Matthias Söllner
Title
Prof. Dr.
Last Name
Söllner
First name
Matthias
Email
matthias.soellner@unisg.ch
Skype
taolin.de
181 results
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Item type:Publication, Improving Students’ Argumentation Skills Using Dynamic Machine-Learning–Based Modeling(Informs, 2024-06); ; ; ;Koedinger, KenArgumentation is an omnipresent rudiment of daily communication and thinking. The ability to form convincing arguments is not only fundamental to persuading an audience of novel ideas but also plays a major role in strategic decision making, negotiation, and constructive, civil discourse. However, humans often struggle to develop argumentation skills, owing to a lack of individual and instant feedback in their learning process, because providing feedback on the individual argumentation skills of learners is time-consuming and not scalable if conducted manually by educators. Grounding our research in social cognitive theory, we investigate whether dynamic technology-mediated argumentation modeling improves students’ argumentation skills in the short and long term. To do so, we built a dynamic machine-learning (ML)–based modeling system. The system provides learners with dynamic writing feedback opportunities based on logical argumentation errors irrespective of instructor, time, and location. We conducted three empirical studies to test whether dynamic modeling improves persuasive writing performance more so than the benchmarks of scripted argumentation modeling (H1) and adaptive support (H2). Moreover, we assess whether, compared with adaptive support, dynamic argumentation modeling leads to better persuasive writing performance on both complex and simple tasks (H3). Finally, we investigate whether dynamic modeling on repeated argumentation tasks (over three months) leads to better learning in comparison with static modeling and no modeling (H4). Our results show that dynamic behavioral modeling significantly improves learners’ objective argumentation skills across domains, outperforming established methods like scripted modeling, adaptive support, and static modeling. The results further indicate that, compared with adaptive support, the effect of the dynamic modeling approach holds across complex (large effect) and simple tasks (medium effect) and supports learners with lower and higher expertise alike. This work provides important empirical findings related to the effects of dynamic modeling and social cognitive theory that inform the design of writing and skill support systems for education. This paper demonstrates that social cognitive theory and dynamic modeling based on ML generalize outside of math and science domains to argumentative writing.Type:journal articleJournal:Information Systems ResearchVolume:36Issue:1Scopus© Citations 15 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Lawfulness by design – development and evaluation of lawful design patterns to consider legal requirements(European Journal of Information Systems (EJIS), 2023-03-01) ;Dickhaut, Ernestine; ; New political objectives, emerging regulatory regimes for the digital sphere, and higher penalties for violations have intensified the pressure to develop lawful IT artefacts. As the adaptation of existing IT artefacts to new regulations can be expensive and arduous, a more attractive approach would be to design IT artefacts lawfully from the beginning. A major challenge is that the law is generally technology-neutral, and lawful design requires legal expertise throughout the development, which is costly and time consuming due to communication challenges between legal experts and developers. One possible approach to proactively consider IT regulations in the systems development is design patterns that convey legal design knowledge and support developers in determining the appropriate design options. Consequently, we develop a framework for lawful design patterns and demonstrate their feasibility and advantages using the example of developing AI-based assistants and the regulation of the General Data Protection Regulation (GDPR). Using the design pattern framework, we develop design patterns for lawful AI-based assistants and evaluate them using (a) an experimental approach to show the usefulness of the patterns for developers and (b) rely on a legal simulation study to holistically evaluate how design patterns contribute to lawful IT.Type:journal articleJournal:European Journal of Information Systems (EJIS)Scopus© Citations 30 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Leveraging Low Code Development of Smart Personal Assistants: An Integrated Design Approach with the SPADE Method(2023-03-31); ; ; Smart personal assistants (SPAs) promise individualized user interactions owing to their varying interaction possibilities, knowledgeability, and human-like behaviors. To support the widespread adoption and use of SPAs, organizations such as Google or Amazon provide low code environments that support the development of SPAs (e.g., for Google Home or Amazon’s Alexa). These so-called low code platforms enable domain experts (e.g., business users without programming skills or experience) to develop SPAs for their purposes. However, using these platforms alone does not guarantee a useful and good conversation with novel SPAs due to non-intuitive design choices. Following a design science research approach, we propose the Smart Personal Assistant for Domain Experts (SPADE) method to address the missing link. This method supports domain experts in the development and contextualization of sophisticated SPAs for various application scenarios and focuses especially on conversational and anthropomorphic design steps. Our proof of concept and proof of value results show that SPADE is useful for supporting domain experts to create effective SPAs in different domains beyond private set-ups.Type:journal articleJournal:Journal of Management Information Systems (JMIS)Volume:40Issue:1Scopus© Citations 28 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Designing Conversational Evaluation Tools: A Comparison of Text and Voice Modalities to Improve Response Quality in Course Evaluations(Association for Computing Machinery, 2022-11-11); ; ; ;Käser, TanjaKoedinger, Kenneth R.Conversational agents (CAs) provide opportunities for improving the interaction in evaluation surveys. To investigate if and how a user-centered conversational evaluation tool impacts users' response quality and their experience, we build EVA - a novel conversational course evaluation tool for educational scenarios. In a field experiment with 128 students, we compared EVA against a static web survey. Our results confirm prior findings from literature about the positive effect of conversational evaluation tools in the domain of education. Second, we then investigate the differences between a voice-based and text-based conversational human-computer interaction of EVA in the same experimental set-up. Against our prior expectation, the students of the voice-based interaction answered with higher information quality but with lower quantity of information compared to the text-based modality. Our findings indicate that using a conversational CA (voice and text-based) results in a higher response quality and user experience compared to a static web survey interface.Type:journal articleJournal:Proceedings of the ACM on Human-Computer Interaction (PACMHCI)Volume:6Issue:CSCW2DOI:10.1145/3555619Scopus© Citations 16 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Individualisierung in der beruflichen Bildung durch Hybrid Intelligence. Potentiale und Grenzen(Franz Steiner Verlag, 2021); ; ; ;Thiel de Gafenco, MarianType:journal articleJournal:Zeitschrift für Berufs- und WirtschaftspädagogikVolume:Beiheft 31 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Supporting Cognitive and Emotional Empathic Writing of StudentsWe present an annotation approach to capturing emotional and cognitive empathy in student-written peer reviews on business models in German. We propose an annotation scheme that allows us to model emotional and cognitive empathy scores based on three types of review components. Also, we conducted an annotation study with three annotators based on 92 student essays to evaluate our annotation scheme. The obtained inter-rater agreement of α = 0.79 for the components and the π = 0.41 for the empathy scores indicate that the proposed annotation scheme successfully guides annotators to a substantial to moderate agreement. Moreover, we trained predictive models to detect the annotated empathy structures and embedded them in an adaptive writing support system for students to receive individual empathy feedback independent of an instructor, time, and location. We evaluated our tool in a peer learning exercise with 58 students and found promising results for perceived empathy skill learning, perceived feedback accuracy, and intention to use. Finally, we present our freely available corpus of 500 empathy-annotated, student-written peer reviews on business models and our annotation guidelines to encourage future research on the design and development of empathy support systems.Type:journal articleJournal:The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Design and Evaluation of an Adaptive Empathy Learning Tool(Hawaii International Conference on System Sciences, 2021-01) ;Wambsganss, Thiemo ;Weber, FlorianEmpathy is an elementary skill for daily interactions and for professional communication, agile teamwork and successful leadership and thus elementary for educational curricula. However, educational organizations face difficulties in providing the boundary conditions necessary for their students to develop empathy skills due to the lack of individual support in traditional large-scale and growing distance-learning scenarios. Drawing on cognitive dissonance theory, we propose an adaptive empathy learning tool that helps students develop their ability to react to other people’s observed experiences through individual feedback in large-scale or distance learning scenarios. Based on a design science research project, we propose a set of design principles and instantiate and evaluate them with our prototype Eva in an online experiment with 65 students. The findings suggest that an adaptive empathy learning tool that follows our design principles is a promising approach to individually support students in their ability to react to other people’s observed abilities in traditional learning scenarios.Type:journal article - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Scopus© Citations 109 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Enhancing Problem-Solving Skills with Smart Personal Assistant TechnologySmart Personal Assistants (SPAs; such as Amazon’s Alexa or Google’s Assistant) let users interact with computers in a more natural and sophisticated way that was not possible before. Although there exists an increasing amount of research of SPA technology in education, empirical evidence of its ability to offer dynamic scaffolding to enhance students problem-solving skills is still scarce. To fill this gap, the aim of this paper is to find out whether interactions with scaffolding-based SPA technology enable students to internalize and apply problem-solving steps on their own in a 10th grade high school and a vocational business school class. Students in the experiment classes completed their assignments using Smart Personal Assistants, whereas students in the control classes completed the same assignments using traditional methods. This study used a mixed-method approach consisting of two field quasi-experiments and one post-experiment focus group discussion. The empirical results revealed that students in the experiment classes acquired significantly more problem-solving skills than those in the control classes (Study 1: p = 0.0396, study 2: p < 0.001), and also uncovered several changes in students’ learning processes. The findings provide first empirical evidence for the value of using SPA technology on skill development in general, and on problem-solving skill development in particular.Type:journal articleJournal:Computers & EducationVolume:165Scopus© Citations 109 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Ladders for Learning: Is Scaffolding the Key to Teaching Problem Solving in Technology-mediated Learning Contexts?The success of innovative teaching/learning approaches aiming to foster problem solving in management education depends on useful and easy-to-use IT components in the learning process. However, the complexity of problem solving in self-regulated learning approaches may overwhelm the learner and can lead to unsatisfying learning outcomes. Research suggests the implementation of technology-enhanced scaffolds as a mechanism to guide the learners in their individual problem-solving process to enhance their learning outcomes. We present a theoretical model based on adaptive structuration theory and cognitive load theory that explains how technology-enhanced scaffolding contributes to learning outcomes. We test the model with a fully randomized between-subject experiment in a flipped classroom for management education focusing on individual problem solving. Our results show that technology-enhanced scaffolding contributes significantly to the management of cognitive load as well as to learning process satisfaction and problem-solving learning outcomes. Thereby, our paper provides new conceptual and empirically tested insights for a better understanding of technology-enhanced scaffolds and their design to assist problem solving and its respective effects in flipped classrooms for management education.Type:journal articleJournal:Academy of Management Learning & Education (AMLE)Volume:19Issue:4Scopus© Citations 45