An Automatic Feedback Model for Learning Programming via Block-Based Programming Platforms

Abstract

Block-based programming platforms (BBPP) are often introduced to students for teaching programming. To facilitate students learning to program with BBPPs, students need quality feedback. However, BBPPs' feedback systems sometimes fail to support students in learning programming. In this study, a new BBPP, including a novel automatic feedback model, is created to support secondary school students in learning programming concepts and applying problem-solving strategies for problems in BBPPs better. The proposed feedback model analyses the students' blocks used in BBPPs and compares them with the correct solution by calculating the distance of the codes represented by the block patterns. Teachers' and students' initial evaluations about the BBPP were generally positive and promising. The proposed model is considered to have the potential for practical application in the design and implementation of the feedback model for BBPPs. We hope that the findings of this study will assist in the future design and implementation of feedback for BBPPs to facilitate the structural and strategic knowledge dimensions of programming.