Massive open online courses (MOOCs) provide hundreds of students with teaching materials, assessment tools, and collaborative instruments. The assessment activity, in particular, is demanding in terms of both time and effort; thus, the use of artificial intelligence can be useful to address and reduce the time and effort required. This paper reports on a system and related experiments finalised to improve both the performance and quality of formative and summative assessments in specific data science courses. The system is developed to automatically grade assignments composed of R commands commented with short sentences written in natural language. In our opinion, the use of the system can (i) shorten the correction times and reduce the possibility of errors and (ii) support the students while solving the exercises assigned during the course through automated feedback. To investigate these aims, an ad-hoc experiment was conducted in three courses containing the specific topic of statistical analysis of health data. Our evaluation demonstrated that automated grading has an acceptable correlation with human grading. Furthermore, the students who used the tool did not report usability issues, and those that used it for more than half of the exercises obtained (on average) higher grades in the exam. Finally, the use of the system reduced the correction time and assisted the professor in identifying correction errors.

Online proctoring generally refers to the practice of proctors monitoring an exam over the internet, usually through a webcam. This technology has gained relevance during the current COVID-19 pandemic, given that the social distance owing to health reasons has consequently led to the switching of all learning and assessment activities to online platforms. This paper summarises the available state-of-the-art of commercial proctoring systems by identifying the main features, describing them, and analysing the way in which different proctoring programs are grouped on the basis of the services they offer. Furthermore, the paper reports on two case studies concerning online exams taken with both automated and human proctoring approaches. The outcomes from state-of-the-art approaches and the experience gained by the two case studies are then summarised in the conclusion, where the need for an organisational effort in loading photographs that can be used to easily recognise student faces, and using an automated online proctoring program to support manual proctoring have been suggested.

On 6 April 2009, an earthquake occurred in Abruzzo, a small region in the middle-east of Italy. Its chief town, L'Aquila, was the epicenter. We carried out an observational analysis to evaluate the potential association between the earthquake and the rate of cardiovascular and cerebrovascular admissions of the residents in the province of L'Aquila. We used administrative discharge data, extracting all admissions made from 6 April to 31 July 2008 (pre-earthquake control period) or from 6 April to 31 July 2009 (post-earthquake period), assigned to diagnosis-related groups (DRGs) related to cardiovascular or cerebrovascular diseases. The overall number of hospitalizations for cardio- or cerebrovascular diseases by residents in L'Aquila before and after the earthquake was 10,833. In the whole region, the hospitalization rate was slightly lower in 2009 (-0.9%), whereas only in the local health unit (LHU) of L'Aquila it showed an increase by +13.2% (P < 0.01), essentially due to cardiovascular diseases (+21.9%) in elderly people (+26.9%; P < 0.01). The proportion of the main comorbidities in the admissions for cardiovascular diseases of the residents in L'Aquila significantly increased (P = 0.03), but no significant differences could be observed for each comorbidity separately. Our study supports previous findings of an association between earthquakes and an increase in cardiovascular diseases in the elderly.

The aim of this study was to investigate the injury patterns and the hospitalizations of patients who were admitted to hospital following the 2009 earthquake in the city of L’Aquila, Central Italy. To the best of our knowledge, this is the first study to analyze the patterns of earthquake-related injuries in Italy. We reviewed the hospital discharge data of 171 patients admitted to hospital within the following 96 h from the mainshock. This is an observational and descriptive study: We controlled for variables such as patient demographics, primary and secondary ICD-9-CM (International Classification of Diseases) diagnosis codes in order to identify the multiple injured patients, main type of injury that resulted in the hospital admission, discharge disposition, and average length of stay (LOS). Seventy-three percent of the 171 patients were admitted to hospital on the first day. Multiple injuries accounted for 52% of all trauma admissions, with a female to male ratio of 63% versus 37%. The most common type of injuries involved bone fractures (46.8%), while lower extremities were the most frequently affected sites (38.75%). The average LOS was 12.11 days. This study allows the evaluation of the impact of earthquake-related injuries in relation both to the health needs of the victims and to the use of the health care resources and assistance.

According to the most recent deaf literature, playing with digital games shows positive effects on deaf children's specific skills. The goal of this paper is to present the first guidelines for the design of games for deaf children. Our review of deaf literature, briefly sketched in the paper, considers such abilities as well as deaf children's preferences most relevant for the design of digital games for them. Literature findings are then used to compile the guidelines, with accompanying usage examples. Guidelines and literature findings are correlated at the end of this paper.