The Programming Learning Assessment Model for Measuring Student Performance

With recent pandemic, many students cannot join the class in physical classroom. The needs for e-learning and self-assessment become more salient than before. The teaching mode has been changing from teacher-centered to student-centered method. E-learning environment is practically a highly essential software application in the education field. However, programming-specific functionalities are hardly to be found on most of the general-purpose learning platforms, which may be unwieldy and unnecessarily complex to instructors and students in the programming learning process. This research aims to design a self-assessment model for a better support of programming e-learning, especially with exist of mandatory programming-specific functionalities. It’s believed that student background and effort have close correlation with their programming performance. More data to verify the correlations associated with positive learning outcome. In this research, we highlight the relationship between student background and student performance levels for introducing personalised self-assessment sets for students to learn programming. We propose and discuss Language, Education, Achievement, and Programming (LEAP) and Programming Learning Assessment (PLA) models to fill in the gap between the background knowledge and student competencies. To measure the correlation between proposed models and student performance, an experiment that involves 65 respondents was conducted. The data was analysed with structured and statistical approaches. Preliminary study shows that there are multivariate effects of the English fluency on PLA model. With the increasing demands of IT and software development skills, this research will help in motivating and encouraging more people to learn programming.