Workshop C (1-day, in English)

Title: An Applied Introduction to No-Code Regression and Machine Learning
for Language Assessment

Vahid Aryadoust
National Institute of Education, Nanyang Technological University Singapore

Workshop Description 

     As Artificial Intelligence (AI) continues to advance at a remarkable pace, the field of language assessment must look beyond traditional methods to explore the potential of AI and machine learning (ML). Embracing these technologies is essential for adapting to technological shifts and understanding their impact on assessment practices. In response to this need, I am proposing a one-day workshop designed to teach no-code regression and ML, using JASP, a free software with a user-friendly graphical interface. Specifically, the workshop aims to provide language assessment professionals with practical tools and insights to running multiple linear regression in two ways: the statistical method and ML-based method. Next, the ML algorithm in JASP is used to compare the results of regression modeling and ML analysis in terms of fit, accuracy, precision etc.

     Some of the concepts and methods covered in this workshop include data preprocessing and preparation for regression analysis, understanding the principles behind multiple statistical and ML-based linear regressions, and their assumptions, conducting and interpreting multiple linear regression using traditional statistical methods, and exploring the fundamentals of ML algorithms as they apply to language assessment. By the end of the session, participants will gain a foundational understanding of integrating regression and ML into language assessment analytics and develop the skills necessary to make informed methodological choices in their research and practice. At the end, limitations of no-code machine learning are discussed, and further considerations are explored for when and how to incorporate code-based machine learning approaches for greater flexibility and customization.

     The primary participants for this workshop include language educators and assessment professionals, graduate students, and researchers interested in incorporating no-code machine learning into their practice. Participants must install JASP on their personal laptops before attending the workshop.

Presenter Biodata: 

Vahid Aryadoust is Associate Professor of language assessment at Nanyang Technological University in Singapore, with additional roles as Honorary Associate Professor at UCL, London, and Visiting Professor at Xi’an Jiaotong University, China. His research interests include generative AI in language assessment, meta-analysis, and sensor technologies such as eye tracking, brain imaging, and GSR. Dr. Aryadoust has published extensively in reputable journals and authored several books and book chapters with leading publishers. He has led numerous assessment research projects funded by educational institutions in Singapore, the US, the UK, and Canada. He serves on the Advisory Board of various international journals and was awarded the Intercontinental Academia Fellowship (2018–2019). Dr. Aryadoust has received ILTA’s Best Article Award (2024) for his research on sensor technologies in measuring cognitive load in listening assessment, NIE’s Teaching Excellence Award, NTU’s Teaching Award (School), among others. He is a proponent of knowledge-sharing and equity in education, exemplified by his YouTube channel “Statistics and Theory,” which won the John Cheung Social Media Award in 2020 for its innovative use of social media.