Data Analytics for informal learning in school settings
Supervisors: Prof. Dr. Ralph Ewerth, Prof. Dr. Sascha Schanze and Prof. Dr. Andreas Nehring
Nowadays, pupils have the opportunity to acquire knowledge in many different ways. In addition to formal teaching units, informal web offers (e.g. Wikipedia, Youtube etc.) are often used to acquire or deepen new knowledge.
This doctoral projects focuses on the investigation of subject-oriented search behaviour of school pupils. To this end, subject-specific learning scenarios will be developed (in close cooperation with experts from educational sciences), and, respectively, studies will be conducted with pupils in local schools. The recorded data will be analysed with respect to the students’ individual learning prerequisites, behavioural patterns and the achieved learning outcomes. Consequently, the objective is to identify specific prerequisites and behaviours which favour successful learning and thus, should be specifically promoted by learning platforms and teachers.
Some existing studies propose metrics for the assessment of learning goals and knowledge gain and provide a base for the planned research (Gadiraju et al. 2018, Yu et al. 2018). The aim is to investigate their transferability to school contexts, and to adapt and develop them in a suitable manner.
Gadiraju, U., Yu, R., Dietze, S., & Holtz, P. (2018). Analyzing Knowledge Gain of Users in Informational Search Sessions on the Web, full research track paper at ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR2018), New Brunswick, NJ, US, 11-15 March 2018, ACM.
Yu, R., Gadiraju, U., Holtz, P., Rokicki, M., Kemkes, P., & Dietze, S. (2018). Predicting User Knowledge Gain in Informational Search Sessions, full research track paper at 41st Int. ACM SIGIR Conference on Research and Developmen