MAPPING RESEARCH TRENDS IN AGENT-DRIVEN SOCIALLY SHARED REGULATION LEARNING (SSRL) FOR DIGITAL LEARNING PLATFORM: A BIBLIOMETRIC PERSPECTIVE (2018-2024)

Abstract

The recent surge in artificial intelligence (AI) research has transformed applications across various sectors, including healthcare, education, manufacturing, and digital learning. Although digital learning, collaborative learning, and socially shared regulation learning (SSRL) have experienced significant growth, a thorough examination of scholarly contributions, emerging trends, and influential figures in these fields is still absent. Despite increasing interest in utilizing intelligent agents to enhance SSRL, there is a lack of comprehensive mapping in this interdisciplinary area. Addressing this gap, this study systematically analyses 1,200 publications indexed in Scopus, covering a period from 2018 to 2024. Using Scopus analyzer and VOSviewer, we examined publication trends, co-authorship networks, key research clusters, and thematic patterns. The keywords guiding this analysis were "agent," "digital learning," "socially shared regulation learning," and "collaborative learning." Findings reveal significant growth in this research area, with prominent clusters focused on intelligent agent implementation, collaborative learning frameworks, and SSRL in educational settings. Key contributors and leading journals were identified, highlighting the most influential entities driving research in this field. In conclusion, the study underscores a progressive shift towards integrating intelligent agents in SSRL, suggesting impactful directions for future research and the potential for intelligent agent applications to enhance collaborative digital learning environments. This trend mapping offers valuable insights into both current advancements and prospective developments in agent-driven SSRL.