Suchergebnisse - "Vaithilingam P"

Measuring GitHub Copilot's Impact on Productivity.

Autoren: Ziegler, Albert Kalliamvakou, Eirini Li, X. Alice et al.

Quelle: Communications of the ACM; Mar2024, Vol. 67 Issue 3, p54-63, 10p

Schlagwörter: SOFTWARE development tools, COMPUTER programming, LABOR productivity, SOFTWARE engineers, COMPUTER programmers, ARTIFICIAL intelligence software

Firma/Körperschaft: GITHUB Inc.

Technological Interventions for Vocational Inclusion of Individuals with Disabilities: A Scoping Review.

Autoren: Hamideh Kerdar, Sara Marleen Kirchhoff, Britta Adolph, Lars et al.

Quelle: Journal of Vocational Rehabilitation; Nov2025, Vol. 63 Issue 3, p325-341, 17p

Schlagwörter: RESEARCH funding, CINAHL database, DESCRIPTIVE statistics, SOCIAL integration, SYSTEMATIC reviews, VOCATIONAL rehabilitation, TECHNOLOGY, PEOPLE with disabilities, PSYCHOLOGY information storage & retrieval systems

Evaluating teachers’ perspectives on education-based assessments strategies with artificial intelligence.

Autoren: Cheah, Kenny S. L. Tang, ShanShan Kularajasingam, Janitha et al.

Quelle: International Journal of Education & Practice (2311-6897); 2025, Vol. 13 Issue 3, p923-942, 20p

Schlagwörter: ARTIFICIAL intelligence, EDUCATIONAL evaluation, ETHICAL problems, TEST validity, COLLEGE teacher attitudes, EDUCATIONAL support, OUTCOME-based education

Beyond the Benchmark: A Customizable Platform for Real-Time, Preference-Driven LLM Evaluation.

Autoren: Zografos, George Moussiades, Lefteris

Quelle: Electronics (2079-9292); Jul2025, Vol. 14 Issue 13, p2577, 19p

Schlagwörter: LANGUAGE models, EVALUATION methodology, MEASUREMENT-model comparison, DECISION support systems

Evaluating large language models: a systematic review of efficiency, applications, and future directions.

Autoren: Saleh, Yasmeen Abu Talib, Manar Nasir, Qassim et al.

Quelle: Frontiers in Computer Science; 2025, p1-13, 13p

Towards an understanding of large language models in software engineering tasks.

Autoren: Zheng, Zibin Ning, Kaiwen Zhong, Qingyuan et al.

Quelle: Empirical Software Engineering; Mar2025, Vol. 30 Issue 2, p1-38, 38p

Java coding using artificial intelligence.

Autoren: Uandykova, Mafura Baitenova, Laura Mukhamejanova, Gulnar et al.

Quelle: Frontiers in Computer Science; 2025, p1-12, 12p

An empirical study on developers’ shared conversations with ChatGPT in GitHub pull requests and issues.

Autoren: Hao, Huizi Hasan, Kazi Amit Qin, Hong et al.

Quelle: Empirical Software Engineering; Nov2024, Vol. 29 Issue 6, p1-43, 43p

Generative AI in mobile networks: a survey.

Autoren: Karapantelakis, Athanasios Alizadeh, Pegah Alabassi, Abdulrahman et al.

Quelle: Annals of Telecommunications; Feb2024, Vol. 79 Issue 1/2, p15-33, 19p

Large language models: an overview of foundational architectures, recent trends, and a new taxonomy.

Autoren: Mienye, Ibomoiye Domor Jere, Nobert Obaido, George et al.

Quelle: Discover Applied Sciences; Sep2025, Vol. 7 Issue 9, p1-35, 35p

Considering the ethics of large machine learning models in the chemical sciences.

Autoren: Spotte-Smith, Evan Walter Clark

Quelle: Machine Learning: Science & Techonology; Sep2025, Vol. 6 Issue 3, p1-23, 23p

Investigation of Generative AI Adoption in IT-Focused Vocational Secondary School Programming Education.

Autoren: Annuš, Norbert

Quelle: Education Sciences; Sep2025, Vol. 15 Issue 9, p1152, 26p

Schlagwörter: GENERATIVE artificial intelligence, VOCATIONAL education, COMPUTER programming education, COMPUTER science students, INTELLIGENT tutoring systems, INDIVIDUALIZED instruction

Interviewing AI: Using qualitative methods to explore and capture machines' characteristics and behaviors.

Autoren: Jarrahi, Mohammad Hossein

Quelle: Big Data & Society; Jul-Sep2025, Vol. 12 Issue 3, p1-15, 15p

Schlagwörter: QUALITATIVE research, TRIANGULATION, CRITICAL discourse analysis, ETHICAL problems, SELF-organizing systems, INQUIRY (Theory of knowledge)

A Student-Centric Evaluation Survey to Explore the Impact of LLMs on UML Modeling.

Autoren: Al-Ahmad, Bilal Alsobeh, Anas Meqdadi, Omar et al.

Quelle: Information; Jul2025, Vol. 16 Issue 7, p565, 34p

Schlagwörter: SOFTWARE engineering, LANGUAGE models, MODELING languages (Computer science), ENGINEERING education, ENGINEERING students, UNIFIED modeling language

Bugs in large language models generated code: an empirical study.

Autoren: Tambon, Florian Moradi-Dakhel, Arghavan Nikanjam, Amin et al.

Quelle: Empirical Software Engineering; Jun2025, Vol. 30 Issue 3, p1-48, 48p

MP: motion program synthesis with machine learning interpretability and knowledge graph analogy.

Autoren: Cai, Cheng-Hao

Quelle: Automated Software Engineering; Jun2025, Vol. 32 Issue 1, p1-40, 40p

Can Generative Artificial Intelligence Outperform Self-Instructional Learning in Computer Programming?: Impact on Motivation and Knowledge Acquisition.

Autoren: Mellado, Rafael Cubillos, Claudio

Quelle: Applied Sciences (2076-3417); Jun2025, Vol. 15 Issue 11, p5867, 32p

Schlagwörter: GENERATIVE artificial intelligence, ARTIFICIAL intelligence, INSTRUCTIONAL films, REAL-time programming, COMPUTER programming, KNOWLEDGE acquisition (Expert systems)

The AI of Oz: A Conceptual Framework for Democratizing Generative AI in Live-Prototyping User Studies.

Autoren: Santiago III, Jose Maria Sendner, Moritz Ralser, David et al.

Quelle: Applied Sciences (2076-3417); May2025, Vol. 15 Issue 10, p5506, 23p

Schlagwörter: GENERATIVE artificial intelligence, USER interfaces, ARTIFICIAL intelligence, DESIGNERS

Not Merely Useful but Also Amusing: Impact of Perceived Usefulness and Perceived Enjoyment on the Adoption of AI-Powered Coding Assistant.

Autoren: Kim, Young Woo Cha, Min Chul Yoon, Sol Hee et al.

Quelle: International Journal of Human-Computer Interaction; May2025, Vol. 41 Issue 10, p6210-6222, 13p

Schlagwörter: STRUCTURAL equation modeling, TECHNOLOGY Acceptance Model, INTRINSIC motivation, INNOVATION adoption, ARTIFICIAL intelligence, KNOWLEDGE base

Review and Mapping of Search-Based Approaches for Program Synthesis.

Autoren: Saber, Takfarinas Tao, Ning

Quelle: Information; May2025, Vol. 16 Issue 5, p401, 28p

Schlagwörter: SOFTWARE development tools, SEARCH algorithms, COMMUNITY-based programs, HEURISTIC programming, METAHEURISTIC algorithms