Examining the Factors Affecting University Students' Perceived Learning Levels in Programming

This study explores the relationship between university students' attitudes toward programming, their motivation, anxiety levels, self-efficacy perceptions, and how these factors influence their perceived learning in programming. A correlational research method was employed, and data were collected from 207 university students. After analysing the data for normality and checking the assumptions for multiple regression analysis, the responses of 10 participants were excluded from the dataset. As a result, the analysis was conducted using data from 197 students. Data were collected online through Google Forms, using several instruments: a demographic information form, the Computer Programming Attitude Scale, the Learning Motivation in Computer Programming Courses Scale, the Computer Programming Self-Efficacy Scale for Computer Literacy Education, the Programming Anxiety Scale, and the Perceived Learning Scale. The study reveals that university students possess a strong attitude, motivation, self-efficacy, and perceived learning in programming, while their anxiety levels are moderate. A strong positive relationship was found between students' perceived learning levels in programming and their self-efficacy perceptions. Additionally, perceived learning moderately and positively correlated with students' motivation and attitudes toward programming. Conversely, a moderate negative correlation was found between perceived learning and programming-related anxiety. Ultimately, students' perceived learning levels in programming were predicted by their self-efficacy and motivation.