Abstract
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.
Highlights
The aim of an adaptive e-learning system is to guide the learner to a comprehensive learning process based on the learner’s knowledge [1]
Adaptive learning can be performed in three different non-disjoint ways: 1) personalization of the learning processes: where the learning process of each student is personalized according to the student profile and behavior [2][3], 2) content personalization: where the learning objects offered to the student are personalized according to the student experience [4][5][6]; and 3) interface adaptation: where the learning management system interface is adapted according to every student's needs, preferences and history[7][8]
Adaptive e-learning systems tend to be self-contained, which means that the information that updates the student profile is automatically generated from the competences the learner acquires in the virtual learning environment (VLE) [9][10]
Summary
The aim of an adaptive e-learning system is to guide the learner to a comprehensive learning process based on the learner’s knowledge [1]. Adaptive systems should contain a great amount of information about students in order to select the content to be provided, along with the interface and the learning activities for each student Such information is what we call the learning profile of the student. Adaptive e-learning systems tend to be self-contained, which means that the information that updates the student profile is automatically generated from the competences (or skills) the learner acquires in the virtual learning environment (VLE) [9][10]. If so, they tend to use questionnaires [11][12] to find out about students’ prior knowledge.
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