An Ontology-Based Approach for Context-Aware e-Learning Nicola Capuano, Matteo Gaeta, Saverio Salerno Centre of Research in Pure and Applied Mathematics CRMPA, Fisciano, Salerno, Italy {ncapuano, mgaeta, salerno}@unisa.it Guseppina Rita Mangione MOMA S.p.A. Baronissi, Salerno, Italy mangione@momanet.it Abstract — Context-aware e-learning is an educational model that foresees the selection of learning resources to make the e- learning content more relevant and suitable for the learner in his/her situation. The research reported in this paper was purposed to improve an existing system for personalized e- learning with contextualisation features. This has been done by defining a context model, an ontology-based model to represent a teaching domain that includes contextualization information and a methodology to generate personalized and context-aware learning experiences basing on such structures. Keywords — adaptive e-learning, learning context, knowledge representation, context-aware e-learning, learning design I. INTRODUCTION Personalized e-learning is defined in [1] as a educational model that is tailored to the individual learner’s needs and interests. Personalized learning can be used for developing individual learning programs and engage learners into the learning process so that learner’s potentials and success can be optimized. Personalized e-learning is not restricted by time, place and learner’s other requirements. It is mostly focusing on learner’s preferences and current state to provide the learning content correctly. Differently from context- aware e-learning, it does not consider a learner’s situation. Context Aware e-Learning, on the other side, provides a learner with highly customized learning content [2]. The customization of content is made by selecting or filtering learning resources in order to make the e-learning content more relevant and suitable for the learner in his/her situation. The filtering process is done considering several parameters related to the environment where the learning takes place. The purpose of this paper is to report a work performed to define theoretical and technological components needed to extend an already existing system for personalized e-learning with learning contextualization features. The paper is structured as follows: in the second section a state of the art on learning context modelling is presented while the third section briefly describes the learning platform IWT (Intelligent Web Teacher) [3] that we used as starting point to apply contextualization features. The fourth section describes the proposed approach from the theoretical point of view by introducing our definition of learning context and methodological components needed to support it and provide contextualisation features in IWT. The fifth section describes the developed prototype while the last one presents some conclusions and planned future works. II. RELATED WORK Several definitions of context are available in literature. According to [4], context is defined as “that which surrounds, and gives some meaning to, something else”. In [5] instead it is defined as “any information that is used to characterize the situation of an entity”. Moreover, according to the ubiquitous computing, “Context is any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application including the user and applications themselves.” [2]. The IMS Learning Resource Meta-Data Information Model [6] defines a learning context as “the typical learning environment where use of learning object is intended to take place”. It also proposes a list of feasible contexts for a learning object i.e. school, higher education and training. Other authors [7] define the learning context as the learner environment and talk about three main environments: the external environment (e.g. classroom, working space, in- person coaches, etc.), the internal environment (e.g. previous beliefs, thoughts, hopes, etc.) and the digital environment. According to [8], instead, a context model for e-learning is composed by seven levels (i.e. technological, pedagogical, methodological, organisational, psychological, related to the subject domain and to the course), each one characterised by several aspects and variants. In [9] a “static” context model for context-aware e- learning has been defined basing on the analysis of the relevant literature about the topic. The static nature of the context is due to the fact that only parameters that do not change within the entire e-learning course structure have been considered. The defined model is composed by several context parameters divided in sub context parameters. In [2] the same authors have systematized and aggregated such parameters into the following sub-contexts: • Profile Context giving information on learner’s personal information, personality type and level of expertise; • Preference Context giving information about learner’s approach to learning, intention and learning style; • Infrastructure Context describing learner’s situation in terms of network and device used by the learner; • Learning Context giving information about the learning pace, state and comprehension level of the learner. According to [10] the learning context describes a class of learners within a technological infrastructure with a set of parameters related to the learner category, the educative modality end the educational objective. 2011 Third International Conference on Intelligent Networking and Collaborative Systems 978-0-7695-4579-0/11 $26.00 © 2011 IEEE DOI 10.1109/INCoS.2011.53 789