Returning Students Need AI-Driven Learning to Recover Ground Lost Due to COVID-19

As the last school year came to a close, the Brookings Institution has made sobering predictions about the likely impact of COVID-19 on students by the fall of 2020. They predicted that some students would be performing at grade level, while others will have so lost much ground that they would be performing at a lower level than they did a year before. Now that students are returning to class, we will find out soon enough whether those predictions are proving true. The achievement gap among students is likely to be very wide, and could grow worse over the coming year as COVID-19 continues to disrupt education.

Teachers will need help in order to meet these challenges. Fortunately, AI-driven learning can provide that help, not by replacing teachers but by helping them provide support to the students who need it most.

For language learners, one of the first challenges teachers will face will be to help students overcome the effects of language attrition. Learners who have been out of school for extended periods of time may not have had much opportunity to practice speaking a foreign language, and so their language proficiency will suffer. These attrition effects depend on the amount of time that has elapsed since the learner last practiced, and are likely to be greater for beginner and intermediate students.

AI-driven learning can help by automatically measuring each student’s performance level and providing them with the individualized practice that they need to regain proficiency. Alelo’s Enskill platform does this by putting learners in conversational simulations with AI avatars, and measuring both the accuracy of the learners’ language (in terms of objectives that the learners completed) and fluency (in terms of conversational turns per minute) to arrive at an overall mastery score. Learners who continue to practice these simulations typically quickly improve their mastery scores, showing that they are overcoming the effects of language attrition.

Enskill also automatically assigns individualized practice exercises to each learner, focusing on language skills that require improvement. This can be a great help in closing the achievement gaps among students, since teachers may not be able to provide each student with individualized assignments.

Looking ahead, we see an ongoing need for teachers to track the performance of each learner, to identify which students are progressing, which students are struggling, and which students are losing motivation and disengaging. The new version of Enskill, designed with COVID-19 in mind, makes learner performance statistics available to teachers, so they can track student progress over time. The performance patterns provide early indicators of students who are having difficulties. This is particularly critical during the COVID-19 pandemic, when many students must work remotely and teachers are not able to track their progress as they would face to face in a classroom.

Our upcoming webinar will discuss how artificial intelligence (AI) technologies can help language learners get back on track and stay on track. It will also offer webinar participants free resources to use with students.

How to Use Artificial Intelligence to Help Learners Recover Ground Lost During COVID-19

Friday, September 4th, 1:00 PM – 2:00 PM ET (Register)

Friday, September 11th, 1:00 PM – 2:00 PM ET (Register)

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