AI Events & Webinars Higher Education Insights Student Retention Students at Risk

Practical Insights from an AI/ML Student Retention Pilot


Join us to explore how Cowley College, in partnership with Datatelligent is integrating machine learning into their established Student-at-Risk/Student Retention solutions.  This session will deliver actionable insights on enhancing student retention strategies through AI.

Attendees will learn:

  • Understand how Datatelligent incorporated machine learning into the existing Student-at-Risk solution, focusing on identifying the key features driving student re-enrollment.
  • How Cowley’s staff and advisors are using ML outputs to prioritize support for students most at risk.
  • Key takeaways and initial lessons from the joint pilot, highlighting both successes and areas for improvement.

Event Details

Event Title: Practical Insights from an ML/AI Student Retention Pilot

Date / Time: May 8, 2024, from 12:00 to 1:00 pm CT

Location: Zoom meeting

Blog Higher Education Industry Student Retention

Understanding Trends in Undergraduate Degree Attainment



The pursuit of higher education is a critical milestone for countless individuals around the world. Whether it’s an associate degree, a bachelor’s degree, or a specialized certificate, earning an undergraduate credential opens doors to career opportunities, personal growth, and societal impact. In this blog post, we delve into the latest findings from the National Student Clearinghouse Research Center’s report on undergraduate degree earners for the academic year 2022-23.


The report reveals a concerning trend: the number of undergraduate degree earners has declined for the second consecutive year. In the 2022-23 academic year, there was a 2.8% decrease, resulting in 99,200 fewer graduates compared to the previous year. This decline raises questions about the factors contributing to this downturn.

First-time completers, who represent 73.3% of all graduates, experienced a decline of 73,600 individuals. These are students who successfully complete their degree requirements for the first time. The 2.8% decrease in this group reflects broader challenges in higher education. As institutions adapt to changing demographics, economic shifts, and technological advancements, understanding the needs of first-time completers becomes crucial.

While overall degree attainment declined, there’s a silver lining: the number of students earning certificates reached a ten-year high. Certificates, often shorter and more focused than traditional degrees, provide specialized skills and knowledge. The report attributes this increase to a 6.2% rise in first-time award earners. Whether in fields like healthcare, information technology, or skilled trades, certificates offer a pathway to employment and career advancement.

Despite the surge in certificates, associate and bachelor’s degrees remain foundational. These degrees continue to be valued by employers and serve as stepping stones for further education. However, institutions must address challenges such as affordability, access, and student support to reverse the decline in degree earners.

To combat this trend, educational leaders and policymakers can consider the following strategies:

  • Strengthening Student Support and Flexibility:
    • Support systems: Enhance academic advising, tutoring, and mental health services, and establish mentorship programs to support students throughout their educational and career journeys.
    • Flexible learning options: Expand online and hybrid courses, and offer more classes during evenings and weekends to accommodate non-traditional students and those with additional responsibilities.
  • Improving Educational Pathways and College Readiness:
    • Short-term and stackable credentials: Develop certificate programs aligned with industry needs and offer credentials that can be built upon towards a degree.
    • College readiness initiatives: Collaborate with high schools to ensure students are prepared for college and offer bridge programs to ease the transition to higher education.
  • Enhancing Financial Accessibility:
    • Increase scholarship and grant awareness: Promote the availability of scholarships and grants to help reduce financial barriers for prospective students.
  • Adopting Data-Informed Strategies and Promoting Lifelong Learning:
    • Data-driven approaches: Use analytics to identify at-risk students early and tailor programs to meet diverse needs.
    • Lifelong learning culture: Encourage continuous education for adult learners and partner with businesses to support education benefits and career advancement.

The decline in undergraduate degree earners is a multifaceted issue that requires a collaborative and strategic response. By enhancing financial aid, strengthening support systems, and promoting flexible learning options, we can create a more inclusive and supportive educational environment. Additionally, by fostering a culture of lifelong learning and utilizing data-driven approaches, we can ensure that higher education remains relevant and accessible to all. As we work towards these goals, we can reverse the current trend and pave the way for a brighter future in higher education.

  1. National Student Clearinghouse Research Center. “Undergraduate Degree Earners Report: Academic Year 2022-23.” April 11, 2024. “,by%2073%2C600%20(%2D2.8%25).
  2. Weissman, Sara. “Degrees Earned Fall Again, Certificates Rise.” Inside Higher Ed, April 11. 2024.
  3. Katharine Meyer “The case for college: Promising solutions to reverse college enrollment declines.” Brookings Institution, June 5, 2023.
AI Blog Higher Education Industry

Caution: AI Approaching Higher Education



Interest in Artificial Intelligence (AI) is growing across all industries, spurred by daily advancements that showcase its potential to enhance efficiency and predict trends. Higher education institutions, faced with declining enrollments in part due to shifting demographics, are especially interested in using AI to improve their operations around student recruitment and retention. But before colleges and universities start using AI, it is crucial to consider the responsible incorporation of AI, ensuring its use enhances existing processes while mitigating potential pitfalls.

ethical considerations

Using historical data by AI introduces the risk of perpetuating existing biases, a challenge highlighted by Amazon’s reevaluation of an AI recruitment tool biased against female candidates¹. Similarly, the application of AI in risk assessments within the legal system² has faced scrutiny for racial biases. These examples underline the urgent need for comprehensive AI governance frameworks, discussed during the March 2024 Data Analytics Alliance for Higher Education meeting, that prioritize ethical data use and rigorous oversight to combat bias.

AI “Hallucinations” and Misinformation
The phenomenon of AI “hallucinations”³ — baseless but authoritative assertions made by AI systems — has raised significant concerns regarding the use of tools like ChatGPT. Examples such as Google’s Bard AI misrepresenting facts about the James Webb Space Telescope⁴ and Microsoft’s Bing chatbot displaying unpredictable behavior and professing “love” for a New York Times columnist⁵ highlight the risk of misinformation. These incidents reinforce the importance of strong training data curation to mitigate the spread of misinformation in educational settings.

The deployment of AI in analyzing large datasets accentuates privacy and security concerns, particularly around the potential for de-anonymization. AI’s ability to infer sensitive personal information from non-sensitive data⁶ introduces new data protection challenges. Therefore, adopting AI technology requires robust privacy safeguards, including secure platform designs and ethical data handling practices.

A foundational principle for effective AI utilization is the term “Garbage in, garbage out,” emphasizing the critical role of data quality. Higher education institutions often rely on data from student information systems (SIS) and learning management systems (LMS) to train AI models. However, these sources frequently contain incomplete or inaccurate data, potentially leading to unreliable AI outputs.

To navigate these challenges and lay the groundwork for effective AI implementations, the use of a Unified Data Platform (UDP) is vital. A UDP consolidates and harmonizes data from diverse systems, ensuring AI models are trained on high-quality, comprehensive datasets. Key characteristics of an effective UDP include:
  • Centralized Data: Aggregates data from various institutional systems and external sources, providing a complete data ecosystem for accurate AI analysis.
  • Scalability: Offers a scalable infrastructure to accommodate increasing data volumes and complex AI use cases.
  • Robust Security Measures: Incorporates advanced security features to protect sensitive data, ensuring privacy and compliance with data protection laws.
  • AI-Ready Infrastructure: Facilitates the deployment of AI by ensuring the platform and tools are primed for AI applications, supporting advanced analytics, and making data AI-ready.

In response to growing inquiries from our higher education customers interested in AI, Datatelligent recommends that customers consider its Datatelligent Platform for Higher Education, which leverages a UDP to develop standard analytic solutions that most colleges and universities need. Karl Oder, one of the Chief Architects of the platform, talked about what we are doing with the platform. “We’re busy creating several AI prototypes with our partner, Snowflake, using the AI-Ready tools they provide.”

In addition to getting your data “AI-ready” by establishing a UDP, schools should also spend time prepping for the AI Project⁷, starting with selecting the right use case. For higher education institutions, Datatelligent has developed prototypes on our platform that can accelerate this process, including:

  • Admissions and enrollment – predictive factors that will influence admissions and student enrollment projections
  • Student success and retention – identifying student success characteristics and predicting students at risk of leaving.
  • Graduation and program success – predictive factors driving graduation rates and overall program success.

Integrating AI in higher education calls for a balanced, thoughtful approach that acknowledges AI’s transformative potential alongside its challenges. By addressing issues of bias, misinformation, privacy, and ethical governance through strategic planning, institutions can harness AI to enhance educational outcomes and operational efficiency. Central to this endeavor is establishing a Unified Data Platform, ensuring data integrity, and laying a solid foundation for the responsible use of AI technologies.

  1. Dastin, Jeffrey. “Insight – Amazon Scraps Secret AI Recruiting Tool that Showed Bias against Women.” Reuters, August 10, 2018.
  2. Angwin, Julia , Surya Mattu, and Lauren Kirchner. “Machine Bias.” Pro Publica, May 23, 2016.
  3. “What Are AI Hallucinations?” IBM.Com. February 1, 2024.
  4. Mihalcik, Carrie. “Google ChatGPT Rival Bard Flubs Fact About NASA’s Webb Space Telescope.” CNET, February 9, 2023.
  5. McMillan, Malcolm. “Bing ChatGPT Goes off the Deep End — And the Latest Examples Are Very Disturbing.” Tom’s Guide, February 17, 2023.
  6. Ahmed, Hafiz. “Challenges of AI and Data Privacy—And How to Solve Them.” @ISACA 32, (2021).
  7. Sassi, Steve. “AI Project Prep for Higher Education.” Datatelligent.Ai. March 26, 2024.
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