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Thiemo Wambsganss
Former Member
Title
Prof. Dr.
Last Name
Wambsganss
First name
Thiemo
Email
thiemo.wambsganss@unisg.ch
Phone
+41 71 224 3234
Web Site
35 results
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Item type:Publication, How a Swiss luxury retailer implements process mining to improve data-driven customer excellence(2024); ; ; In today’s digital transformation era, process mining has emerged as a crucial technology, playing an integral part in the digital strategies of many organizations. Despite its significance, implementing process mining to leverage data-driven decision-making and boosting process efficiency presents notable challenges for such companies. This case study delves into the journey of the fictitious Swiss luxury retailer Elysian as they utilize process mining to derive data-driven insights on process inefficiencies and bottlenecks to increase their customer excellence for online retail procurement. The case highlights the capabilities of process mining for organizations. It is among the first to offer students hands-on guidance on process discovery, conformance, and enhancement using real-world data. Students take the role of Lisa Dister, Head of procurement in the business unit home care, who urgently requires improving process transparency after an unsatisfying internal audit result. This immersive experience helps students understand the application of process mining in high-volume data scenarios and equips them with skills in data literacy. Moreover, students are challenged to suggest recommendations for long-term process optimization and reflect on the effectiveness of process mining for tackling procurement issues.Type:journal articleJournal:Journal of Information Technology Teaching Cases - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Improving Students’ Argumentation Skills Using Dynamic Machine-Learning–Based Modeling(Informs, 2024-06); ; ; Scopus© Citations 18 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Measuring university students’ ability to recognize argument structures and fallaciesTheory: Argumentation is crucial for all academic disciplines. Nevertheless, a lack of argumentation skills among students is evident. Two core aspects of argumentation are the recognition of argument structures (e.g., backing up claims with premises, according to the Toulmin model) and the recognition of fallacies. As both aspects may be related to content knowledge, students studying different subjects might exhibit different argumentation skills depending on whether the content is drawn from their own or from a foreign subject. Therefore, we developed an instrument to measure the recognition of both argument structures and fallacies among the groups of preservice teachers and business economics students in both their respective domains (pedagogy and economics), and a neutral domain (sustainability). For the recognition of fallacies, we distinguished between congruent and incongruent fallacies. In congruent fallacies, the two aspects of argument quality, i.e., deductive validity and inductive strength, provide converging evidence against high argument quality. In incongruent fallacies, these two aspects diverge. Based on dual process theories, we expected to observe differences in the recognition of congruent and incongruent fallacies.Type:journal articleJournal:Frontiers in PsychologyVolume:14Issue:1270931Scopus© Citations 5 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Conversational Agents for Information Retrieval in the Education Domain: A User-Centered Design Investigation(2022-11-11); ; Text-based conversational agents (CAs) are widely deployed across a number of daily tasks, including information retrieval. However, most existing agents follow a default design that disregards user needs and preferences, ultimately leading to a lack of usage and an unsatisfying user experience. To better understand how CAs can be designed in order to lead to effective system use, we deduced relevant design requirements from both literature and 13 user interviews. We built and tested a question-answering, text-based CA for an information retrieval task in an education scenario. Results from our experimental test with 41 students indicate that following a user-centered design has a significant positive effect on enjoyment and trust in a CA as opposed to deploying a default CA. If not designed with the user in mind, CAs are not necessarily more beneficial than traditional question-answering systems. Beyond practical implications for effective CA design, this paper points towards key challenges and potential research avenues when deploying social cues for CAs.Type:journal articleJournal:Proceedings of the ACM on Human-Computer Interaction (PACMHCI)Volume:6Issue:CSCW2DOI:10.1145/3555587Scopus© Citations 20 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Improving Students Argumentation Learning with Adaptive Self-Evaluation Nudging(2022-11-11); ; Scopus© Citations 23 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Enhancing argumentative writing with automated feedback and social comparison nudgingThe advantages offered by natural language processing (NLP) and machine learning enable students to receive automated feedback on their argumentation skills, independent of educator, time, and location. Although there is a growing amount of literature on formative argumentation feedback, empirical evidence on the effects of adaptive feedback mechanisms and novel NLP approaches to enhance argumentative writing remains scarce. To help fill this gap, the aim of the present study is to investigate whether automated feedback and social comparison nudging enable students to internalize and improve logical argumentation writing abilities in an undergraduate business course. We conducted a mixed-methods study to investigate the impact of argumentative writing on 71 students in a field experiment. Students in treatment group 1 completed their assignment while receiving automated feedback, whereas students in treatment group 2 completed the same assignment while receiving automated feedback with a social comparison nudge that indicated how other students performed on the same assignment. Students in the control group received generalized feedback based on rules of syntax. We found that participants who received automated argumentation feedback with a social comparison nudge wrote more convincing texts with higher-quality argumentation compared to the two benchmark groups (p < 0.05). The measured self-efficacy, perceived ease of use, and qualitative data provide valuable insights that help explain this effect. The results suggest that embedding automated feedback in combination with social comparison nudges enables students to increase their argumentative writing skills by triggering psychological processes. Receiving only automated feedback in the form of in-text argumentative highlighting without any further guidance appears not to significantly influence students’ writing abilities when compared to syntactic feedback.Type:journal articleJournal:Computers & EducationVolume:191Issue:104644Scopus© Citations 65 - 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); ; ; Scopus© Citations 16 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Taxonomy for Deep Learning in Natural Language Processing(Hawaii International Conference on System Sciences, 2021); Söllner, MatthiasType:journal article - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Improving Explainability and Accuracy through Feature Engineering: A Taxonomy of Features in NLP-based Machine Learning(2021); ; Fromm, HansjörgType:journal articleJournal:Forty-Second International Conference on Information Systems - Some of the metrics are blocked by yourconsent settings
Item type:Publication, ArgueTutor: An Adaptive Dialog-Based Learning System for Argumentation Skills(ACM CHI Conference on Human Factors in Computing Systems, 2021-04); Scopus© Citations 104