3 MIN. READ
The vast proliferation of data and machine learning’s ability to rapidly categorize and analyze it have altered processes across every industry. Technology and data analytics have already made a substantial impact on education, from kindergarten to graduate school.
Some educational professionals may fear that technological advances will lead to de-personalization of education, isolation of students, and machines replacing valuable in-person teachers. The use of artificial intelligence (AI) and data analytics however can provide both educators and students with tremendous benefits, and its use is primed to continue to grow.
A recent study by Ivy Tech Community College in Indianapolis shows that data analytics can drastically decrease student failure rates. Ivy Tech used a machine-learning model to provide highly personalized intervention services for at-risk students. Their AI-generated program encouraged at-risk students to interact more with their teachers and peers, providing needed support for students and an added sense of job security for teachers.
Ivy Tech generated the data points it needed by interviewing members of the academic affairs and student success departments about the characteristics and habits of highly successful students. They then asked department members what advice they would give to struggling students. Data that related to better school performance was used to build a machine-learning model.
The Ivy Tech study found that during the first school term of the machine learning model’s deployment, faculty and staff identified 16,247 out of 60,000 students statewide that were at risk of failing one or more courses. The school deployed 800 faculty and staff members to call the at-risk students and offer specific pieces of advice.
For example, students struggling with algebra would receive information about times and locations of math tutoring sessions. By mid-term, the failure rate fell by 3.3% on a year-over-year basis, with 3,100 more students passing their classes than at the same time during the previous year.
Key areas where AI is growing in education
AI’s potential goes far beyond intervening for the benefit of struggling students. Both classroom and administrative applications exist. Data analytics based on AI will continue helping higher education institutions improve instruction, enhance educational effectiveness, manage budgets and market degree programs to the people who benefit from them.
Key areas where AI continues to grow in education through 2025 and beyond include:
- Student experience
- Student needs
- Future staffing needs
- Growth and sustainability
- Institutional effectiveness
With such a large list of applications, an implementation plan is vital, experts say. If AI programs are installed haphazardly, they may not work together and result in a chaotic environment that destroys their effectiveness.
Institutions must proceed on a step-by-step basis that fully integrates new programs into the institution and then builds successive programs on that foundation.
AI offers all sorts of opportunities for educators
Without question, AI and data analytics are a force in higher education. As the Ivy Tech Community College study shows, AI has the power to help educators improve student performance, increase student engagement and enhance instruction. Educational institutions will continue adding AI programs for administrative and classroom deployment, helping teachers make the experience more cohesive and personalized.
AI will also help educators with grading. Grading homework and tests is often tedious work. When AI can help relieve the grading burden, teachers are freed up to provide personalized instruction to students and create innovative new methods of enhancing student learning and engagement.
Technology is driving student engagement and retention at diverse organizations throughout the country. Learn how a large online university is using its digital presence to support and drive student admissions, retention, and communications.
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