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Apr 06 2021
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3 Ways to Use AI to Improve Student Success During Online Learning

To improve student engagement and graduation rates, consider these recommendations.
Tommy Weir is founder and CEO of enaible, a provider of AI-powered productivity solutions.
by

Tommy Weir is founder and CEO of enaible, a provider of AI-powered productivity solutions.

The U.S. higher education system has been rocked by the pandemic, with many large institutions experiencing unprecedented drops in student enrollment. One reason for this is that educators are missing key signals during online learning — cues they ordinarily receive during in-person courses — that can reveal how students are faring. This is directly affecting college enrollment and graduation rates.

At the center of the issue is a lack of visibility into student productivity. I’ve spoken with numerous university presidents about their primary concerns, and they include ensuring that students complete the courses they are registered for and avoiding having to return federal funds when students drop out of courses. They also need support when it comes to encouraging students to return next semester.

To fundamentally address these issues, higher education institutions must first understand how their students learn. This includes knowing how students are using their time and knowing what times of the day are the most and least productive for students. This requires educators to know which assignments are yielding the most positive output and which ones may need to be revisited. Most important, instructors must know how to translate this information into student success initiatives. This is where artificial intelligence can play a key role.

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1. Educators Can Use AI to Improve Student Support

Having the right data can help professors receive the insights they need to keep students engaged and on track. But data alone doesn’t make the grade. You need AI.

A great professor is one who can make real-time adjustments based on data-informed feedback. What works and what doesn’t? Are student patterns changing? Why? Are certain patterns predicting a student will likely fall behind? If so, educators can step in to provide individualized support before the student loses hope.

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2. AI Can Help Design Individualized Assignments and Group Projects

The pandemic has forced many students to work extra jobs to help their families survive, and that is one cause for the steep enrollment decline. To address this issue, educators need to know when students are prioritizing necessary work over attending classes and completing assignments. These students will require individualized attention and projects.

Some universities are already using AI to derive data value from systems and activity logs such as Blackboard, student information systems and Google apps, using it to proactively pinpoint areas that need improvement.

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3. AI Can Offer Customized Recommendations for Improving Courses

AI-enabled data analytics makes productivity tangible. AI can offer customized recommendations that help students get on — and stay on — the path to success.

For example, data can reveal when a student suddenly changes study patterns, a potential sign that the student may not be doing well. Data can also reveal the factors that help students succeed in particular courses and help with recommendations for course correction when there is still time to take preventive steps.

This data is the lynchpin of higher education efforts to effectively identify and resolve problems that occur during online or blended learning. With the help of customized, actionable recommendations generated by AI, both professors and students can have a better understanding of how to improve productivity and help students succeed.

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