Fall 2024-2025

Learning Analytics: RTL specialization 0000003150
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) 0000001944/0000002350
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.

Master Seminar: Thesis Writing Practices 0000000943

This seminar is designed for Master’s students who are working on their master’s thesis  and the first-year PhD students who are beginning their work with empirical research in social sciences.

The primary aim of this seminar is to enhance students’ skills in scientific writing and academic research. Through bi-weekly sessions, students share their outlines and 2-3 drafts of their writing  and engage in peer feedback.Through these peer circles, the students will learn to both receive and provide constructive feedback, while developing an evaluative judgement of structural and style requirements in scientific writing. The seminar provides motivation and practice to support progress in writing first scientific work that includes elements such as  the literature review, methodology, results, and discussion.

Master Seminar: Methods in Learning Analytics 101/ 0000004966

This course is an advanced statistical course for social science students. We will cover some sections from the book "Learning Analytics Methods and Tutorials". This course provides an in-depth exploration of the core methods and techniques in Learning Analytics, with a strong emphasis on practicing data analysis. This course aims to help students develop a solid understanding of key concepts and analytical methods in data exploration, causal inference, and measurement handling within the field of learning analytics. Through classroom activities, students will have opportunities to apply these skills, enhancing their analytical fluency and critical thinking in data analysis.