Response Time Effort

linear on the fly testing

Wise and Kong (2005) defined an index to flag examinees not putting forth minimal effort, based on their response time.  It is called the response time effort (RTE) index. Let K be the number of items in the test. The RTE for each examinee j is

response time effort

where TCji is 1 if the response time on item i exceeds some minimum cutpoint, and 0 if it does not. 

How do I interpret Response Time Effort?

This therefore evaluates the proportion of items for which the examinee spent less time than the specified cutpoint, and therefore ranges from 0 to 1. You, as the researcher, needs to decide what that cutpoint is: 10 second, 30 seconds… what makes sense for your exam?  It is then interpreted as an index of examinee engagement.  If you think that each item should take at least 20 seconds to answer (perhaps an average of 45 seconds), and Examinee X took less than 20 seconds on half the items, then clearly they were flying through and not giving the effort that they should.  Examinees could be flagged like this for removal from calibration data.  You could even use this in real time, and put a message on the screen “Hey, stop slacking, and answer the questions!”

How do I implement RTE?

Want to calculate Response Time Effort on your data? Download the free software SIFT.  SIFT provides comprehensive psychometric forensics, flagging examinees with potential issues such as poor motivation, stealing content, or copying amongst examinees.

 

Nathan Thompson, PhD

Nathan Thompson, PhD, is CEO and Co-Founder of Assessment Systems Corporation (ASC). He is a psychometrician, software developer, author, and researcher, and evangelist for AI and automation. His mission is to elevate the profession of psychometrics by using software to automate psychometric work like item review, job analysis, and Angoff studies, so we can focus on more innovative work. His core goal is to improve assessment throughout the world.

Nate was originally trained as a psychometrician, with an honors degree at Luther College with a triple major of Math/Psych/Latin, and then a PhD in Psychometrics at the University of Minnesota. He then worked multiple roles in the testing industry, including item writer, test development manager, essay test marker, consulting psychometrician, software developer, project manager, and business leader. He is also cofounder and Membership Director at the International Association for Computerized Adaptive Testing (iacat.org). He’s published 100+ papers and presentations, but his favorite remains https://scholarworks.umass.edu/pare/vol16/iss1/1/.

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