Institut für Wirtschaftsinformatik
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Publikation An early warning system that combines machine learning and a rule-based approach for the prediction of cancer patients’ unplanned visits(Sun SITE Central Europe, 2023) Witschel, Hans Friedrich; Laurenzi, Emanuele; Jüngling, Stephan; Kadvany, Yannick; Trojan, Andreas; Martin, Andreas; Fill, Hans-Georg; Gerber, Aurona; Hinkelmann, Knut; Lenat, Doug; Stolle, Reinhard; van Harmelen, Frank04B - Beitrag KonferenzschriftPublikation LLMs in automated essay evaluation: a case study(AAAI Press, 03/2024) Kostic, Milan; Witschel, Hans Friedrich; Hinkelmann, Knut; Spahic, Maja; Petrick, Ron; Geib, Christopher04B - Beitrag KonferenzschriftPublikation ChEdBot: designing a domain-specific conversational agent in a simulational learning environment using LLMs(AAAI Press, 2024) Martin, Andreas; Pande, Charuta; Witschel, Hans Friedrich; Mathez, Judith; Petrick, Ron; Geib, Christopher04B - Beitrag KonferenzschriftPublikation Semantic verification in large language model-based retrieval augmented generation(AAAI Press, 2024) Martin, Andreas; Witschel, Hans Friedrich; Mandl, Maximilian; Stockhecke, Mona; Petrick, Ron; Geib, Christopher04B - Beitrag KonferenzschriftPublikation Using generative artificial intelligence in university teaching(Springer, 2024) Kaufmann, Carla; Schmiedel, Theresa; Christen, Patrik; Abraham, Ajith; Bajaj, Anu; Hanne, Thomas; Hong, Tzung-Pei04B - Beitrag KonferenzschriftPublikation An intelligent platform-based tool for the development of digital transformation strategies(Elsevier, 2024) Gatziu Grivas, Stella; Hanne, Thomas; Imhof, Denis; Bugmann, Diego; Schmitter, PaulDigital transformation strategies are of elementary importance for organizations competing in the digital age. Challenges such as faster changing customer needs, new value creation structures in digital eco-systems, or the use of collective intelligence to innovate business models require leveraging digital technologies. To achieve this and remain competitive, appropriate digital transformation strategies need to be in place. Yet, studies show that organizations struggle with strategy formulation and implementation. Based on workshops with practitioners the authors obtained concrete needs, pains, and gains as requirements for the development of an own, new intelligent and platform-based assessment tool. The proposed tool collects, calculates, and visualizes in a self-service manner, relevant company data to support decision-makers and organizations in digital transformation strategy development and implementation.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation CyMed: A framework for testing connected medical devices(Springer, 2024) Scherb, Christopher; Hadayah, Adrian; Heitz, Luc; Grieder, Hermann; Asprion, Petra; Hinkelmann, Knut; Smuts, HanlieConnected Medical Devices (CMDs) significantly benefit patients but are also vulnerable to malfunctions that can harm. Despite strict safety regulations for market entry, there’s a notable shortage of specific cybersecurity frameworks for CMDs. Existing regulations on cybersecurity practices are often broad and lack detailed implementation steps. This paper introduces the CyMed framework, designed for vendors and end-users, offering explicit strategies to enhance the cybersecurity of CMDs. The effectiveness of CyMed is assessed through practical testing and expert interviews.04B - Beitrag KonferenzschriftPublikation Using AI assistants in higher education: The role of critical thinking(International Academy of Technology, Education and Development (IATED), 2024) Jäger, Janine; Richter, Sarah-Louise; Spasova, Tsvetana; Gómez Chova, Luis; González Martínez, Chelo; Lees, JoannaStudent’s use of AI assistants gradually becoming a reality in higher education (Crompton and Burke, 2023; von Garrel and Mayer, 2023), and is reshaping teaching and learning methods. Critical thinking is a key skill to harness AI's potential to improve learning processes and outcomes (Rusandi et al., 2023). Therefore, in this paper we argue that critical thinking, defined as the ability to “raise vital questions and problems, formulate them clearly, gather and assess relevant information, use abstract ideas, think open-mindedly, and communicate effectively with others” (Duron et al., 2006, p. 160), is crucial for students navigating the challenges introduced by AI technologies. Critical thinking can enable students to evaluate the quality of information provided by AI tools, to assess biases, identify limitations, and make informed decisions regarding the application of AI assistants. After a brief theoretical overview of critical thinking in the age of AI, the paper outlines the learning design of a module on critical thinking, including an introduction to the workings of curative and generative AI, conducted for undergraduate business students at a Swiss university of applied sciences. During the course, students engaged in guided exercises with selected AI tools, followed by in-depth discussion and reflection on the user experiences and outputs generated by the AI. Before and after the AI-related teaching interventions, students were surveyed about their use of and attitudes towards AI tools. Moreover, the paper presents initial findings from the survey (n=85), highlighting differences in frequency of use and attitudes towards AI assistants. The results suggest that students tend to incorporate AI tools into their academic routines, regardless of instructional intervention. However, even small-scale interventions contribute to a noticeably more critical attitude towards AI tools, addressing concerns and narrowing the gap between AI pioneers and late adopters within the student cohort. While the results of this pilot study cannot be generalized, they provide a good indication of the importance of fostering critical thinking skills in the use of AI assistants in learning processes. In conclusion, this paper illustrates how even small-scale interventions that promote critical thinking can empower students to critically evaluate AI output, engage in meaningful interactions with AI tools, and use AI assistants in ways that enhance their learning experience. We outline our future research initiatives and suggest that critical thinking should be integrated into higher education curricula as a core skill to enhance students' understanding of AI assistants, enabling them to use AI tools effectively, but also in a responsible and informed way.04B - Beitrag KonferenzschriftPublikation Comparative analysis of generative AI models in educational exercise performance(International Academy of Technology, Education and Development (IATED), 2024) Meyer, Lukas; Dannecker, Achim; Gómez Chova, Luis; González Martínez, Chelo; Lees, JoannaThe integration of artificial intelligence (AI) in educational settings presents great opportunities for enhancing learning experiences. Within the context of a Swiss University of applied Sciences employing a flipped classroom methodology and in class exercises, a noticeable shift in student behaviour has been observed. The quality of using generative AI for solving case study based exercises in Business Process and Project Management was analysed using OpenAI’s ChatGPT Model 3.5. However, it is unknown how the different models are performing compared to each other when solving exercises in business education. This paper aims to extend the discourse of solving class exercises by conducting a comparative analysis of various generative AI models in the context of educational exercises within the flipped classroom setting, particular in Business Process and Project Management. The study systematically assesses the performance of different AI models, such as GPT-4, BERT, BART, T5, LLM API, etc, in answering selected exercises derived from real-world business scenarios. This study analyzes the accuracy, relevance, completeness, and contextual understanding exhibited by each AI model in response to a series of exercises. These exercises are designed to mimic real-world business challenges in Business Process and Project Management, thereby providing a meaningful evaluation of each model's use in an educational context. The study further delves into the nuances of prompt construction, examining how variations in prompt design influence the performance of AI models, thereby shedding light on the critical role of effective communication in leveraging AI for educational purposes. The findings of this research provide educators, researchers, and practitioners with a comprehensive understanding of the comparative strengths and weaknesses of various generative AI models in the context of business education, particularly in Business Process and Project Management. By highlighting key differences in selecting and deploying AI tools for educational exercises, the paper aims to contribute insights into the optimization of AI-assisted learning environments.04B - Beitrag KonferenzschriftPublikation Quality and students' perception of feedback generated by GPT-4 on a complex group task(International Academy of Technology, Education and Development (IATED), 2024) Dannecker, Achim; Meyer, Lukas; Gómez Chova, Luis; González Martínez, Chelo; Lees, JoannaAI in education is a significant and widely debated subject, present at various educational levels. Students utilise AI for easy referencing of concepts to complete university assignments. It is also integrated into lecture content, facilitating discussions on effective prompting within specific contexts. Moreover, AI can act as a peer, aiding in the interactive development of assignment solutions. Instructors employ AI for task development and student outcome evaluation. This study explores how generative AIs can support or even supplant the feedback process for complex group tasks within the classroom. It focuses on a project management group task centred around developing project objectives according to IPMA standards, a task aimed at achieving multiple learning objectives. Students must comprehend an interview with a client, grasp project objective theory, categorise objectives, formulate them SMART, and ideally align them with company goals described in a case study. After working on the task during class time, groups receive guidance from instructors who provide coaching and support. Following completion, solutions are uploaded for individual feedback from instructors. Using the GPT-4 AI model, we trained it with past semester feedback and provided the theoretical context of the group task. With these inputs, we analysed, evaluated, and provided feedback generated by GPT-4 to groups. Subsequently, we surveyed groups to gauge the feedback's usefulness and compared this with lecturer assessments. This task forms part of a module for undergraduate business students focusing on business process and project management, developed in line with evidence-based university teaching criteria. The module is taught uniformly across the university's three locations, comprising seven classes in Spring 2024 (5 in German, 2 in English), utilising the same translated case study, exercises, and evaluation exam. The module's methodology combines case study teaching and the flipped classroom concept. A case study, based on a start-up company's real-life experiences, was developed. Over 12 weeks, students acquainted themselves with business process and project management theories, engaging in group exercises during class sessions. This study demonstrates how GPT-4-generated feedback can be utilised for complex group tasks and provides insights into its requirements in terms of theory, training data, and prompt structure.04B - Beitrag Konferenzschrift