Individualize learning through gamification and realtime dashboards
Booth #12
Lecturers can track the development of a course in real-time, while students have access to their progress with an individualized dashboard. The bonus system honours student activity by providing additional services and material.
Authors
Dr Lukas Emanuel Fässler, D-INFK, Lecturer Group
Dr Markus Dahinden, D-INFK, Information technology and education David Sichau, D-INFK, Lecturer Group
Oliver Probst, D-INFK, Computer Science Library
Abstract
Over the past 10 years, we have created engaging self-learning materials and a motivat-ing didactical model to teach our first semester natural science students in computer science, which opens the possibility to discover important basic digital literacy compe-tences on a scientific level. The aim of this project is to investigate how we can provide our learning materials and services for different student groups (e.g. novices, advanced, repeaters, etc.) on the basis of data from learning analytics. In order to achieve this goal, we have planned three complementary activities: Firstly, a gamification concept in the form of a bonus system is to be implemented for our courses. The idea is, that active learners are provided with attractive materials and services (e.g. repetition questions, mock exams, possibility for a preliminary grade, personal feedback on current perfor-mance, etc.) depending on their learning activity. In a second step, a student learning dashboard will be developed which is based on data from their learning analytics. It allows the visualization of the individual learning progress in small steps, so that even short activities lead to visible progress and put them into the context of the courses’ learning goals. Thirdly, another dashboard helps the lecturers to monitor learning progress of large distributed cohorts in real-time. As a basis for the above-mentioned developments, a framework for learning analytics has to be created, which allows the collection and aggregation of student data from different data sources. This new struc-ture could be of broad interest for many lecturers and learning professionals at ETH.