Intelligent academic analytics for early identification of student support needs

Key Points

• This research aims to explore how intelligent academic analytics can detect student support needs early.
• Utilized data analytics tools to monitor academic performance and behaviors of students.
• Conducted a randomized trial to assess the impact of early identification on student outcomes.
• Focused on multiple disciplines within academic settings.
• Early identification led to a significant increase in student engagement with support services, with a 30% boost.
• Students receiving timely interventions improved their average grades, with a mean change of +1.2 on a 4-point scale.
• Feedback indicated a 75% satisfaction rate among students who received early support.

Abstract