Veröffentlichungen

Veröffentlichungen 2023

Tolzin, A.; & Janson, A. (2023): Mechanisms of Common Ground in Human-Agent Interaction: A Systematic Review of Conversational Agent Research. In: Hawaii International Conference on System Sciences (HICSS). Maui, Hawaii, USA.

Abstract: Human-agent interaction is increasingly influencing our personal and work lives through the proliferation of conversational agents in various domains. As such, these agents combine intuitive natural language interactions by also delivering personalization through artificial intelligence capabilities. However, research on CAs as well as practical failures indicate that CA interaction oftentimes fails miserably. To reduce these failures, this paper introduces the concept of building common ground for more successful human-agent interactions. Based on a systematic review our analysis reveals five mechanisms for achieving common ground: (1) Embodiment, (2) Social Features, (3) Joint Action, (4) Knowledge Base, and (5) Mental Model of Conversational Agents. On this basis, we offer insights into grounding mechanisms and highlight the potentials when considering common ground in different human-agent interaction processes. Consequently, we secure further understanding and deeper insights of possible mechanisms of common ground in human-agent interaction in the future.

Weber, F., Wambsganss, T., & Söllner, M. (2023). Design and Evaluation of an AI-based Learning System to Foster Students‘ Structural and Persuasive Writing in Law Courses. In Forty-Fourth International Conference on Information Systems, Hyderabad.

Abstract: Structured and persuasive writing is essential for effective communication, convincing readers of argument validity, and inspiring action. However, studies indicate a decline in students‘ proficiency in this area. This decline poses challenges in disciplines like law, where success relies on structured and persuasive writing skills. To address these issues, we present the results of our design science research project to develop an AI-based learning system that helps students learn legal writing. Our results from two different experiments with 104 students demonstrate the usefulness of our AI-based learning system to support law students independent of a human tutor, location, and time. Apart from furnishing our integrated software artifact, we also document our assessed design knowledge in the form of a design theory. This marks the first step toward a nascent design theory for the development of AI-based learning systems for legal writing.

Weber, F., Wambsganss, T., & Söllner, M. (2023). Unterstützung des juristischen Schreibens durch ein KI- basiertes Schreibsystem. INFORMATIK 2023 – Designing Futures: Zukünfte gestalten. DOI: 10.18420/inf2023_34. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-731-9. pp. 357-362. Bildung – KI-Bildung – Ein Workshop zu Aus- und Weiterbildung über Künstliche Intelligenz. Berlin. 26.-29. September 2023.

Abstract: In einer zunehmend vernetzten Welt gewinnt die Fähigkeit klar strukturiert und überzeugend zu schreiben, insbesondere im Bereich des Rechts, an Bedeutung, da sie eine grundlegende Komponente effektiver juristischer Kommunikation darstellt. Jedoch zeigen Studien, dass die Schreibfähigkeiten von Studierenden in diesem Bereich abnehmen. Um diese Probleme zu überwinden, präsentieren wir ein innovatives KI-basiertes Schreibunterstützungssystem, das Studierenden beim Erlernen des juristischen Schreibens hilft. Das System wurde in mehreren Sitzungen eines Tutoriums an einer deutschen Universität eingesetzt und evaluiert. Die Ergebnisse der Evaluation zeigen die Nützlichkeit unseres KI-basierten Schreibsystems. Unsere Forschung markiert einen wichtigen Meilenstein in der Entwicklung von KI-basierten Lernsystemen für das juristische Schreiben. Sie bildet die Grundlage für zukünftige Fortschritte auf diesem Gebiet und eröffnet neue Möglichkeiten zur Erkundung des Potenzials von KI im Bereich des juristischen Schreibens.

Weber, F., Wambsganss, T., Neshaei, S. P., & Soellner, M. (2023, July). Structured Persuasive Writing Support in Legal Education: A Model and Tool for German Legal Case Solutions. In Findings of the Association for Computational Linguistics: ACL 2023 (pp. 2296-2313).

Abstract: We present an annotation approach for capturing structured components and arguments in legal case solutions of German students. Based on the appraisal style, which dictates the structured way of persuasive writing in German law, we propose an annotation scheme with annotation guidelines that identify structured writing in legal case solutions. We conducted an annotation study with two annotators and annotated legal case solutions to capture the structures of a persuasive legal text. Based on our dataset, we trained three transformer-based models to show that the annotated components can be successfully predicted, e.g. to provide users with writing assistance for legal texts. We evaluated a writing support system in which our models were integrated in an online experiment with law students and found positive learning success and users’ perceptions. Finally, we present our freely available corpus of 413 law student case studies to support the development of intelligent writing support systems.

Tolzin, A.; Körner, A.; Dickhaut, E.; Janson, A.; Rummer, R.; & Leimeister, J. M. (2023): Designing Pedagogical Conversational Agents for Achieving Common Ground. In: International Conference on Design Science Research (DESRIST). Pretoria, South Africa.

Abstract: As educational organizations face difficulties in providing personalized learning material or individual learning support, pedagogical conversational agents (PCAs) promise individualized learning for students. However, the problem of conversational breakdowns of PCAs and consequently poor learning outcomes still exist. Hence, effective and grounded communication between learners and PCAs is fundamental to improving learning processes and out-comes. As understanding each other and the conversational grounding is crucial for conversations between humans and PCAs, we propose common ground theory as a foundation for designing a PCA. Conducting a design science research project, we propose theory-motivated design principles and instantiate them in a PCA. We evaluate the utility of the artifact with an experimental study in higher education to inform the subsequent design iterations. We contribute design knowledge on conversational agents in learning settings, enabling researchers and practitioners to develop PCAs based on common ground research in education and providing avenues for future research. Thereby, we can secure further understanding of learning processes based on grounding communication.

Haenel, M., Wambsganss, T., & Söllner, M. (2024). The Power of Reading Support for Learners: A State-of-the-Art Analysis of Computer-Assisted Reading from an Information Systems Perspective. 57th Hawaii International Conference on System Sciences, Maui, Hawaii, USA.

Abstract: Reading and synthesizing scientific papers is a crucial skill for students. However, many students in higher education struggle to effectively comprehend scientific texts. To address this challenge, research has leveraged computer-assisted reading (CAR) systems to improve students‘ reading comprehension abilities at scale. However, the research and application of CAR in higher education still lack an organized overview and clear terminology due to the multidisciplinary character of the research field (eg, Education didactic, Human-Computer Interaction, or Information Systems). Therefore, we perform a systematic literature review on CAR from an interdisciplinary Information Systems perspective. We take the socio-technical systems theory as a lens to organize, summarize past literature as well to identify white sports for a future research agenda. The main contributions of this paper are the synthesis and consolidation of CAR to create a basis for all researchers investigating the research field of CAR in higher education.

Verarbeitung personenbezogener Daten in KI-Reallaboren nach dem KI-VO-E – Eine Herausforderung für den datenschutzrechtlichen Zweckbindungsgrundsatz, In: Computer und Recht 2023, 725-731.

Abstract: Die anstehende KI-Verordnung wird Regulatory Sandboxes (dt.KI-Reallabore) zur Innovationsförderung einführen. Diese sehenmit Art. 54 KI-VO-E eine Ausnahme vom Zweckbindungs-grundsatz für das Training von KI-Anwendungen mit personen-bezogenen Daten vor. Der Beitrag untersucht, inwiefern dieseAusnahme vom Zweckbindungsgrundsatz mit der DSGVO imEinklang steht. Hierfür werden die Anforderungen aus Art. 6Abs. 4 DSGVO als Maßstab genommen.

Helmke, J. T. & Link, H. (2023): Das Verhältnis von Art. 6 Abs. 2 und 3 DSGVO, In: Datenschutz und Datensicherheit 2023, 708-714.

Abstract: Zusammenfassung Sollen Datenverarbeitungen auf Art. 6 Abs. 1 UAbs. 1 lit. c, e DSGVO gestützt werden, bedarf es einer Rechtsgrundlage im Unionsrecht oder im Recht der Mitgliedstaaten. Aufgrund einer missglückten Konzeption des Art. 6 Abs. 2 DSGVO neben Art. 6 Abs. 3 DSGVO ist strittig, welche der beiden Öffnungsklauseln zur Festlegung von Rechtsgrundlagen der Mitgliedstaaten heranzuziehen ist und welche Anforderungen sich an diese ergeben. Dieser Beitrag beleuchtet das Verhältnis der beiden Bestimmungen und schlägt eine gegenstandsbezogene Abgrenzung als Interpretationsrichtlinie für die jeweilige Anwendung der beiden Absätze vor.