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Improving AI's Ability to Identify Students Who Need Help


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A student in need of help?

Researchers have designed an artificial intelligence model better able to predict how much students are learning in educational games.

Credit: North Carolina State University News

Researchers at North Carolina State University's Center for Educational Informatics have developed an artificial intelligence (AI) model to predict students' absorption of knowledge via educational gameplay.

The model utilizes multi-task learning, in which it is asked to execute multiple tasks to forecast whether students would answer each question on a test correctly, based on their game behavior.

The AI was assigned to learn 17 tasks correlating with the test's 17 questions.

The model studies each student's gameplay and question-answering pattern on the test's first question, and identifies common behaviors of students who answered the question correctly or incorrectly to ascertain how new students would answer; it performs this function for all questions.

The multi-task model is about 10% more accurate than models dependent on conventional AI training, and the researchers think the AI could help flag students who may need additional instruction.

From NC State University News
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA


 

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