Sergio Miranda

LIA: An Intelligent Advisor for E-Learning

Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, until now very few systems were able to leave academic laboratories and be integrated into real commercial products. One of these few exceptions is the Learning Intelligent Advisor (LIA) described in this article, built on results coming from several research projects and currently integrated in a complete e-learning solution named Intelligent Web Teacher (IWT). The purpose of this article is to describe how LIA works and cooperates with IWT in the provisioning of individualized e-learning experiences. Defined algorithms and underlying models are described as well as architectural aspects related to the integration in IWT. Results of experimentations with real users are discussed to demonstrate the benefits of LIA as an add-on in online learning.

Automatic generation of assessment objects and Remedial Works for MOOCs

In the MOOC environments, the students feel to be alone in the process of choosing courses leading to their learning needs and work objectives. They perceive also to be controllers of their progresses with respect to calendars, fruition, assessment results. Students come into the MOOC environments to develop or enhance professional competences, to earn formative credits and to achieve certifications to get more employment opportunities, but the statistics underline high level of drop-out and few released useful credits and final certifications. These problems are mainly related to the difficulty to guarantee the “teaching presence” in courses with thousands of learners having different background and to the ineffective assessment methods for a meaningful learning process looking at the objectives and giving feedbacks for individual learning paths construction. The work, in particular, exploits the adaptation and personalization features of IWT platform in order to provide ARWE (Adaptive Remedial Work Environment) in order to fill the lack of a one-to-one tutoring mitigating the drop-out problem in MOOCs. The main original contribution of this work concerns the definition of an approach to automatically generate quizzes, exploiting a semantic-based method, in order to populate the e-Testing tool existing in ARWE, decreasing, de facto, the effort for instructors in the assessment authoring phase.

A SKOS-based framework for Subject Ontologies to improve learning experiences

Subject Ontologies represent conceptualizations of disciplinary domains in which concepts symbolize topics that are relevant for the considered domain and are associated each other by means of specific relations. Usually, these kind of lightweight ontologies are adopted in knowledge-based educational environments to enable semantic organization and search of resources and, in other cases, to support personalization and adaptation features for learning and teaching experiences. For this reason, applying effective management methodologies for Subject Ontologies is a crucial aspect in engineering the environments. In particular, this paper proposes an approach to use SKOS (a Semantic Web-based vocabulary providing a standard way to represent knowledge organization systems) for modelling subject ontologies. Moreover, the paper underlines the main benefits of SKOS. It focuses on alternative strategies for storing and accessing ontologies in order to support the knowledge sharing, knowledge reusing, planning, assessment, customization and adaptation processes related to learning scenarios. The results of an early experimentation allowed the authors defining a framework able to support, from both methodological and technological viewpoints, the use of Subject Ontologies in the context of a Semantic Web-based Educational System. The defined framework has high performances in terms of response and this may really improve the user experience. We defined a framework to use Subject Ontologies in Educational Systems.Subject Ontologies support learning scenarios by representing themes to treat.SKOS is a good technical approach to improve the learning experience of users.We identified a good strategy to treat Subject Ontologies and support SWBESs.The described approach may improve the performance of the learning processes.

A personality based adaptive approach for information systems

We defined a new adaptive approach to suggest the best interaction to the users.We get the personality of the users by inferring it from the social networks.The adaptive system instantiates for each user the best process and interface.The proposed approach includes two different layers of personalization.The approach suggests the interaction process for collaborative learning. In every context where the objective is matching needs of the users with fitting answers, the high-level performance becomes a requirement able to allow systems being useful and effective. The personalization may affect different moments of computer-humans interaction routing the users to the best answers to their needs. The most part of this complex elaboration is strictly related with the needs themselves and the residual is independent from it. It is what we may face by getting personality traits of the users.In this paper, we describe an approach that is able to get the personality of the users by inferring it from the social activities they do in order to drive them to the interactive processes they should prefer. This may happens in a wide set of situations, when they are deepened in a collaborative learning experience, in an information retrieval problem, in an e-commerce process or in a general searching activity.We defined a complete model to realize an adaptive system that may interoperate with information systems and that is able to instantiate for all the users the processes and the interfaces able to give them the best feeling and to the system the highest possible performance.

CADDIE and IWT: two different ontology-based approaches to Anytime, Anywhere and Anybody Learning

The Semantic Web seems to offer great opportunities for educational systems aiming to accomplish the AAAL: Anytime, Anywhere, Anybody Learning. In this scenario, two different research projects are here introduced: CADDIE (Content Automated Design & Development Integrated Editor), developed at the DIST of the University of Genoa, and IWT (Intelligent Web Teacher), developed at the DIIMA of the University of Salerno, each of them characterized by the use of ontologies and semantic technologies in order to support instructional design and personalized learning processes. The former aims to develop a learning resources and instructional paths authoring tool based on a logical and abstract annotation model, created with the goal of guaranteeing the fexibility and personalization of instructional design, the reusability of teaching materials and of the related whole knowledge structures. The latter represents an innovative e-learning solution able to support teachers and instructional designers to model educational domains knowledge, users’ competences and preferences by a semantic approach in order to create personalized and contextualized learning activities and to allow users to communicate, to cooperate, to dynamically create new content to deliver and information to share as well as enabling platform for e-learning 2.0.

LIA: An Intelligent Advisor for e-Learning

Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, till now very few systems were able to leave academic labs and be integrated in real commercial products. One of this few exceptions is the Learning Intelligent Advisor (LIA) described in this paper, built on results coming from several research projects and currently integrated in a complete e-learning solution named IWT. The purpose of this paper is to describe how LIA works and how it cooperates with IWT in the provisioning of an individualized and personalized e-learning experience. Results of experimentations with real users coming from IWT customers are also presented and discussed in order to demonstrate the benefits of LIA as an add-on in on-line learning.

Design patterns for secure virtual organization management architecture

The work presented in this paper describes an architecture for a secure Virtual Organization Management framework. This work is taking place in the BEinGRID EU project, which aims to advance the take up of Grid technologies in the business domain by conducting a number of business experiments and in parallel producing a number of components.

Adaptive Feedback Improving Learningful Conversations at Workplace

This work proposes the definition of an Adaptive Conversation-based Learning System (ACLS) able to foster computer-mediated tutorial dialogues at the workplace in order to increase the probability to generate meaningful learning during conversations. ACLS provides a virtual assistant generating adaptive feedbacks, in the form of recommendations, for the conversation partners. The concepts extracted from the conversation texts trigger the recommendations, while queries on the organizational knowledge, represented by means of Semantic Web technologies, generate their content. Lastly, the Fuzzy Formal Concept Analysis is exploited to conceptualize domain knowledge.

Unlocking Serendipitous Learning by Means of Social Semantic Web

Serendipitous Learning is the learning process occurring when hidden connections or analogies are unexpectedly discovered, mostly during searching processes (for instance on the Web) which are typical for informal learning activities, especially accomplished at the workplace context. Moreover, serendipitous processes have high probability to occur in the contexts where learners have high autonomy, more chances to intervene in different activities and to interact with resources and people. This paper proposes an approach based on the Social Semantic Web vision to sustain and improve Serendipitous Learning. The proposed approach considers two connected ontology layers to model knowledge by using several SemanticWeb vocabularies like SIOC, Dublin Core, SKOS, and so on. The SKOS role is particularly relevant because it allows connections among heterogeneous resources, also across multiple communities. The proposed approach models the above-mentioned connections at the conceptual level and facilitate learners in discovering them and following unexpected paths.

A Recommender System for Learning Goals

The aim of a recommender system is to estimate the utility of a set of objects belonging to a given domain, starting from the information available about users and objects. Adaptive e-learning systems are able to automatically generate personalized learning experiences starting from a learner profile and a set of target learning goals. Starting form research results of these fields we defined a methodology to recommend learning goals and to generate learning experiences for learners of an adaptive e-learning system.