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Using clickers to predict students final courses grades, an artificial intelligence approach

Conference contribution
Authors Fionn Delahunty
Alexander Schliep
Published in Extended Abstract of KUL-2019 presentation
Publication year 2019
Published at Department of Computer Science and Engineering, Computer Engineering (GU)
Language en
Keywords Artificial Intelligence, clickers, Data Science, interactive learning, pedagogy
Subject categories Statistics, computer and systems science, Didactics


Clickers are useful for improving interaction in teaching. Here, we demonstrate how artificial intelligence can improve this usefulness even further by predicting final exam scores of students early in the semester. We also investigate how the number of attempts a student makes effect the correctness of the answer.

Page Manager: Webmaster|Last update: 9/11/2012

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