A Semi-Automated System for Recognizing Prior Knowledge

Joaquim Moré, Jordi Conesa, David Baneres, Montserrat Junyent


Adaptive e-learning systems are able to automatically generate personalized learning paths from the students’ profile. Generally, the student profile is updated with information about knowledge the student has acquired, courses the student has passed and previous work experience. Unfortunately, dealing with courses that students passed in other learning environments is very difficult, error prone and requires a lot of manual intervention. In addition, the recognition of external courses is a process that all institutions, on-site and online learning organization, must perform during the access of new students, since it can be greatly useful not only for personalization but also for recognizing the courses the students attended. In this paper, we propose an intelligent system that analyzes the academic record of students in textual format to identify what subjects the students studied in the past and therefore are potentially recognizable. In addition, the proposed system is able to enrich the information the institution has about the students’ background, facilitating the identification of personalized learning paths.


Recognition; prior learning; support system; adaptive learning; background knowledge; context

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Copyright (c) 2017 Joaquim Moré, Jordi Conesa, David Baneres, Montserrat Junyent

International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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