The integration of Artificial Intelligence into educational environments is reshaping the way digital resources support teaching and learning, which reinforces the need to understand how prompting strategies can enhance engagement, autonomy, and personalisation. This study examines the pedagogical role of prompt engineering in the transformation of static digital materials into adaptive and interactive learning experiences aligned with the principles of Education 4.0. A systematic literature review was conducted between 2023 and 2025 following the PRISMA protocol, comprising a sample of 166 studies retrieved from the ACM Digital Library and Scopus databases. The search strategy employed the keywords “artificial intelligence” OR “intelligent tutoring systems” AND “e-learning” OR “digital education” AND “personalised learning” OR “academic performance” OR “student engagement” OR “motivation” OR “ethical issues” OR “student autonomy” OR “limitations of AI”. The analysis identified consistent improvements in academic performance, motivation, and student engagement, although persistent limitations remain related to technical integration, ethical risks, and limited pedagogical alignment. Building on these findings, the article proposes a structured prompt engineering methodology that integrates interdependent components including role definition, audience specification, feedback style, contextual framing, guided reasoning, operational rules, and output format. A practical illustration shows that embedding prompts into digital learning resources, exemplified through PDF-based exercises, enables AI agents to support personalised and adaptive study sessions. The study concludes that systematic prompt design can reposition educational resources as intelligent, transparent, and pedagogically rigorous systems for knowledge construction.

This study explores how artificial intelligence can promote accessibility and inclusiveness in digital culinary environments. Centred on the Receitas +Power platform, the research adopts an exploratory, multidimensional case study design integrating qualitative and quantitative analyses. The investigation addresses three research questions concerning (i) user empowerment beyond recommendation systems, (ii) accessibility best practices across disability types, and (iii) the effectiveness of AI-enabled inclusive solutions. The system was developed following user-centred design principles and WCAG 2.2 standards, combining generative AI modules for recipe creation with accessibility features such as voice interaction and adaptive navigation. The evaluation, conducted with 87 participants, employed the System Usability Scale complemented by thematic qualitative feedback. Results indicate excellent usability (M = 80.6), high reliability (Cronbach’s α = 0.798–0.849), and moderate positive correlations between usability and accessibility dimensions (r = 0.45–0.55). Participants highlighted the platform’s personalisation, clarity, and inclusivity, confirming that accessibility enhances rather than restricts user experience. The findings provide empirical evidence that AI-driven adaptability, when grounded in universal design principles, offers an effective and ethically sound pathway toward digital inclusion. Receitas +Power thus advances the field of inclusive digital gastronomy and presents a replicable framework for human–AI co-creation in accessible web technologies.

The integration of Artificial Intelligence (AI) into educational environments is rede-fining how digital resources support teaching and learning, highlighting the need to understand how prompting strategies can enhance engagement, autonomy, and per-sonalisation. This study explores the pedagogical role of prompt engineering in trans-forming static digital materials into adaptive and interactive learning experiences aligned with the principles of Education 4.0. A systematic literature review, conducted under the PRISMA protocol, examined the use of educational prompts and identified key AI techniques applied in education, including machine learning, natural language processing, recommender systems, large language models, and reinforcement learning. The findings indicate consistent improvements in academic performance, motivation, and learner engagement, while also revealing persistent limitations related to technical integration, ethical risks, and weak pedagogical alignment. Building on these insights, the article proposes a structured prompt engineering methodology encompassing in-terdependent components such as role definition, audience targeting, feedback style, contextual framing, guided reasoning, operational rules, and output format. A practical illustration demonstrates how embedding prompts into digital learning resources, exemplified through PDF-based exercises, enables AI agents to facilitate personalised, adaptive study sessions. The study concludes that systematic prompt design can repo-sition educational resources as intelligent, transparent, and pedagogically rigorous systems for knowledge construction.

This study explores how artificial intelligence can promote accessibility and inclusiveness in digital culinary environments. Centred on the Receitas +Power platform, the research adopts an exploratory, multidimensional case study design integrating qualitative and quantitative analyses. The investigation addresses three research questions concerning (i) user empowerment beyond recommendation systems, (ii) accessibility best practices across disability types, and (iii) the effectiveness of AI-enabled inclusive solutions. The system was developed following user-centred design principles and WCAG 2.2 standards, combining generative AI modules for recipe creation with accessibility features such as voice interaction and adaptive navigation. The evaluation, conducted with 87 participants, employed the System Usability Scale complemented by thematic qualitative feedback. Results indicate excellent usability (M = 80.6), high reliability (Cronbach’s α = 0.798–0.849), and moderate positive correlations between usability and accessibility dimensions (r = 0.45–0.55). Participants highlighted the platform’s personalisation, clarity, and inclusivity, confirming that accessibility enhances rather than restricts user experience. The findings provide empirical evidence that AI-driven adaptability, when grounded in universal design principles, offers an effective and ethically sound pathway toward digital inclusion. Receitas +Power thus advances the field of inclusive digital gastronomy and presents a replicable framework for human–AI co-creation in accessible web technologies.

Artificial intelligence has become fundamental to the advancement of digital gastronomy, a domain that integrates computer vision, natural language processing, graph-based modelling, recommender systems, multimodal learning, IoT and robotics to support culinary, nutritional and behavioural processes. Despite this progress, the field remains conceptually fragmented and lacks comprehensive syntheses that combine methodological insights with bibliometric evidence. To the best of our knowledge, this study presents the first systematic review to date dedicated to artificial intelligence in digital gastronomy, complemented by a bibliometric analysis covering publications from 2018 to 2025. A structured search was conducted across five major databases (ACM Digital Library, IEEE Xplore, Scopus, Web of Science and SpringerLink), identifying 233 records. Following deduplication, screening and full-text assessment, 53 studies met the predefined quality criteria and were included in the final analysis. The methodology followed established review protocols in engineering and computer science, incorporating independent screening, systematic quality appraisal and a multidimensional classification framework. The results show that research activity is concentrated in food recognition, recipe generation, personalised recommendation, nutritional assessment, cooking assistance, domestic robotics and smart-kitchen ecosystems. Persistent challenges include limited cultural diversity in datasets, annotation inconsistencies, difficulties in multimodal integration, weak cross-cultural generalisation and restricted real-world validation. The findings indicate that future progress will require more inclusive datasets, culturally robust models, harmonised evaluation protocols and systematic integration of ethical, privacy and sustainability principles to ensure reliable and scalable AI-driven solutions.

The lack of accessibility in digital gaming platforms remains a significant barrier to equitable user participation. To address this issue, this article presents an inclusive solution developed as a multimedia project designed to promote access to digital games for any user through the ipcb.games platform. The platform offers features that enhance accessibility, including voice-based authentication, voice-assisted registration, facial recognition, visual and auditory feedback, and a simplified interface. It also enables users to submit their own games for subsequent approval and integration. The development process followed a multimedia project methodology, structured into phases of analysis, planning, design, production, testing, and validation. The proposal was informed by a systematic review of scientific literature on digital inclusion and accessibility, complemented by a comparative analysis of existing platforms. During usability testing, the platform was evaluated by approximately 50 teachers from different educational levels, who provided highly positive feedback. Future work includes implementing voice-controlled gameplay, enabling keyboard-based navigation, re-implementing a functional eye-tracking system, and creating pedagogical groups, further strengthening the platform’s role in educational contexts.