Predicting Quitting in Students in Speed-Reading Course: A Case Study
Conference paper > Summary Text · 2023
Authors: İnanç KABASAKAL
The 10th InTraders International Conference on Social Sciences and Education, Macedonia, Üsküp, International, Verbal, Summary Text, 2023-2023, pp 10-10
Summary
<p>Speed-reading courses are designed to improve their students’ reading speed and comprehension. The use of e-learning environments enables data collection that helps assessment of students and predictive analyses. Student dropout prediction is among the popular problems in this context. This study presents a neural network-based prediction model that identifies impending dropouts from a speed-reading course. Assessment scores obtained in the last ten sections were analyzed to predict dropouts who will not proceed to the next level. Despite the challenge of predicting short-term dropouts, the tests resulted in an accuracy of 81% on average, while 57% of predicted students actually dropped out before the next level, and 53% of dropouts were successfully predicted on time.</p>