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Towards the transition to blended and remote education, evaluating the levels of students’ digital competence and designing educational programs to advance them is of paramount importance. Existing validated digital competence scales usually ignore either important digital skills needed or new socio-technological innovations. This study proposes and validates a comprehensive digital competence scale for students in higher education. The suggested instrument includes skills of online learning and collaboration, social media, smart and mobile devices, safety, and data protection. The scale was evaluated on a sample of 156 undergraduate and postgraduate students just before and at the beginning of the COVID-19 crisis. The final scale is composed of 28 items and six digital competence components. The evaluation study revealed valid results in terms of model fit criteria, factor loadings, internal validity, and reliability. Individual factors like the students’ field of study, computer experience and age revealed significant associations to the scale components, while gender revealed no significant differences. The suggested scale can be useful to the design of new actions and policies towards remote education and the digital skills’ development of adult learners.

Artificial intelligence (AI) is forcing a dramatic transformation of the methods by which we acquire knowledge and engage in collaborative learning. Although there are several studies on how AI can support collaborative learning, there are no published studies examining how students can actually collaborate among themselves while interacting with AI tools. For this study, thirty postgraduate students were organized into teams of three, and each team developed a project mainly exploiting responses from ChatGPT, Google Gemini, and MS Copilot, as well as the internet and class resources. Each team selected a specific internet of things (IoT) application area and described the technologies and real-world cases in this area. Then, each team delivered a report with the full description of their project and their interactions with these generative AI (GenAI) tools and presented their work in class. Additionally, students answered an online questionnaire with closed- and open-ended questions and participated in focus group discussions. Members of each team collaborated to design prompts using five suggested modes of collaboration. Eventually, half of the students exploited all five collaborative modes, but they mostly liked and preferred three of these collaborative modes. On average, teammates initially disagreed 24% of the time but eventually reached an agreement. Students appreciated GenAI tools for their quick and well-structured responses, natural communication style, broad subject coverage, as well as their ability to simplify complex topics and support personalized learning. However, they expressed concerns about GenAI tools’ inaccurate and inconsistent responses and identified key risks, such as passive learning, over-dependence, outdated information, and privacy issues. Finally, students recommended that GenAI tools should provide a shared and well-organized discussion space for collaborative prompt asking, allowing all team members to simultaneously view each other’s prompts and the tool’s responses. They also advised source verification and proper training to ensure these tools remain supplementary rather than primary learning resources.

The integration of augmented reality (AR) in education is promising since it enhances teaching and offers more engaging and appealing learning experiences. Teachers can have a catalytic role towards the adoption of AR in education; therefore, their perspectives with regard to AR in teaching and learning are very important. The current study explores teachers’ views on the integration of AR in education through an open-ended questionnaire that has been answered by 93 educators worldwide. A set of digital skills that can support student-centered pedagogies in an appropriate infrastructure are the main requirement for effective teaching with AR. Among the perceived benefits and opportunities are interactive teaching and learning, increased interest and engagement, better understanding of complex concepts. As barriers, participants reported the lack of AR educational applications, the cost of buying and maintaining AR equipment and resources, the lack of teachers’ and students’ digital skills, classroom management issues, and security and ethical issues. Moreover, survey participants highlighted the need for raising teachers’ awareness for the added value of AR in education and the need for teachers’ continuous professional development. Implications and future research recommendations on the integration of AR in education are discussed.

The literature provides rich evidence on students’ levels of digital skills as well as on their frequency of Internet and social media use. Several studies have examined the relationships between social media use and academic achievement. However, there are not any studies investigating the relationships between social media use and digital skills of higher education students. To fill this research gap, this study examines the links between the frequency of social media use and students’ digital skills. The survey was conducted with 155 university students in Greece. The instrument on six digital skills components was evaluated in terms of reliability and consistency. The research findings reveal a strong positive association between the use of YouTube and students’ digital skills on content evaluation and protection. Age and educational level differences were noted in several digital skills components, whereas age and gender were related to the frequency of Instagram use. The main conclusion is that the generic use of Facebook and Instagram does not affect students’ digital skills. However, combined literature evidence implies that when social media are used for educational purposes, they might influence students’ perceived levels of digital skills. Implications and limitations are discussed in the study.

Important variables related to transfer information & communication technologies (ICT) training include the individual’s perceived motivation to learn, motivation to transfer, and intention to transfer the ICT training. Most previous studies investigate the transfer of ICT training and its application in the daily teaching practice by ordinary teachers, usually neglecting the important population of the teachers’ trainers. These teachers’ trainers receive advanced ICT training before start training their colleagues. Therefore, the main purpose of this study is to investigate the teachers’ trainers’ transfer of ICT training analyzing the structural relationships of their afore-mentioned variables with their gender, ICT self-efficacy, and a set of ICT individual factors. The study employed structural equation modeling using data collected from 117 teachers’ trainers in primary and secondary education who participated in a national ICT Transfer Training Programme for teachers’ trainers in Greece. The results reveal strong associations between ICT-related self-efficacy and transfer training measures. Both gender and ICT factors cause significant differences in the levels of their ICT self-efficacy measures. ICT expertise and gender highlight significant relationship paths in the model, while gender seems to play a moderating role as well.

This study investigated how undergraduate students collaborated when working with ChatGPT and what teamwork approaches they used, focusing on students’ preferences, conflict resolution, reliance on AI-generated content, and perceived learning outcomes. In a course on the Applications of Information Systems, 153 undergraduate students were organized into teams of 3. Team members worked together to create a report and a presentation on a specific data mining technique, exploiting ChatGPT, internet resources, and class materials. The findings revealed no strong preference for a single collaborative mode, though Modes #2, #4, and #5 were marginally favored due to clearer structures, role clarity, or increased individual autonomy. Students reasonably encountered initial disagreements (averaging 30.44%), which were eventually resolved—indicating constructive debates that improve critical thinking. Data also showed that students moderately modified ChatGPT’s responses (50% on average) and based nearly half (44%) of their overall output on AI-generated content, suggesting a balanced yet varied level of reliance on AI. Notably, a statistically significant relationship emerged between students’ perceived learning and actual performance, implying that self-assessment can complement objective academic measures. Students also employed a diverse mix of communication tools, from synchronous (phone calls) to asynchronous (Instagram) and collaborative platforms (Google Drive), valuing their ease of use but facing scheduling, technical, and engagement issues. Overall, these results reveal the need for flexible collaborative patterns, more supportive AI use policies, and versatile communication methods so that educators can apply collaborative learning effectively and maintain academic integrity.

The OpenLang Network platform is a sustainable online environment designed to support language learning, intercultural exchange, and open educational practices across Europe. This paper presents the conceptual framework and design of an AI-enhanced OpenLang Network platform, in which Generative AI is embedded across all language learning services offered by the platform. The integration of Generative AI transforms the placement tests offered by the platform into adaptive diagnostic tools, extends the platform’s tandem language learning service through AI-mediated conversation, and enriches the open educational resources of the platform through automated adaptation, translation, and content generation. These innovations collectively reposition the OpenLang Network platform as a dynamic, learner-centred, and sustainable ecosystem that unites human collaboration with AI-powered personalisation. Through a pedagogically informed integration of Generative AI, the case of the OpenLang Network platform demonstrates how AI can enhance openness, collaboration, and personalisation in language learning.

As our society increasingly relies on digital platforms for information, the spread of fake news has become a pressing concern. This study investigates the ability of Greek and Portuguese Instagram users to identify fake news, highlighting the influence of cultural differences. The responses of 220 Instagram users were collected through questionnaires in Greece and Portugal. The data analysis investigates characteristics of Instagram posts, social endorsement, and platform usage duration. The results reveal distinct user behaviors: Greeks exhibit a unique inclination towards social connections, displaying an increased trust in friends’ content and investing more time on Instagram, reflecting the importance of personal connections in their media consumption. They also give less importance to a certain post’s characteristics, such as content opposing personal beliefs, emotional language, and poor grammar, spelling, or formatting when identifying fake news, compared to the Portuguese, suggesting a weaker emphasis on content quality in their evaluations. These findings show that cultural differences affect how people behave on Instagram. Hence, content creators, platforms, and policymakers need specific plans to make online spaces more informative. Strategies should focus on enhancing awareness of key indicators of fake news, such as linguistic quality and post structure, while addressing the role of personal and social networks in the spread of misinformation.

This study investigates the psychological, educational, and technological difficulties faced by primary education students with special needs during online teaching. An interpretative phenomenological analysis was used for the qualitative analysis of data obtained through semi-structured interviews with twenty-two (22) teachers in primary education at a European country. The results revealed that their students showed negative emotions and behaviour. Those diagnosed with autism and learning disabilities had difficulty concentrating in class, while those with sensory disabilities had epileptic instances. Students with mild mental retardation in particular found it difficult to use digital tools. Many problems, however, are due to the lack of infrastructure and digital skills, as well as proper preparation of teachers for online teaching. Therefore, students and teachers should be equipped with the necessary digital skills, specialised digital tools and accessible open educational resources (OER) in order to effectively participate in online education.

The aim of this study was to investigate STEM teachers’ attitude towards STEM Distance Teaching (DT), as well as their perceived barriers and training needs. A mixed survey was conducted on 158 STEM teachers in secondary education who taught their courses fully online due to COVID-19. The results revealed that STEM teachers perceive STEM DT quite positively, but their attitude can be affected by several factors, such as the efficiency of the schools’ digital infrastructure, as well as their gender, age, and STEM teaching subject. The qualitative thematic analysis identified several barriers to efficiently applying STEM DT, including the (i) lack of students’ interaction and engagement, (ii) inefficiency of digital infrastructure, (iii) lack of students’ and teachers’ digital skills, (iv) lack of space/equipment, and (v) increased teaching workload. The generated themes of training needs highlighted the need for targeted and adjusted training to every STEM discipline, as well as training on DT tools and pedagogies. Finally, the results indicated the STEM teachers’ need for psychological support and consulting.