TUM community selects the best ideas for study and teaching
The winners of the TUM Future Learning Award 2023
In 2020, President Thomas F. Hofmann launched the TUM Future Learning Initiative. Its aim: giving the creativity of the university community a space to develop ideas for the teaching of the future. This year, the competition took place for the second time.
In March, the President called on all students and alumni to present their proposals for innovations in study and teaching. Numerous proposals were received and ten made it to the final. In an online vote, the TUM family decided which concepts were the most convincing. At the Dies Academicus, the President presented the winners of the TUM Future Learning Initiative 2023:
Cracking open exams
Knowledge is developing dynamically, and yet many exams are still static, testing what students have learned in an extensive end-of-term exam. Leonidas Askianakis wants to change this. With his “Beyond Exams” concept, he wants to enable new forms of performance assessment – through intermediate examinations, compulsory exercises, peer evaluation or lab practicals during the semester. This makes it easier to apply skills and knowledge in practice, improves learning success and reduces stress during the exam phase.
Making lectures more interactive
With his “Engaging Lectures” proposal, Ábel Sáfrán also wants to achieve greater flexibility: The 90-minute lecture blocks are to be restructured to facilitate individual access to the course content. An integrated digital platform is intended to support this and enable uncomplicated quizzes, surveys, tasks, or practical excercises. In this way, students can increase their ability to concentrate, receive immediate feedback and improve their learning and examination success.
Personalization through AI
At TUM, there are countless opportunities to further your education, get involved in student activities, or receive support. With their “TUM Navigator”, Team Edventure around Asfa Zaigham, Gabriela Cintra dos Santos and Razin Abdullah want to create a tool that ensures students never miss out on interesting opportunities. Based on a machine learning algorithm, the program provides personalized recommendations on courses, extracurricular activities, offers of assistancem, or scholarships - according to the individual student's interests.
Together with the university's departments, these concepts are now to be further developed and implemented. In this way, the teaching of the future will become the present of studies at TUM.
Technical University of Munich
- Konstantin Götschel – TUM Center for Study and Teaching
- goetschel@zv.tum.de
