student learning Archives - ASEE Computers in Education Journal

Mark A. Palmer

Formerly IME Department
Kettering University
Currently Flushing, MI
MarkAPalmer@att.net

Abstract – This paper describes the development and use of “automatically-personal e-mail” routines allowing one to send interpretive e-mails to one’s class based on clicking a command in an Excel grade book. The macros are included in a template file which are available under the Attribution-NonCommercial-ShareAlike 4.0 International Creative Commons License. Nudges, in the form of light-touch directed-feedback have been shown to be effective in engaging students, but they are often time consuming for faculty. The author has found that he can send detailed performance updates to students automatically through macros in a well defined Excel Gradebook. This increases student engagement as they see it as a way of demonstrating caring. Using an Engineering Materials Course as an example, the author demonstrates the steps necessary to send 6 such nudges throughout an 11 week term. Sample commented coding and examples of the messages sent to students are provided as examples. Read the full article here “Improving Student Success by Being Automatically Personal”

Shaymaa E. Sorour

Dept. of Educational Technology
Faculty of Specific Education Kafrelsheikh University
Egypt
shaymaasorour@gmail.com

Hanan E. Abdelkader

Dept. of Computer Teacher Preparation
Faculty of Specific Education
Mansoura University
Egypt
h_elrefaey@yahoo.com

Abstract—This research focuses on understanding student performance by giving automatic feedback after writing freestyle comment data in each lesson. Writing comments express students’ learning activities, tendencies, attitudes, and situations involved with the lesson. Random Forest and Support Vector Machine were applied to analyze the students’ prediction results. Also, a Majority Vote (MV) method is employed in consecutive lessons during the semester to the predicted results. The proposed system tracks student’s learning activities and attitudes with different courses and provides valuable feedback to improve educational performance.

Keywords—Automatic feedback, Comment data, SVM, RF, MV

I. INTRODUCTION

Improving the performance of students, determining their actual progress, and enhancing their learning process can be extremely valuable in the educational environment. To achieve a high level of student performance, we have to find ways to measure their current progress and predict the results of the learning process at the earliest stages. Read the full article here “The Effect of An Automatic Feedback System on Students’ Comments to Improve their Performance”