Modelling and Using Response Times in Online Courses
Name
6063-Article Text-32408-3-10-20191214.pdf
Size
802.83 KB
Format
Adobe PDF
Checksum (MD5)
31e213f8795a4cf4fa557f655ee3bd88
Author(s)
Rushkin, Ilia
Chuang, Isaac
Tingley, Dustin
Date Issued
2019
Journal
Journal of Learning Analytics
Publisher
Society for Learning Analytics Research
Version
Final published version
Abstract
© 2019, UTS ePRESS. All rights reserved. Each time a learner in a self-paced online course seeks to answer an assessment question, it takes some time for the student to read the question and arrive at an answer to submit. If multiple attempts are allowed, and the first answer is incorrect, it takes some time to provide a second answer. Here we study the distribution of such “response times.” We find that the log-normal statistical model for such times, previously suggested in the literature, holds for online courses. Users who, according to this model, tend to take longer on submits are more likely to complete the course, have a higher level of engagement, and achieve a higher grade. This finding can be the basis for designing interventions in online courses, such as MOOCs, which would encourage “fast” users to slow down.
MIT Department
Massachusetts Institute of Technology. Department of Physics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.18608/JLA.2019.63.10
