Although the scale and reach of massive open online courses (MOOCs) is growing every year, a human teacher cannot guide, correct, and give feedback to thousands of students all working at the same time. To address this problem, Stanford University researchers have developed Codewebs, an artificially intelligent tutor for online students that can analyze and assess submitted code.
The researchers say Codewebs also can give students fast, tailored feedback and guidance. Codewebs runs machine-learning algorithms on a database of code submissions from thousands of students in courses offered by Coursera. The software breaks down the students' attempts at coding into small pieces and indexes them, enabling the system to compare the submissions with the database and cluster them according to their similarity with one another. The index lets a human instructor pick one submission, write feedback, and then have it automatically sent out to all of the students who wrote similar solutions.
"If a student hands in homework, not only does it say, 'Good job, you solved it like your peers,' but if it looks like the student is solving the problem in a way that is detrimental to their learning, we could give feedback to push them away from that," says Stanford's Chris Piech.
From New Scientist
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