Search Results (355)

Illustrated digital picture books are widely used for second-language reading and vocabulary growth. We ask how close current generative AI (GenAI) tools are to producing such books on demand for specific learners. Using the ChatGPT-based Learning And Reading (C-LARA) platform with GPT-5 for text/annotation and GPT-Image-1 for illustration, we ran three pilot studies. Study 1 used six AI-generated English books glossed into Chinese, French, and Ukrainian and evaluated them using page-level and whole-book Likert questionnaires completed by teachers and students. Study 2 created six English books targeted at low-intermediate East-Asian adults who had recently arrived in Adelaide and gathered student and teacher ratings. Study 3 piloted an individually tailored German mini-course for one anglophone learner, with judgements from the learner and two germanophone teachers. Images and Chinese glossing were consistently strong; French glossing was good but showed issues with gender agreement, register, and naturalness of phrasing; and Ukrainian glossing underperformed, with morphosyntax and idiom errors. Students rated tailored English texts positively, while teachers requested tighter briefs and curricular alignment. The German pilot was engaging and largely usable, with minor image-consistency and cultural-detail issues. We conclude that for well-supported language pairs (in particular, English–Chinese), the workflow is close to classroom/self-study usability, while other language pairs need improved multi-word expression handling and glossing. All resources are reproducible on the open-source platform. We adopt an interdisciplinary stance which combines aspects taken from computer science, linguistics, and language education. Full article

In disciplines such as epidemiology, economics, and public health, inference and estimation of heterogeneous treatment effects (HTE) are critical. This approach helps reveal differences in treatment effect estimates between subgroups, which supports personalized decision-making processes. While a variety of meta-learners (e.g., S-, T-, X-learners) have been proposed for estimating HTE, there is a lack of consensus on their relative strengths and weaknesses under different data conditions. To address this gap and provide actionable guidance for applied researchers, this study conducts a comprehensive simulation-based comparison of these methods. We first introduce the causal inference framework and review the underlying principles of the methods used to estimate these effects. We then simulate different data generating processes (DGPs) and compare the performance of S-, T-, X-, DR-, and R-learners with the causal forest, highlighting the potential of meta-learners for HTE estimation. Our evaluation reveals that each learner excels under distinct conditions: the S-learner yields the least bias and is most robust when the conditional average treatment effect (CATE) is approximately zero; the T-learner provides accurate estimates when the response functions differ significantly between the treatment and control groups, resulting in a complex CATE structure, and the X-learner can accurately estimate the HTE in imbalanced data.Additionally, by integrating Z-bias—a bias that may arise when adjusting the covariate only affects the treatment variable—with a specific sensitivity analysis, this study demonstrates its effectiveness in reducing the bias of causal effect estimates. Finally, through an empirical analysis of the Trends in International Mathematics and Science Study (TIMSS) 2019 data, we illustrate how to implement these insights in practice, showcasing a workflow for HTE assessment within the meta-learner framework. Full article

Astronomy provides an exceptional context for developing data literacy, critical thinking, and computational skills in education. This paper presents a project-based learning (PBL) framework that integrates exploratory data analysis (EDA), fuzzy logic, and explainable artificial intelligence (XAI) to teach students how to extract and interpret scientific knowledge from real astronomical data. Using open-access resources such as NASA’s JPL Horizons and ESA’s Gaia DR3, together with Python libraries like Astroquery and Plotly, learners retrieve, process, and visualize dynamic datasets of comets, asteroids, and stars. The methodology follows the full data science pipeline, from acquisition and preprocessing to modeling and interpretation, culminating with the application of the FAS-XAI framework (Fuzzy-Adaptive System for Explainable AI) for pattern discovery and interpretability. Through this approach, students can reproduce astronomical analyses and understand how data-driven methods reveal underlying physical relationships, such as orbital structures and stellar classifications. The results demonstrate that combining EDA with fuzzy clustering and explainable models promotes deeper conceptual understanding and analytical reasoning. From an educational perspective, this experience highlights how inquiry-based and computationally rich activities can bridge the gap between theoretical astronomy and data science, empowering students to see the Universe as a laboratory for exploration, reasoning, and discovery. This framework thus provides an effective model for incorporating artificial intelligence, open data, and reproducible research practices into STEM education. Full article

This study investigates how natural language processing (NLP) can support the assessment and learning of science vocabulary among multilingual and multicultural learners, drawing on data from two federally funded studies in the United States. Students define and use target vocabulary in a sentence, with responses transcribed and scored using NLP tools. Employing a mixed-methods design and guided by established socioecological theoretical frameworks, we examine how students’ sociocultural contexts and background knowledge influence their understanding of science word knowledge and applicability. Our findings highlight both the potential and challenges of using AI tools in equitable and culturally responsive ways, offering insights to improve NPL-based assessment tools that support literacy teaching and learning in diverse student populations. Full article

Background: Artificial intelligence (AI) is increasingly shaping medical education through adaptive learning systems, simulations, and large language models. These tools can enhance knowledge retention, clinical reasoning, and feedback, while raising concerns related to equity, bias, and institutional readiness. Methods: This narrative review examined AI applications in medical and health-profession education. A structured search of PubMed, Scopus, and Web of Science (2010–October 2025), supplemented by grey literature, identified empirical studies, reviews, and policy documents addressing AI-supported instruction, simulation, communication, procedural skills, assessment, or faculty development. Non-educational clinical AI studies were excluded. Results: AI facilitates personalized and interactive learning, improving clinical reasoning, communication practice, and simulation-based training. However, linguistic bias in Natural language processing (NLP) tools may disadvantage non-native English speakers, and limited digital infrastructure hinders adoption in rural or low-resource settings. When designed inclusively, AI can amplify accessibility for learners with disabilities. Faculty and students commonly report low confidence and infrequent use of AI tools, yet most support structured training to build competence. Conclusions: AI can shift medical education toward more adaptive, learner-centered models. Effective adoption requires addressing bias, ensuring equitable access, strengthening infrastructure, and supporting faculty development. Clear governance policies are essential for safe and ethical integration. Full article

The research aims to derive the positive and negative values and strange habits included in Ibn Battuta’s journey called “Tuhfat An-Nuzzar fi Ghara’ibal-Amsar wa-‘Aja’ib Al-Asfar” by Shams al-Din bin Abdullah al-Lawati, the Moroccan al-Tanji, known as Ibn Battuta (d. 1377 AD), presented and investigated by Ali al-Muntasir al-Katani (D.T), which was included in Ibn Battuta’s trip, to the peoples of the countries he visited on the African and Asian continents. A total of 440 respondents participated in the study: 195 teachers in the supplementary track and 245 fourth-year regular track students at an Arab College of Education from all disciplines: early childhood, Arabic language, science, mathematics and computer science, English language, and special education. The respondents were asked to select an enrichment text or a story of one or more pages from Ibn Battuta’s travels, with the aim of eliciting the positive and negative values and strange customs of the peoples and countries Ibn Battuta visited in Africa and Asia. The study results indicated that Ibn Battuta’s travelogue, “Tuhfat An-Nuzzar fi Ghara’ibal-Amsar wa-‘Aja’ib Al-Asfar,” is considered an important literary reference, rich with texts and stories from which we can deduce the values and customs of the people of the countries Ibn Battuta visited in Africa and Asia. Teachers can use this information for discussion and constructive dialogue with their students in schools, in various educational subjects such as social studies, religion, literature, Arabic language, history, and geography. Most of the study participants support the idea of integrating Ibn Battuta’s travelogue into various lessons. The study recommends the importance of integrating and expanding it to include other subjects in schools, colleges, and universities. This integration should be systematically built around various activities that achieve “meaningful learning,” ensure active student participation, and enhance value for the learner and society. In conclusion, I recommend conducting detailed studies and research on the educational values derived from travel literature. Full article

In an increasingly interconnected world, cybersecurity professionals play a pivotal role in safeguarding organizations from cyber threats. To secure their cyberspace, organizations are forced to adopt a cybersecurity framework such as the NIST National Initiative for Cybersecurity Education Workforce Framework for Cybersecurity (NICE Framework). Although these frameworks are a good starting point for businesses and offer critical information to identify, prevent, and respond to cyber incidents, they can be difficult to navigate and implement, particularly for small-medium businesses (SMBs). To help overcome this issue, this paper identifies the most frequent attack vectors to SMBs (Objective 1) and proposes a practical model of both technical and non-technical tasks, knowledge, skills, abilities (TKSA) from the NICE Framework for those attacks (Objective 2). This research develops a scenario-based curriculum. By immersing learners in realistic cyber threat scenarios, their practical understanding and preparedness in responding to cybersecurity incidents is enhanced (Objective 3). Finally, this work integrates practical experience and real-life skill development into the curriculum (Objective 4). SMBs can use the model as a guide to evaluate, equip their existing workforce, or assist in hiring new employees. In addition, educational institutions can use the model to develop scenario-based learning modules to adequately equip the emerging cybersecurity workforce for SMBs. Trainees will have the opportunity to practice both technical and legal issues in a simulated environment, thereby strengthening their ability to identify, mitigate, and respond to cyber threats effectively. We piloted these learning modules as a semester-long course titled “Hack Lab” for both Computer Science (CS) and Law students at CSU during Spring 2024 and Spring 2025. According to the self-assessment survey by the end of the semester, students demonstrated substantial gains in confidence across four key competencies (identifying vulnerabilities and using tools, applying cybersecurity laws, recognizing steps in incident response, and explaining organizational response preparation) with an average improvement of +2.8 on a 1–5 scale. Separately, overall course evaluations averaged 4.4 for CS students and 4.0 for Law students, respectively, on a 1–5 scale (college average is 4.21 and 4.19, respectively). Law students reported that hands-on labs were difficult, although they were the most impactful experience. They demonstrated a notable improvement in identifying vulnerabilities and understanding response processes. Full article

This study examined the utilization of artificial intelligence (AI) in inquiry-based science learning among gifted and non-gifted students. The participants included 484 students (197 gifted and 287 non-gifted; 226 males and 233 females) who completed three validated questionnaire instruments: the AI-Assisted Scientific Inquiry Learning Questionnaire (AASILQ), the AI-Assisted Science Learning Questionnaire (AASLQ), and the AI Literacy Questionnaire (AILQ). Factor analyses confirmed four latent constructs in the AASILQ, two in the AASLQ, and four in the AILQ, with all scales demonstrating strong internal consistency. Group comparisons were conducted according to educational placement and gender. The results indicated significant differences regarding educational placement: gifted students reported lower levels of AI-Assisted Scientific Inquiry Learning yet demonstrated higher AI literacy and greater confidence in the safe use of AI. Gender analyses revealed that female students expressed heightened concern regarding privacy issues. These findings extend the literature on AI integration in science education by highlighting nuanced differences in how gifted and non-gifted learners engage with AI, thereby offering implications for the design of equitable and responsive AI-supported learning environments. Full article

This systematic review synthesizes empirical evidence on the role of Artificial Intelligence (AI) in inclusive education. The review aimed to examine (1) the impact of AI technologies on learning outcomes and engagement among students with special needs, (2) barriers and enablers influencing AI adoption by educators, and (3) the role of theoretical frameworks in guiding AI-based interventions. A comprehensive search was conducted in Scopus, Web of Science, DOAJ, and Google Scholar for English-language, peer-reviewed studies published between 2020 and 2025. Sixteen (16) studies met the inclusion criteria and were appraised using the Mixed Methods Appraisal Tool (MMAT). Findings indicate that AI tools enhance personalization, accessibility, and engagement, particularly for learners with disabilities, while barriers such as infrastructure gaps and low digital literacy persist. Enablers include institutional support and teacher training, though theoretical frameworks were inconsistently applied. Limitations include the exclusion of grey literature and reliance on short-term studies. AI can advance inclusive education when integrated with ethical, pedagogical, and institutional strategies, while future research should prioritize longitudinal, theory-driven, and culturally responsive models. Full article

This study investigated the enhancement of topic-specific pedagogical content knowledge (TSPCK) among life science educators, with a particular focus on cellular respiration. The research identified a lack of studies on this topic, especially within South African educational settings, thereby emphasizing the challenges educators and learners face. With an emphasis on lesson planning, teaching, and reflections, this study used a qualitative research methodology to investigate how the lesson study approach enhances Grade 11 educators’ TSPCK in cellular respiration. The design used was lesson study. The lesson study approach has been identified as an effective strategy for enhancing educators’ TSPCK. Six educators from secondary schools participated. Data came from field notes and observations made while the lessons were being taught, as well as from educators’ reflective diaries and questionnaires. The findings revealed that educators utilize contextualization, differentiated teaching, collaborative planning, and a focus on conceptual understanding. Through the improvement of lesson designs, assessment methodologies, technological integration, and an emphasis on critical thinking and problem-solving, educators refined their cellular respiration TSPCK components. The results of this study will enhance educator professional development, impact curriculum design, and promote teaching and learning methodologies. This research will contribute to developing effective teaching approaches for cellular respiration and offer insights for initiatives aimed at advancing Life Sciences Education in South Africa. Full article

The goal of this study was to examine problem-solving processes of elementary-aged children (4th grade U.S., ages 9–10) and their parents as they applied themselves to hands-on science activities together, with the larger goal of studying how parents influence the development of children’s science inquiry skills. In this diverse group of families, which was approximately equally balanced in terms of ethnicity (Hispanic and non-Hispanic) and parent and child gender, the influence of parent language, dyad ethnicity, and dyad gender was examined while controlling for family socio-economic status. Four problem-solving processes were examined: writing a hypothesis, recording results, drawing/sketching the process, and writing an explanation of how or why a process worked. The study included 153 families in a metropolitan area in the southwestern U.S. (Phoenix, AZ), approximately balanced in terms of child and parent ethnicity and gender. Gender differences were not observed for any of the problem-solving processes. Differences in some problem-solving processes, especially for writing a hypothesis, were observed based on parent language and dyad ethnicity. Families employed the strategy of drawing/sketching out solutions with a similar level of detail, regardless of parent education, language, ethnicity, and gender. Thus, we propose the use of drawing/sketching in the elementary science classroom as a useful strategy for reaching a diverse audience of learners. Family socio-economic status (as measured by parent education and family income) was strongly associated with parent language and dyad ethnicity. Implications for these findings are discussed. Full article

Environmental and Sustainability Education (ESE) encompasses more than the acquisition of environmental knowledge; it nurtures holistic learner development and empowers learners to understand and respond to human impacts on the environment. Schoolgrounds, when effectively utilised, provide a readily available resource for promoting environmental learning through context-based pedagogy. Yet, a review of the literature reveals a paucity of research in South Africa examining schoolgrounds as enablers of ESE. This study explored the accessibility and use of schoolgrounds to support environment-inclined pedagogy in Grade 7 Natural and Social Sciences at two schools in the Mpumalanga Province. Adopting a qualitative–interpretive paradigm, the study employed a phenomenological case study design, using purposive and convenient sampling to select participants and research sites. The sample comprised 46 participants: 40 learners, 4 teachers, and 2 principals. Data were generated through observations, semi-structured interviews, and survey questionnaires, and were thematically analysed. Findings indicate that while schoolgrounds are accessible to both teachers and learners, their pedagogical use remains limited and largely incidental. The study argues that more deliberate integration of schoolgrounds into teaching practices is needed. It concludes with education policy and pedagogical recommendations aimed at promoting schoolground-based ESE as a vital contributor to sustainability-oriented teaching and learning. Full article

The emergence of STEAM education, which integrates the Arts into Science, Technology, Engineering, and Mathematics (STEM), reflects a growing recognition of the need to develop both technical proficiency and creative capacity in learners. This shift emphasizes the importance of preparing students to tackle complex, real-world problems through innovative and interdisciplinary thinking. Drawing on an integrative review of 108 scholarly articles, from Scopus, ERIC, and Web of Science, we included peer-reviewed articles published between 2010 and 2024; this paper traces the conceptual evolution of STEAM education and examines its pedagogical implications for the psychomotor domain. It critically explores how incorporating the Arts reshapes traditional understandings of skill acquisition by highlighting hands-on, embodied, and creative approaches to problem-solving. The article, therefore, explores the concept of psycho-productive competency to capture the interplay between psychomotor skills and cognitive–emotional dimensions of learning. Findings underscore the need for teaching strategies and learning environments that move beyond technical demonstration to foster creativity, innovation, and holistic development. This re-examination of the psychomotor domain positions educational practice in line with the demands of a rapidly changing, knowledge-driven world. Full article

Attention and brain focus are essential in human activities that require learning. In higher education, a popular means of acquiring knowledge and information is through serious games. The need for integrating digital learning tools, including serious games, into university curricula has been demonstrated by the students’ preferences that are oriented more towards engaging and interactive alternatives than traditional education. This study examines real-time attention measurement in serious games using wearable brain–computer interfaces (BCIs). By capturing electroencephalography (EEG) signals non-invasively, the system continuously monitors players’ cognitive states to assess attention levels during gameplay. The novel approach proposes adaptive attention measurements to investigate the ability to maintain attention during cognitive tasks of different durations and intensities, using a single-channel EEG system—NeuroSky Mindwave Mobile 2. The measures have been achieved on ten volunteer master’s students in Computer Science. Attention levels during short and intense tasks were compared with those recorded during moderate and long-term activities like watching an educational lecture. The aim was to highlight differences in mental concentration and consistency depending on the type of cognitive task. The experiment was designed following a unique protocol applied to all ten students. Data were acquired using the NeuroExperimenter software 6.6, and analytics were performed in RStudio Desktop for Windows 11. Data is available at request for further investigations and analytics. Experimental results demonstrate that wearable BCIs can reliably detect attention fluctuations and that integrating this neuroadaptive feedback significantly enhances player focus and immersion. Thus, integrating real-time cognitive monitoring in serious game design is an efficient method to optimize cognitive load and create personalized, engaging, and effective learning or training experiences. Beta and attention brain waves, associated with concentration and mental processing, had higher values during the gameplay phase than in the lecture phase. At the same time, there are significant differences between participants—some react better to reading, while others react better to interactive games. The outcomes of this study contribute to the design of personalized learning experiences by customizing learning paths. Integrating NeuroSky or similar EEG tools can be a significant step toward more data-driven, learner-aware environments when designing or evaluating educational games. Full article

Gifted students often display advanced verbal abilities that facilitate second language acquisition; however, when instruction is insufficiently stimulating, they may experience boredom and demotivation. Due to rising interest in immersive technologies such as augmented reality (AR) and limited evidence of their impact on gifted language learners, a systematic scoping review was necessary to synthesise existing research and identify gaps. It examined the impact of AR on both linguistic development and motivational outcomes among gifted learners in ESL/EFL contexts. It was preregistered in the Open Science Framework (OSF) and conducted according to PRISMA-ScR guidelines. Eligible studies included gifted learners in ESL/EFL contexts, published between 2020 and 2025 in English, Spanish, French, or Italian. Exclusion criteria comprised non–peer-reviewed papers and studies unrelated to AR. Searches were conducted in Scopus, Web of Science, ERIC, and Redalyc. A total of 34 studies were included. Findings indicate that AR interventions improve vocabulary, listening, pronunciation, and fluency; writing also benefits, although grammar remains challenging. AR enhances intrinsic motivation, reduces anxiety, and fosters engagement, especially in younger learners. The results suggest that AR can be a valuable tool in EFL/ESL classrooms to support both linguistic development and motivation among gifted students, though sustainable implementation requires overcoming technological and pedagogical barriers. Full article