Publikationen von Markus Krause

Plagiarism in online learning environments has a detrimental effect on the trust of online courses and their viability. Automatic plagiarism detection systems do exist yet the specific situation in online courses restricts their use. To allow for easy automated grading, online assignments usually are less open and instead require students to fill in small gaps. Therefore solutions tend to be very similar, yet are then not necessarily plagiarized. In this paper we propose a new approach to detect code re-use that increases the prediction accuracy by dynamically removing parts in assignments which are part of almost every assignment—the so called common ground. Our approach shows significantly better F-measure and Cohen's Kappa results than other state of the art algorithms such as Moss or JPlag. The proposed method is also language agnostic to the point that training and test data sets can be taken from different programming languages.

Many MOOCs report high drop off rates for their students. Among the factors reportedly contributing to this picture are lack of motivation, feelings of isolation, and lack of interactivity in MOOCs. This paper investigates the potential of gamification with social game elements for increasing retention and learning success. Students in our experiment showed a significant increase of 25% in retention period (videos watched) and 23% higher average scores when the course interface was gamified. Social game elements amplify this effect significantly – students in this condition showed an increase of 50% in retention period and 40% higher average test scores.

We present a novel way to recognize users by the way they press a button. Our approach allows low-effort and fast interaction without the need for augmenting the user or controlling the environment. It eschews privacy concerns of methods such as fingerprint scanning. Button pressing behavior is sufficiently discriminative to allow distinguishing users within small groups. This approach combines recognition and action in a single step, e.g., getting and tallying a coffee can be done with one button press. We deployed our system for 5 users over a period of 4 weeks and achieved recognition rates of 95% in the last week. We also ran a larger scale but short-term evaluation to investigate effects of group size and found that our method degrades gracefully for larger groups.