One-minute Paper as a Basis of Automatic Prediction of Student’s Grade
Yoshio Yamagishi, Kanazawa Institute of Technology, Japan
EdMedia + Innovate Learning, in Vancouver, BC, Canada ISBN 978-1-939797-24-7 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
One-minute paper (OMP), which is usually assigned at the end of a class and requires students to write down about the class in a minute or two, may reflect student’s learning level. We explore the potentiality of OMP as a basis of automatic prediction of student’s grade. Total 2198 OMPs were collected in our lecture named “Fundamental Programing”, which is for the first year students of Department of Media Informatics, Kanazawa Institute of Technology for two years. Those OMPs were inputted to three classifiers based on different machine learning algorithms such as Naïve Bayes, Support Vector Machine and Convolution Neural Network, and we found that the accuracies of these three classifiers are 30%, 39% and 40% respectively. The correlation between student’s final grade and number of OMP submission is also investigated. We found positive correlation (R=0.57) between them, and the prediction accuracy based on the linear regression is 29%
Yamagishi, Y. (2016). One-minute Paper as a Basis of Automatic Prediction of Student’s Grade. In Proceedings of EdMedia 2016--World Conference on Educational Media and Technology (pp. 903-909). Vancouver, BC, Canada: Association for the Advancement of Computing in Education (AACE).
© 2016 Association for the Advancement of Computing in Education (AACE)