Computer Games for Entertainment and Education: A Literature Review and Exploration on Artificial Intelligence Integration

Intelligent systems reference library, Journal Year: 2025, Volume and Issue: unknown, P. 25 - 62

Published: Jan. 1, 2025

Language: Английский

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An explainable machine learning method for predicting and designing crashworthiness of multi-cell tubes under oblique load

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 147, P. 110396 - 110396

Published: Feb. 26, 2025

Language: Английский

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What factors predict user acceptance of ChatGPT for mental and physical healthcare: an extended technology acceptance model framework

AI & Society, Journal Year: 2025, Volume and Issue: unknown

Published: May 3, 2025

Language: Английский

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Deep Learning in Oncology: Transforming Cancer Diagnosis, Prognosis, and Treatment

Emerging Trends in Drugs Addictions and Health, Journal Year: 2025, Volume and Issue: unknown, P. 100171 - 100171

Published: Feb. 1, 2025

Language: Английский

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Issues and trends in generative AI technologies for decision making

Intelligent Decision Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

Generative AI (GenAI) technologies are examined through the lens of issues and trends related to decision making. After examining foundations technology particularly large language models (LLM), opportunities for GenAI be used in decision-making process intelligence, design, choice implementation explored. With its ability rapidly generate insights, present optimized solutions, provide detailed analysis given input, has demonstrated that it can assist augment human Although systems have potential transform content creation cognition, they also raise around accuracy, misinformation, ethics, bias, morality, social impacts, privacy, copyright, legality, explainability, among others. Addressing these challenges is important maximize efficacy

Language: Английский

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Exploring the influence of artificial intelligence integration on personalized learning: a cross-sectional study of undergraduate medical students in the United Kingdom

BMC Medical Education, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 17, 2025

Abstract Background With the integration of Artificial Intelligence (AI) into educational systems, its potential to revolutionize learning, particularly in content personalization and assessment support, is significant. Personalized supported by AI tools, can adapt individual learning styles needs, thus transforming how medical students approach their studies. This study aims explore relationship between use for self-directed among undergraduate UK variables such as year study, gender, age. Methods cross-sectional involved a sample 230 from universities, collected through an online survey. The survey assessed usage including students’ attitudes towards accuracy, perceived benefits, willingness mitigate misinformation. Data were analyzed using descriptive statistics linear logistic regression examine associations demographics. Results analysis revealed that age significantly influenced pay tools ( p = 0.012) gender was linked concerns about inaccuracies 0.017). Female more likely take steps risks misinformation 0.045). also found variability based on with first-year showing higher reliance tools. Conclusion has greatly enhance personalized students. However, issues surrounding misinformation, equitable access need be addressed optimize education. Further research recommended longitudinal effects outcomes.

Language: Английский

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Evolution of Polish E-Consumers’ Environmental Awareness and Purchasing Behavior over Ten Years

Sustainability, Journal Year: 2024, Volume and Issue: 16(11), P. 4686 - 4686

Published: May 31, 2024

With the development of e-commerce in Poland, consumer awareness has evolved. Buyers not only compared prices and assessed quality products but also began to take into account impact their purchases on environment, which was previously an overlooked aspect. This growing environmental is part a broader effort address issues support practices that promote sustainability. Currently, there noticeable increase ecological among society, government bodies, scientific community, strengthening human interaction with natural environment. The aim this study examine changes attitudes Polish e-consumers over ten years online shopping behavior. explored how have evolved last decade what these had purchasing behavior consumers. Longitudinal studies were used enable analysis time. research technique based repeated measurements same phenomena features, carried out diverse samples from population, using methods tools. conducted twice, 2010 2020, sample 1150 people each years. employed survey questionnaire, included scales for assessing personality traits determinants shopping. A significant change found e-consumers’ towards environment preferences. clear behavior, including importance convenience, access detailed product information, wide range offered, reflecting more conscious convenience-oriented

Language: Английский

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Towards reconciling usability and usefulness of policy explanations for sequential decision-making systems

Frontiers in Robotics and AI, Journal Year: 2024, Volume and Issue: 11

Published: July 22, 2024

Safefy-critical domains often employ autonomous agents which follow a sequential decision-making setup, whereby the agent follows policy to dictate appropriate action at each step. AI-practitioners reinforcement learning algorithms allow an find best policy. However, systems lack clear and immediate signs of wrong actions, with consequences visible only in hindsight, making it difficult humans understand system failure. In learning, this is referred as credit assignment problem. To effectively collaborate system, particularly safety-critical setting, explanations should enable user better predict behavior so that users are cognizant potential failures these can be diagnosed mitigated. diverse have innate biases or preferences may enhance impair utility explanation agent. Therefore, paper, we designed conducted human-subjects experiment identify factors influence perceived usability objective usefulness for setting. Our study had two factors: modality shown (Tree, Text, Modified Programs) “first impression” agent, i.e., whether saw succeed fail introductory calibration video. findings characterize preference-performance tradeoff wherein participants language-based significantly more useable; however, were able objectively agent’s when provided form decision tree. results demonstrate user-specific factors, such computer science experience (p < 0.05), situational watching crash id="m2">< impact perception explanation. This research provides key insights alleviate prevalent issues regarding innapropriate compliance reliance, exponentially detrimental settings, providing path forward XAI developers future work on policy-explanations.

Language: Английский

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A methodical examination of single and multi-attacker flood attacks using RPL-based approaches

Computers & Industrial Engineering, Journal Year: 2024, Volume and Issue: 194, P. 110356 - 110356

Published: Aug. 1, 2024

Language: Английский

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Kimya, Fizik, Biyoloji ve Fen Bilimleri Öğretmenlerinin Yapay Zekâ Kullanımına Yönelik Görüş ve Tutumlarının Teknoloji Kabul Modeline göre Analizi

Batı anadolu eğitim bilimleri dergisi, Journal Year: 2024, Volume and Issue: 15(2), P. 1606 - 1641

Published: Aug. 9, 2024

Bu çalışmanın amacı, Kimya, Fizik, Biyoloji ve Fen Bilimleri öğretmenlerinin derslerinde yapay zekâ kullanımına yönelik görüş tutumları arasındaki ilişkinin Teknoloji Kabul Modeli (TAM) çerçevesinde algılanan kullanım kolaylığı fayda değişkenleri açısından derinlemesine incelenmesidir. Araştırmada karma yöntem kullanılmış olup, nitel veriler yarı yapılandırılmış görüşme formu aracılığıyla, nicel ise “Yapay Zekâya Yönelik Genel Tutum Ölçeği” ile toplanmıştır. Araştırma örneklemini, 2022-2023 yıllarında Türkiye’nin farklı bölgelerinde görev yapan dört branştan 51 öğretmen (25 kadın, 26 erkek) oluşturmaktadır. Nitel araştırma sonuçlarına göre, öğretmenlerin büyük çoğunluğu (%90.2) kullanımını faydalı bulmakta performanslarını artıracağını düşünmektedir (%84.3). Ayrıca, %58.8'i kullanmaktadır. Ancak, kullanmayan öğretmenler (%41.2), bu teknolojinin zor yeterli beceriye sahip olmadıklarını düşünmektedir. puan ortalaması 3.58 olarak bulunmuş da zekâya genel tutumlarının yüksek olduğunu göstermektedir. Tutumların cinsiyet değişkeni anlamlı bir ilişkisinin olmadığı belirlenmiştir. Hem hem de verilerden elde edilen sonuçlar, olumlu tutum sergilediklerini, ancak verilerde olumsuz sergileyen uygulamaların kullanımında zorluk yaşadıklarını ortaya koymaktadır. Öğretmenlerin uygulamayı bulsalar dahi, kullanımının kolay durumlarda derslerine entegre etmedikleri görülmektedir. çıkarım, TAM modeli önemli sonuçtur. Öğretmenlere verilecek eğitimlerle uygulamalarının özellikle kimya fizik gibi soyut kavramlar içeren derslerde artırılabileceği önerilmektedir. değerlendirildiğinde, yetiştirme programlarına teknolojilerinin entegrasyonu, araçları daha etkin kullanmalarını eğitim süreçlerinin kalitesini artırmalarını sağlayacaktır.

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