Search

The knowledge, skills, and abilities that human capital offers create tangible and intangible assets that equip organizations to thrive. In particular, in today’s Industry 4.0 environment, training, recruiting, and retaining highly qualified ICT-ready professionals remains a problem for many organizations including educational, governmental, healthcare, and business organizations. The COVID-19 pandemic revealed the importance of digital assets to our economies, and it is also demonstrating that there is potentially a new digital divide with even worse implications for companies, economies, and society, which is threatening the resilience of business, governance, and society. In this paper, we respond to the question “how can we develop ICT human capital in our global economy in an equitable, inclusive, and purposeful manner such that not organizations thrive, but also to promote social justice and equity in our global economy?”

Deploying ad-hoc learning environments to use and represent data from multiple sources and networks and to dynamically respond to user demands could be very expensive and ineffective in the long run. Moreover, most of the available data is wasted without extracting potentially useful information and knowledge because of the lack of established mechanisms and standards. It is preferable to focus on data availability to choose and develop interoperability strategies suitable for smart learning systems based on open standards and allowing seamless integration of third-party data and custom applications. This paper highlights the opportunity to take advantage of emerging technologies, like the linked open data platforms and automatic reasoning to effectively handle the vast amount of information and to use data linked queries in the domain of cognitive smart learning systems.

The growth of data produced for example by IoT devices has playing a major role in developing healthcare applications able to effectiveness handle the vast amount of information. The challenge lies in representing volumes of data, integrating and understanding their various formats and sources. Cognitive computing systems offer promise for analysing, accessing, integrating, and investigating data in order to improve outcomes across many domains, including healthcare. This paper presents an ontology-based system for the eHealth domain. It provides semantic interoperability among heterogeneous IoT fitness and wellness devices and facilitates data integration and sharing. The novelty of the proposed approach lies in exploiting semantic web technologies to explicitly describe the meaning of sensor data and define a common communication strategy for information representation and exchange.

Peer assessment mechanism is becoming increasingly important in different computer programming courses to give students opportunities to learn from each other, to improve the learning experience and to reach efficient learning outcomes. Nevertheless, new methodological approaches developed to help students in computer programming courses have had to deal with a thorough study of the aspects related to the gender difference in this context. The paper presents a web-based system, which improved students' program skills by reviewing peers' source codes and delivering feedback to peers. The purpose was to provide evidence that peer assessment in computer programming has a positive instructive effect. Moreover, we want to investigate if there is a gender gap in the traditional introductory programming course and how can we use peer assessment principles to reduce it.

In this paper we introduce an update of our work on developing a distance learning environment based on a collaborative bookmark management system approach. We introduce EasyInfo, an hybrid recommender architecture extension, which processes resources to extract concepts (not just words) from the documents using semantic capabilities. Then, the classifi cation, recommendation and sharing phases take advantage of the word senses to classify, retrieve and suggest documents with high semantic relevance with respect to the student and resource models.

The Web provides not only several data sources with useful and relevant information with e-Learning purposes, but also information that is not easy to retrieve. The web of linked data is a repository based on semantic technologies. Several researchers have been oriented to this kind of interoperable e-Learning repositories and establish that the Linked Data approach has the potential to fulfill the e-Learning vision of Web-scale interoperability of e-Learning resources as well as highly personalized and adaptive e-Learning applications. The paper presents an automatic concept extraction system used to improve personalized searching framework. It could be considered as one possible instance of a more general concept concerning the transition from the Document Web to the Document/Data Web and the consequent managing of these immense volumes of data.

The process of summarizing information is becoming increasingly important in the light of recent advances in resource creation/distribution technology and the resulting infux of large amounts of information in everyday life. These advances are also challenging educational institutions to adopt the opportunities of distributed knowledge sharing and communication. The paper describes a summarization system to support tutors in managing student communication and interaction within a learning framework. Results show the adequacy of the system in identifying a good content summarization and then in improving the effciency and effectiveness of the context in which summarization can be integrated.

The paper presents an ontological approach for enabling semantic-aware information retrieval and browsing framework facilitating the user access to its preferred contents. Through the ontologies the system will express key entities and relationships describing learning material in a formal machineprocessable representation. An ontology-based knowledge representation could be used for content analysis and concept recognition, for reasoning processes and for enabling user-friendly and intelligent multimedia content search and retrieval.