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Disruption of Norms: A Conceptualised Antecedent of UTAUT 1

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21st European, Mediterranean, and Middle Eastern Conference on information Systems

作者： Moges, Aragaw Demissie Mkansi, Marcia Amadi-Echendu, Anthea UNISA Pretoria South Africa

ISBN: (数字)9783031813252

ISBN: (纸本)9783031813245;9783031813252

Technology adoption has dominated research across several disciplines, most notably in the era of rapid growth of the Fourth Industrial Revolution, Fifth Industrial Revolution, and Internet of Things. At the epicentre of technology adoption is the use of UTAUT which seek to explain user intentions of digital systems and subsequent behaviour. While the UTAUT model provides a good framework for understanding technology acceptance behaviour, it lacks a new antecedent, which is referred to in this study as disruption of norms or disruption of rules and practices. Using a systematic literature review approach, the study fleshes out the contextual features of disruption of norms and how it influences technology adoption. The findings emphasise that norm disruption is typically imposed by external forces including, but not limited to, government, economic upheavals, regulation, pandemics, humanitarian, environmental, and technological interruptions. The study contributes to UTAUT theory by identifying and introducing the missing antecedent that could extend the core assumption of the theory.

关键词： Norm disruption UTAUT adoption and use of technology new antecedent

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Transforming Education with AI and Robotics: Potential, Perceptions, and Infrastructure Needs 21st

Transforming Education with AI and Robotics: Potential, Perc...

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21st European, Mediterranean, and Middle Eastern Conference on information Systems

作者： Vasou, Marina Kyprianou, Georgios Amanatiadis, Angelos Chatzichristofis, Savvas A. Neapolis Univ Pafos Intelligent Syst Lab Paphos Cyprus Democritus Univ Thrace Dept Prod & Management Engn Komotini Greece

ISBN: (纸本)9783031813214;9783031813221

The rapid rise of artificial intelligence (AI) is reshaping various industries, with education emerging as a pivotal field ripe for transformation. AI's ability to analyze vast amounts of data, recognize patterns and make predictive decisions positions it as a game-changer in the educational sector. This study investigates the integration of AI and robotic systems in education, examining their potential to revolutionize learning experiences and outcomes. AI transforms education by enabling personalized learning paths, enhancing student engagement through adaptive learning platforms, and providing real-time feedback and assessment. It facilitates differentiated instruction tailored to individual student needs and fosters an environment where students can learn at their own pace. The research, involving a survey of 248 respondents from Cyprus and Greece, highlights a strong correlation between higher educational attainment and greater awareness and appreciation of AI's role in education. There is significant support among educators and students for integrating AI into educational practices, underscoring a readiness to embrace these technologies for improved educational outcomes. However, the study also identifies critical challenges, including inadequate infrastructure and the need for substantial financial support to fully leverage AI's potential. This research emphasizes the transformative impact of AI in education and advocates for strategic investments to overcome existing barriers and enhance the educational landscape through advanced technologies.

关键词： Artificial Intelligence in Education Robotics Personalized Learning Educational Technology Infrastructure

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A Journey Through SPACE Unpacking the Perceived Productivity of GitHub Copilot

A Journey Through SPACE Unpacking the Perceived Productivity...

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25th International Conference on Agile Software Development (XP)

作者： Wivestad, Viggo Tellefsen Ulfsnes, Rasmus SINTEF Digital N-7034 Trondheim Norway Norwegian Univ Sci & Technol N-7491 Trondheim Norway

ISBN: (纸本)9783031727801;9783031727818

This study examines the influence of perceived changes in productivity in the context of introducing AI Coding Assistants, specifically GitHub Copilot, within two large-scale agile organizations. Using a cross-sectional survey, we measured self-reported changes in productivity using the SPACE framework. Our comparative analysis suggests several perceived benefits of AI Code Assistant adoption, though with a more conservative impact than previously reported. Further, a correlational analysis employing Kendall's tau and PLSR with 10-fold cross-validation suggests that perceived changes to productivity are moderately associated only with four of the nine features tested, namely job satisfaction, flow, task completion speed, and ability to focus on satisfying work. However, the SPACE framework's ability to fully capture perceived productivity was further challenged, indicating discrepancies in its dimensions of "Performance" and "Communication and collaboration".

关键词： Developer Productivity AI Code Assistants SPACE GitHub Copilot

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Towards Continuous Certification of Software Systems for Aerospace

Towards Continuous Certification of Software Systems for Aer...

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25th International Conference on Agile Software Development (XP)

作者： Ferreira Ribeiro, J. Eduardo Univ Porto Dept Informat Engn Fac Engn P-4200465 Porto Portugal

ISBN: (纸本)9783031727801;9783031727818

Safety-critical systems are subject to strict regulation by domain-specific standards and documents. One such example is the DO-178C standard for aerospace, which provides guidance to organizations to ensure system safety and produce the necessary evidence for certification. In these regulated environments, most organizations rely on traditional development processes, unlike the widespread adoption of Agile in the broader software industry. This PhD research is a collaboration between academia and industry, involving the Faculty of Engineering at the University of Porto (FEUP), the University of Coimbra (UC), and Critical Software SA (CSW), as part of the Doctoral Program in Informatics Engineering at FEUP. The study focuses on integrating Agile methods and practices into safety-critical software development for aerospace applications, specifically adhering to the DO-178C standard. The goal is to define a new process that enhances safety-critical software development, moving towards continuous certification of software systems for aerospace. The research aims to establish a quasi-continuous certification process by evaluating new guidelines, practices, and tools, thereby ensuring high-quality and traceable software releases. Preliminary results are promising, as the initial case study involving a real industry project demonstrated positive outcomes using our innovative process. The findings are anticipated to advance the adoption of Agile methods and practices in safety-critical domains.

关键词： Agile, Aerospace DO-178C FAA Safety-critical Software development

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A Lightweight Predictive Maintenance Strategy for Marine HFO Purification Systems 21st

A Lightweight Predictive Maintenance Strategy for Marine HFO...

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21st European, Mediterranean, and Middle Eastern Conference on information Systems

作者： Kalafatelis, Alexandros S. Stamou, Nikolaos Dailani, Alkmini Theodoridis, Theodoros Nomikos, Nikolaos Giannopoulos, Anastasios Tsoulakos, Nikolaos Alexandridis, Georgios Trakadas, Panagiotis Natl & Kapodistrian Univ Athens Dept Ports Management & Shipping Euboea 34400 Greece Laskaridis Shipping Co Ltd Athens Greece Natl & Kapodistrian Univ Athens Dept Digital Ind Technol Euboea 34400 Greece

ISBN: (纸本)9783031813214;9783031813221

The maritime industry heavily relies on vessel maintenance to ensure the operational integrity and safety, as it is responsible for transporting more than 80% of global trade. Despite the industry's strong need for efficient maintenance techniques, there has been a noticeable gap in research regarding the use of data-driven methods to enhance vessel reliability. This study seeks to fill this gap, by examining the feasibility of deploying deep learning models to predict the Remaining Useful Life (RUL) of Heavy Fuel Oil (HFO) purification systems, taking into account also the challenges of the limited computational resources available on maritime vessels, as well as the substantial costs associated with implementing such models. Towards this direction, the impact of various optimization techniques (early stopping and pruning) on three state-of-the-art models (Long Short-Term Memory Network, Convolutional Neural Network, Autoencoders) was evaluated using operational vessel data provided by Laskaridis Shipping Co. Ltd., demonstrating the feasibility of deploying predictive maintenance (PdM) systems in real-world edge-constrained marine settings, potentially transforming maintenance practices and reducing operational costs.

关键词： Predictive maintenance Pruning Maritime industry

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Agile Software Engineering Capstone Courses: Exploring the Impact of Gender

Agile Software Engineering Capstone Courses: Exploring the I...

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25th International Conference on Agile Software Development (XP)

作者： Saeter, Gyda Elisa Lund, Camilla Kielland Stray, Viktoria Univ Oslo N-0373 Oslo Norway

ISBN: (纸本)9783031727801;9783031727818

The wide adoption of agile methodologies in software development necessitates an educational approach that prepares students for industry practices. This study aims to explore an agile capstone course, focusing on student learning experiences in teamwork while examining the gender dynamics affecting team roles and engagement. We conducted a comprehensive study of the capstone course "Software Engineering with Project Work" at the University of Oslo, analyzing 27 presentations and interviewing 10 students and two teaching assistants. The course is designed to immerse informatics students of different specializations in agile methodologies and collaborative project work. Our findings suggest that the students learn essential collaboration and technical skills. However, during their final presentations, significant gender differences emerged in the topics discussed: women predominantly spoke about design and process, whereas men focused more on technical aspects such as architecture, technical solutions, and algorithms. Our results underscore the need for educational strategies that promote inclusivity and equal participation in agile software development courses.

关键词： Collaboration Knowledge sharing Human and social aspects of agile software development Gender diversity Teaching experiences Empirical studies with students

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Automated Machine Learning in a Multi-agent Environment 21st

Automated Machine Learning in a Multi-agent Environment

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21st European, Mediterranean, and Middle Eastern Conference on information Systems

作者： Bakas, Nikolaos Lavdas, Spyros Vavousis, Konstantinos Christodoulou, Christos Langousis, Andreas Natl Infrastruct Res & Technol GRNET 7 Kifisias Ave Athens 11523 Greece Amer Coll Greece Sch Liberal Arts & Sci Dept InformationTechnol Athens Greece Double Eye Themidos Siapkara Pitsillidou 12 Limassol 3117 Cyprus Univ Patras Dept Civil Engn Patras 26504 Greece

ISBN: (纸本)9783031813214;9783031813221

We introduce a novel machine learning framework called Agentic Automated Machine Learning (AutoML), designed to integrate advanced agentic capabilities with traditional AutoML workflows. Agentic AutoML extends the machine learning model development lifecycle by incorporating Large Language Models (LLMs), with statistical analysis, model training, and hyperparameter tuning, etc., all tailored to a simple user experience. The Agentic AutoML builds on standard AutoML machine learning algorithms, including tree-based methods such as random forests and gradient boosting, as well as formula-driven models such as polynomial regression and artificial neural networks, also equipped with automatic statistical analysis, sensitivity assessments, error analysis, and automated report generation. Agentic AutoML architecture offers real-time guidance throughout the entire project workflow, enhancing user interaction and decision-making. By simplifying the application of machine learning algorithms, Agentic AutoML significantly broadens accessibility for users with varying levels of programming skills and machine learning expertise, making it a valuable tool for diverse user groups.

关键词： Automated Machine Learning Agentic workflows Deep learning Feature Selection

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Factors Limiting the Benefits of the Scrum Framework - What Years of Cumulative Scrum Practice by Professional Scrum Trainers Teaches Us About business Difficulties 1

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21st European, Mediterranean, and Middle Eastern Conference on information Systems

作者： Moussaoui, Theo Deneckere, Rebecca Goood 47 Blvd Courcelles F-75008 Paris France Univ Paris Pantheon Sorbonne Ctr Rech Informat Paris France

ISBN: (数字)9783031813252

ISBN: (纸本)9783031813245;9783031813252

Scrum is being used more and more in the software development world and beyond. Alongside this growth, many companies are struggling to exploit its full potential. This research operates on the principle that Scrum, having been utilized for nearly 30 years, should confer certain benefits. Our focus is then to identify the factors that may limit the expected benefits of Scrum. Consequently, we interviewed a dozen Professional Scrum Trainers to draw on their experience. This study give a glimpse into what years of practice shows about the use of Scrum. This research offers valuable insights for companies aiming to begin Scrum implementation or enhance their product development processes using Scrum.

关键词： Scrum Agile environment Limiting factor Interview Professional Scrum Trainer

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Artificial Intelligence Use and Potential within Project Management 21st

Artificial Intelligence Use and Potential within Project Man...

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21st European, Mediterranean, and Middle Eastern Conference on information Systems

作者： Senarath, Vishmi Berntzen, Lasse Univ South Eastern Norway Honefoss Norway Univ South Eastern Norway Horten Norway

ISBN: (纸本)9783031813214;9783031813221

This study explores the impact of Artificial Intelligence (AI) on project management in Norway using a mixed-methods approach. Initially, a questionnaire was answered by 84 respondents, followed by in-depth interviews with seven experienced project managers. The primary objective was to assess the extent of AI integration in project management practices and its perceived benefits. The findings reveal that a significant number of project managers in Norway have already incorporated AI tools into their workflows. These tools are primarily utilized for task automation, predictive analytics, and resource allocation. Project managers reported that AI significantly enhances efficiency by automating routine tasks, thereby allowing them to focus on more strategic activities. Additionally, AI tools provide valuable insights through data analysis, enabling more informed decision-making and greater project flexibility. Despite the overall positive reception, some respondents highlighted challenges such as the steep learning curve associated with new AI technologies and concerns over data security. These challenges, however, are manageable and can be addressed with proper training and robust data protection measures. The consensus is clear - AI has the potential to transform project management, making it more dynamic and adaptable to changing project demands. This study underscores the growing importance of AI in the project management domain in Norway. It suggests that ongoing advancements in AI technology will likely lead to even greater integration and reliance on these tools in the future. Further research is recommended to explore long-term impacts and the development of best practices for AI adoption in project management.

关键词： Project management Artificial intelligence Agile

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The AI Scrum Master: Using Large Language Models (LLMs) to Automate Agile Project Management Tasks

The AI Scrum Master: Using Large Language Models (LLMs) to A...

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25th International Conference on Agile Software Development (XP)

作者： Alliata, Zorina Singhal, Tanvi Bozagiu, Andreea-Madalina Zorina Alliata Munich Germany Tanvi Singhal Munich Germany Andreea-Madalina Bozagiu Bucharest Romania

ISBN: (纸本)9783031727801;9783031727818

There is a high demand across industries for intelligent devices to automate and optimize processes. Generative AI has soared in popularity and it is the first AI technology to be used by everyone. It is already automating junior-level office work, as well as highly complex creative tasks. This paper studies how Generative AI can automate some of the Agile project management tasks, such as reporting and creating requirements that correctly cover the scope.

关键词： AI Agile Scrum Master Project Management LLM Generative AI

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