Showing 1 - 4 of 4 Research Library Publications
Posted: | Janet Mee, Ravi Pandian, Justin Wolczynski, Amy Morales, Miguel Paniagua, Polina Harik, Peter Baldwin, Brian E. Clauser

Advances in Health Sciences Education

 

Recent advancements enable replacing MCQs with SAQs in high-stakes assessments, but prior research often used small samples under low stakes and lacked time data. This study assesses difficulty, discrimination, and time in a large-scale high-stakes context

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: | 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.

Posted: | D. Franzen, M. Cuddy, J. S. Ilgen

Journal of Graduate Medical Education: June 2018, Vol. 10, No. 3, pp. 337-338

 

To create examinations with scores that accurately support their intended interpretation and use in a particular setting, examination writers must clearly define what the test is intended to measure (the construct). Writers must also pay careful attention to how content is sampled, how questions are constructed, and how questions perform in their unique testing contexts.1–3 This Rip Out provides guidance for test developers to ensure that scores from MCQ examinations fit their intended purpose.