This work analyses the use of artificial intelligence in education from an interdisciplinary point of view. New studies demonstrated that an AI can “deviate” and become potentially malicious, due to programmers’ biases, corrupted feeds or purposeful actions. Knowing the pervasive use of artificial intelligence systems, including in the educational environment, it seemed necessary to investigate when and how an AI in education could deviate. We started with an investigation of AI and the risks it poses, wondering if they could be applied also to educative AI. We then reviewed the increasing literature that deals with the use of technology in the classroom, and the criticism about it, referring to specific use cases. Finally, as a result, the authors formulate questions and suggestions for further research, to bridge conceptual gaps underlined by lack of research.
In this article we analysed the association between psychopathic traits manifested at early age and behavioral problems in adolescents with an extension of correspondence analysis. The used technique allows to verify the relationship between row and column variables in a two-way contingency table. The data are obtained submitting to a sample of 689 high school students two questionnaires: The Inventory of Callous-Unemotional Traits (ICU) and The Strengths and Difficulties Questionnaire (SDQ)). Founding has an important pedagogical impact. The educational professionals, who spend most of the day with the kids, hardly can identify the Callous-unemotional traits but, at same time, could identify easily behavioral problems allowing the implementation of early treatments or the use of pedagogical strategies for young people that could have a high risk of psychopathic traits.
BACKGROUND: In March 2020, with the scope to reduce the spread of COVID-19, most national governments around the world canceled in-person education and moved to online learning. Therefore, teachers and students had to adapt a new way of teaching. Most of Italian teachers never had such an experience before and encountered difficulties in effectively carrying out this process on their own. Difficulties that can naturally increase anxiety and stress, leading, in situations perceived as extreme situations, to burnout syndrome. OBJECTIVES: This paper endeavored to verify levels of job stress and burnout of Italian teachers caused by the COVID-19 pandemic using the validate Maslach Burnout Inventory-General. This study aimed to measure the association among the three main dimensions of burnout and the variables of teachers’ personal and working lives that changed due to COVID-19. METHOD: The aim of this paper was to verify burnout state and to measure the association among the three dimensions of burnout and the personal and working lives of Italian teachers using structural equation model analysis. The analysis was conducted in December 2021 and considered the situation in which the Italian teachers (from primary to middle and upper school) are working since March 2020. RESULTS: The results showed that teachers were emotionally exhausted, they did not feel able to fully fulfill their task towards the students. This involved a high absenteeism, a lower quality of work performance and the impossibility of making an objective evaluation of the students with an inevitable flattening of the class level. In contrast, the study shows that teachers who experienced few problems had relatively low levels of burnout. CONCLUSION: The findings brought out some proposals to reduce the risk of burnout and increase the individual well-being of schoolwork organization with positive effects on the lives of students: to strengthen social identity, to avoid a full-time online connection, to promote a psychological support service and to promote resilience training.
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