A Comparative Study on AI-Based Learning Behaviors: Evidence from Vietnam DOI
Nam Tien Duong, Thuy Dung Pham Thi, Van Kien Pham

и другие.

International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 17

Опубликована: Ноя. 28, 2024

AI-based learning systems are transforming education in academic and corporate settings, with global spending on AI-enabled training expected to exceed $200 billion by 2025. This study examines how these enhance outcomes for college students employees, focusing system functionality, self-efficacy, familiarity, social influence. Using structural equation modeling data from 598 participants (258 students, 340 employees), findings reveal that familiarity positively impacts self-efficacy across both groups, while influence varies. Students benefit media-rich environments, employees gain job-relevant content supervisor System functionality enhances participation motivation, but self-efficacy's direct effect is significant only employees. These results highlight the need tailor user profiles. Limitations include reliance self-reported specific contexts. Future research should incorporate objective measures of explore additional factors like teaching strategies.

Язык: Английский

Unlocking the metaverse: Determinants of voluntary adoption in e-commerce DOI
Radka Bauerová,

Michal Halaška

Sustainable Futures, Год журнала: 2025, Номер 9, С. 100436 - 100436

Опубликована: Янв. 16, 2025

Язык: Английский

Процитировано

0

When Technology Meets Anxiety:The Moderating Role of AI Usage in the Relationship Between Social Anxiety, Learning Adaptability, and Behavioral Problems Among Chinese Primary School Students DOI Creative Commons
GuangYuan Ma,

S S Tian,

Yang Song

и другие.

Psychology Research and Behavior Management, Год журнала: 2025, Номер Volume 18, С. 151 - 167

Опубликована: Янв. 1, 2025

This study aims to examine the relationships between social anxiety, learning adaptability, AI technology usage, and behavioral problems among primary school students, with a focus on mediating role of adaptability moderating usage. A cross-sectional survey was conducted 1240 students aged 8-15 in Luzhou, Sichuan Province. Social anxiety measured using Anxiety Scale for Children (SASC), assessed Children's Learning Adaptability Questionnaire (CSAQ), were evaluated Child Behavior Checklist (CBCL), tool usage gauged through self-developed questionnaire. Data analysis involved correlation multiple regression analyses SPSS, moderated mediation effect analyzed Process Model 59. found significantly positively predict problems, indicating that higher levels associated more problems. partially mediated this relationship, suggesting not only directly impacts but also indirectly heightens risk by reducing adaptability. Additionally, relationship stronger observed at Specifically, positive influence became pronounced as increased, frequent use can amplify impact outcomes. increases diminishing plays its effects becoming highlights need educators improving students' judiciously incorporate technology, consider individual differences, particularly mental health, foster comprehensive healthy student development.

Язык: Английский

Процитировано

0

A Hybrid SEM-ANN Approach for Predicting the Impact of Psychological Needs on Satisfaction with Generative AI Use DOI
İbrahim Arpacı, İsmail Kuşci

Technology Knowledge and Learning, Год журнала: 2025, Номер unknown

Опубликована: Янв. 24, 2025

Язык: Английский

Процитировано

0

Implementing AI to Improve Educational Equity and Outcomes in a Rural School District DOI
Ketan Sarvakar,

Dolly Prajapati

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 457 - 480

Опубликована: Фев. 13, 2025

This chapter, as outlined by the authors, investigates use of artificial intelligence (AI) in rural school districts to enhance operational efficiency and educational outcomes. Through a survey-based approach, chapter evaluates AI adoption its effects various contexts, focusing on schools' specific challenges, such limited resources technological infrastructure. Findings reveal that can offer personalized learning, boost student engagement, streamline administrative tasks, thereby supporting better learning environment despite resource constraints. The study highlights ongoing obstacles, inadequate infrastructure need for specialized teacher training. Proposed solutions include targeted investments, comprehensive training programs, policy measures promote education. By providing insights into AI's benefits, this aims guide policymakers, educators, stakeholders effectively leveraging improve equity outcomes underserved communities.

Язык: Английский

Процитировано

0

Learning and Teaching in the Era of Generative Artificial Intelligence Technologies: An In‐Depth Exploration Using Multi‐Analytical SEMANN Approach DOI Open Access
Muhammad Farrukh Shahzad, Shuo Xu, Xin An

и другие.

European Journal of Education, Год журнала: 2025, Номер 60(1)

Опубликована: Фев. 18, 2025

ABSTRACT The arrival of generative artificial intelligence (GAI) technologies marks a significant transformation in the educational landscape, with implications for teaching and learning performance. These can generate content, simulate interactions, adapt to learners' needs, offering opportunities interactive experiences. In China's education sector, incorporating GAI address challenges, enhance practices, improve This study scrutinises impact on performance focusing mediating roles e‐learning competence (EC), desire (DL), beliefs about future (BF), as well moderating role facilitating conditions amongst Chinese educators. Data was collected from 411 teachers across various institutions China using purposive sampling. PLS‐SEM ANN were employed assess suggested structural model. results indicate that significantly influence by EC, DL, BF roles. Furthermore, positively moderate association BF. underscores critical self‐determination theory shaping effective incorporation education, valuable insights outcomes sector.

Язык: Английский

Процитировано

0

Exploring Chinese Consumers’ Attitudes Towards Pet Nutritional Products and Their Continuous Purchase Intentions: A Dual-Phase Analysis Using SEM and ANN DOI Creative Commons

Jiexiang Jin,

Binbin Yang

Behavioral Sciences, Год журнала: 2025, Номер 15(3), С. 255 - 255

Опубликована: Фев. 23, 2025

As the role of pets evolves, they are increasingly regarded as members family. Although incapable making independent decisions, become unique consumer groups through purchases specific products and services made by their owners. In China, pet economy has developed into a novel economic sector. With growing concern for health, demand nutritional continues to rise. This study aims explore Chinese consumers’ attitudes intentions towards in this burgeoning market. A survey was carried out on 600 consumers who had purchased 2024. two-stage analysis using structural equation modeling artificial neural network examined correlation within research model across 506 samples. The results indicate that perceived benefits, severity, susceptibility, health consciousness positively influence products, while barriers, risks, risks negatively impact attitudes. significantly enhance continuous purchase intentions. lays an essential groundwork advancing food refining marketing approaches, conducting future research.

Язык: Английский

Процитировано

0

Evaluating the influence of generative AI on students’ academic performance through the lenses of TPB and TTF using a hybrid SEM-ANN approach DOI
Mostafa Al‐Emran, Mohammed A. Al‐Sharafi, Behzad Foroughi

и другие.

Education and Information Technologies, Год журнала: 2025, Номер unknown

Опубликована: Март 12, 2025

Язык: Английский

Процитировано

0

Leveraging SmartPLS and AI for Educational Model Optimization DOI

Hendra Kusumah,

Muhammad Alghifari,

Euis Siti Nur Aisyah

и другие.

Опубликована: Авг. 7, 2024

Язык: Английский

Процитировано

1

A Comparative Study on AI-Based Learning Behaviors: Evidence from Vietnam DOI
Nam Tien Duong, Thuy Dung Pham Thi, Van Kien Pham

и другие.

International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 17

Опубликована: Ноя. 28, 2024

AI-based learning systems are transforming education in academic and corporate settings, with global spending on AI-enabled training expected to exceed $200 billion by 2025. This study examines how these enhance outcomes for college students employees, focusing system functionality, self-efficacy, familiarity, social influence. Using structural equation modeling data from 598 participants (258 students, 340 employees), findings reveal that familiarity positively impacts self-efficacy across both groups, while influence varies. Students benefit media-rich environments, employees gain job-relevant content supervisor System functionality enhances participation motivation, but self-efficacy's direct effect is significant only employees. These results highlight the need tailor user profiles. Limitations include reliance self-reported specific contexts. Future research should incorporate objective measures of explore additional factors like teaching strategies.

Язык: Английский

Процитировано

0