Why learning remains important

Chennai, India, December 5, 2025 - When AI writes code, formulates texts, and delivers analyses in seconds, learning suddenly seems like a detour. Why invest years in studying and learning the basics when machines are faster? Andreas Lingnau, professor of computer science at the German University of Applied Sciences (DHAW), provided a clear answer to this question at the International Conference on Technology for Education (T4E) in Chennai.

INTERNATIONAL CONFERENCE, INTERNATIONAL RESPONSIBILITY
T4E is one of the key international forums for digital education. Every year, experts from teaching and research discuss technological possibilities and the responsibilities that come with them. With powerful AI, the focus is shifting away from simply producing results to the ability to critically examine them. Andreas Lingnau supported T4E in terms of content and organization as a member of the organizing committee and as one of three international outreach chairs. The Indian Institute of Technology Madras (IIT) provided the perfect setting for the conference.

REFUTE PROBLEMS: CRITICALLY EVALUATING AI OUTPUT
The focus of Andreas Lingnau's conference trip was a joint workshop with Prof. Viraj Kumar (International Institute of Science, Bengaluru) and Prof. Megha Sharma (Cambridge Institute of Technology, Bengaluru). The topic was Refute Problems: a task format that specifically trains judgment skills.

Students work with program code that delivers correct results for some examples and appears to be correct at first glance. Upon closer inspection, however, the code is flawed or incomplete and must be analyzed, questioned, and refuted with justification. This is not an artificial exercise: in the IT sector, further developing foreign code is part of everyday professional life. And with the increasing use of generative AI, professionals are increasingly faced with code that was not written by a human being. For this reason, Andreas Lingnau began a research collaboration last year with Prof. Viraj Kumar, who already has experience in this field. The goal is to use Refute Problems as a realistic exercise in his teaching at DHAW. In the workshop, he reported on his didactic goals. Students analyze AI-generated output, identify weaknesses, and justify their assessment. This makes Refute Problems more than just a didactic format. They show why academic education is more relevant today than ever before.

WHAT STUDENTS LEARN THROUGH REFUTE PROBLEMS
- Analyzing: reading, structuring, and understanding content
- Evaluating: classifying solutions professionally instead of adopting them
- Questioning: recognizing and testing assumptions
- Justifying: explaining decisions in a comprehensible manner
- Reflecting: using tools in a controlled manner
These future skills are central to the professional use of AI and are becoming an increasingly valuable qualification for starting a career.

ANDREAS LINGNAU: TEACHING WITH METHODS FROM PRACTICE
At DHAW, Andreas Lingnau already incorporates Refute Problems into the Programming 1 module, among others. He is also working on a concept to support students in solving tasks with the help of AI. His insights from international collaboration flow directly into his teaching and are adapted to the structures of online study. For Lingnau, this is the core of modern teaching: "It was once again an honor for me to serve on the organizing committee of the International Conference on Technology for Education (T4E) this year. I was also particularly pleased to be invited to give a workshop at IIT Madras on the special features of DHAW and the use of innovative teaching methods."

CONCLUSION: WHEN TOOLS ARE FASTER, UNDERSTANDING COUNTS
So is it still worth learning basics such as programming? Absolutely, says Andreas Lingnau. And not only that: he warns against the loss of genuine professional skills:

"Studies have already shown that the use of AI in teaching can lead to the risk of so-called de-skilling, i.e., the loss of skills. There are certainly tasks that we can assign to AI, but on the other hand, we must ensure that genuine professional skills are not lost at some point and that we do not become completely dependent on AI."

Future-oriented university teaching prepares students for an AI-driven world of work. With knowledge that makes a difference in professional life. And with future skills that remain when systems fail: analytical thinking, classification, reasoning, and responsible decision-making.

Suitable study programs and continuing education courses at DHAW (all in German):
- General Computer Science (B.Sc.)
- Artificial Intelligence (B.Sc.)
- Cyber Security (B.Sc.)
- Continuing Education in AI Management

Deutsche Hochschule f?r angewandte Wissenschaften (DHAW)
J?gerallee 26
14469 Potsdam
Germany

https://deutschehochschule.de/

Frau Marit Bolduan
+49 331 76 99 13 7

m.bolduan@deutschehochschule.de

The German University of Applied Sciences (DHAW) is a modern university with a clear vision. We want to teach first-class specialist knowledge that impresses with its quality, practical relevance, and topicality. Our aim is to provide you with the theoretical and practical tools you need for a successful career. This will ensure that our university's alumni are sought-after specialists on the job market.

This release was published on openPR.