Quantitative Data Analysis for Language Assessment Volume II: Advanced Methods, 1st Edition (Hardback) book cover

Quantitative Data Analysis for Language Assessment Volume II

Advanced Methods, 1st Edition

Edited by Vahid Aryadoust, Michelle Raquel


248 pages

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Hardback: 9781138733145
pub: 2019-05-01
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Volume II of Quantitative Data Analysis for Language Assessment demonstrates advanced quantitative techniques for language assessment. The volume takes an interdisciplinary approach and taps into expertise from language assessment, data mining, and psychometrics. The techniques covered include Structural Equation Modeling, Data Mining, Multidimensional Psychometrics and Multilevel Data Analysis.Volume II is distinct among available books in language assessment, as it engages the readers in both theory and application of the methods and introduces relevant techniques for theory construction and validation. This book is highly recommended to graduate students and researchers who are searching for innovative and rigorous approaches and methods to achieve excellence in their dissertations and research. It is also a valuable source for academics who teach quantitative approaches in language assessment and data analysis courses.

Table of Contents


List of Figures

List of Tables


Part I. Advanced item response theory (IRT) models in language assessment

1. Mixed Rasch modeling in assessing reading comprehension (Purya Baghaei, Christoph J. Kemper, Samuel Greif & Monique Reichert)

2. Multidimensional Rasch models in first language listening tests (Christian Spoden & Jens Fleischer)

3. The Log-Linear Cognitive Diagnosis Modeling (LCDM) in second language listening assessment (Elif Toprak, Vahid Aryadoust & Christine Goh)

4. Hierarchical Diagnostic Classification Models in assessing reading comprehension (Hamdollah Ravand)

Part II. Advanced statistical methods in language assessment

5. Structural equation modeling in language assessment (Xuelian Zhu, Vahid Aryadoust & Michelle Raquel)

6. Growth modelling using growth percentiles for longitudinal studies (Daeryong Seo & Husein Taherbahi)

7. Multilevel modeling to examine sources of Variability in Second Language Test Scores (Yo In’nami & Khaled Barkaoui)

8. Longitudinal Multilevel modeling to examine changes in second language test scores (Khaled Barkaoui & Yo In’nami)

Part III. Nature-inspired data mining methods in language assessment

9. Classification and Regression Trees in predicting listening item difficulty (Vahid Aryadoust & Christine Goh)

10. Evolutionary Algorithm-Based Symbolic Regression to determine the relationship of reading and lexico-grammatical knowledge (Vahid Aryadoust)


About the Editors

Vahid Aryadoust is an Assistant Professor of language assessment literacy at the National Institute of Education of Nanyang Technological University, Singapore. He has led a number of language assessment research projects funded by, for example, the Ministry of Education (Singapore), Michigan Language Assessment (USA), Pearson Education (UK), and Paragon Testing Enterprises (Canada), and published his research in, for example, Language Testing, Language Assessment Quarterly, Assessing Writing, Educational Assessment, Educational Psychology, and Computer Assisted Language Learning. He has also (co)authored a number of book chapters and books which have been published by Routledge, Cambridge University Press, Springer, Cambridge Scholar Publishing, Wiley Blackwell, etc. He is a member of the Advisory Board of multiple international journals including Language Testing, Language Assessment Quarterly, Educational Assessment, Educational Psychology, and Asia Pacific Journal of Education. In addition, he has been awarded the Intercontinental Academia Fellowship (2018-2019) which is an advanced research program launched by the University-Based Institutes for Advanced Studies. Vahid’s areas of interest include theory-building and quantitative data analysis in language assessment, neuroimaging in language comprehension, and eye tracking research.

Michelle Raquel is a Senior Lecturer at the Centre of Applied English Studies, University of Hong Kong where she teaches language testing and assessment to postgraduate students. She has extensive assessment development and management experience in the Hong Kong education and government sector. In particular, she has either led or been part of a group that designed and administered large-scale computer-based language proficiency and diagnostic assessments such as the Diagnostic English Language Tracking Assessment (DELTA). She specializes in data analysis, specifically Rasch measurement, and has published several articles in international journals on this topic as well as academic English, diagnostic assessment, dynamic assessment of English second language dramatic skills, and English for specific purposes (ESP) testing. Michelle’s research areas are classroom-based assessment, diagnostic assessment, and workplace assessment.

Subject Categories

BISAC Subject Codes/Headings:
EDUCATION / Bilingual Education
EDUCATION / Testing & Measurement
PSYCHOLOGY / Assessment, Testing & Measurement