2026 ASEE Annual Conference & Exposition

KICK 4.0 - AI Chatting Skills in the Engineering Laboratory

Presented at Experimentation and Laboratory-Oriented Studies Division (DELOS) Poster Session

This article describes the KICK 4.0 project, which aims to successfully integrate natural language processing (NLP) systems into laboratory-based engineering education. The focus is on acquiring new skills in the critical and constructive use of AI systems, recognizing the potential and limitations of AI technologies, and generating AI tool responses that promote learning for students.
The aim of the project is to develop a real-world teaching and learning scenario for an ongoing course and to answer the following research questions with the participation of students and teachers: What skills are required for dealing with NLP AI? What are the strengths and limitations of NLP AI technology? How can users be supported in developing individual problem-solving skills and creative thinking? And how can the acceptance of AI technologies in the university environment be increased?
To this end, a chatbot was developed as a “digital assistant” using a design-based research (DBR) approach and integrated into a course on learning to use software for solving complex fluid mechanics calculations.
To achieve this, a requirements analysis was carried out based on a literature review according to Kitchenham and on target group surveys conducted through workshops and focus group discussions with students and teachers. The surveys were evaluated using qualitative content analysis methods as described by Mayring. Based on the results of the requirements analysis, an evaluation framework was developed and criteria for assessing the effectiveness of the chatbot in terms of competence enhancement and feedback quality were defined.
The chatbot was developed using the Retrieval-Augmented Generation (RAG) method. This method allows the information sources for the chatbot to be selected. Furthermore, system prompts make it possible to specifically influence the AI in order to generate individualized responses.
The current results show that students generally find the use of tools such as ChatGPT helpful. They particularly appreciate the immediate availability and ease of use. Teachers increasingly recognize the potential of AI tools as a means to improve the quality of their courses while saving resources.
Both students and teachers share concerns that the accessibility of AI tools—for example, due to potential costs—could limit equal opportunities for use. However, both groups also see great potential in AI tools to improve the organization of students’ learning processes.
Based on these findings, the developed chatbot is being enhanced through targeted system prompts to provide individualized and adaptive feedback to students.
This study aims to demonstrate that AI technologies can be applied in the context of laboratory-based teaching at universities. The results of the literature review show that previous research has primarily focused on model development and language-based tasks, revealing a research gap in engineering education and laboratory-specific applications.
The surveys of students and instructors indicate that NLP AI tools, such as ChatGPT, are perceived as having high potential for supporting individual learning processes. Likewise, instructors increasingly recognize the benefits of AI tools for improving their own courses. Overall, the acceptance of AI tools is steadily increasing as their integration into higher education continues to grow.

Authors

Johannes Kubasch University of Wuppertal [biography]

Johannes Kubasch is a mechanical engineer and research associate at the Chair of Technical and Engineering Education at the University of Wuppertal. As a engineer in automotive engineering, he initially worked in the automotive supply industry in the development of airbag systems before moving to the University of Wuppertal to work in the field of engineering education. In the past, he worked on the AdeLeBk.nrw project to digitize the university training of prospective teachers at vocational schools and to adapt the learning content to the requirements of later professional practice.
Dr. Dominik May http://orcid.org/0000-0001-9860-1864 University of Wuppertal [biography]

Dr. May serves as a Professor for Technical Education and Engineering Education Research at the School of Mechanical Engineering and Safety Engineering at University of Wuppertal. His work revolves around generating both fundamental and practical knowledge that defines, informs, and enhances the education of engineers.

His primary research thrust centers around the development, implementation, practical utilization, and pedagogical value of online laboratories. These laboratories span a range of formats, including remote, virtual, and cross-reality platforms. Dr. May's scholarly pursuits extend into the sphere of online experimentation, particularly within the context of engineering and technical education. Prior to his role at the University of Wuppertal, Dr. May held the position of Assistant Professor within the Engineering Education Transformations Institute at the University of Georgia (Athens, GA, USA).

Central to Dr. May's scholarly endeavors is his commitment to formulating comprehensive educational strategies for Technical and Engineering Education. His work contributes to the establishment of an evidence-based foundation that guides the continual transformation of Technical and Engineering Education. Additionally, Dr. May is actively involved in shaping instructional concepts tailored to immerse students in international study contexts. This approach fosters intercultural collaboration, empowering students to cultivate essential competencies that transcend cultural boundaries.

Beyond his academic role, Dr. May assumes the position of President at the "International Association of Online Engineering (IAOE)," a nonprofit organization with a global mandate to advocate for the broader advancement, distribution, and practical application of Online Engineering (OE) technologies. His leadership underscores his commitment to leveraging technological innovation for societal progress. Furthermore, he serves as the Editor-in-Chief for the "International Journal of Emerging Technologies in Learning (iJET)," a role that facilitates interdisciplinary discussions among engineers, educators, and engineering education researchers. These discussions revolve around the interplay of technology, instruction, and research, fostering a holistic understanding of their synergies.

Dr. May is an active member of the national and international scientific community in Engineering Education Research. He has also organized several international conferences himself – such as the annual "International Conference on Smart Technologies & Education (STE)" – and serves as a board member for further conferences in this domain and for several Divisions within the American Society for Engineering Education.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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