Personalization is becoming a mandatory requirement in Web-based Education and long distance learning in general, representing a flexible way of learning the exact amount of knowledge to reach a given learning goal. This approach saves time and money and it is particularly suited for life-long learning. The drawback is that the teacher has to produce some effort to prepare didactic material and while research in this field proposes several intelligent systems providing personalization with advanced didactic strategies, teacher’s point of view is less considered. In this chapter we extend our previous work that aimed to build an adaptive system for education called LS-Plan, taking into account both teacher’s and student’s needs. In particular we carried out a comprehensive evaluation of the system embedded into an Adaptive Educational Hypermedia called Lecomps5, in order to experiment and prove the added value of the system.
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Thanks to the modern information technologies, Web-based education is widely used for distance learning, with both economic and didactic benefits. The absence of temporal and spatial constraints allows for (e-)learning in different contexts such as schools, companies and so on, saving money and time as well. By distance learning new didactic scenarios and opportunities have been considered from a pedagogical point of view, giving a strong boost to the literature of the field of Web-based learning. From a didactic point of view different approaches are possible: the student-centered approach, where students autonomously build their own knowledge, playing an active role in the learning process, as opposed to the traditional role where they act as passive learners only; the collaborative or socialapproach where students learn, thanks to their belonging to a community of learners, i.e., through knowledge sharing among students and among students and teachers or tutors, using social and wiki services like chat, forum and blog. In this context, personalization, i.e., the capability of an educational system to produce learning paths depending on the student’s personal traits and needs, is considered a very important requirement for distance learning and researchers have heavily focused on this aspect in recent years. The goal is to provide an alternative to the traditional one-size-fits-all approach: courses and contents have to be tailored to the particular student, with her previous knowledge, learning styles, interests, progresses and needs while taking the course. To this aim, many Web-based Educational Systems (WBESs) have been proposed in the literature, with a student model management capability, applying different techniques for building and updating such a model and for personalizing the educational activity.
In this chapter we extend a previous work where we presented some case studies concerning the application of an e-learning personalization engine called LS-Plan (Limongelli, Sciarrone & Vaste, 2008; Limongelli, Sciarrone & Vaste, 2009) to the Java language learning domain. Here we present a comprehensive evaluation of the LS-Plan system, an engine for providing a WBES with the capability to automatically produce personalized courses, adapting them on the basis of the student needs. Firstly a student model is built; secondly the student model is updated taking into account student’s characteristics, navigational behaviors and performance in the study, as measured by means of quizzes. Knowledge and learning styles are the student’s characteristics taken into account by the system. Quiz results and navigational behaviors are considered for the student model management and for adapting the proposed course to student’s needs. In this process the teacher is involved too: she is required to tag the learning materials while inserting them into the system.