By Topic

The Use of Data Mining to Determine Cheating in Online Student Assessment

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Burlak, G.N. ; Centra de Investigation en Ingenieria y Ciencias Aplicadas, Univ. Autonoma del Estado de Morelos ; Hernandez, A. ; Ochoa, A. ; Munoz, J.

We can find several online assessment applications, Windows oriented or Web based, licensed or gnu free software, proprietary or standardized. All of them executing basic questions and test interoperability stages: providing assessment items, training and/or evaluation, and the assignment of a grade. Tons of information resulting of this educational process is stored into databases, including starting times, local or remote IP addresses, finishing times and, the student's behavior: frequency of visits, attempts to be trained, and preliminary grades for specific subjects, demographics and perceptions about subject under evaluation. We propose the use of data mining to identify students (persons) that commit cheat in online assessments (cyber cheats) and identify patterns to detect and avoid this practice

Published in:

Electronics, Robotics and Automotive Mechanics Conference, 2006  (Volume:1 )

Date of Conference:

Sept. 2006