Showing 1 - 3 of 3 Research Library Publications

Reading Differences in Eye-Tracking Data as a Marker of High-Functioning Autism in Adults and Comparison to Results from Web-Related Tasks

Posted: | Victoria Yaneva, Le An Ha, Sukru Eraslan, Yeliz Yesilada, Ruslan Mitkov

Neural Engineering Techniques for Autism Spectrum Disorder: Volume 2, Pages 63-79

 

Automated detection of high-functioning autism in adults is a highly challenging and understudied problem. In search of a way to automatically detect the condition, this chapter explores how eye-tracking data from reading tasks can be used.

Category:Health Professions, Assessment-Oriented Research, Applications of Technology

Eye-Tracking Scanpath Trend Analysis for Autism Detection

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.

Category:Assessment-Oriented Research, Applications of Technology

The Optimal Number of Options for Multiple-Choice Questions on High-Stakes Tests: Application of a Revised Index for Detecting Nonfunctional Distractors

Posted: | M.R. Raymond, C. Stevens, S.D. Bucak

Adv in Health Sci Educ 24, 141–150 (2019)

 

Research suggests that the three-option format is optimal for multiple choice questions (MCQs). This conclusion is supported by numerous studies showing that most distractors (i.e., incorrect answers) are selected by so few examinees that they are essentially nonfunctional. However, nearly all studies have defined a distractor as nonfunctional if it is selected by fewer than 5% of examinees.

Category:Assessment-Oriented Research, General Measurement