An Assessment of IELTS Speaking Test

Karim, Shahzad; Haq, Naushaba

doi:10.11591/ijere.v3i3.6047

Cited by 8 publications

(19 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…IELTS speaking test with various tasks has content validity, matching the communicative requirements of the test. Speech functions like comparing, summarizing, explaining, suggesting, contrasting, narrating, paraphrasing and analyzing occur regularly in a candidate's output without the influence of external test structure [15].…”

Section: Content Validitymentioning

confidence: 99%

“…It scores on the predicted behaviour on a criterion which is expected to happen in the future. The relationship between the ability the test appears to measure and the performance predicted plays an indispensable role in the assessment of predictive ability [15]. However, according to Quaid [17], language production in the IELTS tasks (micro level) may not necessarily indicate the overall language adequacy (macro level).…”

Section: Predictive Validitymentioning

confidence: 99%

“…However, according to Quaid [17], language production in the IELTS tasks (micro level) may not necessarily indicate the overall language adequacy (macro level). Due to the same structures and content in general and academic oral tests, assessing general speaking ability in general context is easier than that in an academic context [15].…”

Section: Predictive Validitymentioning

confidence: 99%

“…Admittedly, IELTS speaking test meets the criterion of face validity. As mentioned in the literature review, there are two factors influencing face validity of a test: the familiarity of test format and authenticity in test task [15]. Therefore, the analysis of face validity of IELTS speaking test will follow this section as discussed below.…”

Section: Face Validitymentioning

confidence: 99%

“…Marker variability in IELTS speaking test which is a subjectively scored test is the inevitable outcome of rating procedure. From a rater perspective, inter-rater and intra-rater are two types of raters' grading [15]. Based on theory in the aforementioned literature review, inter-rater reliability refers to the consistency of different raters agreeing on the same performances, while intra-rater reliability refers to the consistency of the same rater repeating the same performance by applying the same criteria.…”

Section: Marker Variabilitymentioning

confidence: 99%

See 4 more Smart Citations

An Evaluation of IELTS Speaking Test

Li¹

2019

OALib

View full text Add to dashboard Cite

In this paper, an evaluation of IELTS Speaking Test was discussed in detail with the support of the brief introduction of purpose of a test, reliability and validity in a test and three eras of language testing. Focusing on examination contexts, both strength and weakness of IELTS Speaking test were discussed from perspectives of validity, reliability and practicality. To conclude, the IELTS speaking test is generally reliable and valid, although there are some controversial elements affecting the degree of reliability and validity, which would be further researched and discussed in this paper. Thereafter, possible suggestions were given following: 1) an intervention; and 2) video-conferencing delivery; and 3) double-marking method. IELTS Speaking Test is one particular module of the IELTS test, which is taken in different locations on the same or different day from listening, reading and writing test in the IELTS. By adopting face-to-face form, the candidate's performance is scored by the examiner only once and the whole process is recorded as a backup. Several weeks later, assessment results will be sent to candidates both online and by mail. In the whole process of testing, subjective elements such as marker performance and candidates' preferences will considerably influence assessment results.

show abstract

Section: Content Validitymentioning

confidence: 99%

Section: Predictive Validitymentioning

confidence: 99%

Section: Predictive Validitymentioning

confidence: 99%

Section: Face Validitymentioning

confidence: 99%

Section: Marker Variabilitymentioning

confidence: 99%

See 3 more Smart Citations

An Evaluation of IELTS Speaking Test

Li¹

2019

OALib

View full text Add to dashboard Cite

show abstract

Globalization and International Students: Re-modelling Micro-international Aspects for the Entrepreneurial University

Hancock

Moore

Stokes

2016

Innovative Business Education Design for 21st Century Learning

View full text Add to dashboard Cite

A Machine Learning Assessment System for Spoken English Based on Linear Predictive Coding

Wang

2022

Mobile Information Systems

View full text Add to dashboard Cite

In the teaching of English, there is an increasing focus on practical communication skills. As a result, the speaking test component has received more and more attention from education experts. With the rapid development of modern computer technology and network technology, the use of computers to assess the quality of spoken English has become a hot topic of research in related fields at present. A machine learning assessment system based on linear predictive coding is proposed in order to achieve automatic scoring of spoken English tests. First, the principle of linear predictive coding and decoding is analyzed, and the traditional linear predictive coding and decoding algorithm is improved by using hybrid excitation instead of the traditional binary excitation. Second, the overall structure of the machine learning assessment system is designed, which mainly includes division into four modules: acoustic model acquisition module, speech recognition module, standard pronunciation transcription module, and decision module. Then, the speech recognition module is implemented by an improved linear predictive speech coding method to acquire the feature parameters of the speech signal and generate the speech feature vector. Finally, the convolutional neural network algorithm is used to train the speech features so as to implement the acoustic model acquisition module. The experimental results show that the improved linear predictive speech coding method yields more natural and higher intelligibility speech signals. The designed machine learning evaluation system is able to accurately detect information about the quality of the learner’s pronunciation.

show abstract

An Assessment of IELTS Speaking Test

Cited by 8 publications

References 4 publications

An Evaluation of IELTS Speaking Test

An Evaluation of IELTS Speaking Test

Globalization and International Students: Re-modelling Micro-international Aspects for the Entrepreneurial University

A Machine Learning Assessment System for Spoken English Based on Linear Predictive Coding

Contact Info

Product

Resources

About