Reducing Novice Programmers’ Cognitive Load and Improving Learning Efficiency by Using Gap-Filled Programming Practice System

ID: 43213 Type: Brief Paper: Demonstration
  1. Yu-Jen Lo, Chiung-Chen Lin, Lily Hou, and Jane-Dong Wu, Taipei Municipal Nei-Hu High School, Taiwan
  2. Yu-Chi Feng, National Experimental High School at Hsinchu Science Park, Taiwan
  3. Te-Chin Chu and Greg Lee, National Taiwan Normal University, Taiwan

Thursday, June 26 3:25-3:45 PM Location: B3109 View on map

Presider: Arnon Hershkovitz, Tel Aviv University, Israel

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.

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