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Die Entwicklung von vollautomatisierten Fahrzeugen wird in der gesellschaftlichen Diskussion immer präsenter. Wichtig für die Durchsetzung und verbreitete Nutzung dieser technischer Neuerungen ist jedoch vor allem die Akzeptanz der Bevölkerung – in diesem Fall nicht nur die der potenziellen KäuferInnen sondern auch die der übrigen Verkehrs-teilnehmenden. Vorgestellt wird eine explorative Online-Studie zur Akzeptanz von auto-nomen Fahren basierend auf quantitativen und qualitativen Daten einer Stichprobe von N = 89. Die Ergebnisse zeigen unter anderem eine geringe Vertrautheit mit dem Thema, ein vergleichsweise ausgeprägtes Vertrauen aber eine geringe Nutzungsabsicht.
Resource Usage in Online Courses: Analyzing Learner’s Active and Passive Participation Patterns
(2015)
The paper analyzes the experience with an open university course for a very heterogeneous target group in which MOOC-like materials and activities were used. The course was conducted in a specifically prepared and extended Moodle environment. The analysis involves questionnaires as well as performance data that reflect the resource access on the learning platform. A special focus is put on the participants’ acceptance and usage of student-generated versus teacher-provided learning content. Network analysis techniques have been used to identify "interest clusters" of students around certain resources.
With the spread of mobile devices among both, men and women, app-based games also become more popular. While traditionally, digital games are more famous among men, women seem to spend more time and money on mobile gaming. There are a lot of open questions with regard to women and gaming in general; research on gender differences in app-based mobile gaming is almost nonexistent. Taking an exploratory perspective, our study investigates gender differences in general usage patterns, attachment towards the game and motivational differences for choosing to play the famous QuizClash app. Also, we identify differences in reported and actual performance in specific categories and capture anticipation of success as well as likeliness of choosing specific knowledge categories depending on the opponents’ performance profile.