Identifying Evidences of Computer Programming Skills Through Automatic Source Code Evaluation
Andres Porfirio, Roberto Rodrigues Pereira Junior, Eleandro Maschio · 2020
This research is contextualized in the teaching of computer programming. Continuous assessment of source codes produced by students on time is a challenging task for teachers. The literature presents different methods for automatic evaluation of source code, mostly focusing on technical aspects. This research presents the A-Learn EvId method, having as the main differential the evaluation of high-level skills instead of technical aspects. The following results are highlighted: updating the state of the art through systematic mapping; a set of 37 skills identifiable through 9 automatic source code evaluation strategies; construction of datasets totaling 8651 source codes.