic discourse socialisation are related to linguistic knowledge, presentation skills and content-related difficulties. Linguistic difficulties constrain students to express complex concepts and ideas while engaged in oral presentations. Difficulties related to presentation skills are associated with how to prepare PowerPoint slides and how to organise the content of the presentations. This study also reveals that content difficulties may be related to the specific topics the students are asked to prepare presentations on. In this study I argue that understanding the challenges faced by undergraduate international students in their oral academic discourse socialisation can be one of the essential steps to help them overcome the challenges they face.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.130
GPT teacher head0.399
Teacher spread0.269 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations18
Published2014
Admission routes1
Has abstractyes

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