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This study aims to investigate the relationship between the personal traits and computational thinking skills of second graders within the context of robotics activities.

Through literature review, a research model and hypotheses were tested with 122 second graders after robotic activities.

The hypothesized model showed that learning preference, intrinsic motivation and self-efficacy were the main predictors of coding achievement and computational thinking skills, while no direct relationship was found between learning preference, intrinsic or extrinsic motivation. The final path analysis revealed that intrinsic and extrinsic motivation predict self-efficacy, self-efficacy predicts coding achievement and coding achievement predicts computational thinking skills. Another important finding was the strong impact of self-efficacy on coding achievement, as well as computational thinking skills. Results are interpreted with reference to implications for potential methods of improving computational thinking skills when using robotics in the lower grades in elementary schools.

This study not only examined these relationships but also proposed, tested and built a research model containing a wide range of personal traits based on path analysis and multiple regression analysis, which, to the best of the researchers’ knowledge, has not been investigated in the current literature.

As reflected in the final research model, self-efficacy played an important role in impacting second grader’s coding achievement and computational thinking skills.

Few studies have investigated the various relationships in the context of robotics instruction in elementary schools as in this study. Given the increasing popularity of robotics education in elementary schools, the re-examination and identification of the pivotal role of self-efficacy in predicting second graders’ learning of coding and computational thinking skills have important implications for the implementation of robotics education.