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Jan Marco Leimeister
Title
Prof. Dr.
Last Name
Leimeister
First name
Jan Marco
Email
janmarco.leimeister@unisg.ch
Phone
+41 71 224 3330
Now showing
1 - 10 of 82
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PublicationCollaborative Work Practices for Management Education: Using Collaboration Engineering to Design a Reusable and Scalable Collaborative Learning Instructional Design( 2023-01-06)
;Oeste-Reiß, SarahPandemics like COVID-19 highlight the needs and pitfalls of inclusive and equitable education in a digital society. IT-based instructional designs are needed to increase learners’ expertise, and to develop higher-order thinking skills. Instructional designs for collaborative learning (CL) seem to be a promising solution. However, they are mostly suitable for face-to-face and not for distance teaching. The core problem that impedes their reusability and scalability is a ‘collaboration problem’ for which collaboration engineering (CE) provides guidance. Therefore, we deploy a design science research study and contribute to CL and CE literature. We develop requirements and provide the design of an IT-based collaborative work practice fostering CL. We provide empirical evidence with an online experiment in a large-scale lecture with undergraduate business information students. This reveals that groups of learners who followed our CL experience achieve higher levels of expertise than those who followed a traditional ad hoc CL experience.Type: conference paperJournal: Hawaii International Conference on System Sciences (HICSS) -
PublicationTransferring Well-Performing Collaborative Work Practices with Parameterized Templates and Guidebooks: Empowering Subject Matter Experts for an Adaptation to Slightly Different Contexts( 2023-01-06)
;Oeste-Reiß, SarahCollaborative work practices (CWPs) package facilitation expertise and have the potential to increase team productivity up to 90%. Collaboration engineers develop CWPs and deploy them to practitioners that execute them. These CWPs, however, are typically customized to conditions of a specific use case. This creates the challenge that changing use case conditions or even small variations across contexts, hinder well-performing CWPs of being applied more often to create a long-term value. Practitioners fail to adapt existing CWPs due to missing collaboration expertise and adaptation guidelines. To address this challenge in collaboration engineering literature, we introduce a) the Subject Matter Expert role; b) the ‘CWP Adaptation Approach’ that formalizes the transfer of CWPs to different contexts with parameterized Templates and Guidebooks. To show a first proof-of-concept, we further inductively generalize from an exemplarily use case with a well-performing CWP in the educational domain.Type: conference paperJournal: Hawaii International Conference on System Sciences (HICSS) -
PublicationEntwurfsmuster für die interdisziplinäre Gestaltung rechtsverträglicher Systeme(Springer Vieweg, 2022-04-06)
;Dickhaut, Ernestine ;Thies, Laura Friederike ;Friedewald, Michael ;Kreutzer, MichaelHansen, MaritType: conference paper -
PublicationAdaptive Empathy Learning Support in Peer Review Scenarios( 2022-05-05)
;Koedinger, KennethAdvances in Natural Language Processing offer techniques to de- tect the empathy level in texts. To test if individual feedback on certain students’ empathy level in their peer review writing pro- cess will help them to write more empathic reviews, we developed ELEA, an adaptive writing support system that provides students with feedback on the cognitive and emotional empathy structures. We compared ELEA to a proven empathy support tool in a peer review setting with 119 students. We found students using ELEA wrote more empathic peer reviews with a higher level of emotional empathy compared to the control group. The high perceived skill learning, the technology acceptance, and the level of enjoyment provide promising results to use such an approach as a feedback application in traditional learning settings. Our results indicate that learning applications based on NLP are able to foster empathic writing skills of students in peer review scenarios.Type: conference paperJournal: ACM CHI Conference on Human Factors in Computing System (CHI)Scopus© Citations 15 -
PublicationAI-based Argumentation Tutoring – A Novel System Class to Improve Learners’ Argumentation Skills( 2021-07-29)Argumentation is an omnipresent foundation of our daily communication and thinking. The ability to form convincing arguments is not only the fundament for persuading an audience of novel ideas but also plays a major role in strategic decision-making, negotiation, and productive civil discourse. However, students often struggle to develop argumentation skills due to a lack of individual and instant feedback in their learning journey, since providing feedback on the individual argumentation skills of learners is very time consuming and not scalable if conducted manually by educators. Following a design science research approach, we propose a new class of argumentation learning systems that provide students with individual and ongoing tutoring to support them in learning how to argue. We build our socio-technical design on a combination of user-centered design principles, a conceptualization of argumentation structures in student-written text, and Natural Language Processing and Machine Learning classifiers to provide individual feedback. To investigate if the new system class of AI-based argumentation tutoring systems helps students to improve their argumentation skills, we evaluated the novel artifact class in two empirical studies in comparison to traditional argumentation learning systems. In a laboratory experiment (study 1), as well as in a field experiment in a large-scale lecture over three months (study 2), we found that AI-based argumentation tutoring systems based on our design principles, argumentation schemes, and algorithms improve the short- and long-term argumentation skills of students significantly compared to the traditional argumentation learning approaches.Type: conference paperJournal: Annual Meeting of the Academy of Management (AOM)
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PublicationType: conference paper
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PublicationAL: An Adaptive Learning Support System for Argumentation Skills(ACM CHI Conference on Human Factors in Computing Systems, 2020-04)Recent advances in Natural Language Processing (NLP) bear the opportunity to analyze the argumentation quality of texts. This can be leveraged to provide students with individual and adaptive feedback in their personal learning journey. To test if individual feedback on students' argumentation will help them to write more convincing texts, we developed AL, an adaptive IT tool that provides students with feedback on the argumentation structure of a given text. We compared AL with 54 students to a proven argumentation support tool. We found students using AL wrote more convincing texts with better formal quality of argumentation compared to the ones using the traditional approach. The measured technology acceptance provided promising results to use this tool as a feedback application in different learning settings. The results suggest that learning applications based on NLP may have a beneficial use for developing better writing and reasoning for students in traditional learning settings.Type: conference paperJournal: ACM CHI Conference on Human Factors in Computing Systems
Scopus© Citations 66 -
PublicationA Corpus for Argumentative Writing Support in GermanIn this paper, we present a novel annotation approach to capture claims and premises of arguments and their relations in student-written persuasive peer reviews on business models in German language. We propose an annotation scheme based on annotation guidelines that allows to model claims and premises as well as support and attack relations for capturing the structure of argumentative discourse in student-written peer reviews. We conduct an annotation study with three annotators on 50 persuasive essays to evaluate our annotation scheme. The obtained inter-rater agreement of α = 0.57 for argument components and α = 0.49 for argumentative relations indicates that the proposed annotation scheme successfully guides annotators to moderate agreement. Finally, we present our freely available corpus of 1,000 persuasive student-written peer reviews on business models and our annotation guidelines to encourage future research on the design and development of argumentative writing support systems for students.Type: conference paperJournal: International Conference on Computational Linguistics (COLING)
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PublicationDesign and Evaluation of an Adaptive Dialog-Based Tutoring System for Argumentation Skills( 2020-12-13)Recent advances in Natural Language Processing not only bear the opportunity to design new dialog-based forms of human-computer interaction but also to analyze the argumentation quality of texts. Both can be leveraged to provide students with individual and adaptive tutoring in their personal learning journey to develop argumentation skills. Therefore, we present the results of our design science research project on how to design an adaptive dialog-based tutoring system to help students to learn how to argue. Our results indicate the usefulness of an adaptive dialog-based tutoring system to support students individually, independent of a human instructor, time and place. In addition to providing our embedded software artifact, we document our evaluated design knowledge as a design theory. Thus, we provide the first step toward a nascent design theory for adaptive conversational tutoring systems to individual support metacognition skill education of students in traditional learning scenarios.Type: conference paperJournal: International Conference on Information Systems (ICIS)
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PublicationType: conference paperJournal: Conference on Human Factors in Computing Systems (CHI)
Scopus© Citations 24