Showing 1 - 9 of 9 Research Library Publications
Posted: | Victoria Yaneva (editor), Matthias von Davier (editor)

Advancing Natural Language Processing in Educational Assessment

 

This book examines the use of natural language technology in educational testing, measurement, and assessment. Recent developments in natural language processing (NLP) have enabled large-scale educational applications, though scholars and professionals may lack a shared understanding of the strengths and limitations of NLP in assessment as well as the challenges that testing organizations face in implementation. This first-of-its-kind book provides evidence-based practices for the use of NLP-based approaches to automated text and speech scoring, language proficiency assessment, technology-assisted item generation, gamification, learner feedback, and beyond.

Posted: | Erfan Khalaji, Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva

Behavior & Information Technology

 

This study builds upon prior work in this area that focused on developing a machine-learning classifier trained on gaze data from web-related tasks to detect ASD in adults. Using the same data, we show that a new data pre-processing approach, combined with an exploration of the performance of different classification algorithms, leads to an increased classification accuracy compared to prior work.

Posted: | Victoria Yaneva, Brian E. Clauser, Amy Morales, Miguel Paniagua

Advances in Health Sciences Education: Volume 27, p 1401–1422

 

After collecting eye-tracking data from 26 students responding to clinical MCQs, analysis is performed by providing 119 eye-tracking features as input for a machine-learning model aiming to classify correct and incorrect responses. The predictive power of various combinations of features within the model is evaluated to understand how different feature interactions contribute to the predictions.

Posted: | Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva, Simon Harper

ACM SIGACCESS Accessibility and Computing

 

In this article, we first summarise STA (Scanpath Trend Analysis) with its application in autism detection, and then discuss future directions for this research.

Posted: | P. Harik, R.A. Feinberg RA, B.E. Clauser

Integrating Timing Considerations to Improve Testing Practices

 

This chapter addresses a different aspect of the use of timing data: it provides a framework for understanding how an examinee's use of time interfaces with time limits to impact both test performance and the validity of inferences made based on test scores. It focuses primarily on examinations that are administered as part of the physician licensure process.

Posted: | M.J. Margolis, R.A. Feinberg (eds)

Integrating Timing Considerations to Improve Testing Practices

 

This book synthesizes a wealth of theory and research on time issues in assessment into actionable advice for test development, administration, and scoring. 

Posted: | M. J. Margolis, M. von Davier, B. E. Clauser

Integrating Timing Considerations to Improve Testing Practices

 

This chapter addresses timing considerations in the context of other types of performance assessments and reports on a previously unpublished experiment examining timing with respect to performance on computer-based case simulations that are used in physician licensure.

Posted: | D. Jurich

Integrating Timing Considerations to Improve Testing Practices

 

This chapter presents a historical overview of the testing literature that exemplifies the theoretical and operational evolution of test speededness.

Posted: | V. Yaneva, L. A. Ha, S. Eraslan, Y. Yesilada, R. Mitkov

IEEE Transactions on Neural Systems and Rehabilitation Engineering

 

The purpose of this study is to test whether visual processing differences between adults with and without high-functioning autism captured through eye tracking can be used to detect autism.