TY - CHAP A1 - Brandenburger, Bonny A1 - Teichmann, Malte T1 - Looking for participation BT - adapting participatory learning oriented-didactic design elements of FabLabs in learning factories T2 - 12th Conference on Learning Factories N2 - A stronger learner orientation through participatory learning increases learning motivation and results. But what does participatory learning mean? Where do learning factories and fabrication laboratories (FabLabs) stand in this context, and how can didactic implementation be improved in this respect? Using a newly developed analytical framework, which contains elements of the stage model of participation and general media didactics, we compare a FabLab and a learning factory example concerning the degree of participation. From this, we derive guidelines for designing participative teaching and learning processes in learning factories. We explain how FabLabs can be an inspiration for the didactic design of learning factories. KW - participatory learning KW - FabLabs KW - subject-oriented learning KW - analytical framework Y1 - 2022 UR - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4073886 SN - 1556-5068 SP - 1 EP - 6 PB - Social Science Electronic Publishing CY - [Erscheinungsort nicht ermittelbar] ER - TY - CHAP A1 - Diaz Ferreyra, Nicolás Emilio A1 - Shahi, Gautam Kishore A1 - Tony, Catherine A1 - Stieglitz, Stefan A1 - Scandariato, Riccardo ED - Schmidt, Albrecht ED - Väänänen, Kaisa ED - Goyal, Tesh ED - Kristensson, Per Ola ED - Peters, Anicia T1 - Regret, delete, (do not) repeat BT - an analysis of self-cleaning practices on twitter after the outbreak of the covid-19 pandemic T2 - Extended abstracts of the 2023 CHI conference on human factors in computing systems N2 - During the outbreak of the COVID-19 pandemic, many people shared their symptoms across Online Social Networks (OSNs) like Twitter, hoping for others’ advice or moral support. Prior studies have shown that those who disclose health-related information across OSNs often tend to regret it and delete their publications afterwards. Hence, deleted posts containing sensitive data can be seen as manifestations of online regrets. In this work, we present an analysis of deleted content on Twitter during the outbreak of the COVID-19 pandemic. For this, we collected more than 3.67 million tweets describing COVID-19 symptoms (e.g., fever, cough, and fatigue) posted between January and April 2020. We observed that around 24% of the tweets containing personal pronouns were deleted either by their authors or by the platform after one year. As a practical application of the resulting dataset, we explored its suitability for the automatic classification of regrettable content on Twitter. KW - privacy KW - self-disclosure KW - online regrets KW - deleted tweets KW - crisis communication KW - COVID-19 Y1 - 2023 SN - 978-1-45039-422-2 U6 - https://doi.org/10.1145/3544549.3585583 SP - 1 EP - 7 PB - ACM CY - New York, NY ER - TY - CHAP A1 - Kocur, Alexander A1 - Clausen, Sünje A1 - Hofeditz, Lennart A1 - Brünker, Felix A1 - Fromm, Jennifer A1 - Stieglitz, Stefan T1 - Fighting false information BT - designing a conversational agent for public sector organizations T2 - ECIS 2023 research-in-progress papers N2 - The digital transformation poses challenges for public sector organizations (PSOs) such as the dissemination of false information in social media which can cause uncertainty among citizens and decrease trust in the public sector. Some PSOs already successfully deploy conversational agents (CAs) to communicate with citizens and support digital service delivery. In this paper, we used design science research (DSR) to examine how CAs could be designed to assist PSOs in fighting false information online. We conducted a workshop with the municipality of Kristiansand, Norway to define objectives that a CA would have to meet for addressing the identified false information challenges. A prototypical CA was developed and evaluated in two iterations with the municipality and students from Norway. This research-in-progress paper presents findings and next steps of the DSR process. This research contributes to advancing the digital transformation of the public sector in combating false information problems. KW - false information KW - conversational agents KW - crisis communication KW - media literacy Y1 - 2023 UR - https://aisel.aisnet.org/ecis2023_rip/65 PB - AIS Electronic Library (AISeL) CY - [Erscheinungsort nicht ermittelbar] ER - TY - CHAP A1 - Rojahn, Marcel A1 - Gronau, Norbert T1 - Digital platform concepts for manufacturing companies BT - a review T2 - 10th International Conference on Future Internet of Things and Cloud (FiCloud) N2 - Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms. Y1 - 2023 SN - 979-8-3503-1635-3 U6 - https://doi.org/10.1109/FiCloud58648.2023.00030 SP - 149 EP - 158 PB - IEEE CY - [Erscheinungsort nicht ermittelbar] ER - TY - CHAP A1 - Böhme, Lukas A1 - Wuttke, Tobias A1 - Bender, Benedict A1 - Teusner, Ralf A1 - Baltes, Sebastian A1 - Matthies, Christoph A1 - Perscheid, Michael T1 - From full-fledged erp systems towards process-centric business process platforms T2 - Twenty-ninth Americas Conference on Information Systems, Panama, 2023 N2 - Enterprise Resource Planning (ERP) systems are critical to the success of enterprises, facilitating business operations through standardized digital processes. However, existing ERP systems are unsuitable for startups and small and medium-sized enterprises that grow quickly and require adaptable solutions with low barriers to entry. Drawing upon 15 explorative interviews with industry experts, we examine the challenges of current ERP systems using the task technology fit theory across companies of varying sizes. We describe high entry barriers, high costs of implementing implicit processes, and insufficient interoperability of already employed tools. We present a vision of a future business process platform based on three enablers: Business processes as first-class entities, semantic data and processes, and cloud-native elasticity and high availability. We discuss how these enablers address current ERP systems' challenges and how they may be used for research on the next generation of business software for tomorrow's enterprises. KW - ERP system KW - enterprise system KW - business process platform Y1 - 2023 U6 - https://doi.org/10.48550/arXiv.2306.02995 PB - arXiv.org, Cornell University CY - Ithaca, NY ER - TY - CHAP A1 - Bender, Benedict A1 - Gronau, Norbert A1 - Winter, Robert ED - Bui, Tung X. T1 - Minitrack introduction enterprise-level information systems BT - research minitrack T2 - Proceedings of the 56th Hawaii International Conference on System Sciences N2 - While Information Systems (IS) Research on the individual and workgroup level of analysis is omnipresent, research on the enterprise-level IS is less frequent. Even though research on Enterprise Systems and their management is established in academic associations and conference programs, enterprise-level phenomena are underrepresented. This minitrack provides a forum to integrate existing research streams that traditionally needed to be attached to other topics (such as IS management or IS governance). The minitrack received broad attention. The three selected papers address different facets of the future role of enterprise-wide IS including aspects such as carbonization, ecosystem integration, and technology-organization fit. KW - information systems research KW - enteprise-level KW - enterprise systems Y1 - 2023 SN - 978-0-9981331-6-4 SN - 2572-6862 SP - 5809 EP - 5810 PB - Hawaii International Conference on System Sciences CY - Honolulu, HI ER - TY - CHAP A1 - Gonnermann, Jana A1 - Teichmann, Malte T1 - Influence of pre-experience on learning, usability and cognitive load in a virtual learning environment T2 - Americas conference on information systems N2 - Virtual reality can have advantages for education and learning. However, it must be adequately designed so that the learner benefits from the technological possibilities. Understanding the underlying effects of the virtual learning environment and the learner’s prior experience with virtual reality or prior knowledge of the content is necessary to design a proper virtual learning environment. This article presents a pre-study testing the design of a virtual learning environment for engineering vocational training courses. In the pre-study, 12 employees of two companies joined the training course in one of the two degrees of immersion (desktop VR and VR HMD). Quantitative results on learning success, cognitive load, usability, and motivation and qualitative learning process data were presented. The qualitative data assessment shows that overall, the employees were satisfied with the learning environment regardless of the level of immersion and that the participants asked for more guidance and structure accompanying the learning process. Further research is needed to test for solid group differences. KW - immersion KW - virtual learning environments KW - learner characteristics KW - vocational training KW - cognitive load theory Y1 - 2023 UR - https://aisel.aisnet.org/amcis2023/sig_ed/sig_ed/25/ IS - 1871 PB - AIS CY - Atlanta ER - TY - CHAP A1 - Grum, Marcus A1 - Thim, Christof A1 - Roling, Wiebke A1 - Schüffler, Arnulf A1 - Kluge, Annette A1 - Gronau, Norbert ED - Masrour, Tawfik ED - El Hassani, Ibtissam ED - Barka, Noureddine T1 - AI case-based reasoning for artificial neural networks T2 - Artificial intelligence and industrial applications N2 - Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level. KW - case-based reasoning KW - neural networks KW - industry 4.0 Y1 - 2023 SN - 978-3-031-43523-2 SN - 978-3-031-43524-9 U6 - https://doi.org/10.1007/978-3-031-43524-9_2 VL - 771 SP - 17 EP - 35 PB - Springer CY - Cham ER - TY - CHAP A1 - Grum, Marcus ED - Rutkowski, Leszek ED - Scherer, Rafał ED - Korytkowski, Marcin ED - Pedrycz, Witold ED - Tadeusiewicz, Ryszard ED - Zurada, Jacek M. T1 - Learning representations by crystallized back-propagating errors T2 - Artificial intelligence and soft computing N2 - With larger artificial neural networks (ANN) and deeper neural architectures, common methods for training ANN, such as backpropagation, are key to learning success. Their role becomes particularly important when interpreting and controlling structures that evolve through machine learning. This work aims to extend previous research on backpropagation-based methods by presenting a modified, full-gradient version of the backpropagation learning algorithm that preserves (or rather crystallizes) selected neural weights while leaving other weights adaptable (or rather fluid). In a design-science-oriented manner, a prototype of a feedforward ANN is demonstrated and refined using the new learning method. The results show that the so-called crystallizing backpropagation increases the control possibilities of neural structures and interpretation chances, while learning can be carried out as usual. Since neural hierarchies are established because of the algorithm, ANN compartments start to function in terms of cognitive levels. This study shows the importance of dealing with ANN in hierarchies through backpropagation and brings in learning methods as novel ways of interacting with ANN. Practitioners will benefit from this interactive process because they can restrict neural learning to specific architectural components of ANN and can focus further development on specific areas of higher cognitive levels without the risk of destroying valuable ANN structures. KW - artificial neural networks KW - backpropagation KW - knowledge crystallization KW - second-order conditioning KW - cognitive levels KW - NMDL Y1 - 2023 SN - 978-3-031-42504-2 SN - 978-3-031-42505-9 U6 - https://doi.org/10.1007/978-3-031-42505-9_8 SP - 78 EP - 100 PB - Springer CY - Cham ER - TY - CHAP A1 - Brandenburger, Bonny A1 - Brüsch, Julia A1 - Voigt, Maximilian A1 - Busch, Magnus T1 - Towards an open hardware process model for long-term sustainability T2 - ECIS 2023 research-in-progress papers N2 - The rise of open source models for software and hardware development has catalyzed the debate regarding sustainable business models. Open Source Software has already become a dominant part in the software industry, whereas Open Source Hardware is still a little-researched phenomenon but has the potential to do the same to manufacturing in a wide range of products. This article addresses this potential by introducing a research design to analyze the prototyping phase of six different Open Source Hardware projects tackling ecological, social, and economical challenges. Using a design science research methodology, a process model is developed to concretise the prototype development steps. The prototype phase is important because it is where fundamental decisions are made that affect the openness of the final product. This paper aims to advance the discourse on open production as a concept that enables companies to apply the aspect of openness towards collaboration-oriented and sustainable business models. KW - open hardware KW - prototyping process KW - co-creation KW - documentation KW - sustainable product development Y1 - 2023 UR - https://aisel.aisnet.org/ecis2023_rip/77 SP - 1428 EP - 1439 PB - Association for Information Systems (AIS) CY - Atlanta, GA ER -