Investigating the Use of Augmented Reality and Machine Learning in Electrical Engineering Courses

2023 | International Conference on Business Informatics | Citations: 0

Authors: Al Mehdawi, Miles; Dreesbach, Tobias; Gösling, Henning; Brinkmann, Marcel

Abstract: The use of augmented reality (AR) in education and training is growing increasi ... Expand

Abstract: The use of augmented reality (AR) in education and training is growing increasingly. However, applications to integrate augmented reality learning content into training for basic electrical engineering courses are scarce. The individual learning objectives of trainees complicate the digitalization of learning content, particularly for the drawing of circuit diagrams. To increase trainees' learning outcome while simultaneously relieving instructors of classroom supervision, we designed and developed an AR-based prototype, to enhance hand-drawn circuit diagrams in vocational training. The context sensitivity is achieved by combining AR with image recognition. In an experiment with twelve participants, a positive impact of the prototype on trainees' learning outcomes was observed, in comparison to a control group that received instructions without the prototype. Collapse

Topics: augmented reality smart device artificial intelligence smart glass extended reality

Methods: design artifact experimental group qualitative interview survey parametric test

Business Inferences and Risk Modeling with Machine Learning; The case of Aviation Incidents

2023 | HICSS | Citations: 0

Authors: Cankaya, B.; Topuz, K.; Glassman, A.

Abstract: Machine learning becomes truly valuable only when decision-makers begin to depe ... Expand

Abstract: Machine learning becomes truly valuable only when decision-makers begin to depend on it to optimize decisions. Instilling trust in machine learning is critical for businesses in their efforts to interpret and get insights into data, and to make their analytical choices accessible and subject to accountability. In the field of aviation, the innovative application of machine learning and analytics can facilitate an understanding of the risk of accidents and other incidents. These occur infrequently, generally in an irregular, unpredictable manner, and cause significant disruptions, and hence, they are classified as "highimpact, low-probability" (HILP) events. Aviation incident reports are inspected by experts, but it is also important to have a comprehensive overview of incidents and their holistic effects. This study provides an interpretable machine-learning framework for predicting aircraft damage. In addition, it describes patterns of flight specifications detected through the use of a simulation tool and illuminates the underlying reasons for specific aviation accidents. As a result, we can predict the aircraft damage with 85% accuracy and 84% in-class accuracy. Most important, we simulate a combination of possible flight-type, aircraft-type, and pilot-expertise combinations to arrive at insights, and we recommend actions that can be taken by aviation stakeholders, such as airport managers, airlines, flight training companies, and aviation policy makers. In short, we combine predictive results with simulations to interpret findings and prescribe actions.A machine-learning (ML) algorithm was chosen for its fast performance, short run-time, and interpretability. The ML algorithms were compared and evaluated on a confusion matrix for their mean receiver operating characteristic curve (ROC), Collapse

Topics: decision making decision support system graphical user interface usability missing data

Methods: simulation machine learning multinomial logistic regression computational algorithm support vector machine

Context and Aggregation: An Experimental Study of Bias and Discrimination in Organizational Decisions

2023 | Organization Science | Citations: 1

Authors: Christensen, Michael; Dahl, Christian M.; Knudsen, Thorbjørn; Warglien, Massimo

Abstract: This paper addresses a notable gap at the intersection of organizational economi ... Expand

Abstract: This paper addresses a notable gap at the intersection of organizational economics and organization science: how does organizational context influence aggregation of individual behavior in organizational decisions? Using basic centralized versus decentralized organizational structures as building blocks for our experimental design, we examine whether assignment of organizational positions, incentive schemes, and structural configuration induce endogenous adaptation in the form of change in reservation levels (bias) or modified discrimination capability in subjects’ behavior. We found that evaluators adapted their reservation and discrimination levels in centralized structures, whereas they did not generally adapt their reservation and discrimination levels when placed in decentralized structures. We identify mechanisms that explain these findings; explain how they influence aggregate, organizational behavior; and discuss implications for research and practice.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: M. Warglien acknowledges financial support from the European Union's Horizon 2020 research and innovation programme under [Grant Agreement 732942].Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1502. Collapse

Topics: organization structure organizational context decision making organizational productivity graphical user interface

Methods: experiment statistical hypothesis test experimental design theoretical contribution cluster analysis

Theories: organizational behavior theory

Guidance in Business Intelligence & Analytics Systems: A Review and Research Agenda

2023 | European Conference On Information Systems | Citations: 0

Authors: Gunklach, Jonas; Nadj, Mario

Abstract: While the data amount grows exponentially, the number of people with analytical ... Expand

Abstract: While the data amount grows exponentially, the number of people with analytical and technical skills is only slowly increasing. This skill gap is putting pressure on the labor market and increasing the need for personnel with these skills. At the same time, companies are forced to think of alternative ways to empower their less-skilled workforce to take on Business Intelligence and Analytics (BI&A) tasks. One promising attempt to address these challenges may turn to the concept of guidance. However, the current body of research on guidance in BI&A systems is scattered and lacks a structured investigation from which future research avenues can be derived. To address this gap, this article analyzes five categories, namely BI&A phases, guidance degree, guidance generation, user roles, and interactivity form. Reviewing 82 articles, our contribution is to synopsize articles on guidance in BI&A systems and to suggest five research avenues. Collapse

Topics: analytical information system data visualization data quality business intelligence artificial intelligence

Methods: exploratory data analysis machine learning literature sample time series analysis longitudinal research

A Chat-based personal recommendation mechanism with opinion intelligence

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Li, Yung-Ming; hsieh, chin yu; Hsu, Cheng-Chi

Abstract: A Chat-based personal recommendation mechanism with opinion intelligence" (2023 ... Expand

Abstract: A Chat-based personal recommendation mechanism with opinion intelligence" (2023). AbstractWith the rapid development of the Internet and mobile devices, users around the world have accumulated a large amount of comment data on the Internet. Nowadays, users tend to search for information on the Internet before making purchase decisions. How to provide personalized services while avoiding information overload has gradually become an important issue. This study proposes a dialogue-based personalized recommendation mechanism with opinion intelligence. In addition to understanding user preferences through dialogue and interaction with users, we further analyze the content of reviews and the social influence of review authors to better help users. The results show that the dialogue mechanism proposed in this study has a good recommendation effect and can effectively improve user experience. Collapse

Topics: recommender system social influence decision making user experience usability

Methods: experiment chatbot term frequency–inverse document frequency naïve bayes natural language processing

Touching Space: Distributed Ledger Technology for Tracking and Tracing Certificates

2023 | HICSS | Citations: 1

Authors: Moriggl, Pascal; Asprion, Petra; Schneider, Bettina; Scherb, Christopher

Abstract: Components built into space vehicles and equipment (space products) must meet di ... Expand

Abstract: Components built into space vehicles and equipment (space products) must meet different regulatory requirements; in detail, each component must be certified and sustainably traceable at all times. Space engineers have expressed the need for an interoperable system to collect, manage and route certifications for components, parts and materials that go into space products. The lack of a unified approach in the European space industry is a challenge for companies involved in product development. This research proposes an open-source, secure, fast and distributed ledger technology (DLT) based solution that fits into any IT environment and is well adapted to the needs of manufacturing companies in the space sector. The results show that a blockchain-based solution based on 'Hyperledger Fabric' combined with the InterPlanetary File System is viable. The results can guide other researchers and practitioners to consider DLTs when changing their certification management paradigm with suppliers, customers and auditors. Collapse

Topics: blockchain JavaScript authorization business process management graphical user interface

Methods: design artifact literature study qualitative interview

AI-based Technologies for Conversational Agent Design – Development Tools and Architectures for Intelligent Interactions

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Strohmann, Timo; Khosrawi-Rad, Bijan; Schmidt, Lukas; Hiske, Patrick

Abstract: Conversational agents are becoming increasingly intelligent due to artificial i ... Expand

Abstract: Conversational agents are becoming increasingly intelligent due to artificial intelligence (AI) advances, improving human-machine interaction. As conversational agents are already being used in various realworld applications, research shows the enormous potential of exploring advanced areas such as companionship or learning support. Particularly, those intelligent and future-oriented application areas rely on using AI-based technologies. However, implementations are often prototypical without comprehensive technological information. Moreover, the possibilities for practical implementation of conversational agents are growing, making the choice of architecture and tools for implementation complex. We address this problem by developing a taxonomy that helps characterize AI-based tools and services for intelligent interactions. We then derive archetypes for AI-based tools using cluster analysis and give meta-architectures that exemplify how to integrate AI-based services into typical technical conversational agent architectures. With our research, we aim to expand the knowledge base for developing conversational agents and support developers in their implementation. Collapse

Topics: artificial intelligence usability user interface database system Google+

Methods: cluster analysis sentiment analysis chatbot language model design artifact

Designing forecasting software for forecast users: Empowering non-experts to create and understand their own forecasts

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Stromer, Richard; Triebe, Oskar; Kim, Elijah; Hausleitner, Bernhard; Kobiella, Charlotte; Zanocco, Chad; Rajagopal, Ram

Abstract: Ram, "Designing forecasting software for forecast users: Empowering non-experts ... Expand

Abstract: Ram, "Designing forecasting software for forecast users: Empowering non-experts to create and understand their own forecasts" (2023). AMCIS AbstractForecasts inform decision-making in nearly every domain. Forecasts are often produced by experts with rare or hard to acquire skills. In practice, forecasts are generally used by domain experts and managers with little forecasting expertise. Our study focuses on how to design forecasting software that empowers nonexpert users. We study how users can make use of state-of-the-art forecasting methods, embed their domain knowledge, and how they build understanding and trust towards generated forecasts. To do so, we codesigned a forecasting software prototype using feedback from users and then analyzed their interactions with our prototype. Our results identified three main considerations for non-expert users: (1) a safe stepwise approach facilitating causal understanding and trust; (2) a white box model supporting human-reasoningfriendly components; (3) the inclusion of domain knowledge. This paper contributes insights into how nonexpert users interact with forecasting software and recommends ways to design more accessible forecasting software. Collapse

Topics: usability human computer interaction decision making Python graphical user interface

Methods: design artifact personal interview cognitive walkthrough survey qualitative interview

Giving DIAnA More TIME – Guidance for the Design of XAI-Based Medical Decision Support Systems

2023 | DESRIST | Citations: 0

Authors: Bunde, Enrico; Eisenhardt, Daniel; Sonntag, Daniel; Profitlich, Hans-Jürgen; Meske, Christian

Abstract: Future healthcare ecosystems integrating human-centered artificial intelligence ... Expand

Abstract: Future healthcare ecosystems integrating human-centered artificial intelligence (AI) will be indispensable. AI-based healthcare technologies can support diagnosis processes and make healthcare more accessible globally. In this context, we conducted a design science research project intending to introduce design principles for user interfaces (UIs) of explainable AI-based (XAI) medical decision support systems (XAI-based MDSS). We used an archaeological approach to analyze the UI of an existing web-based system in the context of skin lesion classification called DIAnA (Dermatological Images – Analysis and Archiving). One of DIAnA’s unique characteristics is that it should be usable for the stakeholder groups of physicians and patients. We conducted the in-situ analysis with these stakeholders using the think-aloud method and semi-structured interviews. We anchored our interview guide in concepts of the Theory of Interactive Media Effects (TIME), which formulates UI features as causes and user psychology as effects. Based on the results, we derived 20 design requirements and developed nine design principles grounded in TIME for this class of XAI-based MDSS, either associated with the needs of physicians, patients, or both. Regarding evaluation, we first conducted semi-structured interviews with software developers to assess the reusability of our design principles. Afterward, we conducted a survey with user experience/interface designers. The evaluation uncovered that 77% of the participants would adopt the design principles, and 82% would recommend them to colleagues for a suitable project. The findings prove the reusability of the design principles and highlight a positive perception by potential implementers. Collapse

Topics: explainable artificial intelligence artificial intelligence usability user experience user interface

Methods: qualitative interview design principle personal interview cognitive walkthrough survey

Theories: theory of interactive media effects theory of affordance sociotechnical systems theory

Studying the ability to use sport watches when running - insights from a small pilot study

2022 | European Conference On Information Systems | Citations: 0

Authors: Barreflod, Olle; Koncz, Martin; Landgren, Jonas; Eklund, Martin

Abstract: Digitalization is a phenomenon that seems to affect all aspects of contemporary ... Expand

Abstract: Digitalization is a phenomenon that seems to affect all aspects of contemporary society. The sports domain is by no means excluded from this development. In sports, the sport watch might be one of the most iconic symbols in how digitalization has enhanced, changed and developed how physical activities are experienced and measured. Despite the massive adoption of sport watches among runners and other athletes, few studies have explored how sports watches are used in the specific activity they are designed for. The study presented in this research in progress paper is small and should be viewed as a small attempt to outline an approach to study digital technology use in sports activities. Collapse

Topics: pandemic information system use mobile system telephone smart watch

Methods: experiment survey electrocardiography field study qualitative content analysis