Publication
AI-powered prompt engineering for education 4.0: Transforming digital resources into engaging learning experiences
| datacite.subject.fos | Ciências Sociais::Ciências da Educação | |
| dc.contributor.author | Serra, Paulo | |
| dc.contributor.author | Oliveira, Ângela | |
| dc.date.accessioned | 2025-12-10T11:40:40Z | |
| dc.date.available | 2025-12-10T11:40:40Z | |
| dc.date.issued | 2025 | |
| dc.date.updated | 2025-12-09T11:22:34Z | |
| dc.description.abstract | 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. | eng |
| dc.description.version | N/A | |
| dc.identifier.citation | SERRA, Paulo ; OLIVEIRA, Ângela (2025) - AI-powered prompt engineering for education 4.0: Transforming digital resources into engaging learning experiences. Education Sciences, 15:12, p.1640. DOI: 10.3390/educsci15121640 | |
| dc.identifier.doi | 10.3390/educsci15121640 | en_US |
| dc.identifier.slug | cv-prod-4619425 | |
| dc.identifier.uri | http://hdl.handle.net/10400.11/10393 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | MDPI | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Artificial intelligence | |
| dc.subject | Prompt engineering | |
| dc.subject | Education 4.0 | |
| dc.subject | Digital educational resources | |
| dc.subject | Large Language Models | |
| dc.subject | Personalised learning | |
| dc.subject | Educational recommender systems | |
| dc.title | AI-powered prompt engineering for education 4.0: Transforming digital resources into engaging learning experiences | eng |
| dc.type | research article | en_US |
| dspace.entity.type | Publication | |
| oaire.citation.title | Education Sciences | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Marques Oliveira | |
| person.givenName | Angela Cristina | |
| person.identifier.ciencia-id | 471B-8360-6CF9 | |
| person.identifier.orcid | 0000-0003-0172-4679 | |
| person.identifier.scopus-author-id | 55810696000 | |
| rcaap.cv.cienciaid | 471B-8360-6CF9 | Ângela Cristina Marques de Oliveira | |
| rcaap.rights | openAccess | en_US |
| relation.isAuthorOfPublication | 743a5c35-45ff-4434-bd00-b2c14691ba19 | |
| relation.isAuthorOfPublication.latestForDiscovery | 743a5c35-45ff-4434-bd00-b2c14691ba19 |