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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