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Learning analytics for sensor-based adaptive learning

Junior Research Group Neuro-cognitive plasticity
Federal Ministry of Education and Research
Project description

The ubiquitous availability of smartphones, tablets and tracking wristbands enables us to gather and process personal sensor data. It is unclear, however, how these sensor data can be used to create a personalized and adaptive learning experience. In the current project we examine whether metrics can be derived from sensors in order to support learning as well as teaching scenarios in different contexts of learning.

Learning analytics aim at analysing learning processes in order to foster successful learning and to increase deeper understanding of the learning process itself. Thus, learning analytics can provide valuable insights for teachers and institutions to identify problems in a learning process. However, learning analytics provide huge potential for the learner as well. In the current project LISA (Learning analytics for sensor-based adaptive learning) IWM, HU Berlin, and HTW Berlin focus on exploring and making use of learning analytics in different learning scenarios and target groups (university, self-regulated acquisition of basic knowledge, vocation and scenario specific knowledge transfer) of the three industrial partners. Moreover, we aim at extending the current state-of-the-art by utilizing smartphones, tablets and tracking wristbands to gather, process and feedback personal sensor-based data to support individuals’ learning processes. Providing information about individual learning habits and progress over time, but also momentary indicators of concentration and mood, enables the learner to acquire in-depth insight into learning process characteristics. This allows the learners to plan and evaluate the success of past learning sessions and enables them to adapt future learning sessions.

The IWM primarily focuses on project accompanied evaluation of the learning scenarios. Moreover, IWM is involved in the development of an innovative didactic concept to foster self-regulated learning.


Hochschule für Technik und Wirtschaft Berlin - Research Center for Culture and Computer Science (Prof. Dr. Albrecht Fortenbacher) 

Humboldt-Universität zu Berlin - Computer Science Education / Computer Science and Society (Prof. Dr. Niels Pinkwart) 

NEOCOSMO GmbH (Dr. Volker Zimmermann) 

SGM Solutions & Global Media GmbH (Dipl. Inform. Boris Groth) 

Promotion Software (Ralph Stock)