Use of Data Mining to Determine Cheating in Online Student Assessment

are proposing a model to help organizations detect and prevent cheats in online assessments. First we analyze different student personalities, stress situations generated by online assessments, and the common cheating practices used by students to obtain a better grade on the exams. Following this discussion, we present our proposed DMDC (Data Mining to Detect Cheats) model. We will explain the components of our model. Next, we present the analysis of the designed database schema to register the student's information. In the following section, we will explain the use of Weka [2] to carry out data mining in order to find fraud behavior patterns that fits suspect profiles. Finally, we discuss the data preliminary obtained by the application of the proposed model in a real university environment and summarize our conclusions. There are several online assessment applications developed as per various technology specifications. All of them execute certain basic functions such as provid...

• Type: Conference
• Year: 2006
• Where: DMIN
• Authors: Alberto Ochoa, Amol Wagholikar
• Keywords: Data Mining, DMIN 2006, DMIN 2007, Online Assessments, Student's Behavior