Perceptions of STEM education and artificial intelligence: a Twitter (X) sentiment analysis DOI Creative Commons
Demetrice Smith-Mutegi, Yoseph Mamo, Jinhee Kim

и другие.

International Journal of STEM Education, Год журнала: 2025, Номер 12(1)

Опубликована: Фев. 11, 2025

Язык: Английский

Exploring the mediating roles of self-control, management, and meaningful learning self-awareness in the relationship between academic self-discipline and GAI acceptance DOI Creative Commons
Kıvanç Bozkuş, Özge Canoğulları

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

Опубликована: Апрель 4, 2025

Язык: Английский

Процитировано

0

Legal regulation of AI-assisted academic writing: challenges, frameworks, and pathways DOI Creative Commons

Runyang Gao,

Danghui Yu,

Biao Gao

и другие.

Frontiers in Artificial Intelligence, Год журнала: 2025, Номер 8

Опубликована: Апрель 7, 2025

Introduction The widespread application of artificial intelligence in academic writing has triggered a series pressing legal challenges. Methods This study systematically examines critical issues, including copyright protection, integrity, and comparative research methods. We establishes risk assessment matrix to quantitatively analyze various risks AI-assisted from three dimensions: impact, probability, mitigation cost, thereby identifying high-risk factors. Results findings reveal that challenges fundamental principles traditional law, with judicial practice tending position AI as creative tool while emphasizing human agency. Regarding new risks, such “credibility illusion” “implicit plagiarism,” have become prominent AI-generated content, necessitating adaptive regulatory mechanisms. Research data protection personal information security face dual require technological institutional innovations. Discussion Based on these findings, we propose three-dimensional framework “transparency, accountability, technical support” present systematic policy recommendations design, organizational structure, international cooperation perspectives. results deepen understanding attributes creation, promote theoretical innovation digital era ethics, provide practical guidance for institutions formulating usage policies.

Язык: Английский

Процитировано

0

Effects of Generative Artificial Intelligence on K-12 and Higher Education Students’ Learning Outcomes: A Meta-Analysis DOI
Xiaohong Liu,

B. J. Guo,

Wei He

и другие.

Journal of Educational Computing Research, Год журнала: 2025, Номер unknown

Опубликована: Апрель 11, 2025

Generative artificial intelligence (GenAI) has significant potential for educational innovation, although its impact on students’ learning outcomes remains controversial. This study aimed to examine the of GenAI K-12 and higher education students, explore moderating factors influencing this impact. A meta-analysis 49 articles showed that mean effect sizes achievement motivation were 0.857 0.803, respectively, indicating a positive education. However, varied according moderators, including level, subject classification, interface, development, interaction approaches, experimentation time, which enhanced Specifically, had greater academic performance students interacted more effectively with using text than mixed media, such as images or audio. Although novel motivation, size decreases over time. These findings provide empirical support beneficial effects offer insights optimizing use in teaching practices.

Язык: Английский

Процитировано

0

Determinants of students’ adoption of AI chatbots in higher education: the moderating role of tech readiness DOI
Muhammad Khalilur Rahman,

Md. Arafat Hossain,

Noor Azizi Ismail

и другие.

Interactive Technology and Smart Education, Год журнала: 2025, Номер unknown

Опубликована: Апрель 9, 2025

Purpose This study aims to investigate the key factors influencing students’ adoption of artificial intelligence (AI) chatbot applications in higher education. It further examines mediating and moderating role AI chatbots tech readiness determining effect perceived usefulness, subjective norms, simplicity literacy on intention use applications. Design/methodology/approach A survey was conducted at Malaysian universities whereby 430 students participated 426 responses were deemed valid for analysis. The data carefully examined ensure accuracy proposed model. To comprehend intricate relationships model, authors used partial least squares structural equation modeling (PLS-SEM) technique. Findings results revealed that usefulness (PU), norm (SN), (TL) (TS) have a significant impact significantly influences findings indicated mediates PU, SN, TL TS chatbots. Tech (TR) moderates PU Originality/value research addresses new insight into within education, particularly demonstrating how act as mediators moderators shaping perceptions

Язык: Английский

Процитировано

0

Perceptions of STEM education and artificial intelligence: a Twitter (X) sentiment analysis DOI Creative Commons
Demetrice Smith-Mutegi, Yoseph Mamo, Jinhee Kim

и другие.

International Journal of STEM Education, Год журнала: 2025, Номер 12(1)

Опубликована: Фев. 11, 2025

Язык: Английский

Процитировано

0