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Аналитика сотрудничества в высшем образовании и профессиональной среде: систематический обзор подходов и теоретических оснований
The article presents a review of studies in the field of Collaboration Analytics and their application to the analysis of collaborative activities in higher education. Based on a systematic search and comparison of works, key constructs of collaboration we identified – participation, coordination, and cognitive regulation – as well as approaches to their theoretical interpretation. The findings show that, in university practice, the most in-demand data include records of student activity on digital platforms (message logs, timestamps, relational links), results of content analysis of communication (discourse coding, semantic mapping), and multimodal indicators of interaction (e.g., time series of actions and distribution of roles within groups). To process these data, methods of network analysis, epistemic network analysis (ENA), machine learning, and digital trace visualization are actively employed. These approaches enable instructors to diagnose team dynamics, provide more accurate feedback, and support the development of students’ metacompetencies. As a comparative context, studies of corporate analytics were examined, which made it possible to identify models of monitoring and visualization of participants’ contributions that can potentially be transferred to the university setting. The practical significance of the results lies in providing educators and educational researchers with tools for the informed selection of analytical methods and indicators, as well as in outlining the possibilities of adapting corporate practices to university models of collaborative learning. For readers, the value of the article consists in systematizing fragmented research and identifying promising approaches that may enhance the quality of student group work and its assessment.