The Effect of Learners’ Characteristics on Learning Performance in Non-Face-To-Face Liberal Arts Coding Class

The Effect of Learners’ Characteristics on Learning Performance in Non-Face-To-Face Liberal Arts Coding Class

Purpose: In this study, we investigate the characteristics of learners in the liberal arts coding class and study the relationship between learners’ characteristics and learning outcomes to find methods to enhance learning performance. Through this study, we intend to provide the basic data to be used by the schools and educators operating coding education in the real world to establish the teaching strategy for coding education according to the characteristics of the learners. Method: The collected data was analyzed using SPSS 23, as follows. The reliability of the measurement tools on self-efficacy, learning interest, learning motivation, digital literacy, and learning satisfaction were calculated and verified. Through a survey, data on self-efficacy, learning motivation, digital device efficacy, learning satis-faction, and academic achievement were collected and descriptive statistical analysis was performed to identify trends. We performed multiple regression analyses with self-efficacy, learning motivation, and digital device ef-ficacy as independent variables, whereas learning satisfaction and academic achievement as dependent varia-bles. Before the regression analysis, a Pearson correlation analysis was performed between self-efficacy, learning motivation, digital device efficacy, learning satisfaction, and academic achievement to confirm the significance of the relationship between the measurement variables. Results: The significance test results of the regression model showed that self-efficacy and digital device effi-cacy had a positive effect on learning satisfaction and learning motivation and digital device efficacy also had a positive effect on academic achievement. In other words, we evaluated that higher self-efficacy and digital device efficacy lead to higher learning satisfaction whereas higher learning motivation and digital device efficacy lead to higher academic achievement. Conclusion: Through this study, we confirmed that learners’ characteristics have a high influence on both learning satisfaction and academic achievement. In the future study, we plan to add multiple factors of learners’ characteristics that affect learning performance and studies on educators’ characteristics to obtain various and meaningful results.