Unterrichtsentwicklung durch Wettbewerbe: Analyse zweier Informatikwettbewerbe für den Schulunterricht

When the first PISA-results were published in Germany in the end of 2001 (“PISA-Shock”), many discussions started about reforming teaching with the help of new ideas and innovative approaches. Around the same time, the number of competitions in German schools started to grow immensely. Although many schools have taken part in such competitions, we are lacking studies investigating their potential. Only as recent as 2006, a scientific meeting was held at the Körber-Forum in Hamburg called “Why competitions for pupils? Impulses for education and learning”, which initiated a wider and more systematic discussion about the meaning of competitions at school and in teaching. Two competitions in computer science – the Movingart-Competition for the lower secondary school ages and the Software Challenge for the senior years, both organized by the computer science department of Kiel University – are investigated in this dissertation as to whether and how far they represent useful tools in the development of teaching. The findings show that both competitions offer new and important impulses for teaching in its structure and its organization: pupils develop more competences, their motivation rises, and they get deeper insights into the subject; teachers start cooperations across different subjects and receive more options for adapting their teaching to invidual pupils. Thus, both competitions offer a great contribution to improve the quality of teaching and strongly offer the schools taking part an increased educational benefit. It is to be presumed that new future competitions for schools which are constructed in the same or a comparable way as Movingart and Software-Challenge will contribute in a similar improving way to the quality of teaching

Context based learning: a survey of contextual indicators for personalized and adaptive learning recommendations. A pedagogical and technical perspective

Learning personalization has proven its effectiveness in enhancing learner performance. Therefore, modern digital learning platforms have been increasingly depending on recommendation systems to offer learners personalized suggestions of learning materials. Learners can utilize those recommendations to acquire certain skills for the labor market or for their formal education. Personalization can be based on several factors, such as personal preference, social connections or learning context. In an educational environment, the learning context plays an important role in generating sound recommendations, which not only fulfill the preferences of the learner, but also correspond to the pedagogical goals of the learning process. This is because a learning context describes the actual situation of the learner at the moment of requesting a learning recommendation. It provides information about the learner current state of knowledge, goal orientation, motivation, needs, available time, and other factors that reflect their status and may influence how learning recommendations are perceived and utilized. Context aware recommender systems have the potential to reflect the logic that a learning expert may follow in recommending materials to students with respect to their status and needs. In this paper, we review the state-of-the-art approaches for defining a user learning-context. We provide an overview of the definitions available, as well as the different factors that are considered when defining a context. Moreover, we further investigate the links between those factors and their pedagogical foundations in learning theories. We aim to provide a comprehensive understanding of contextualized learning from both pedagogical and technical points of view. By combining those two viewpoints, we aim to bridge a gap between both domains, in terms of contextualizing learning recommendations