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Record W1604204581

Voices from Chinese students: professors' use of English affects academic listening (1)

2004· article· en· W1604204581 on OpenAlexaboutno aff
Jinyan Huang

Bibliographic record

VenueCollege student journal · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningPsychologyPronunciationMathematics educationSlangCollege EnglishInformational listeningClass (philosophy)PedagogyLinguisticsListening comprehension
DOInot available

Abstract

fetched live from OpenAlex

Research in English for Academic Purposes has begun to show that non-native speakers of English have much difficulty in English academic listening at American universities. Chinese students, who are from a very different educational system and cultural environment, experience special challenges in English academic listening. This paper focuses on how American professors' use of English in class affects Chinese students' understanding of academic lectures. Seventy-eight Chinese students who enrolled in 2000 winter semester at an American university participated in this study. The results show that 1) rapidness of professors' English speech; 2) professors' lack of clear pronunciation; 3) professors' use of long and complex sentences; 4) professors' use of colloquial and slang expressions; 5) professors' lack of clear definition of terms and concepts; and 6) professors' use of discourse markers affect Chinese students' English academic listening at an American university. It offers important suggestions for American professors as how to make their lectures more accessible to Chinese students. ********** Academic Listening: Definition and Importance Academic listening involves listening and speaking tasks in university classes. According to Flowerdew (1995), it has its own characteristics and places special demands upon listeners. To be a successful academic listener, a student needs relevant background knowledge, ability to distinguish between important and unimportant information, and appropriate skills like note-taking, etc. Richards (1983) also suggests many micro-skills are required for listening to academic lectures: the ability to identify purpose and scope of a lecture, ability to identify topic of a and follow topic development, and ability to identify role of discourse markers in signaling structure of a lecture (p.229). Academic listening plays a very important role in a student's academic success. It plays an even more important role than academic reading or academic aptitude (Conaway, 1982). In a study by Powers (1985), American and Canadian professors of engineering, psychology, chemistry, computer science, English and business rated listening and speaking highest when asked to tell relative importance of listening, speaking, reading and writing for international students' success in their academic departments. The findings point to idea that academic listening plays a crucially important role in one's academic success. Research in English for Academic Purposes (EAP) has begun to show that non-native speakers of English have much difficulty understanding academic lectures at American universities. According to a study by Anderson-Mejias (1986), it is in listening rather than reading and speaking that non-native learners experience a great deal of difficulty. Ferris and Tagg (1996) investigated university professors' views on ESL students' difficulties with listening tasks. Instructors at four different institutions and in a variety of academic disciplines responded to questions and provided comments about their ESL students' listening skills. All respondents felt that their ESL students had great difficulty with comprehension, responding to questions, and class participation. Among ESL learners in American universities, Chinese students are largest group. Data from Open Doors (2000) shows that two world regions sending largest proportions of students to US are Asia and Latin America and students from China are largest single group. Chinese students, who are from a very different educational system and cultural environment, experience special challenges in understanding academic lectures in English. The question of which factors most affect their academic listening skills merits closer examination. This study is an evaluation of Chinese students' challenges in understanding English academic lectures at an American university. …

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: 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
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.037
GPT teacher head0.324
Teacher spread0.287 · 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

Citations42
Published2004
Admission routes1
Has abstractyes

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