Witschel, Hans Friedrich
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Hans Friedrich
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Witschel, Hans Friedrich
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- PublicationVisualization of patterns for hybrid learning and reasoning with human involvement(Springer, 2020) Witschel, Hans Friedrich; Pande, Charuta; Martin, Andreas; Laurenzi, Emanuele; Hinkelmann, Knut; Dornberger, Rolf [in: New trends in business information systems and technology]04A - Beitrag Sammelband
- PublicationA dialog-based tutoring system for project-based learning in information systems education(Springer, 2020) Witschel, Hans Friedrich; Diwanji, Prajakta; Hinkelmann, Knut; Dornberger, Rolf [in: New trends in business information systems and technology. Digital innovation and digital business transformation]04A - Beitrag Sammelband
- PublicationEnhance classroom preparation for flipped classroom using AI and analytics(SciTePress, 2018) Diwanji, Prajakta; Hinkelmann, Knut; Witschel, Hans Friedrich; Hammoudi, Slimane; Smialek, Michal; Camp, Olivier; Filipe, Joaquim [in: ICEIS 2018. 20th International Conference on Enterprise Information Systems. Proceedings]In a flipped classroom setting, it is important for students to come prepared for the classroom. Being prepared in advance helps students to grasp the concepts taught during classroom sessions. A recent student survey at Fachhochschule Nordwestschweiz (FHNW), Business School, Switzerland, revealed that only 27.7% students often prepared before a class and only 7% always prepared before a class. The main reason for not preparing for classes was lack of time and workload. A literature review study revealed that there is a growth of the use of Artificial Intelligence (AI), for example, chatbots and teaching assistants, which support both teachers and students for classroom preparation. There is also a rise in the use of data analytics to support tutor decision making in real time. However, many of these tools are based on external motivation factors like grading and assessment. Intrinsic motivation among students is more rewarding in the long term. This paper proposes an application based on AI and data analysis that focuses on intrinsically motivating and preparing students in a flipped classroom approach.04B - Beitrag Konferenzschrift
- PublicationLearning Business Rules for Adaptive Process Models(2012) Hinkelmann, Knut; Witschel, Hans Friedrich; Nguyen, Tuan Q. [in: BUSTECH 2012 - Second International Conference on Business Intelligence and Technology]This work presents a new approach to handling knowledge-intensive business processes in an adaptive, flexible and accurate way. We propose to support processes by executing a process skeleton, consisting of the most important recurring activities of the process, through a workflow engine. This skeleton should be kept simple. The corresponding workflow is complemented by two features: firstly, a task management tool through which workflow tasks are delivered and that give human executors flexibility and freedom to adapt tasks by adding subtasks and resources as required by the context. And secondly, a component that learns business rules from the log files of this task management and that will predict subtasks and resources on the basis of knowledge from previous executions. We present supervised and unsupervised approaches for rule learning and evaluate both on a real business process with 61 instances. Results are promising, showing that meaningful rules can be learned even from this comparatively small data set.04B - Beitrag Konferenzschrift
- PublicationRefining process models through the analysis of informal work practice(2011) Brander, Simon; Hinkelmann, Knut; Hu, Bo; Martin, Andreas; Riss, Uwe; Thönssen, Barbara; Witschel, Hans FriedrichThe work presented in this paper explores the potential of leveraging the traces of informal work and collaboration in order to improve business processes over time. As process executions often differ from the original design due to individual preferences, skills or competencies and exceptions, we propose methods to analyse personal preferences of work, such as email communication and personal task execution in a task management application. Outcome of these methods is the detection of internal substructures (subtasks or branches) of activities on the one hand and the recommendation of resources to be used in activities on the other hand, leading to the improvement of business process models. Our first results show that even though human intervention is still required to operationalise these insights it is indeed possible to derive interesting and new insights about business processes from traces of informal work and infer suggestions for process model changes.04B - Beitrag Konferenzschrift