Online tutoring system for programming courses to improve exam pass rate

Abstract

University students enrolled in the first year of the Computer Science degree may have problems approaching programming, negatively affecting their study during the course. Tutoring programming projects are very important in helping students with difficulty in learning by providing the right approach to study, improving their knowledge and skills in computing. The aim of this work is to realize a new Java Programming tutoring online course that allows students to have an effective online tool to achieve the learning goals of the course and this will enhance the programming exam pass rate. The course we have designed consists of tools to help students with video tutorials, self-assessment quizzes, code evaluations and exercises to solve using an online Java editor. Because the Moodle platform lacks tools to check the quality of the code syntax, a new software was created. It performs a syntax analysis of the Java code and, as a tutor, automatically provides feedbacks and tips to the students to improve the quality. For each online tool the immediate feedback technique is used to amplify students’ engagement. A Clustering Machine Learning technique is performed to identify different students’ behaviors. A correlation between them and the final performance showed the most influential features of the completed activities. Quantitative analysis highlighted the effectiveness of the tutoring system and the online course designed in this work to enhance the final exam pass rate. At the end, students filled a questionnaire to report their perception and satisfaction about the course.

Keywords

• Tutoring
• Feedback
• Java Programming
• Moodle
• Machine Learning