On the use of case-based planning for e-learning personalization

•Selection+sequencing of contents for e-learning personalization by using AI planning.•Automated compilation of PDDL files, making our approach solver independent.•Case-based planning to adapt and repair routes to meet new requirements.•Integration on top of Moodle Learning Management System.•Good performance from short to long courses and up to 100 students.

In this paper we propose myPTutor, a general and effective approach which uses AI planning techniques to create fully tailored learning routes, as sequences of Learning Objects (LOs) that fit the pedagogical and students’ requirements.myPTutor has a potential applicability to support e-learning personalization by producing, and automatically solving, a planning model from (and to) e-learning standards in a vast number of real scenarios, from small to medium/large e-learning communities. Our experiments demonstrate that we can solve scenarios with large courses and a high number of students. Therefore, it is perfectly valid for schools, high schools and universities, especially if they already use Moodle, on top of which we have implemented myPTutor. It is also of practical significance for repairing unexpected discrepancies (while the students are executing their learning routes) by using a Case-Based Planning adaptation process that reduces the differences between the original and the new route, thus enhancing the learning process.