Seminar: Current Topics in Learning Analytics
Investigating learning traces is currently highly required in e-learning environments. Due to the increasing variety of collectible student data in computer-based-learning and assessment environments, there arise new possibilities to improve both teaching and learning. To address these requirements and possibilities, different communities have evolved such as Learning Analytics and Educational Data Mining.
Different learning environments generate big amounts of educational data. The data types could be categorized into assessment data, collaboration data, communication data, and so on. The different data sources (e. g. learning platforms, games, assessment systems) could offer new insights into students’ learning trajectories and currently hidden problems in teaching and assessment.
The aim of Learning Analytics, therefore, is to obtain the most accurate information about a person's learning process and interactions with the learning environment. In the following step, the interpretation of the collected data could lead to an adaptive learning environment, i.e. the adaptation of the learning environment to the individual human. Furthermore, the collected data could be used to ensure the quality of the overall teaching and assessment process including learning materials and assessment methods.
The course and meetings will be held in English.
Interest in learning technologies.