Tracing 40 years of research on Artificial Intelligence and human metacognition from 1985 to 2024

Abstract Background & problem statement Human metacognition, defined as the awareness and regulation of one’s cognitive processes, plays a critical role in effective learning and decision-making. With the advancement of Artificial Intelligence (AI), educational technologies now offer personalized support to human being to accomplish certain tasks. It may indirectly, enhance or hinder human metacognitive skills. However, despite growing research interest, a comprehensive understanding of global research trends in understanding how AI intermediates with human metacognition remains lacking. Purpose This study aims to systematically map the scientific landscape of how AI intermediates with human metacognition through a bibliometric analysis, identifying key contributors, influential publications, and emerging research themes. Methodology A total of 144 articles published between 1985 and 2024 were retrieved from the Scopus database. Using bibliometric tools such as VOSviewer and Bibliometrix (R-package), the study employed performance analysis, co-authorship analysis, and co-word analysis to examine publication trends, leading countries, collaboration networks, prolific journals, and thematic clusters within the field. Findings & contributions The analysis reveals a gradual increase in publications with AI and human metacognition as common point of study from 1985, with a sharp rise post-2009 and a peak in 2023. The United States leads in research output and the most cited work is by Graesser (2005), focusing on metacognitive scaffolding through intelligent tutoring systems such as iSTART and AutoTutor. The study also highlighted the limited number of empirical studies discussing the negative effects of AI on human metacognitive abilities although few studies discussed about overreliance on AI, fear of failure and other aspects. Theoretically, this research repositions AI not only as a facilitator of technology but as a cognitive collaborator that directly influences metacognitive activities such as planning, monitoring, and reflective judgment. This theoretical framework helps to develop metacognitive theory in the digital era by situating AI as a collaborator in, not a substitute for, human cognitive control.