Technology Enhanced Assessment based on Semantic Web
Speaker Prof. Dr. Lilia Cheniti Belcadhi
ISITC, PRINCE Research Lab, Sousse University, Tunisia
Luogo e orario: Giovedi 30 Maggio 2019 in Aula D dalle 15 alle 16. Il seminario verrà tenuto in lingua inglese, ed aperto a tutti gli interessati, in particolare gli studenti di dottorato e magistrale di Informatica e STEM.
Nowadays, several critical challenges, opportunities, and trends in learning must be considered in the development and implementation of new learning environments. These include encouraging lifelong learning, valuing both informal and formal learning, addressing the open and social dimensions of learning, and recognizing the different contexts where learning takes place. It is also crucial to address what today’s learners need. Considering the new requirements in terms of learning raises also challenges with regard to the assessment of learning. Learner-centred and networked learning require new assessment models that address how to recognize and evaluate self-directed learning achievements. Assessment is an integral part of instruction, as it determines whether the lesson’s educational goals and standards are being met. Besides we observe that technologies used to facilitate assessment can be split into three categories:
- Technologies for aligned assessment, to allow alignment of assessment with the intended learning outcomes by making possible scenarios in which students can demonstrate the competencies they have developed in authentic contexts,
- Technologies for embedded assessment, to enable the integration of assessment activities into learning flows, where the result of the assessment may condition the following learning activity to be presented to the students and Technologies for scalable assessment, which are especially critical in courses with no constraints in class size (e.g., Massive Open Online Courses).
Considering Assessment, some research challenges can be encountered, such as diversity of web tools used by learners, difficulty to search and filter information: and need for Dynamic attribution of resources and resources interoperability. To deal with these challenges, it is necessary to retrieve relevant data for learning and assessment activities from different tools. Semantic web provides a common framework that allows data, information and knowledge to be shared and reused across applications.
We therefore propose a framework for Technology Enhanced Assessment based on Semantic Web, that is able to address various technologies for assessment and provide assessment according to the needs of the learner. In our research framework, models have been established and that can be seen as of two types: models as component and model as a basis for design. Moreover, we have focused on a particular type of models, which is ontologies, in the elaboration of the following models: student model, tutor model, metadata model, context model, interaction model, adaptation model, recommendation model, collaboration model, inquiry model, etc. Semantic web approach enables us to solve the problem of finding information by avoiding polysemy and reducing the number of results. The semantic web offers tools and infrastructures for semantic representation by means of ontologies. The latter fosters interoperability at semantic level because it provides a unique meaning for a concept and a relationship in ontology.
Prof. Lilia Cheniti – Belcadhi is Associate Professor at Higher Institute of Computer Sciences and Telecommunications H-Sousse, University of Sousse (Tunisia). She received a PhD in Computer Science with Honours by the Faculty of Sciences, University of
Tunis and University of Hannover (Germany). She won the following awards: First National Prize for Academic Excellence (Foreign Degrees) of the President of the Tunisian Republic; Graduate Merit Award of the Technical University of Braunschweig, Germany, for the best results in Computer Science and Mathematics degrees at the university.