Nikleia Eteokleous

The importance of Education for Sustainability (EfS) in shaping values and fostering responsible sustainable behaviour has been acknowledged from the early years of education. Our research explores Preservice Preschool Teachers’ (PPTs) perceptions of using game-based learning (GBL) activities to teach EfS, and the impact of designing and delivering such activities on their confidence in teaching EfS. The research used qualitative methods. Data were collected from 12 university students, who developed and implemented GBL activities for preschool children on Monachus monachus. Preservice teachers participated in a group interview and filled reflective reports to describe their overall experience. A reflexive thematic analysis was performed using NVivo software. Outcomes indicate that participants appreciate GBL as an effective pedagogical approach in preschool education, given that it is appropriately and pedagogically designed. Participation, emotional engagement and understanding of complex sustainability concepts emerged as benefits from the involvement in GBL activities, both for the children and for the preservice teachers. Other benefits for the research participants concerned the development of their classroom adaptability, collaboration skills, reflection and confidence. Authentic, collaborative experiential approaches in teacher education and actual teaching opportunities can effectively empower preservice teachers’ confidence to teach about sustainability.

The present study concentrates on the inclusion of sustainability, in line with the UN sustainable development goals (particularly SDG4 – quality education), as a significant element of academics’ digital competences. It aims to evaluate and discuss the academics’ self-report digital competences in relation to the promotion of sustainability through their courses at a private university in Cyprus. The Check-In tool was used based on the DigCompEdu framework to measure the academics’ self-reports on digital competences. Semi-structured interviews were conducted to identify academics’ attempts to facilitate learners’ digital competences within their courses. Results provide significant insights into the intersection of sustainable development, education for sustainability and academics’ digital competences. While the majority of participants reported high levels of digital competence, there is a clear need for ongoing training and support, mainly in the areas of assessment and learner empowerment in order to be able to integrate the goals of sustainable development in their teaching. Areas for improvement and practical implications are discussed.

Purpose: This study investigates how artificial intelligence (AI) integrates into school leadership by examining organisational benefits and ethical challenges. As AI permeates educational administration, school leaders must navigate risks and opportunities in data privacy, fairness, and accountability. Design/methodology/approach: A PRISMA-aligned structured literature review was conducted on publications from 2019 to 2025. Searches were performed in Scopus, Web of Science, ERIC, and Google Scholar, focussing on K–12 school leadership, with selective higher education sources included only for transferable governance mechanisms (e.g. policy, procurement, documentation/explainability, and auditability). Studies were screened for leadership relevance and ethical-legal engagement. Findings were synthesised using reflexive thematic analysis and conceptual mapping, yielding a final corpus of 50 publications. Findings: AI affords benefits for school leadership, including administrative efficiency, decision support and, under data governance, more equitable resource allocation. However, adoption introduces ethical-legal challenges. Key concerns include algorithmic bias, opacity in decision-making, and diffuse accountability. Many systems lack robust oversight, clear roles, and targeted training for ethical implementation. Practical implications: School leaders should embed AI in distributed leadership, mandate explainability and audits in procurement, invest in privacy/data literacy, and align analytics with instructional priorities to secure equity, lawful processing, and reviewable accountability. A one-page governance map (Leaders' Governance Guide) is provided, mapping use cases to risks, safeguards, and an equity note. Originality/value: The review links benefits and risks to accountability and legal implications, proposing a leadership governance frame to support equitable, transparent AI in schools.

This mixed-methods study examines the digital competence of primary school teachers in Greece and Cyprus working in multilingual and multicultural mainstream classrooms. In response to the increasing diversity in European education, it explores how teachers perceive and implement digital competence to support inclusive and quality education. Using the DigCompEdu framework and an extended TPACK model, data were collected from 146 in-service teachers through a structured questionnaire. Cluster analysis revealed three distinct competence profiles-high, moderate, and low-while Kruskal–Wallis tests confirmed significant differences among them. Thematic analysis of open-ended responses, supported by Pearson correlation analysis, highlighted how teachers’ beliefs, infrastructural conditions, and pedagogical practices intersect. Highly competent teachers reported the use of inclusive digital strategies yet pointed to systemic barriers such as limited training and poor infrastructure. Less confident teachers expressed foundational challenges and dependence on external support. Across all profiles, contextual factors—school resources, time, student digital readiness, and access to professional development—were key. The study concludes that digital competence is not merely technical but deeply context-sensitive and pedagogical. It calls for differentiated, equity-oriented professional learning pathways aligned with Sustainable Development Goals 4 and 10, contributing to inclusive education and education for sustainability in linguistically diverse classrooms.

This mixed-methods study examines the digital readiness of primary school teachers in Greece and Cyprus working in multilingual and multicultural mainstream classrooms. In response to the increasing diversity in European education, it explores how teachers perceive and implement digital competence to support inclusive and quality education. Using the DigCompEdu framework and an extended TPACK model, data were collected from 146 in-service teachers through a structured questionnaire. Cluster analysis revealed three distinct competence profiles—high, moderate, and low—while Kruskal–Wallis tests confirmed significant differences among them. Thematic analysis of open-ended re-sponses, supported by Pearson correlation analysis, highlighted how teachers’ beliefs, infrastructural conditions, and pedagogical practices intersect. Highly competent teachers reported the use of inclusive digital strategies, yet pointed to systemic barriers such as limited training and poor infrastructure. Less confident teachers expressed foundational challenges and dependence on external support. Across all profiles, contextual fac-tors—school resources, time, student digital readiness, and access to professional development—were key. The study concludes that digital competence is not merely technical, but deeply context-sensitive and pedagogical. It calls for differentiated, equity-oriented professional learning pathways aligned with Sustainable Development Goals 4 and 10, contributing to inclusive education and education for sustainability in linguistically diverse classrooms.

In education, e-learning is highly adopted to improve the learning experience and increase learning efficiency and engagement. Yet, an explosion of online learning materials has overwhelmed learners, especially when trying to achieve their learning goals. In this scope, recommender systems are used to guide learners in their learning process by filtering out the available resources to best match their needs, i.e. to offer personalized content and learning paths. Concurrently, process mining has emerged as a valuable tool for comprehending learner behavior during the learning journey. To synergize these disciplines and optimize learning outcomes, our paper introduces an ontology-based framework that aims to recommend an adaptive learning path, driven by a learner’s learning objective, personalized to his learning style, and enriched by the past learning experience of other learners extracted via process mining. The learning path considers pedagogical standards by employing Bloom’s taxonomy within its structure. The framework establishes an Ontological Foundation, to model the Learner, Domain, and Learning Path. Choosing Computer Science as a domain, we construct a knowledge base using synthesized data. For past learning experience, we analyze Moodle log data from 2018 to 2022, encompassing 471 students in the Computer Science and Engineering Department at Frederick University, Cyprus.