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The increasing popularity of distance education poses exciting new challenges. In particular, current pedagogical paradigms, such as competency-based education, require students' continuous evaluation. That is, to master skills, students need to receive constant feedback to guide their experimentation processes. However, teaching teams are usually under-dimensioned to support the large number of students that online courses usually have. This paper presents the approach we have adopted at the National University of Distance Education to overcome this problem for the case of computer programming practices, which complements human evaluation with an automatic assessment system. The paper describes our system and reports its benefits with an empirical study from 2011 to 2018 that involved 14,944 students.

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Competency-based education is becoming increasingly adopted by higher education institutions all over the world. This paper presents a framework that assists instructors in this pedagogical paradigm and its corresponding open-source implementation. The framework supports the formal definition of competency assessment models and the students' evaluation under these models. It also provides distinct learning analytics for identifying course shortcomings and validating corrective actions instructors have introduced in a course. Finally, this paper reports the benefits of applying our framework to an engineering course at the Pontifical Catholic University, Valparaíso, Chile for three years.INDEX TERMS Competency-based education, course assessment, course monitoring, learning outcome.

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