Courses and seminars
Spring 2024
Introduction to Educational Technology and Learning Analytics
We are teaching an elective course open to any TUM student - this is the first offering of its kind at TUM. The course serves as a gentle introduction to educational technology and learning analytics - the buzz words you may have heard around new tools and data that enters classrooms in secondary schools, university, and workplaces. Just what is the history behind these tools? What kinds are there? What do we know about their effectiveness? Should they support adaptive curriculum? Or adaptive assessment? Or is it about scaling peer interactions? What about AI in education? The course will help you understand this landscape and equip you to think critically about these things and understand 'where to next' in your own ambitions around EdTech and the use of data in learning and teaching.
Educational Data Challenges
The course will provide students who have a limited background in analysing quantitative data with the opportunity to work with educational datasets where data comes from observed behaviours, digital traces, multimodal sources (audio or video, sensors), text, and so on. The course is taught in Spring 2023.
Advanced seminar: Dashboards in Educational Sciences: Design, Applications, Evidence
The course presents educational stakeholders with a broad view on dashboards in educational settings that are used to offer learners and teachers feedback they need to improve learning and teaching practices. The course reviews basic elements around the design, existing applications, and evidence of effectiveness of educational dashboards. The course is suitable for a wide range of educational researchers and practitioners regardless of their background in data science in education or learning analytics.
Advanced seminar: Social network analysis in educational research
The seminar focuses on the theory and methods of quantitative network analysis in educational research.
Fall 2023-2024
Learning Analytics: RTL specialization Link to the course
This course will introduce you to rapidly evolving field of learning analytics - the use of educational data science and educational technology to improve teaching and learning. Learning analytics is not just about the use of computational techniques applied to trace data from learning environments. It also considered the adoption processes within the classroom, or a school, a university, or a workplace. It is not just about data crunching, but also about understanding the ethical concerns embedded within the use of data in educational settings, it is about inquiring into the design of feedback systems, about making decisions with data in learning settings, and of course about understanding how these all help people learn better.
Introduction to Quantitative Methods (lectures and practical sessions in R) Link to the course
The module "Introduction to methods in Teaching and Learning Science" aims at facilitating the students basic quantitative methods in the field of empirical research methods. Basic knowledge is provided in the lecture "Introduction to quantitative methods". Further the acquired knowledge is applied and advanced through the attached exercise course which are adapted to the students' individual state of the knowledge. To test both theoretical knowledge and the advanced use of the research methods a written exam which includes the contents of both courses is necessary. Furthermore the lecture and the exercise are complemented by tutorial to compensate the students' different prerquisites.
Spring 2023
Introduction to Educational Technology and Learning Analytics (Course n 0000003531)
We are teaching an elective course open to any TUM student - this is the first offering of its kind at TUM. The course serves as a gentle introduction to educational technology and learning analytics - the buzz words you may have heard around new tools and data that enters classrooms in secondary schools, university, and workplaces. Just what is the history behind these tools? What kinds are there? What do we know about their effectiveness? Should they support adaptive curriculum? Or adaptive assessment? Or is it about scaling peer interactions? What about the MOOCs? And of course, how about a new kid on the block - the use of AI in the classroom as mnore applications of generative language models appear - such as chatGPT3? The course will help you understand this landscape and equip you to think critically about these things and understand 'where to next' in your own ambitions around EdTech and the use of data in learning and teaching.
Advanced Seminar: Learning Analytics
This advanced seminar offers students an opportunity to understand what learning analytics are and help them get started with research using learning analytics. The students will develop 'a starting kit' in mixed methods to work with process data, such as log data, text data, and interaction data that comes from learning environments. By the end of the course, the students will be able to associate research questions with selected types of analysis and will be able to apply selected learning analytics techniques to the data. The course is focused on analytical methods and hands-on experience working in R.