Assistance in computer programming learning using educational data mining and learning analytics

Abstract

The learning of programming presents many difficulties for students. Nowadays, a number of software tools are available that enable students in programming courses to develop and exercise their knowledge and skills. However, these tools do not examine their work or provide students with indications on their learning process. In this paper we introduce a learning approach for programming based on the analysis of students' mistakes during practical lessons in programming subjects. This approach makes use of compiler messages to analyse their quantity and semantic value, and report the individual and comparative learning progress. This approach is illustrated in practice by a case study conducted in a class of undergraduate students of computer science. This study makes it possible to provide an analytic representation of reflective learning practice, giving us a better understanding on programming learning processes.