AI Learning Analytics Research

I am undertaking a study on how artificial-intelligence-driven learning analytics and feedback can create highly personalized learning experiences for students who are pursuing innovation and entrepreneurship subjects. The goal is to map current academic and industry knowledge, surface successful use-cases, and spot gaps where new products or pedagogical approaches could emerge. Your work will centre on four key activities: • A systematic literature review (peer-reviewed journals, conference proceedings, and authoritative white papers from the past five years). • Comparative analysis of leading AI analytics platforms or prototypes already influencing student learning in entrepreneurship courses. • Identification of measurable student outcomes (engagement, retention, creative output, business-model quality, etc.) tied to those tools. • Actionable recommendations—including data points and citations—on where further innovation is needed and how educators can adopt or experiment with these solutions. Acceptance criteria: every claim must be backed by a properly formatted citation; the final report should be at least 4,000 words, delivered as an editable document, and accompanied by a spreadsheet of all sources (APA format) for easy reference. Additionally, the research must meet publication standards for Q1 or Q2 journals.