http://hdl.handle.net/10071/2100 Mon, 13 Apr 2026 13:11:43 GMT 2026-04-13T13:11:43Z http://hdl.handle.net/10071/35820 Título próprio: Educação transformadora: O projeto #poramoraomar como aprendizagem socioecológica Autoria: Lima, C.; Delfino, D.; Mouro, C. S. L. L. Resumo: Este estudo investiga caminhos para uma educação socioambiental transformadora. A pesquisa qualitativa, com questionários semiestruturados, analisou ações de escolas brasileiras no projeto #PorAmorAoMar, em parceria com a ONU Meio Ambiente por #mareslimpos, voltadas ao enfrentamento do plástico como crise sistêmica. A análise baseou-se na teoria da aprendizagem socioecológica transformadora de Stephen Sterling. Os resultados apontaram uma ampliação na contextualização do tema, apesar dos desafios no enfrentamento à descartabilidade, e indícios de fragilidade nas abordagens críticas e ações continuadas — essenciais à sustentabilidade. Esta pesquisa sinaliza caminhos promissores para a ressignificação da formação docente e dos sistemas escolares. Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/10071/35820 2025-01-01T00:00:00Z http://hdl.handle.net/10071/35772 Título próprio: Prompt assessment for human-AI interaction: Intent, complexity and lay perceptions Autoria: Páez Velázquez, M.; Bobrowicz-Campos, E.; Arriaga, P. Resumo: Large Language Models (LLMs) are democratising access to AI for users with diverse levels of expertise, raising questions about the nature, dynamics, and effects of such interactions, particularly among lay users. Understanding how non-expert users engage with these systems is essential to inform AI literacy frameworks and responsible use guidelines, helping to reduce misinformation and address broader societal implications. To investigate these dynamics, it is first necessary to identify interaction types based on user intent, as well as prompt characteristics such as complexity, appeal, and domain familiarity, given the unprecedented flexibility of LLM use across diverse contexts. However, no categorisation of prompts with comparable complexity levels and demonstrated suitability for lay populations has yet been developed. This categorisation is essential to avoid confounds in the study of human–AI interaction. To address this gap, we applied a three-stage methodological approach. First, we generated prompts and iteratively refined their categories and complexity levels using ChatGPT, all written by the model itself. Second, we conducted a thematic qualitative analysis and curated a pre-set of 34 prompts with comparable complexity, classifying them into two main categories: a) task-oriented and b) reflexive, and two additional control categories; c) both and d) none. Third, we tested these prompts with 28 lay users from different countries through an online survey. For each prompt, participants assessed the category, perceived complexity, how interesting it was, and whether non-experts could easily understand it. Task-oriented prompts achieved a mean category confirmation rate of 62% (Max = 82%), while reflexive prompts reached 52% (Max = 71%). Complexity ratings averaged near the scale midpoint (M = 4.10), similar to interestingness (M = 4.67) and general domain (M = 4.20), indicating that prompts were neither simplistic nor overly demanding, but suitably engaging and accessible for a broad lay population. A final set of 12 prompts with at least 60% category agreement was obtained. This work can contribute to studying prompt categories among lay users of LLM-powered conversational agents, considering intent, complexity, and users’ perceptions of appeal and suitability for a general audience. The final set of prompts provides a resource for advancing research in human–AI interaction, supporting future investigations into trust, emotional responses, and other key constructs in Human Computer Interaction (HCI). Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/10071/35772 2025-01-01T00:00:00Z http://hdl.handle.net/10071/35656 Título próprio: Masculidades criminalizáveis: Gênero nas trincheiras da guerra às drogas Autoria: Meinhardt, Y. M.; Beiras, A.; Oliveira, J. M. de. Resumo: Este ensaio discute a relação entre masculinidades, colonialidade e política antidrogas no Brasil, por meio da articulação entre os estudos críticos à política antidrogas, estudos de gênero e das masculinidades, teoria queer/kuir e estudos decoloniais. Através da análise crítica sobre a criminalização massiva de homens negros promovida pela retórica do envolvimento com tráfico de drogas, argumentamos que a política antidrogas é uma expressão da colonialidade e uma tecnologia de gênero que regula o campo de aparecimento e reconhecimento das identidades através da Guerra às Drogas. Frente à isso, conceituamos a noção de masculinidades criminalizáveis, em referência à experiência racializada de gênero produzida através dos processos de criminalização. Mon, 01 Jan 2024 00:00:00 GMT http://hdl.handle.net/10071/35656 2024-01-01T00:00:00Z http://hdl.handle.net/10071/34717 Título próprio: Life satisfaction and future expectations among young NEETs: A mixed method approach Autoria: Ellena, A. M.; De Luca, G.; Mazzocchi, P.; Rocca, A.; Simões, F.; Marta, E. Resumo: This study examines life satisfaction and future expectations among young NEETs (Not in Education, Employment, or Training) in Italy using a mixed-method approach. Based on a sample of 930 individuals aged 25-29, the research explores both the hedonic and eudaimonic dimensions of well-being. Study 1 employs a binary logit model to analyze the impact of socio-demographic factors, self-efficacy, and trauma-related symptoms (TSC) on life satisfaction. Findings indicate higher life satisfaction among women, caregivers, individuals with higher education, and those from southern regions. Additionally, self-efficacy positively influences well-being, whereas trauma-related symptoms have a negative effect. Study 2 utilizes text mining techniques to examine NEETs’ aspirations, revealing a predominant focus on employment, stability, and family. Gender and regional disparities underscore the need for targeted policy interventions to address psychological and socio-economic barriers. This research highlights the importance of integrated strategies to enhance NEETs’ life satisfaction and future outlook. Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/10071/34717 2025-01-01T00:00:00Z