Mag 212019

Technology Enhanced Assessment based on Semantic Web

Speaker Prof. Dr. Lilia Cheniti Belcadhi
Associate Professor

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.


Short Bio:

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.

Mar 172017

Avviso di seminario: lunedi 27 Marzo 2017 alle ore 16.00, nell’aula F presso il Dipartimento di Matematica ed Informatica dell’Università di Cagliari si terrà il seguente seminario.

Discrimination Discovery Exploiting Ontologies

Prof. Franco Turini, University of Pisa

Discrimination discovery from data consists of designing data mining methods for the actual discovery of discriminatory situations and practices hidden in a large amount of historical decision records. Approaches based on classification rule mining consider items at a flat concept level, with no exploitation of background knowledge on the hierarchical and inter-relational structure of domains. On the other hand, ontologies are a widespread and ever increasing means for expressing such a knowledge. In this talk, we propose a framework for discrimination discovery from ontologies, where contexts of prima-facie evidence of discrimination are summarized in the form of generalized classification rules at different levels of abstraction. Throughout the talk, we adopt a motivating and intriguing case study based on discriminatory tariffs applied by the U.S. Harmonized Tariff Schedules on imported goods.


About the speaker: Franco Turini is currently a full professor in the Department of Computer Science of the University of Pisa, where he also served as Department Chairman. In 78/80 he has been a visiting scientist of the Carnegie-Mellon University (Pittsburgh) and of the IBM Research Center S.Jose, afterwards. In 92/93 he has been visiting professor at the University of Utah.

He has been coordinator of the “Meta- and non-monotonic reasoning area” (BRA Esprit Action No 6810 “Compulog II”) and several other projects including the 2007 Italian PRIN “Anonimo”, focusing on methods for anonymity and privacy protection. He co-edited with Krzysztof Apt a book entitled Meta-logics and Logic Programming, published by The MIT Press, and also editor of Springer and IEEE Proceedings.

His research interests include programming languages design and implementation, formal semantics, and methods for preserving privacy and anomymity.


Contact: Maurizio Atzori, – Dipartimento di Matematica ed Informatica, Università di Cagliari


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