Managing the effectiveness of online courses in universities using an analytical dashboard
TL;DR
A practically viable and scalable model for digitizing managerial processes in higher education institutions using domestic technologies, fully aligned with the principles of evidence-based decision-making, data security, and adaptability to the evolving needs of educational organizations is demonstrated.
Abstract
The article presents the experience of developing and implementing an analytical dashboard “Course monitoring” based on the domestic BI solution Yandex DataLens to support digital management of the effectiveness of online courses within the university’s system of additional professional education (APE). The design process is described in detail — from identifying the target audience (educational program development teams, program coordinators, heads of structural units, and vice-rectors overseeing educational activities, informatization, and information technologies) and selecting key performance metrics (completion rate, net promoter score, customer satisfaction, and practical assignment results) to integrating data from the LMS (Moodle), surveys, and internal databases, followed by prototyping, usability testing, and iterative refinement based on user feedback. The developed analytical dashboard for evaluating the online courses effectiveness enables timely, data-driven managerial decisions, aligns with the principles of evidence-based education and the learner-centered approach, and complies with Russian data security requirements. The dashboard was piloted within two APE programs — “Artificial intelligence in education and research” and “Advanced AI technologies in research and development” — involving 1,935 participants from Southern Federal University. The “Course monitoring” dashboard is implemented on the Yandex DataLens platform and is accessible via a public link, with strict adherence to data confidentiality: all participant data are anonymized, and access to detailed information is restricted in accordance with the university’s internal regulations and the requirements of Federal Law No. 152-FZ “On Personal Data”. The article demonstrates a practically viable and scalable model for digitizing managerial processes in higher education institutions using domestic technologies, fully aligned with the principles of evidence-based decision-making, data security, and adaptability to the evolving needs of educational organizations.