AB  - Recent research suggests that the first weeks of a CS1 course have a strong inuence on end-of-course student performance. The present work aims to refine the understanding of this phenomenon by using in-class clicker questions as a source of student performance. Clicker questions generate per-lecture and per-question data with which to assess student under- standing. This work demonstrates that clicker question per- formance early in the term predicts student outcomes at the end of the term. The predictive nature of these questions applies to code-writing questions, multiple choice questions, and the final exam as a whole. The most predictive clicker questions are identified and the relationships between these questions and final exam performance are examined. Copyright © 2014 ACM.
AU  - Porter, L
AU  - Zingaro, D
AU  - Lister, R
DA  - 2014/01/01
DO  - 10.1145/2632320.2632354
EP  - 58
JO  - ICER 2014 - Proceedings of the 10th Annual International Conference on International Computing Education Research
PY  - 2014/01/01
SP  - 51
TI  - Predicting student success using fine grain clicker data
Y1  - 2014/01/01
Y2  - 2026/05/14
ER  -