ArticleScientific reports2025
Educational impacts of generative artificial intelligence on learning and performance of engineering students in China.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI-assisted history education in China: a secondary evidence map of psychological antecedents and learning outcomes.Frontiers in psychology · 2026Pooled it
- Artificial Intelligence Use and Cognitive Resource Allocation: Nonlinear Associations with Mental Workload and Perceived Performance.Journal of Intelligence · 2026Article
- Behavioral mechanisms and learning outcomes of University Students' GAI-assisted learning in human-AI collaboration.PloS one · 2026Article
- Article
- Generative Artificial Intelligence in Health Informatics Education: A Qualitative Exploration of Student Engagement, Perceived Educational Implications, and Ethical Considerations.Advances in medical education and practice · 2026Article
- The impact of artificial intelligence perception on university students' academic engagement: the mediating role of academic motivation and the moderating role of academic self-efficacy.Frontiers in psychology · 2026Article
- AI utilization, enjoyment, trust and instructor competence as predictors of intercultural communication competence among Chinese students.Scientific reports · 2025Article
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Authors and funding
3 authors.
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Abstract
With the rapid advancement of generative artificial intelligence (AI), its potential applications in higher education have attracted significant attention. This study investigated how 148 students from diverse engineering disciplines and regions across China used generative AI, focusing on its impact on their learning experience and the opportunities and challenges it poses in engineering education. Based on the surveyed data, we explored four key areas: the frequency and application scenarios of AI use among engineering students, its impact on students' learning and performance, commonly encountered challenges in using generative AI, and future prospects for its adoption in engineering education. The results showed that more than half of the participants reported a positive impact of generative AI on their learning efficiency, initiative, and creativity, with nearly half believing it also enhanced their independent thinking. However, despite acknowledging improved study efficiency, many felt their actual academic performance remained largely unchanged and expressed concerns about the accuracy and domain-specific reliability of generative AI. Our findings provide a first-hand insight into the current benefits and challenges generative AI brings to students, particularly Chinese engineering students, while offering several recommendations-especially from the students' perspective-for effectively integrating generative AI into engineering education.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.