Fachschaft Statistik
print
Links und Funktionen
Navigationspfad
Inhaltsbereich

AG Task Force Teaching

Introduction

Welcome to the AG Task Force Teaching of the Student Council at the Institute for Statistics. Our dedicated working group is committed to enhancing teaching quality through continuous dialogue, evaluation, and feedback between students and faculty. Here's how we make a difference:

  1. Round Table for Teaching (Runder Tisch der Lehre): We regularly convene with lecturers to discuss teaching-related issues at the Institute, fostering an open environment for improvement and innovation in educational practices.
  2. Active Teaching Evaluation Sessions: We provide lecturers with opportunities to gain deeper insights into students' perceptions of their courses. These sessions are instrumental in helping educators enhance their teaching methods and course delivery.
  3. Annual Student Questionnaire: Each year, we conduct a comprehensive survey to gather students' feedback on their academic experiences. This feedback is crucial for understanding the needs and concerns of students, and it guides our efforts in making meaningful improvements.
  4. Issue Resolution: We actively address and resolve student-reported issues related to exams or teaching, collaborating closely with lecturers to ensure that all students have a fair and positive learning experience.

Through these initiatives, the AG Task Force Teaching strives to create a dynamic and responsive educational environment that continually adapts to meet the evolving needs of our student community. We kindly ask resolute student council members who find our work interesting to join!

Contact Us

Dear fellow students,

if you have anything to share (complain) with us about the teaching & exam of a certain course held by the institute for statistics, don't hesitate to reach us at this email address: stat.teaching@fs.lmu.de. Group members of the AG Task-Force-Teaching will confidentially process your agenda.

Our Achievements

We also highlight some of our achievements here:

Results of the annual student questionnaire of 2023: please resort to the Presentation.pdf file for more details!

    • General Satisfaction and Workload: Approximately 80% of students reported satisfaction with their courses, finding the workload manageable and well-balanced.
    • Learning Formats: Students demonstrate a clear preference for methods such as tutor-led reviews and lecture repetitions, while Q&A sessions and student presentation are reported to be less helpful.
    • Discrimination: While the majority did not face discrimination, we continue to address and learn from individual reports to ensure inclusivity.
    • Teaching Methods: The community values innovative methods like the inverted classroom and self-study but emphasizes the importance of at least one live session weekly to maintain connection and engagement.
    • Exams and Course Feedback: We advocate for transparent grading and the availability of past exams to better prepare students. We set clear boundaries for old exam issues. Furthermore, there is a clear demand for math pre-course for master students, as well as advanced courses in data visualization and machine learning, which we are actively working to integrate into the curriculum.
Guidelines for Fair Exams: Over the past semester, our working group has been diligently working with faculty members to develop and refine the non-binding Guidelines for Fair Exams, aimed at formalizing and enhancing the fairness of examination practices within the institute. These guidelines, which have now been approved and adopted internally by the institute, serve as a comprehensive framework to ensure exams are conducted in a fair, reliable, and valid manner, truly reflecting students' knowledge and skills.
For a detailed understanding of these guidelines and their applications, we invite you to download and review the complete document, ExamGuidelines.pdf.

Downloads