The relationship between adolescents and digital technologies is a widely debated topic, often framed in terms of prohibitionist approaches on one hand, and digital empowerment on the other. However, as digital engagement becomes an integral part of everyday life, fostering critical thinking and responsible media use appears more effective than restrictive strategies. This paper presents a Media Education project aimed at empowering adolescents in their use of digital tools. The educational intervention was conducted in a lower secondary school, involving 238 students, and included interactive classroom sessions, debates, and playful activities such as video games and avatar creation. The pedagogical approach prioritised active student participation over traditional top-down instruction. A final questionnaire assessed both student satisfaction and the skills acquired. Results from correlation analysis and MANOVA indicate that interactive and playful activities significantly contributed to overall course satisfaction. These findings support recent theories suggesting that playful, participatory learning environments enhance students’ motivation and interest, promoting their immersion in educational contexts.
The unregulated proliferation of hate speech, defined as any expression of beliefs that incite hatred, discrimination, or violence against individuals or social groups (Fortuna & Nunes, 2018), in social media has called into question the efficacy of removal-based content moderation and has driven the need to explore alternative approaches. AI-generated counterspeech could be a scalable and cost-effective intervention (Ashida & Komachi, 2022). Counterspeech is defined as a direct response to hate speech aimed at refuting or undermining it (Wachs et al., 2023). Research in this growing field is fragmented across computational linguistics and social sciences, lacking systematic methods to define and evaluate effective counterspeech, revealing a gap between AI's technical capabilities and evidenced social impact. This review aims to examine evidence from these two fields to identify the differing conceptualizations of counterspeech, map the collaborative approaches used for counterspeech generation and evaluation, and examine the alignment between stated research goals (e.g., reducing hate speech in digital environments) and the operational measures employed to identify them. Only a few studies evaluate counterspeech in real-world interactive settings or measure long-term impact. We identify some key misalignments, such as the reliance on text metrics and human or artificial annotators as proxies for complex social interventions, instead of integrating psychological and behavioral measures. We propose a linked approach to counterspeech that links theoretical frameworks, procedures, measurements and research goals from the perspective of both psychology and computational linguistics to identify promising directions for future interdisciplinary collaboration and more socially meaningful AI-assisted interventions.
As artificial intelligence (AI) systems prove their utility in various aspects of daily life, their potential risk to societal progress is still debated given the increasing rates of their discriminatory behaviors. Some preliminary evidence suggests that the same discriminatory behavior may be perceived differently when performed by a person or an AI system, yet it remains largely unknown how people perceive and respond to AI’s discriminatory behaviors. Through two studies conducted in Türkiye (Study 1) and the United States (Study 2), participants read about either AI’s discrimination against women, humans’ discrimination against women, or an unrelated topic, and indicated the degree of perceived threat to women, willingness to participate in collective action for women’s equal treatment, and their attitudes toward women and feminists. In both cultures, discrimination was perceived to be less threatening to women when committed by AI compared to a human, yet collective action intentions and attitudes toward women and feminists did not differ across conditions. Notably, American men consistently reported less favorable attitudes toward women after reading about discrimination. These findings suggest discrimination by AI requires special attention and underline the importance of investigating the influence of technologies on sustaining intergroup inequality.
Online hate speech against school students is increasing globally. This paper examines how digital literacy programmes and school interventions can help students aged 10 to 18 recognise, resist and respond to hate speech in online spaces. The study reviews research published between the years, 2020 and 2026. It expatiates the causes and effects of online aggression among adolescents. Qualitative data gathered through structured thematic discussions with 16 educationists drawn from government, aided and unaided schools across the State of Kerala. Inductive thematic analysis of these discussions informs the practical approaches presented, drawing on Social Emotional Learning (SEL) and critical media literacy frameworks. The paper highlights several initiatives used in Kerala schools. These include the KITE fake news detection curriculum, the State Council of Educational Research and Training (SCERT) value education framework, the Student Police Cadet programme and the Suraksha Mitram support system. Two conceptual models guide the discussion. The first model explains how films, games and digital media can increase hostility and aggressive behaviour among students. The second model presents a four-component resilience framework that helps students develop responsible digital behaviour and stronger critical thinking. This framework is explicitly exploratory and normative in character: it synthesises existing evidence and programme documentation into a prescriptive architecture designed for iterative evaluation and refinement. The paper recommends a multi-level prevention approach. It focuses on student skill development, positive peer influence, teacher training, family participation and clear school policies. The approach suits government, aided and unaided schools in Kerala.
The research addresses politically motivated hate speech in Albanian-language triggered by recent political events. An evident reactive hate dominates the comment section of political news outlet in social media, so that one is moved to detect the underlying partisan motivations of this hostility. Some comments provide answers and others suggest reasons that reflect a spreading animosity towards politics and its traditional or emerging actors. Robert Entman’s frame paradigm offers a theoretical foundation to detect hate speech embedded in mediated interaction in digital platforms. This research combines framing with interpretative insights derived from critical discourse analysis to capture deeper causal logics embedded in frames as a communicating text. Findings reveal that politically motivated hate speech is often normalized and legitimized in digital interaction when it is frames around some thematic issues such as national identity, moral values, economic development. Hate speech targets include political actors and institutions, collective outer groups in some cases. Recurring narrative patterns highlight responsibility attribution and negative moral evaluation, which reinforce shared perceptions about political legitimacy, and underlying legacy. The research suggests that a context-sensitive approach when addressing hate speech detection helps to understand mechanisms of its construction in order to design preventive initiatives.
This article analyses the role of art and art education as practices of poeticising existence capable of countering the logic of hate and violence in contexts marked by alienation, trauma and social disharmony. Drawing on the theoretical contribution of Michèle Petit, in dialogue with Gaston Bachelard's poetics of rêverie and Hartmut Rosa's sociology of resonance, the article interprets hate as an expression of a silent and discordant relationship with the world and with others. In this context, art is taken as a device of resonance, capable of reactivating speech, imagination and the ability to attribute meaning to experience. From a methodological point of view, the research adopts a theoretical-interpretative approach integrated with case studies, identifying and analysing artistic and educational practices operating as forms of prevention, cultural resistance and therapy. The cases discussed — from the pedagogical atelier, artivism and street art, to artistic practices of trauma processing in war contexts — show how art can transform wounded objects, places and materials into symbolic spaces of reconciliation and healing. Importance is given to the role of the artist and art educator as a passeur: a cultural mediator who does not transmit predefined contents but creates the conditions for a symbolic transition towards forms of subjectivation, emancipation and the construction of bonds. The article concludes by arguing that the poeticization of existence today represents a fundamental educational and cultural resource for imagining and practising a culture of peace.
Public debates on hate speech are often framed in terms of regulation, moderation, or prevention, positioning hostile content primarily as a pathological deviation to be removed from digital environments. This article proposes a different perspective, arguing that hate speech can be approached as a critical object of analysis for contemporary citizenship education. Building on the concept of hate literacy, the paper conceptualizes hostile online discourses as pedagogically relevant artifacts that both reflect and actively shape models of citizenship, participation, and belonging. Rather than interpreting online hostility as an automatic outcome of digital technologies, the article situates hate speech within a dynamic interplay between intentional political actors, platform infrastructures, and hegemonic cultural narratives. From this perspective, hate speech functions as a form of informal civic education, contributing to a hidden curriculum through which norms, hierarchies, and exclusions are learned and normalized. The paper outlines hate literacy as a core civic competence, understood as the ability to critically read, contextualize, and deconstruct hostile discourses by examining their discursive, technological, and political dimensions. By reframing violence and hostility as lenses through which power relations and civic subjectivities can be analyzed, the article advances a pedagogical framework that moves beyond moral condemnation toward critical engagement. The contribution concludes by discussing the implications of this approach for citizenship education in platformed societies.
Over the last twenty-five years, hate speech has become a key category in international public policies, while digital environments have increasingly promoted the rise of the broader and more operational category of toxicity. This article argues that the shift from hate speech to toxic content should not be understood as a merely terminological substitution, but as a semantic and governmental transformation in the way discursive harm is identified, measured, and managed. The paper first reconstructs the historical and normative genealogy of hate speech, then examines the psychological, computational, and platform-based genealogy of toxicity, and finally compares the two frameworks through their conceptual, operational, and political implications. Particular attention is paid to the agency of platforms, algorithmic governance, content moderation, and the tension between discriminatory harm and conversational harm. The article suggests that toxicity offers scalability and technical operability, but may also contribute to the depoliticization of online harm if detached from histories of discrimination, protected characteristics, and asymmetries of power.
In recent years, many new technologies have been used to enhance the learning outcomes of learners in online learning. Video annotation is one of these new technologies which is an innovative way to make learning more interactive and engaging. It can accommodate different learning styles by turning passive video-watching into an active learning experience. This research aims to evaluate the effectiveness of an e-Learning platform incorporating a Video Annotated Technique. Learners can pinpoint challenging parts of educational videos and then receive personalised explanations from their teachers. The primary purpose of these annotations is to clarify and provide thorough explanations of complex topics, ultimately improving understanding and making preparation for final examination tests easier. This paper presents a new personalization approach by managing the learners’ annotations. Furthermore, it offers a video annotation tool incorporated into an e-Learning environment. This tool was tested on a sample of students, and the experimental results demonstrated a significant positive impact on learners’ performance.
Migration has become one of the most contested issues in contemporary European public debate, where news coverage often frames migrants through the language of border control, legality, and public order. Such securitized representations may contribute to keeping migrants at a symbolic distance from audiences, presenting them less as socially embedded individuals and more as categories to be regulated or governed. While previous research has examined media representations of migration and online hate speech separately, less is known about how migration-related news content is associated with the hostile reactions that can emerge among social media audiences exposed to this content. This study addresses this gap by analyzing migration-related Instagram posts published by eight major Italian news organizations between January 2025 and March 2026, together with the comments they generated. A corpus of 368 news posts and 76,998 user comments was analyzed by combining topic modeling of news posts with automated emotion detection and hate speech classification of user comments to examine how securitized thematic environments are associated with hostile audience responses. The results show that audience reactions were marked by a strong prevalence of negative emotions, with anger emerging as the dominant response across the corpus. This affective profile became more polarized in relation to news posts that framed migration through legal-institutional conflict, return procedures, border enforcement, and NGO-related controversies. In these securitized contexts, audience responses were more strongly concentrated around anger and disgust, and this emotional concentration was accompanied by higher levels of hate speech.
Teachers’ practice is increasingly oriented towards designing and working in Innovative Learning Environments (ILE). In-service teachers’ professional development is being designed coherently, sometimes allowing them to experience learning situations in such environments. Two surveys were designed, and validated, to answer to two main questions concerning teachers’ interests and how they evolve once they know ILEs and have this training experience. To get all the information needed, one survey was filled before taking part in the training experience, and the other one after it. 255 answers were received and analyzed to extract several conclusions. Results indicate that teachers, after the training, became increasingly open to embracing more active, participatory methods, integrating more innovative, immersive and interactive technology. They also showed greater interest in how to zone and plan meaningful learning experiences in such environments. Furthermore, the main topics teachers wish to receive further training on relate to designing appropriate learning experiences and selecting suitable methodologies. These findings suggest that engaging teachers in a training experience within an ILE serves as a catalyst for professional development in these topics. The study has implications for both educational administrations and school leaders promoting ILEs.
In recent years, artificial intelligence (AI) has been rapidly developing, and the issues concerning the use and implementation of AI in education and science are becoming increasingly relevant. Meanwhile, the effectiveness of introduction of digital technologies, including AI, into education largely depends on digital competence, the level of knowledge in this area, as well as the attitude of educators towards these technologies. In this regard the aim of the study was to identify the peculiarities of the attitude of students-pre-service teachers in different training fields towards artificial intelligence and their experience of its use in education. The study involved 249 bachelor students in Teacher education of Kazan (Volga Region) Federal University. The study showed that, in general, students show interest in the use of digital tools for both educational and personal purposes. In teaching practice, about 40% of students have experience in using AI at the stage of planning and constructing lessons. Students from different training fields identify the benefits of using AI in different areas of education and set different goals for the use of AI in lessons design. At the same time, pre-service teachers critically assess the possibilities of AI and more than 80% of them point out possible risks in the use of AI in education. About 60% of the respondents agree on the need to adapt to changes brought on by AI. The results of the study can be used in designing the students' curricula and planning their learning process using digital tools, including AI.
The interaction between teachers and e-learning systems plays a crucial role in the effectiveness and quality of online and blended education in secondary schools. This paper examines how teachers influence the use of e-learning platforms through their digital competencies, experience in creating educational materials, and perceptions of the usefulness of information and communication technologies, as well as how e-learning systems shape teaching practices and instructional strategies. The research is based on a quantitative study conducted among secondary school teachers, using a structured survey questionnaire and statistical methods including factor analysis and multiple regression analysis. The findings indicate that teachers’ actual and perceived IT knowledge and their experience in developing digital educational materials significantly affect the intensity and scope of e-learning system usage. The results further highlight the need for systematic professional development of teachers to enhance effective interaction with e-learning systems. The study provides empirically grounded insights that can support the design of teaching strategies and institutional policies aimed at improving the quality of e-teaching in secondary education.
Generative AI introduces complexity by offering potential support for human skills development, while also generating noise and false information in a postdigital context. Grounded in a Vygotskian perspective, this study explores the combined use of argument mapping (AM) and ChatGPT as mediational tools for developing argumentative skills as a proxy for critical thinking in higher education. These tools are conceptualized as socio-technical assemblages providing double stimulation within students’ Zone of Proximal Development (ZPD), addressing how multimodal texts and AI mediate comprehension of information (CoI) and critical thinking (CT). Adopting a case study approach with a quasi-experimental design, the research involved 17 female undergraduate students from the University of Padua, divided into three groups: G1 working with analog texts, G2 with multimodal texts, and a control group interacting only with ChatGPT (G3). Chatbot interactions were analyzed to explore its potential to support reflection and personal information re-elaboration. Results indicate improvements in comprehension and critical thinking, especially in the multimodal group (G2). G1 achieved weaker outcomes, possibly due to limited external stimulation. G3 outperformed G1 but showed stable yet comparatively lower results in advanced argumentative reworking despite a positive median. Overall, AM seems to support text comprehension and meaning reconstruction, while multimodality fosters the integration of multiple perspectives. Generative AI can further support critical engagement and understanding of AI systems when embedded in a structured pedagogical design rather than used “in the wild”.
The vast collection of paper documents and books stored in university archives worldwide represents a significant, yet often inaccessible, cultural heritage. To address this, the University of Genoa, Italy, is digitizing a variety of materials, including books, manuscripts, archival documents, and museum-related items. Making this heritage accessible requires providing alternate descriptions, metadata, and transcriptions, especially for ancient texts where OCR is ineffective. This paper presents the design of a transcription system for the University Museum System (SMA-UniGe), which is currently under development, featuring user-friendly interfaces and engagement techniques. The system leverages gamification to turn transcription into an engaging experience, aligning with the University’s mission to promote public engagement and contribute to social, cultural, and economic development through knowledge sharing.
With reference to the theory of the Zone of Proximal Development, the aim of this paper is to describe an intelligent tutoring model capable of learning and reproducing intervention rules to make learning experiences based on the use of dynamic concept maps more effective. The work starts from DCMapp, a software application for the creation and navigation of dynamic concept maps. DCMapp allows to build maps, draw nodes and arcs, upload multimedia contents and manage the dynamic visualization of concepts. The use of DCMapp has been shown to improve study times and student learning outcomes. The paper proposes the integration of an intelligent tutoring system based on Vygotsky’s theory of the Zone of Proximal Development. This system suggests actions to students to maintain learning within their Zone of Proximal Development, avoiding boredom and confusion. It is trained through the observation of a human tutor and uses artificial neural networks to predict future actions. The goal is to ensure effective and personalized learning, adapting the difficulty of the activities to the cognitive and emotional abilities of the learners.
The public availability of the Generative Artificial Intelligence (Gen-AI) tools, such as ChatGPT, led to diverse reactions in society. In higher education, these emerging technologies have brought several challenges, particularly with regard to ethical considerations, assessment frameworks, and new paradigms in teaching and research practices. In this article, we intend to explore the issues related to integration and ways of using the Gen-AI tools in higher education, especially in initial teacher education, and the implications of this use for education policies. A qualitative approach was used with recourse to non-participant observation and narrative research methods through the analysis of experiences developed in Initiation to Professional Practice curricular unit of a Master’ in Teaching. It was found that future teachers were able to use the ChatGPT as a tool to plan lessons and create digital educational resources, but the results obtained from its use always need careful and rigorous scrutiny and verification. Developing an entrepreneurial mindset in learning is important to increase creativity, innovation, and adaptability among preservice teachers. One also concludes that it is relevant to address and include issues relating to artificial intelligence in higher education, reflecting them particularly in regulations, legislation, and educational policy.
