06/2019 Proceedings

Rüdian, Silvio | Vladova, Gergana | Kazimizade, Gunay | Gundlach, Jana | Pinkwart, Niels

Predicting culture and personality in online courses


Online courses support learners to engage in distance learning. One emerging trend of the educational community is their personaliza- tion. Individual cultural characteristics and personality traits that influence individuals’ behavior in online courses have not yet been examined in detail. It is often practically impossible to collect a lot of personal information regarding personality or culture in online courses. Therefore, it is necessary to fill in a comprehensive ques- tionnaire. We show how accurately personality and cultural traits can be predicted by behavior in an online course. The paper reports exploratory data-informed work. We use a neural network with be- havioral data as input. In case of successful prediction, instructors can use these items to define targeting groups as a pre step for per- sonalization. Our results show, for example, that long-term orien- tation can be predicted best by an individual’s behavior. It corre- sponds to the ability and attitude of the individual to focus on the future. Learners with high long-term orientation will spend longer periods of time in class preparing to successfully complete related exercises. We discuss our findings from an interdisciplinary per- spective and propose perspectives for further research on personalization

Kategorie Proceedings
Autoren Rüdian, Silvio; Vladova, Gergana; Kazimizade, Gunay; Gundlach, Jana; Pinkwart, Niels
Bandtitel SLLL@AIED 2019
Datum 06/2019
Keywords personalization, online courses, e-learning, big five, personality, culture, machine learning