Reducing Novice Programmers’ Cognitive Load and Improving Learning Efficiency by Using Gap-Filled Programming Practice System
Abstract: One of the main challenges for novice programmers is to learn the statement, syntax, logical thinking and program design in a short time. Students usually experience a heavy cognitive load when learning to program. The limitation of teaching hours in high school also leaves no time for instructors to individually assist each student. In this study, we propose a gap-filled programming practice (GFPP) system to help novice programmers reduce their cognitive load and ensure students focus on the specific contents instructors want them to practice. The research shows that students who were taught with GFPP system scored higher than students who were taught with traditional approach. The students can finish the practices efficiently and the positive feedbacks from GFPP system make them feel more confident and unafraid of learning programming.
Presider: Arnon Hershkovitz, Tel Aviv University