Autor: Prof. Dr.-Ing. Prof. e. h. Wilhelm Bauer

Monitoring learners’ mental states via a passive Brain-Computer Interface (BCI) allows to continuously estimate current abilities, available cognitive resources, and motivation. It bears the great potential to adapt educational contents, learning speed, and format to the learner’s needs via an intelligent tutoring system. We present a neurophysiological-based approach to continuously monitor learners’ current affective-emotional and cognitive states by measuring and decoding brain activity via a passive BCI. In two studies (N = 8 and N = 7), we investigate whether we can a) predict learners’ affective and cognitive states during a learning or training session, b) provide continuous feedback of recognized states to the learner and, thereby, c) increase performance and intrinsic motivation. Oscillatory power measures in the alpha (8 – 12 Hz) and theta (4 – 7 Hz) frequency band served as features for the prediction and visualization. Our results reveal that machine learning ...

An important aspect for companies in dealing with the demands of the working world is the continuous and requirement-specific further training of employees. The possibility of workplace-related learning has a major importance in this context. In this context, digital assistance systems can be used to provide targeted support for the learning process. This paper presents current research findings from the funding priority "Work in the Digitalized world" on the use of digital assistance systems for competence development as well as on relevant design criteria for the development and implementation of workplace-related learning assistance systems. In addition, the article explores the question of what role artificial intelligence (AI) can play as a learning technology in in-house further training. In this context, the article highlights the challenges and associated design options for AI-supported learning in the process of work. Finally, the development and design of symbiotic ...