Integrated Multimodal Copy-Paste Checking

Although the use of advanced computing and communications technology has made learning a significantly richer experience for learners, it also introduces greater ease in committing academic cheating. There is a growing increase of internet usage in educational communities. Powerful search engines and media gateways gives an ease of access to wide spreading and different types of information sources, this in turn reduces the need for learners to perform diligent research or study. A learner can easily copy information, found on the internet, relevant to the task at hand. E-learning systems would then need to incorporate extended functionalities to enable multimodal copy-paste checking. Besides the mere detection of text copy-paste activities, there is a need to determine deeper similarity relations in text and various other media formats. Furthermore, the introduction of a facility to monitor and check the student's ways of searching, reading and writing can improve the learning process. Our previous paper [1] describes the architecture and design of an integrated CopyPaste system aimed to provide a platform addressing these concerns. This paper extends the work and shows our pioneering explorations in extending student modeling capability of e-learning systems. We discuss the use of layered similarity assessment techniques to add value to conventional copy-paste detection systems.