Background/Objectives: In the 21st century, communication and collaboration between people is an important element of talent. As artificial intelligence (AI), the cutting edge of computer science, develops, AI and collaboration will become important in the near future.
Methods/Statistical analysis: To achieve this, it is necessary to understand how artificial AI based on computer science works, and how problem-based programming education is effective in computer science education. In this study, 177 college students who received programming education focused on problem-solving learning were identified with computational thinking (CT) at the beginning of the semester, and their satisfaction and post-education satisfaction survey showed that their attitudes and interests influenced their education.
Findings: To pretest the learners, they were diagnosed using a measurement sheet. The learners’ current knowledge statuses were checked, and the correlation between the evaluation results, based on what was taught according to the problem-solving learning technique, was analyzed according to the proposed method. The analysis of the group average score of the learners showed that the learning effect was significant. The results of the measures of the students’ CT at the beginning of the semester were correlated with problem-solving learning, teaching method, lecture satisfaction, and other environmental factors. The ability to solve a variety of problems using CT will become increasingly important, so if students seek to improve their satisfaction with problem-solving learning techniques for computer science education, it will be possible for universities to develop convergence talent more efficiently.
Improvements/Applications: if you pursue a problem-solving learning technique and a way to improve students’ satisfaction, it will help students improve their problem-solving skills. If the method of deriving and improving computational thinking ability in this paper is applied to computer education, it will induce student interest, thereby increasing the learning effect.
University Students' Attitude and Anxiety Towards Computer Science Education through Computational Thinking
