Showing 1 - 2 of 2 Research Library Publications

Detecting High-Functioning Autism In Adults Using Eye Tracking And Machine Learning

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.

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