Inquiry-based learning (IBL) is essential to Science Education since it improves students’ conceptual comprehension, higher-order thinking abilities, and interpersonal skills. Mobile technology (mIBL) promotes active learning, facilitates access to learning materials, and enhances IBL in terms of mobility and rapid feedback. This study assesses the 9th grade students’ awareness of 4Cs skills (Collaboration, Communication, Critical thinking and problem solving, and Creativity) after participating in mobile-technology-supported inquiry-based Teaching Learning Sequence (TLS). Additionally, the study investigates the qualities/characteristics students cite before and after the TLS in relation to these skills. The results of a questionnaire administered to students indicate that their awareness of these skills has increased as a result of the TLS. Specifically, the TLS seems to have a greater impact on Collaboration and Communication than on Critical thinking and problem solving, and Creativity. An additional qualitative investigation of students’ written answers to explanatory open-ended questions before and after the entire procedure found intriguing data confirming their shift in 4Cs awareness.

Educational institutions face growing challenges. Rising enrolment, limited budgets, and sustainability goals demand more efficient resource management and administrative decision-making. To address challenges like these, this work proposes a conceptual framework for smart campus management which integrates Artificial Intelligence (AI) and advanced wireless networks based on 5G. The framework’s design outlines layers for campus data collection (via sensors and connected devices), high-speed communication, and AI-driven analytics for decision support. By leveraging data-driven insights enabled by reliable wireless connectivity, institutions can make more informed decisions, use resources more effectively, and automate routine tasks. Envisioned AI capabilities include forecasting (for predictive maintenance and demand planning), anomaly detection (for fault or irregularity identification), and optimisation (for resource scheduling). Rather than reporting empirical results, the framework is illustrated through hypothetical scenarios (e.g., anticipating equipment maintenance, dynamically scheduling classrooms, or reallocating resources) to present potential benefits and tools for researchers. The discussion also highlights how the framework incorporates data privacy, security, and accessibility considerations to ensure inclusive adoption. Eventually, this conceptual proposal provides a roadmap for administrators and planners, guiding the adoption of AI and wireless innovations in educational management to enable more responsive, efficient governance and, ultimately, improve outcomes for students and staff.

In this study, an inquiry-based sequence was designed, developed and implemented using facets of flipped classroom and aspects of inquiry learning using the ADDIE model. The sequence intends to promote the students’ scientific literacy. The aim of this paper is to examine the effectiveness of specially designed inquiry-based online worksheets (e-WS) to actively engage students in the design of unconfounded experiments by applying the Control of Variables Strategy (CVS). Second-year senior high school (11th grade) students participated in an intervention in which facets of flipped classroom approach with asynchronous and synchronous distance learning sessions were adopted, during the COVID-19 lockdown. Results show that the flipped classroom approach with synchronous and asynchronous sessions was acceptable and adoptable by the students; the existence of probe questions in e-WS, combined with explicit reference to inquiry procedure enhanced students’ awareness of scientific practice and on CVS, while at the end of the intervention, students were capable of applying the CVS in the design of unconfounded experiments.

The increasing integration of Artificial Intelligence (AI) in education (AIEd) and its dependence on contemporary communication infrastructures (5G/6G, the Internet of Things (IoT), and Multi-Access Edge Computing (MEC)) has prompted a surge of research into applications, infrastructural dependencies, and deployment constraints. This is giving rise to a new paradigm termed AI-Enabled Telecommunication-Based Education (AITE). This review synthesises the recent literature (2022–2025) to examine how telecommunications and AI technologies converge to enhance educational ecosystems through adaptive learning systems, intelligent tutoring systems, AI-driven assessment, and administration. The findings reveal that low-latency, high-bandwidth connectivity, combined with edge-deployed analytics, enables real-time personalisation, continuous feedback, and scalable learning models that extend beyond traditional classrooms. In addition, persistent critical challenges are also reported, including issues with ethical governance, data privacy, algorithmic fairness, and uneven access to digital infrastructure, all affecting equitable adoption. By linking pedagogical transformation with telecom performance metrics—namely, latency, Quality of Service (QoS), and device interconnectivity—this work outlines a unified cross-layer framework for AITE. This review concludes by identifying future research avenues in ethical AI deployment, resilient architectures, and inclusive policy design to ensure transparent, secure, and human-centred educational transformation.