Due to a high number of participants and limited human tutoring capacities, close supervision and human guidance is hardly possible in large online courses. Thus, the aim of the IKARion project is to develop methods for intelligent and automated diagnosis and intervention in online learning environments. In this paper, we present our distributed and autonomous feedback system aiming to improve team collaboration and interaction by means of interventions. The feedback system detects and diagnoses existing and emerging problems within the groups based on their interaction patterns. Based on principles of pedagogy and educational psychology, analysis metrics and appropriate measures are provided for different types of feedback including mirroring for exploratory and informative prompts providing appropriate information about progress and actual state for the teamwork, and guiding prompts aiming to modify the interaction and collaboration of a team or an individual student. The distributed feedback system consists of three essential components: Moodle-based learning management system along with various prompts implemented as Moodle plugins, Learning Analytics Backend, and Rule-based Intervention System based on an expert system. We describe, on an architectural level, the distributed feedback system and its components. As a result, we show measurements of two long term experiments carried out in two online courses at university level with a duration of one semester each. We conclude the paper with an outlook on future work.
|Titel||2019 18th International Conference on Information Technology Based Higher Education and Training (ITHET)|
|ISBN (Print)||978-1-7281-2465-0, 978-1-7281-2463-6|
|Publikationsstatus||Veröffentlicht - 09.2019|
|Veranstaltung||18th International Conference on Information Technology Based Higher Education and Training - Magdeburg, Deutschland|
Dauer: 26.09.2019 → 27.09.2019