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Rare diseases pose particular challenges to patients, families, caregivers, clinicians and researchers. Due to the scarce availability of information and their disintegration, in recent years we are witnessing a strong growth of patient communities on social platforms such as Facebook. Although the data generated in this context are of high value, the currently existing ontologies and resources tend to ignore them. The work presented in this paper studies how to extract knowledge from the large availability of unstructured text generated by the users over time, in order to represent it in an organized way and to make logical reasoning above. Starting from the awareness of the need to integrate different methodologies in complex domains, the research shows a combined use of Text Mining and Semantic Web techniques. In particular, we describe the basis of a novel approach for Knowledge Graph Learning with the aim of introducing a patient-centered vision into the world of Linked Open Data. By identifying and representing correlations between concepts of interest, we show how it is possible to answer patients’ questions and provide them with an additional tool for decision making. The outlined contribute minimizes costs through automatic data retrieval and increases the productivity of investigators.

In today’s Industry 4.0 environment, recruiting, training, and retaining highly qualified ICT-ready professionals remains a problem for many organizations in-cluding educational, governmental, healthcare, and business organizations. Through an in-depth literature review and syntheses, 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?” In particular, the pa-per analyses the major obstacles that need to be overcome in order to direct edu-cational aspirations towards STEM education pathways, so that the demand for more people trained in ICT can be met, describing the inequalities of opportuni-ty and the transformations, both internal and external, to which higher education institutions are called to undergo. To accomplish this broad research goal, we in-tend to utilize a grounded theory approach, utilizing rich data that informs the development of frameworks that address the ICT human capital shortage as well as encouraging equitable, inclusive and purposeful methods to diversify ICT-qualified workers. Data that informs this work will be drawn from varied organ-izations, including HEI, business, government, and healthcare and education.

A variety of technology enhanced teaching strategies and learning activities have been applied in education, including assessment mechanisms. In this paper, we aim to examine the extent to which peer assessment promotes deep learning and favours the incremental learning of the concepts presented throughout a traditional introductory programming course. In particular, we want to examine how the enactment of the peer-assessor and peer-assessee roles is associated with students’ learning improvements, after enacting recip-rocal peer assessment. We illustrate a case study based on a novel web-based peer assessment tool to improve engagement and learning outcomes in a pro-gramming course. We want to assess whether programming skills are growing through peer review and whether exposure to different programming tech-niques is helpful to students. One of the most remarkable findings of our ex-perience was that students reported that assessing others’ work was an ex-tremely valuable learning activity.

Digital technology is increasingly central to our lives, particularly among young people. However, a severe concern remains about the existing digital gender gap: despite the demand for ICT professionals is more and more increasing, women are under-represented in the ICT sectors and their low participation rates can be traced back to school years with internalised gender stereotypes. The pre-sent work explores the summer camp “Digital girls” case study with the aim of involving women from an early age in traditionally male sectors. The summer camp is organized by the engineering and computer science departments of two Italian universities that from 2014 have decided to undertake work to dissemi-nate and raise awareness of ICT issues to girls in high school. The summer camp offers a protected context in which participants learn the principles of computer programming and are exposed to workshops on social networks, free software, cybersecurity, and interact with female ICT experts. The paper focuses on the analysis of data relating to the correlation between previous programming expe-rience and the choice of university studies and social perceptions of the work environment.