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 Copy-Paste 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

A UX model for the evaluation of learners' experience on lms platforms over time

Although user experience (UX) is dynamic and evolves over time, prior research reported that the learners' experience models developed so far were only for the static evaluation of learners' experiences. So far, no model has been developed for the dynamic summative evaluation of the UX of LMS platforms over time. The objective of this study is to build a UX model that will be used to evaluate learners' experience on LMS over time. The study reviewed relevant literature with the goal of conceptualizing a theoretical model. The Stimuli-Organism-Response (SOR) framework was deployed to model the experience engineering process. To verify the model, 6 UX experts were involved. The model was also validated using a quasi-experimental design involving 900 students. The evaluation was conducted in four time points, once a week for four weeks. From the review, a conceptual UX model was developed for the evaluation of learners' experience with LMS design over time. The outcome of the model verification shows that the experts agreed that the model is adequate for the evaluation of learners' experience on LMS. The results of the model validation indicate that the model was highly statistically significant over time (Week 1: x2(276) = 273 I 9.339, Week2: x2(276) = 23419.626, Week3: x2(276) =18941.900, Week4: x2(276) = 27580.397, p=000<0.01). Each design quality had strong positive effects on the learners' cognitive, sensorimotor and affective states respectively. Furthermore, each of the three organismic states: cognitive, sensorimotor, and affective, had strong positive influence on learners' overall learning experience. These results imply that the experience engineering process was successful. The study fills a significant gap in knowledge by contributing a novel UX model for the evaluation of learners' experience on LMS platforms over time. UX quality assurance practitioners can also utilize the model in the verification and validation of learner experience over tim