Design and Evaluation of a Deep Learning Recommendation Based Augmented Reality System for Teaching Programming and Computational Thinking

Abstract

Programming is considered a skill to arouse and inspire learner's potential. Learning to program is a complex process that requires students to write grammar and instructions. The structure of a programming language does not cause impose problems to students, the real obstacle is how to apply these learned grammars and present them in a complete and correct program code for problem solving. In this study, a deep learning recommendation system was developed, which includes augmented reality (AR) technology, and learning theory, and is provided for study by students in non-major and also from different learning backgrounds. Those students divided into two groups, the students participating in the experimental group were using the AR system with deep learning recommendation and the students participating in the control group were using the AR system without deep learning recommendation. The results show that students in experimental group perform better than the control group with regards to learning achievement. On the other hand, in the part of computational thinking ability, students using a deep learning recommendation based AR system is significantly better than those using non-deep learning recommendation based AR system. Among the various dimensions of computational thinking, creativity, logical computing, critical thinking, and problem-solving skills are significantly different among the two groups of students. The students in experimental group perform better than the control group with regards to the dimensions of computational thinking, creativity, logical computing, critical thinking, and problem-solving skills.