AI-Powered Student Success Ecosystems: Integrating ECM, DXP, and Predictive Analytics
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V4I1P113Keywords:
Artificial Intelligence, Student Success, Enterprise Content Management, Digital Experience Platform, Predictive Analytics, Higher Education, Learning AnalyticsAbstract
The accelerated nature of digital transformation in higher education has enhanced the necessity of smart, scalable and student-based ecosystems that have the potential to enhance learning outcomes, engagement and retention. The conventional Learning Management Systems (LMS) and standalone academic tools do not offer flexibility and forward-thinking ability to meet various demands of students in real-time. Subsequently, the paper suggests an AI-based Student Success Ecosystem which consists of Enterprise Content Management (ECM), Digital Experience Platforms (DXP), and Predictive Analytics to design a single, data-driven educational system. ECM provides a well-organized approach to academic content, administrative documents and compliance documents, whereas DXP allows students to access support and academic services personally and in any channel. Predictive analytics, which is a machine learning algorithm-driven service, uses historical and real-time data to find at-risk students, predict their performance, and prescribe specific interventions. The suggested architecture is focused on interoperability, data management, and ethical use of AI. A system design, data processing, model development and evaluation methodology are provided. The outcomes of the experiment indicate a positive effect on student retention, academic, and engagement outcomes. The results imply that integrated AI-powered ecosystems can turn higher education institutions into student-focused organizations that are active
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