Overview
Customer Name: New Century Education (NCE)
Industry: Education
Geography: United Arab Emirates (UAE)
Function: Academic Performance Management
Business Value Driver: Enhanced Student Outcomes Through AI-Driven Insights
Challenges
New Century Education (NCE), a leading name in the UAE’s educational sector, is committed to fostering academic success among its diverse student body. However, with thousands of students across multiple campuses, identifying and supporting underperforming students early posed a significant challenge. The reliance on disparate data sources and manual intervention methods meant many students’ academic struggles were only addressed after their performance had already declined.
- Delayed Intervention: Traditional methods identified at-risk students too late for impactful corrective measures.
- Data Silos: Fragmented data sources, including academic, demographic, and behavioral data, hindered holistic student assessments.
- Scalability: A lack of scalable predictive tools limited NCE’s ability to address the growing student population effectively.
Recognizing the need for a proactive and data-driven approach, NCE partnered with SAAL to develop an AI-driven solution to identify at-risk students early and recommend actionable interventions.
Solution
SAAL developed a comprehensive predictive model tailored to NCE’s requirements, leveraging cutting-edge AI and machine learning (ML) technologies. The Student At-Risk solution was designed to empower faculty and administration with timely insights into student performance, enabling targeted and effective interventions.
- Early Identification: The model identifies at-risk students as early as their first semester by analyzing historical school performance data for new students.
- Actionable Recommendation: The system provides faculty with prescriptive analytics, offering tailored strategies to improve individual student outcomes.
- Data Integration: Seamless integration with NCE’s existing Learning Management System and data platform ensures real-time data flow.
- Transparency: Advanced techniques enable faculty to understand the key factors influencing each prediction.
- Scalability and Efficiency: Built to handle large volumes of student data, the model is scalable and designed for efficient processing and deployment.
Results
The “Student At-Risk” solution transformed NCE’s approach to academic performance management, delivering measurable impact:
- Early Interventions: Faculty could identify and address at-risk students weeks before traditional methods allowed, improving CGPA scores and retention rates.
- Enhanced Transparency: Faculty gained a clear understanding of the factors influencing student risk through explainable AI features, fostering trust in the system.
- Widespread Adoption: User-friendly interfaces and intuitive analytics led to rapid adoption across campuses, with faculty actively leveraging insights to drive student success.
- Improved Outcomes: User-friendly interfaces and intuitive analytics led to rapid adoption across campuses, with faculty actively leveraging insights to drive student success.