Mind Meets Machine: A Scientometric Exploration of the Cognitive Frontier in Generative AI
Dublin Core
Title
Mind Meets Machine: A Scientometric Exploration of the Cognitive Frontier in Generative AI
            Creator
Zakky Zamrudi, Teguh Wicaksono, Ervica Zamilah, Suci Norzakia, Mardiana
            Proceedings Item Type Metadata
meta_title
Mind Meets Machine: A Scientometric Exploration of the Cognitive Frontier in Generative AI
            Abstract/Description
This study explores how generative artificial intelligence (GenAI) affects users’ thinking and learning by analyzing research trends from 2016 to 2025 using bibliometric methods. Based on 302 academic papers, it shows how early research focused on technical aspects like deep learning and chatbots, while recent studies (especially in 2025) highlight more human-centered topics such as creativity, decision-making, and language understanding. The findings group the research into four main themes: AI in education, medical training, cognitive science, and decision-making. The study concludes that GenAI is becoming more connected to how people think, learn, and use language, offering guidance for future research and educational practices.
            publication_date
2025/06/15
            pdf_url
https://insyma.org/proceedings/files/articles/zakky_zamrudi.pdf
            abstract_html_url
https://insyma.org/proceedings/items/show/377
            keywords
Generative AI, Cognitive Knowledge, AI in Education, Human-AI Interaction, Research Trends
            firstpage
397
            lastpage
403
            issn
3047-857X
            conference
Proceedings of the International Symposium on Management (INSYMA)
            Volume
22
            publisher_name
Fakultas Bisnis dan Ekonomika, Universitas Surabaya
            no article
66
            Citation
Zakky Zamrudi, Teguh Wicaksono, Ervica Zamilah, Suci Norzakia, Mardiana, “Mind Meets Machine: A Scientometric Exploration of the Cognitive Frontier in Generative AI,” Proceedings of the International Symposium on Management (INSYMA), accessed October 31, 2025, https://insyma.org/proceedings/items/show/377.
