The proceedings contain 64 papers. The special focus in this conference is on Human Factors in Artificial Intelligence and Social Computing. The topics include: Random Samplings Using Metropolis Hastings Algorithm;the...
ISBN:
(纸本)9783030204532
The proceedings contain 64 papers. The special focus in this conference is on Human Factors in Artificial Intelligence and Social Computing. The topics include: Random Samplings Using Metropolis Hastings Algorithm;the Research on Automatic Acquirement of the Domain Terms;behavioral Analysis of Human-Machine Interaction in the Context of Demand Planning Decisions;deep-Learned Artificial Intelligence and System-Informational Culture Ergonomics;Association Matrix Method and Its Applications in Mining DNA Sequences;deep Learning-Based Real-Time Failure Detection of Storage Devices;identifying Touristic Interest Using Big Data Techniques;the Development of the Theory of Quality Assessment of the Information, Taking into Account Its Structural Component;a Meta-Language Approach for Machine Learning;emoVis – An Interactive Visualization Tool to Track Emotional Trends During Crisis Events;machine Self-confidence in Autonomous Systems via Meta-analysis of Decision Processes;research on Accuracy of Flower Recognition Application Based on Convolutional Neural Network;mapping Digital Media Content;social Media Competition for User Satisfaction: A Niche Analysis of Facebook, Instagram, YouTube, Pinterest, and Twitter;the Diffusion of News Applying Sentiment Analysis and Impact on Human Behavior Through Social Media;ensemble-Based Machine Learning Algorithms for Classifying Breast Tissue Based on Electrical Impedance Spectroscopy;Cognitive Solutions in the Enterprise: A Case Study of UX Benefits and Challenges;academic Quality Management System Audit Using Artificial Intelligence Techniques;Axonal Delay Controller for Spiking Neural Networks Based on FPGA;social Convos: A New Approach to Modeling Information Diffusion in Social Media;ubiquitous Fitting: Ontology-Based Dynamic Exercise Program Generation;innovation and Artificial Intelligence;an Analysis of Mobile Questionnaire Layouts.
This study examines the impact of AI programming assistants like GitHub Copilot and ChatGPT on softwareengineering efficiency, an area that has seen limited empirical research. We experimentally evaluated the perform...
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This study examines the impact of AI programming assistants like GitHub Copilot and ChatGPT on softwareengineering efficiency, an area that has seen limited empirical research. We experimentally evaluated the performance of programmers (n=16) in Python coding tasks with and without AI assistance, measuring time-to-completion and feature implementation. Results indicate that participants utilizing AI assistance completed tasks significantly faster (p = 0.033) and implemented more required features (p = 0.012) compared to those relying solely on unaided coding. These findings offer empirical insights into the integration of AI tools in software development workflows, highlighting their potential to enhance efficiency without compromising code quality or completeness, with implications for organizational pipelines and practitioner skills. Responses to exit surveys suggest that participants without IA tools assistance encountered frustrations related to code recall, time constraints, and problem-solving, while assisted participants reported no negative experiences, focusing instead on successful completion of tasks within the allotted time.
In previous work, we have provided a substantive amount of evidence that shows that Calibrated Peer Reviews to facilitate a feeling of "quality" in softwareengineering students have a strongly positive impa...
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ISBN:
(纸本)9798350378986;9798350378979
In previous work, we have provided a substantive amount of evidence that shows that Calibrated Peer Reviews to facilitate a feeling of "quality" in softwareengineering students have a strongly positive impact on student learning. Peer reviews repeatedly expose students to examples of different quality and force students to articulate engineering tradeoffs. Using calibration examples of different quality guides students in their evaluation of peer solutions and fosters an appreciation between good and bad solutions to exercise problems in requirements engineering and testing. The result is a significant improvement in test scores and theory retention, however, the overhead for the instructor to facilitate the peer review process outweighs the time saved for grading. In this article, we introduce "CPRtool" to automate collection and distribution of student solutions and peer feedback.
In project-based softwareengineering courses, development teams conformed by students explore the context and problem to address in their projects, before proposing any solution. The quality of this exploration, and ...
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ISBN:
(纸本)9783031601248;9783031601255
In project-based softwareengineering courses, development teams conformed by students explore the context and problem to address in their projects, before proposing any solution. The quality of this exploration, and the resulting output, usually make a difference on how quickly the development team identifies the goal and scope of the product to be developed. This exploration activity is usually complex and time consuming, since it requires dealing with uncertainties and misunderstandings between the development team and real or fictitious stakeholders. For that reason, the early exploration of the context and problem has been identified as a major and recurrent source of problems in software projects conducted in the industry and the academia. This paper presents an interactive visual tool that helps students explore the context and problem to address in project-based softwareengineering courses. The tool was used and evaluated by students from four different courses in two universities. According to the participants, the perceived usability and usefulness of the tool is high, surpassing the students' previous experiences when they used requirements engineering techniques for the same purpose.
Context: Regulatory acts are a challenging source when eliciting, interpreting, and analyzing requirements. Requirements engineers often need to involve legal experts who, however, may often not be available. This rai...
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ISBN:
(纸本)9798350395525;9798350395518
Context: Regulatory acts are a challenging source when eliciting, interpreting, and analyzing requirements. Requirements engineers often need to involve legal experts who, however, may often not be available. This raises the need for approaches to regulatory Requirements engineering (RE) covering and integrating both legal and engineering perspectives. Problem: Regulatory RE approaches need to capture and reflect both the elementary concepts and relationships from a legal perspective and their seamless transition to concepts used to specify software requirements. No existing approach considers explicating and managing legal domain knowledge and engineering-legal coordination. Method: We conducted focus group sessions with legal researchers to identify the core challenges to establishing a regulatory RE approach. Based on our findings, we developed a candidate solution and conducted a first conceptual validation to assess its feasibility. Results: We introduce the first version of our Artifact Model for Regulatory Requirements engineering (AM4RRE) and its conceptual foundation. It provides a blueprint for applying legal (modelling) concepts and well-established RE concepts. Our initial results suggest that artifact-centric RE can be applied to managing legal domain knowledge and engineering-legal coordination. Conclusions: The focus groups that served as a basis for building our model and the results from the expert validation both strengthen our confidence that we already provide a valuable basis for systematically integrating legal concepts into RE. This overcomes contemporary challenges to regulatory RE and serves as a basis for exposure to critical discussions in the community before continuing with the development of tool-supported extensions and large-scale empirical evaluations in practice.
With organizations seeking faster, cheaper, and smarter ways of delivering higher quality software, many are looking towards generative artificial intelligence (AI) to drive efficiencies and innovation throughout the ...
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With organizations seeking faster, cheaper, and smarter ways of delivering higher quality software, many are looking towards generative artificial intelligence (AI) to drive efficiencies and innovation throughout the software development lifecycle. However, generative AI can suffer from several fundamental issues, including a lack of traceability in concept generation and decision-making, the potential for making incorrect inferences (hallucinations), shortcomings in response quality, and bias. Quality engineering (QE) has long been utilized to enable more efficient and effective delivery of higher quality software. A core aspect of QE is adopting quality models to support various lifecycle practices, including requirements definition, quality risk assessments, and testing. In this position paper, we introduce the application of QE to AI systems, consider shortcomings in existing AI quality models from the international Organization for Standardization (ISO), and propose extensions to ISO models based on the results of a survey. We also reflect on skills that IT graduates may need in the future, to support delivery of better-quality AI.
The proceedings contain 8 papers. The topics discussed include: study group report on square future direction;revisiting the quality in use model;quality consideration for e-learning system based on ISO/IEC 25000 qual...
The proceedings contain 8 papers. The topics discussed include: study group report on square future direction;revisiting the quality in use model;quality consideration for e-learning system based on ISO/IEC 25000 quality standard;usability in software development process -proposal of society/stakeholder centered design (SCD);test management based on quality characteristics;research on quality model of industrial application software;and hidden-use case for eliciting quality in use.
Video Multimodal Entity Linking (VMEL) is a task to link entities mentioned in videos to entities in multimodal knowledge bases. However, current entity linking methods primarily focus on text and image modalities, ne...
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Video Multimodal Entity Linking (VMEL) is a task to link entities mentioned in videos to entities in multimodal knowledge bases. However, current entity linking methods primarily focus on text and image modalities, neglecting the significance of video modality. To address this challenge, we propose a novel framework called the multi-perspective enhanced Subgraph Contrastive Network (SCMEL) and construct a VMEL dataset named SceneMEL, based on tourism domain. We first integrate textual, auditory and visual modal contexts of videos to generate a comprehensive high-recall candidate entity set. Furthermore, a semantic-enhanced video description subgraph generation module is utilized to convert videos into a multimodal feature graph structure and perform subgraph sampling on the domain-specific knowledge graph. Lastly, we conduct contrastive learning on local perspectives (text, audio, visual) within the video subgraphs and the knowledge graph subgraphs, as well as global perspectives, to capture fine-grained semantic information about videos and entities. A series of experimental results on SceneMel demonstrate the effectiveness of the proposed approach.
Higher educational institutions seek to improve the quality and the productivity of the educational process. The current attitude is toward involving students in the learning and evaluation process. Peer review has be...
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ISBN:
(纸本)9798350378986;9798350378979
Higher educational institutions seek to improve the quality and the productivity of the educational process. The current attitude is toward involving students in the learning and evaluation process. Peer review has been proven to be one of the most effective tactics to attain this in softwareengineering disciplines wherein project-based courses are substantial to afford high quality competencies. A few studies in literature empirically studied the impact of peer review in project-based softwareengineering courses. In this work, we attempt to provide more insights by implementing peer assessment in one of the project-based courses offered by the Department of softwareengineering at the Hashemite University, Jordan, that is "Object-Oriented software Development". In this paper, we investigate the validity of peer assessment by examining how well students in this course evaluate their peers and how the strength of students affects their assessment. The work also embeds a rubric that comprises key criteria to assess software system modelling. The results of the study reveal promising signs of using peer assessment in project-based softwareengineering courses.
As part of a large Information and Communication Technology for Development (ICT4D) programme, we conducted a number of research projects to empower fisherfolk in Bangladesh. Due to their low socio-economic status, lo...
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ISBN:
(纸本)9798350322613
As part of a large Information and Communication Technology for Development (ICT4D) programme, we conducted a number of research projects to empower fisherfolk in Bangladesh. Due to their low socio-economic status, low level of digital as well as general literacy and many other similar factors, fisherfolk are very diverse as end users of software. It was important to understand their characteristics before designing any software for them. We started with exploratory research in reviewing literature and hearing from experts who closely work with fisherfolk. Based on the identification of some of the challenges, we designed a prototype software for tacit knowledge transfer among captains of boats. We conducted number of focus groups with the captains of the boats and adopted a co-creation process where the functionality and usability of the prototype software were decided by the end users themselves. From our experience of working with this diverse group of end users we propose specific recommendations for future software development for end users with a low socio-economic background.
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