Data-driven Decision Making in Higher Education Institutions: State-of-play

The paper highlights the importance of using data-driven decision-making tools in Higher Education Institutions (HEIs) to improve academic performance and support sustainable development. HEIs must utilize data analytics tools, including educational mining, learning analytics, business intelligence, extract insights knowledge from data. These can help HEIs’ leadership monitor student enrolment campaigns, track performance, evaluate staff, make decisions. Although decision systems have many advantages, they are still underutilized HEIs, leaving field for further research implementation. To address this, authors summarize benefits applying approaches review various frameworks methodologies, such as a course recommendation system an prediction model, aid decision-making. articulate pedagogical theories, frameworks, phenomena establish mainstay significant components enable scheming superior systems. be utilized by placement agencies or companies find out their probable trainees/ recruitees. They students selection, management being more efficient effective.