Data-Driven Generation of Rubric Parameters from an Educational Programming Environment

• Published in: Artificial Intelligence in Education Vol. 10331; pp. 490 - 493
• Main Authors: Diana, Nicholas, Eagle, Michael, Stamper, John, Grover, Shuchi, Bienkowski, Marie, Basu, Satabdi
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Alice; Automatic assessment; Educational data mining; Programming

We demonstrate that, by using a small set of hand-graded students, we can automatically generate rubric parameters with a high degree of validity, and that a predictive model incorporating these rubric parameters is more accurate than a previously reported model. We present this method as one approa...