AI in education
AI and generative AI are enabling educational institutions to enhance student achievement. These technologies help leaders innovate, measure learning recovery, identify at-risk students, and improve enrollment and retention rates – all while preparing for future challenges. AI agents and AI models from SAS can help you solve problems while protecting data privacy and leading your institution toward new opportunities and bright futures.
AI use cases for education
Advance educational innovation with data and AI solutions from SAS. Our solutions help you plan more thoroughly, run programs more resourcefully, confidently maintain compliance and predict and prepare more accurately.
AI Agent: Proactive guidance for "Near-grad" students
When administrators at a large, urban community college discovered that some students were within one semester of graduating but not completing their degrees, they turned to AI to identify them and then guide and support them in completing their program. The deployment of their AI agent has resulted in a 109% increase in college completion.
By making this tool available 24/7 and empowering the agent to access records, course schedules and other data, the college enabled it to answer questions better. Giving it the ability to reenroll students and recommend support services, such as childcare, financial aid and transportation, made the agent more student-centered and focused on addressing the reasons most often cited for students not completing their degrees.
The value of this solution:
- Better outcomes.
- Increased revenue.
- Improved customer service.
AI techniques used in this solution:
- Machine learning models are used to prepare data on students who are "near grads."
- Data is fed into an LLM-powered chatbot that reaches out to students, encouraging them to reenroll.
How AI helps:
- Lists students who meet the "near grad" criteria.
- Unites data from disparate sources.
- Provides intelligent communications at scale.
The AI models provide:
- The deep learning model performs underlying factor importance, confidence interval and outyear projections.
Administrators at this large, comprehensive urban community college developed an AI agent to target and support students at risk of not completing their degrees.
Improved operational efficiency
Use SAS to make better decisions about how to use resources. Reynolds Community College improved space utilization across hundreds of rooms across its four campuses, saving the college close to US$1 million as a result.
This issue has a direct impact on student outcomes, and it engages multiple operating areas of the college, including decision makers in technology, facilities management and academic affairs. The college considered schedules, facilities costs, forecasted enrollment projections and broader economic data.
The value of this solution:
- Faster decision making.
- Increased revenue.
AI techniques used in this solution:
How AI helps:
- Improved budgeting.
- Better preparation for the incoming number of students.
- Improved proactive intervention.
The AI models provide:
- Projections for underlying factor importance, confidence interval and outyear factors.
Course schedule optimization
Use SAS to optimize course scheduling. Match seat supply with student demand, maximize the options and opportunities for both traditional and nontraditional students and improve student outcomes.
The value of this solution:
- Improved student outcomes.
- Maximized operational efficiency.
AI techniques used in this solution:
- Machine learning models in conjunction with advanced analytics.
How AI helps:
- Improve student outcomes. Create classroom schedules that are better aligned with student needs to improve retention, decrease DFW rates and reduce time to completion.
- Better utilize campus facilities. Reduce capital expenses by more efficiently using the classrooms already available. Institutions can creatively overcome constrained spaces and limited faculty availability by efficiently scheduling courses.
- Reduce schedule turnaround time for dynamic changes. Flexibility allows you to pivot due to unexpected changes during the academic year.
- Gain administrative efficiencies. Automated schedule generation can eliminate the time-consuming manual effort of adjusting course schedules.
The AI models provide:
- Multivariate regression models with stepwise selection at different levels of granularity, and multiobjective mixed-integer linear programming models.
- Generate an automated feasible course schedule and maximize student performance.
- Provide decision support on the assignment of courses to professors, rooms and time slots.
- Predict student performance.
Financial aid optimization
Use synthetic data to fuel a machine learning model to shuffle around flexible financial aid to maximize key performance indicators (KPIs) such as enrollment and net tuition revenue.
The value of this solution:
- Improved student outcomes.
- Better outcomes.
- Increased revenue.
AI techniques used in this solution:
How AI helps:
- Greater student retention.
- Higher enrollment.
- Save funds.
- Maximizes net tuition revenue.
The AI models provide:
- Optimal financial aid for each student.
- Optimizes overall financial aid pool, total enrollment and net tuition revenue.
By using predictive analytics, a large state university had its largest and most academically prepared student body ever.
Enrollment projections
Forecast enrollment counts using institutional data along with economic data.
The value of this solution:
- Faster decision making.
- Increased revenue.
AI techniques used in this solution:
How AI helps:
- Improved budgeting.
- Better preparation for the incoming number of students.
- Improved proactive intervention.
The AI models provide:
- Projections for underlying factor importance, confidence interval and outyear factors.
Reynolds Community College uses SAS to better understand trends in their facilities' utilization and capacity with an interactive dashboard.
Improve productivity and performance with SAS AI
I’m most proud of how we’ve moved the needle on the graduation rates. It’s gone up more than 20% over the last five or six years, which is meaningful because we’re talking about transforming students’ lives.” Dr. Skip Crooker Vice Provost for Decision Support University of Nevada, Las Vegas
Explore other education use cases by AI solution
AI Agents
Process written feedback faster, easier and more accurately with an AI agent for public commentary analysis. Categorize the inputs, identify themes and discern sentiment at scale using natural language processing (NLP) and large language models (LLMs) in education scenarios:
- Gathering parent input in a K-12 environment.
- School district-wide topics to inform ballot initiatives.
- Stakeholder commentary on P-20 data systems.
- College course feedback.
Quantum AI
Revolutionize your business with unprecedented computational power and efficiency to solve complex problems.
- Improve the speed and accuracy of AI models.
- Deliver efficiency enhancements.
- Enhance encrypted communications and transactions.
- Enable continued university participation in scientific advancement.
AI Modeling
Easily create programs that allow computers to predict outcomes and complete tasks for greater productivity and innovation.
- AI modeling can help educators analyze documents.
- Digitize paper records and analyze them with AI models that convert printed letters as optical symbols into digital text and apply NLP to extract meaning.
- Accelerate the path to boost student achievement based on long-term trend analyses in P-20 data systems.
- Improve any process that could benefit from data locked up in paper records.
GenAI
Generate results and synthetic data for improved productivity, operations, customer satisfaction, services and privacy.
- Improve emergency services in any school environment.
- Use chatbots enhanced with NLP-driven GenAI prompts designed to help connect students, administrators or first responders with answers or resources quickly in crisis moments.
Digital Twins
Navigate uncertainty – test and optimize performance or innovations with digital replicas of complex, real-world systems.
- Use digital twins for crowd size prediction and preparation for special events.
- Use data methodically to predict and prepare staffing and resourcing needs for large events, or engage digital twins with machine learning algorithms for real-time insights and situational awareness.
AI Ethics
Maintain privacy, inclusion, equity, transparency and protection of individual rights when using AI.
- Protect and strengthen students’ rights.
- AI use is not risk-free. With SAS, develop and deploy AI models with fairness and transparency, to incorporate regulations across all initiatives and to overcome the spread of misinformation.
The value of AI solutions from SAS
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Leaders in Michigan’s Armada Area and Anchor Bay school district empower their teachers to nudge students to reach higher achievement, showing remarkable improvements across multiple metrics. They did this by changing the focus to nurturing individual potential from attaining grade-level standards using SAS EVAAS for K-12.
Recommended resources on AI in education
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