Abstract
The specific doctoral research focuses on the domain of the optimization of the quality of the offered services by the Higher Educational Institutions (HEI), and thus it proposes an integrated framework for the personalization and parameterization of the design of learning pathways, aiming at facilitating the selection of totally dynamic and personalized educational schemes. Following a process-oriented approach, the proposed framework utilizes learning pathways to orchestrate personalized academic plans based on student’s academic characteristics, academic status, interests, personality type and needs. More specifically, the creation of the proposed framework will include 1) the design and implementation of the learning pathway semantic model that will be responsible for the description of the required concepts, 2) the Semantic Web Rule Language (SWRL) ruleset that will be responsible for the representation of the academic advising knowledge and experience as well as 3) the implementation of the methods and algorithms for the design and execution of personalized and self-evolving learning pathways. In order to facilitate the deployment and evaluation of the abovementioned framework, a software prototype will be designed based on a set of semantic web technologies. The integrated software environment will cover both of the design and execution phase of learning Pathways. Thus, it will present the respective business logic and the complete set of applications to facilitate the execution of the totally personalized and self-evolving learning pathways for the unique case of each student in a HEI. Additionally, the specific doctoral research will comprise of the necessary tools for the creation and maintenance of the semantic infrastructure which refer to the design phase.
Advisory Committee
Supervisor: Achilleas Kameas
Co-supervisors: Panos Fitsilis, Christos Goumopoulos