transform HIGHER ED WITH AI & ANALYTICS
Harness the power of AI and advanced analytics to drive student success, optimize recruitment, and improve retention. With WHALE and the Higher Education Common Data Model, institutions can turn raw data into actionable insights for smarter decision-making.
AI and Analytics:
Essential for Remaining Relevant
In today’s fast-paced educational landscape, institutions must evolve to meet the changing needs of students and society, For example, students now
demand more personalized and flexible learning experiences that cater to their individual needs and schedules. There is also a growing expectation for
institutions to provide robust support systems that can identify and address challenges early, such as academic struggles or engagement issues. Artificial Intelligence (AI) and advanced analytics have become critical tools for staying
relevant and competitive. By harnessing the power of AI, institutions can analyze and turn data into actionable insights that improve student outcomes
and operational efficiency. By leveraging AI and analytics, educational institutions can offer personalized experiences, optimize processes, and make informed decisions that ensure long-term success.
Fierce Challenges Faced by Educational Institutions
Educational institutions today face many challenges, among them are two primary challenges: student acquisition and student retention.
Student Acquisition:
Attracting and enrolling new students has become increasingly competitive, due to several factors. First, the demographic shift in many regions has led to a decline in the traditional college-aged population, reducing the overall pool of prospective students. Second, the rise of alternative education pathways, such as online courses, boot camps, and vocational training programs, offers students more options outside of traditional higher education. Institutions must identify and engage with prospective students effectively, ensuring they reach those most likely to enroll. Without the right tools, many institutions struggle to identify the most successful channels and optimize their recruitment strategies, leading to inefficiencies and missed opportunities.
Student Dropout:
Retention is an equally pressing issue. The dropout rate in higher education remains a significant concern, with approximately 40% of students in the United States failing to complete their degrees within six years of enrolling in a four-year institution. This alarming statistic highlights the challenges institutions face in retaining students and underscores the critical need for early identification of at-risk students. By identifying these students early and providing timely, targeted interventions, institutions can significantly improve retention rates. However, traditional methods of tracking and supporting students often fall short, as they tend to be reactive rather than proactive, leading to persistently high dropout rates that can damage an institution’s reputation and financial health.
WHALE as an AI Accelerator
To tackle these challenges, institutions require efficient, powerful solutions that can be quickly deployed. WHALE (Warehouse of Holistic Academic and Learning Environment), built on the Higher Education Common Data Model (CDM), serves as an accelerator for implementing AI and analytics solutions. WHALE is an open-source data schema specifically designed for higher education, integrating seamlessly with the Dynamics based CDM and ensuring that data across the institution is unified, standardized, and primed for analysis.
Enabling Solutions in Days: WHALE accelerates the deployment of AI-driven solutions, such as those focused on optimizing recruitment and preventing student dropout. By leveraging the Common Data Model, WHALE ensures that data from across the institution is harmonized, enabling accurate, tailored analytics solutions that can be implemented swiftly and effectively.
AI Use Cases
WHALE (Warehouse of Holistic Academic and Learning Environment) can be leveraged in various impactful ways within higher education. For example, by utilizing WHALE, institutions can accelerate the optimization of student recruitment efforts through the data schema, identifying prospective students with the highest likelihood of enrollment and tailoring engagement strategies accordingly. Additionally, WHALE’s data schema can be used to accelerate the enablement of a use case to prevent student dropout by analyzing a wide range of data points to identify at-risk students early in their academic journey, enabling timely and personalized interventions that improve retention rates. These are just two examples of how the Common Data Model, upon which WHALE is built, can drive powerful AI and analytics solutions; the model’s versatility opens the door to countless other applications across the educational landscape.
Optimizing Recruitment
Challenge:
Institutions often struggle to effectively target and engage prospective students who are most likely to enroll, leading to inefficiencies and lower
conversion rates.
How It Works:
By utilizing data that adheres to the Common Data Model, AI algorithms analyze various factors, such as demographic information, engagement levels, and academic interests. These insights allow institutions to predict which prospective students are most likely to enroll, thereby enabling targeted, personalized recruitment strategies. This prioritization improves communication efforts, increases conversion rates, and optimizes the allocation of resources.
Expected Impact
Institutions can expect a significant boost in recruitment efficiency, with higher conversion rates and a more focused use of recruitment resources, leading to a better alignment of institutional offerings with student needs.
Preventing Student Dropout
Challenge:
High dropout rates pose a significant threat to educational institutions, impacting both their reputation and financial stability. Identifying students at risk of dropping out early and intervening effectively is critical but challenging with traditional methods.
How It Works:
WHALE’s integration with institutional data sources allows AI models to continuously assess student risk levels by analyzing academic performance, engagement metrics, and personal circumstances. These models update risk profiles in real-time and provide actionable insights via dashboards, enabling support teams to intervene with personalized strategies tailored to each student’s needs.
Expected Impact
The early identification of at-risk students and timely, targeted interventions can dramatically reduce dropout rates, ensuring that more students complete their degrees. This not only enhances the institution’s reputation but also improves overall student satisfaction and success.
How to Move Forward
Explore how AI and analytics, powered by the Common Data Model and WHALE, can transform your institution. Review our open-source assets, contact us to set up a demo to see these solutions in action and learn how they can help you address the challenges of student recruitment and retention. Reach out to understand how implementing these powerful tools can drive success at your institution and ensure competitiveness in an ever-changing educational landscape.
JOIN THE FUTURE OF HIGHER ED DATA
Turn Data
into Action
Harness AI and analytics to optimize recruitment, boost retention, and improve student success. Transform insights into impact.