As digital transformation in education accelerates, mobile applications have become fundamental to modern learning environments. However, the massive collection of student data by these platforms raises critical ethical concerns regarding privacy and transparency. This study aims to evaluate the privacy policies of the top 100 educational applications on major digital marketplaces to determine their alignment with ethical standards and global data protection regulations such as GDPR and COPPA. The research utilizes a qualitative content analysis and document analysis methodology. The selected applications are evaluated based on four primary dimensions: (1) accessibility and readability, (2) clarity of data collection purposes, (3) disclosure of third-party data sharing, and (4) specific protections for minor users. To assess readability, the Flesch-Kincaid scale is employed to determine whether these legal documents are comprehensible to the average parent or student. The study expects to find a "transparency gap" in the EdTech industry. Many apps use difficult legal terms that make it hard for users to know how their personal information is being used, especially with new AI features. The results of this research will show the current state of data ethics in education. Finally, the study offers suggestions for developers and schools on how to make digital learning safer and more transparent. By focusing on these issues, the research helps to protect the digital rights of learners in the 21st century.

Sustainable web development focuses on designing web pages that minimize their environmental impact by reducing digital carbon emissions while maintaining optimal website performance and user experience. This study emphasizes the necessity of adopting sustainable web development practices in the Balkan region, highlighting the role of institutional education and web developers in encouraging environmentally responsible web practices within a Technology-Enhanced Education context. A descriptive cross-country analysis was conducted on a total of 8,976 websites across five Balkan countries—Albania, Greece, Serbia, Montenegro, and North Macedonia—selected from public domain registries and categorized by sector (education, organization, government, and commercial domains). Data were collected during December, 2025. DNS verification was conducted to identify active domains, and hosting sustainability was determined through the Green Web Foundation API. “Green hosting” is operationally defined as hosting that is completely powered by renewable energy sources. Overall, the findings suggest that the prevalence of green hosting in the region is very low, at approximately 27.77%, with substantial variation across sectors. Educational institutions (.edu) and non-profit organizations (.org) have higher adoption rates, while public administrations (.gov) and small commercial websites generally fall behind. The country with the highest percentage of green hosting is Greece (64.07%), while the lowest is Albania, with less than 1%. These findings reveal significant gaps in knowledge and practices among developers and institutions, indicating an urgent need for targeted educational interventions. Crucially, this study connects empirical evidence directly to education. Recognized knowledge gaps guide curriculum development and the design of practical training modules to equip developers and institutional personnel with the skills to adopt sustainable web practices. This research establishes a regional comparative baseline and offers practical recommendations for incorporating sustainability into web development education. The findings endorse strategies and policies aimed at promoting environmentally sustainable digital infrastructure in the Balkan area.

Each school year begins with a strategic effort to assess the level of competence of students, an effort during which any failure to achieve sufficient acquired levels is considered intolerable. In a context where the heterogeneity of classes represents a major challenge, the integration of artificial intelligence (AI) appears as an opportunity to rethink teaching methods and build a truly "AI-ready" school. This study thus examines how AI tools can help improve mathematical skills and personalize learning among first-year college students.

This design-based study was conducted with a group of students chosen according to a reasoned sample. The goal was to be able to design, test and refine an educational device integrating the learning platform Kwyk.fr. From a diagnostic test, this platform detects the achievements and points to work on for the student and generates an adaptive exercise path.

The analysis of the collected data reveals a notable progression in students' performance, both in terms of consolidation of mathematical skills and in terms of involvement in the proposed activities. These results highlight the potential of AI to support teachers and students in an educational transformation based on real needs, by promoting more targeted learning paths, more effective and better adapted to the diversity of profiles.

Introduction

Chemical engineering is halfway between engineering and chemistry, converting one thing into another. For this, chemical engineers need technical knowledge across different areas such as chemistry, biochemistry, engineering, materials science and information technology, as well as complementary areas such as economics, management, safety and environmental protection.

Changes in the discipline and the professional needs of graduates mean that chemical engineering education should face continuous challenges. A notable pedagogical trend is the incorporation of gamification methodologies.

The aim of this work is to analyse, based on a revision of innovation projects focused on gamification and their outcomes, how gamification-based approaches have enhanced the learning and professional performance of future chemical engineers.

Methods

A comprehensive analysis was conducted of innovation projects involving the use of gamification in Bachelor's and Master's courses of Chemical Engineering at a Spanish university over the past 15 years. These projects were examined in relation to data on academic success and employer evaluations.

Results

The analysis of numerous projects revealed that gamification in chemical engineering had a positive assessment from both students and teachers, remarking the development of critical thinking, reinforcement of student self-confidence, and increased interaction between students and instructors.

However, a trend towards higher scores in the Students’ Evaluation of Teaching (SET) was observed, constituting one of the outcomes of this study. This trend, according to the literature, could have a significant subjective component. By contrast, from employer assessment data, no significant improvement was detected in student maturation, which is an attribute regarded as highly relevant by employers.

Conclusions

Gamification is associated with positive perceptions but demonstrates limited measurable impact on key quality indicators. Current evidence does not suggest that employer priorities were met through these methodologies. However, notable strengths were identified, by integration with other tools such as virtual reality, creating learning environments that more closely resemble the real world.

Large Language Models (LLMs) can help students learn effectively. However, their use can introduce several issues, including ethical breaches and environmental harms. While ethical breaches have been extensively addressed, the environmental harms receive little attention. LLMs require substantial computational power, harming the environment. One LLM prompt results in a carbon footprint four times that of a Google search. There are a few studies that focus on informing LLMs’ environmental harms in education. However, many of those are designed as course materials or general guidance. Students might not have time to learn the course materials and may find the guidance limited in relevance to their own context.
We present an online platform that bootstraps LLMs, promoting their sustainable use through mindful prompting and gamification. Mindful prompting is encouraged by applying course-relevant pre-prompts, setting minimum prompt lengths, limiting one prompt per minute, and recommending the reuse of similar prompt responses. The first two aim for effective prompt interactions, while the last two aim to minimise environmental harm. Gamification is applied by reducing the incentive for students using LLMs excessively. For each assessment, students will get 100 game points if their use of LLMs (measured in the total number of words in prompts and responses) is no more than 25% higher than the average. Otherwise, they will have game points deducted based on a proportion of excessive use.
The platform is being evaluated in an informatics course (60 students) via a quasi-experiment. Our platform will be evaluated based on students’ awareness of the sustainable use of LLMs, the number of reused prompt responses, the number of words in prompts and responses, and their perception of the platform. Other indirect metrics will also be discussed, including academic performance, prompt analysis and response similarity.

This study explores the use of information and communication technologies (ICTs) by physics and chemistry teachers in the Marrakech-Safi region. A questionnaire, based on the DigCompEdu framework and adapted to the Moroccan context, was distributed to 247 teachers. The results show that interactions between teachers and students occur at least once a month, with semiannual communications with parents and between teachers themselves. This study highlights the critical importance of technology in education to improve and facilitate communication and collaboration.

Research question: How does the use of ICT by physics and chemistry teachers in the Marrakech-Safi region improve the quality of interactions between teachers, students, parents and colleagues?

Methodology: Between October 1, 2025, and November 30, 2025, a paper questionnaire based on the DigCompEdu framework was distributed. After validation by a pre-test, the questionnaire was adapted to the Moroccan context. The data of 247 physics and chemistry teachers in the Marrakech-Safi region were statistically analyzed, guaranteeing anonymity and the consent of participants. The objective was to assess teachers' perceptions of their digital skills and use of ICT in education.

Results: Interactions between teachers and students occur monthly, influenced by the type of digital tools used and educational parameters. Communication with parents is biannual, in line with institutional expectations, while coordination between teachers is also biannual, often limited by administrative and time constraints.

This qualitative case study examines how artificial intelligence (AI)-enhanced musical play can foster creativity, cultural awareness, and historical inquiry in early childhood classrooms. Drawing on constructionist theory, culturally responsive pedagogy, and distributed creativity, this study explores preschool children’s engagement with Citizen DJ, an AI-supported digital remix platform that enables users to search, select, and remix public-domain historical audio. Over four weeks, fifteen four-year-old children participated in guided and child-directed remixing activities that emphasized playful exploration, inquiry, and multimodal meaning making rather than performance outcomes. Data sources included video recordings, field notes, educator reflective journals, semi-structured child interviews, and children’s original digital sound compositions. Analysis focused on children’s creative processes, sound selection patterns, and emerging cultural and historical dialogue. Findings indicate that children demonstrated originality and divergent thinking in their musical remixes, frequently drawing on spoken word, animal sounds, and archival recordings. Network analysis revealed fluid movement across thematic sound categories, while a cultural engagement heatmap highlighted sustained interaction with culturally meaningful audio, including folk music, nursery rhymes, and historical speech. These encounters often prompted children’s questions about sound origins, sparking conversations about culture, history, and identity. Educators reported increased confidence in integrating technology-enhanced music activities and described AI-supported remixing as an accessible entry point for inquiry-based, culturally responsive pedagogy. This study contributes to education research by illustrating how AI-driven tools can support developmentally appropriate, play-based engagement with cultural heritage, positioning young children as creative agents and meaning-makers. Implications are discussed for early childhood curriculum design, teacher education, and inclusive approaches to technology-enhanced learning.

Objective: Artificial Hallucination, termed as the “generation of plausible but factually incorrect information”, is a complication in the use of large language models (LLMs). Inappropriate reliance on LLMs, when used as an educational tool, may undermine critical thinking and risk distorting academic understanding, particularly among foundational learners in evidence-based disciplines. Systematic evaluation is therefore required to assess the extent of hallucination of publicly available LLMs for educational use.

Methods: This study evaluated the hallucination rates of four public LLMs: ChatGPT-4o, Microsoft Copilot, Google Gemini 1.5, and Claude Sonnet 3.5. A standardised, expert-validated set of multiple-choice questions, along with a standardised prompting approach, was used to assess answer accuracy, reasoning validity, and citation relevance as binary outcomes. Responses were independently reviewed by two subject experts, with discrepancies resolved by consensus. Categorical analysis, using Chi-square or Fisher–Freeman–Halton tests, was applied to gather quantitative results, and qualitative thematic analysis was used to characterise citation-related errors.

Results & Discussion: Among the four LLMs, ChatGPT-4o demonstrated the highest answer accuracy (84%) and reasoning validity (72%). While ChatGPT-4o produced the greatest number of citations, Copilot yielded the highest proportion of valid (91.8%) and relevant (48.7%) references. The most common sources of hallucination were invalid links and non-scholarly online content. However, no statistically significant difference in hallucination rates was observed among the four models (p > 0.05), indicating comparable susceptibility to misinformation.

Conclusion: Current LLMs do not replace human reasoning. The findings underscore the need for expert oversight, citation verification and a robust validation approach to ensure reliability and mitigate misinformation in evidence-based domains. Integrating a human-over-the-loop approach in LLM literacy initiatives may epistemically enhance and promote responsible AI adoption in higher education

Introduction
Despite their relevance to public health and forensic science, parasites are rarely used as indicators in criminal investigations. To address this educational gap and support the development of forensic parasitology as an emerging discipline, the University of Alcalá (UAH) integrated clinical parasitology content into two undergraduate programmes during the 2023/24 academic year.

Methods
New theoretical and practical components were embedded into the Environmental Toxicology and Public Health module (BSc in Environmental Sciences) and the Forensic Toxicology module (BSc in Criminalistics). Students engaged in outbreak response simulations using a scenario based on an emerging zoonotic protozoan. Workshops incorporated the open access virtual learning platform e-Parasitology© and the UK Recovery Handbook for Biological Incidents. Learners selected appropriate laboratory techniques for parasite identification and developed a tailored response to control the simulated outbreak.

Results
High levels of student engagement and satisfaction were observed across both programmes, despite curricular differences. Based on this positive feedback, virtual forensic parasitology case studies were developed and piloted. The first case, available via e-Parasitology^©, involves the post mortem diagnosis of Ascaris lumbricoides in a young girl, integrating virtual microscopy and autopsy images (http://parasitology.dmu.ac.uk/learn/case_studies/forensic_cs1/index.html). These resources are currently being evaluated for broader implementation in science and medical curricula.

Conclusions
This educational initiative demonstrates the feasibility and effectiveness of embedding parasitology into forensic and biomedical teaching. It highlights the value of virtual simulations and real-world scenarios to promote interdisciplinary thinking, diagnostic skills, and public health preparedness. Future expansions include the development of additional case studies involving protozoan, helminthic, and arthropod parasites, further consolidating forensic parasitology as a relevant educational and research tool.

As artificial intelligence (AI) tools rapidly expand across higher education, instructors are navigating new opportunities and challenges. This session shares findings from a Fall 2025 survey conducted by the presenters, full-time university faculty members who examined how instructors are using AI, how they feel about its growing presence, and what factors shape their willingness to adopt it.

The study gathered data from full- and part-time faculty across disciplines, focusing on the types of AI tools used, frequency of use, perceived benefits, primary concerns, and overall attitudes toward AI. The analysis also draws associations between faculty age/experience and perceptions/likelihood of AI use. These associations will be presented in clear, practitioner-friendly language.

During the session, attendees will explore several guiding questions:
• How are faculty actually using AI?
• What benefits do instructors see for teaching, research, and productivity?
• What concerns or barriers are limiting adoption?

These insights will help participants compare national trends with their own institutional experiences and better understand the evolving role of AI in academic work.

The session will end with a brief reflective activity that invites attendees to consider how the findings apply to their own professional contexts. Participants will think through whether, and in what ways, AI could support their teaching, research, or workflow. The goal is to move from broad discussion to intentional, practice-based decision-making.

This presentation ultimately offers a novel look at faculty use of AI at a pivotal moment in higher education and provides attendees with practical insights to inform their integration or questions to raise to their own university AI task forces.