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Digitalisation has brought about societal and technological change across all areas of life. With its know-how, the ZHAW School of Engineering makes a crucial contribution to the digitalisation process, both in its education and continuing education programmes and its research and development activities.


Smart production sites and robots executing ever more complex tasks has a marked effect on the everyday work of engineers. They will increasingly plan, steer and monitor processes, solve problems and coordinate cross-disciplinary tasks, all of which requires solid digitalisation skills. This is why specialist skills and knowledge in Information Technology and Data Analysis are being taught from the first semester in all ZHAW School of Engineering degree programmes. Practical and, in part, interdisciplinary projects form a key part of the curriculum, fostering generic skills such as working in a team, communication skills as well as project and process management. In addition to conventional forms of learning and teaching, digital methods are being applied inteaching, among them interactive simulations, interconnected knowledge platforms and Virtual Reality environments.

Digital forms of teaching

Continuing Education

Digitalisation may open up a range of opportunities, but it also requires new business models, processes and customer relationships. Plants, systems and entire businesses are increasingly data driven. It is against this background that Data Science has evolved to be one of the key components in any successful transformation strategy. The ZHAW School of Engineering therefore offers a range of continuing education programmes in the fields of Data Science and Industry 4.0.

Continuing education programmes

"Intelligent interconnectedness not only plays an increasingly important role in industry, but in almost all areas of life."

Research and Development

Behind buzzwords such as Data Science, Deep Learning, Smart City or Industry 4.0, new areas of research explore the chances and risks of an intelligently interconnected world. The complexity of these topics requires knowledge from various disciplines and the ability to work together in expert networks. This is why the ZHAW School of Engineering has created theme-based platforms for researchers across specialisations to bundle their know-how. They support companies, institutions and the administration in their transformation processes and in the development of new models for both business and living.

Interdisciplinary Platforms



Allowing chatbots to talk to each other for research purposes

Machine dialogue systems should behave in a manner that is as human-like as possible. ZHAW researchers have now developed a new process for the reliable evaluation of such chatbots, enabling various systems to talk to each other and then be assessed.

Chatbots are already all around us in everyday life.

They answer burning questions in the area of customer support, provide assistance in connection with countless services or are perhaps simply intended to provide us with entertainment. As virtual contacts, chatbots are playing an ever more prominent role in everyday life. But how can we reliably assess which chatbots will prove to be human-like when engaged in dialogue? “Assessing conversations is fundamentally difficult – and even more so at the level of chatbots”, says Don Tuggener. Computational linguistics is one of his research areas at the ZHAW Institute of Applied Information Technology (InIT). “Until now, the evaluation of chatbots by people has been not only time-consuming and expensive, but also inconsistent. This is because each individual provides a subjective assessment on the basis of his or her own dialogue with the chatbot”, explains Tuggener.

Reproducible and reliable evaluation method

Within the framework of the EU LIHLITH research project, the researchers at the InIT have created a new basis for the evaluation of chatbots. “Spot the bot” is the name they give to their process in which various chatbots enter into dialogues with each another. “We let the chatbots talk to other chatbots instead of to people”, explains Jan Deriu, a doctoral student at the InIT. The conversations therefore develop automatically rather than having to be specifically guided by people. The conversation transcripts are then reviewed by people who have the task of identifying the bots. “We have, of course, also mixed in real conversations with people among the pure chatbot dialogues”, says Deriu. “And we have the dialogues assessed section by section, as every chatbot will be unmasked after a while. However, the longer it can fool people, the better the chatbot”.

«Until now, the evaluation of chatbots by people has been not only time-consuming and expensive, but also inconsistent».

ZHAW researcher Don Tuggener

Method successfully presented at international conference

The new process allows for chatbots to be reliably and efficiently evaluated by humans. “We have thus solved a major problem, as until now the evaluation of dialogue systems was expensive, inconsistent and difficult to reproduce”, says Pius von Däniken, a research assistant at the InIT. With their new method, the researchers received an honourable mention in the competition for the Best Paper Award at the EMNLP, one of the top international conferences in the field of natural language processing. “A total of 3,677 papers were submitted to the EMNLP with an acceptance rate of 22%”, says Don Tuggener, commenting on the success. “With our paper, we therefore effectively ended in the top five – not bad for a university of applied sciences up against international competition”.