Search Results (449)

Quantum computers are a new generation of computers, whose principles for designing algorithms have already been defined, despite their hardware implementation still being under development. Attracting more scientists to the field is crucial to developing new algorithms in order to make the most of quantum computers once they are available. Serious games can contribute a lot to this effort. This article focuses on the pilot evaluation of the Quantum Escape serious game, which is based on a 3D format for motivating students and a conceptual simplification strategy for making abstract concepts accessible. Specifically, the game design is grounded in the established Four-Dimensional framework, and it aims to transform abstract concepts like superposition and entanglement, as well as common quantum gates, into intuitive puzzles presented through probabilities. The design of Quantum Escape was evaluated by 27 Computer Science students and graduates, in terms of perceived player experience and perceived short-term learning using a questionnaire based on the established MEEGA+ evaluation framework. The design choices of Quantum Escape seem to be validated, since most novice participants found the game understandable and requiring no prior knowledge, while participants with relevant background in quantum computing also largely endorsed the content’s accuracy. Limitations in the extent of quantum computing concepts and the number of participants dictate further development and evaluation of the game. Full article

This study developed and evaluated a concept-oriented electricity learning system integrating augmented reality (AR) and non-immersive virtual reality (VR) technologies to support different conceptual learning requirements in the “Basic Electrostatic Phenomena and Electrical Circuits” unit. In the proposed framework, AR supported hands-on circuit construction and visualization of invisible electrical phenomena, whereas non-immersive VR was used for voltage measurement and Ohm’s law experimentation through repeated and controllable exploration. A quasi-experimental design was conducted with 87 ninth-grade students from a public junior high school in Taiwan. Two classes were assigned to the experimental group and two to the control group. The intervention lasted five instructional sessions (225 min). Data were collected using an Electricity Achievement Test and a Science Learning Motivation Questionnaire and analyzed using ANCOVA. The results indicated that the experimental group achieved significantly higher science achievement and learning motivation than the control group. Significant improvements were observed in overall science achievement and across all electricity topics, including basic circuit concepts, voltage and current measurement, and resistance and Ohm’s law concepts. The findings suggest that these learning benefits may be associated with the alignment between technological affordances and conceptual learning requirements. Consistent with the Cognitive Theory of Multimedia Learning, Cognitive Load Theory, and Conceptual Change Theory, the framework may have supported learning through visualization, interaction, experimentation, and conceptual change. This study contributes to educational technology and science education research in two ways. First, it proposes a concept-oriented AR/VR framework that systematically aligns technological affordances with conceptual learning tasks and processing demands in electricity education. Second, it provides empirical evidence for the value of concept-oriented technology integration in supporting science achievement and learning motivation. The findings highlight the importance of aligning technological affordances with conceptual learning requirements when designing technology-enhanced science learning environments. Full article

The development of digital learning technologies has introduced innovative tools to enhance science and chemistry education, including PhET simulations. This study aims to evaluate the effectiveness of PhET simulations on students’ learning outcomes through a systematic literature review following the PRISMA 2020 guidelines. A systematic search of Scopus and Crossref databases was conducted (last search: January 2026) using predefined keywords. Eligible studies were empirical research published between 2020 and 2026 that investigated PhET simulations in science-related education and reported learning outcomes, while non-empirical studies and non-Scopus-indexed articles were excluded. Risk of bias was assessed using an adapted Joanna Briggs Institute critical appraisal tool. Due to heterogeneity in study designs and outcome measures, the results were synthesized using a narrative approach. A total of 14 studies across elementary to higher education levels were included. The findings indicate that PhET simulations consistently improve learning outcomes, particularly academic achievement and conceptual understanding, with effects generally favoring simulation-based instruction over traditional methods. However, higher-order skills and affective outcomes such as motivation and attitude remain less frequently investigated. The evidence is limited by variability in study designs, incomplete reporting of non-cognitive outcomes, and the absence of quantitative synthesis. Overall, PhET simulations demonstrate strong potential as an effective interactive learning medium, although their impact depends on instructional design, teacher facilitation, and technological accessibility. Full article

Background: AI-supported game-based learning (AI-GBL) integrates artificial intelligence mechanisms, including adaptive difficulty adjustment, large language model (LLM) scaffolding, intelligent non-player characters (NPCs), and stealth assessment, into game-based educational environments. Objective: This systematic review synthesizes the empirical evidence on AI-GBL effectiveness, adaptive mechanisms, and intelligent assessment approaches across diverse educational contexts. Method: Following PRISMA 2020 guidelines, 55 peer-reviewed empirical studies (2021–2026) were identified from Web of Science and Scopus databases. Two independent reviewers screened records (κ = 0.89; 100% consensus on disagreements), extracted data using a standardized coding scheme, and assessed methodological quality using a five-criterion rubric. A thematic synthesis approach was adopted due to the heterogeneity of the evidence base. Results: The reviewed studies generally suggest promising positive effects of AI-GBL on knowledge acquisition, intrinsic motivation, and affective engagement under a range of educational conditions. LLM-based scaffolding reduces cognitive load but risks fostering passive dependency; adaptive difficulty adjustment benefits depend critically on the direction and magnitude of adaptation; AI NPCs function as credible instructional partners in both EFL and STEM contexts; stealth assessment achieves AUCs of 0.848–0.913. Challenges include algorithmic bias in assessment models, LLM latency, over-reliance risks, and a near absence of longitudinal evidence. Conclusions: AI-GBL’s effectiveness rests on principled alignment between AI mechanisms and learning theory rather than algorithmic sophistication per se. Equity-by-design approaches and longitudinal evidence constitute the field’s priority research needs. Full article

Engineering design education is an effective instructional approach for enhancing students’ motivation, interest, and creativity while introducing them to the engineering design process (EDP). However, there is limited knowledge on how to integrate the EDP into robotics education, particularly AI-robotics, and how students experience AI-enabled robotics project-based learning grounded in an EDP. This pre-/posttest embedded mixed-methods study adds to the scarce body of literature on interdisciplinary education in engineering design, robotics, and AI. This project developed, implemented, and evaluated a project-based engineering design AI-robotics curriculum that introduced novice Computer Science (CS) high school students to robotics, machine learning, and AI. Students’ collaborative robotics projects were grounded in an EDP to introduce the students to engineering practices and promote engagement and interest through design-based, hands-on learning. An analysis of quantitative and qualitative data revealed an improvement in students’ CS attitudes, collaboration, and social interactions after participating in the curriculum. Recommendations for designing AI-robotics projects grounded in an EDP are discussed. Full article

Purpose: To evaluate the effectiveness of serious games, including virtual reality-based interventions, in improving clinical skills acquisition among undergraduate and postgraduate health science students. Methods: This systematic review was prospectively registered in PROSPERO (CRD42024589035) and conducted in accordance with PRISMA 2020 guidelines. PubMed, Scopus, Web of Science, and ScienceDirect were searched from inception to 31 August 2025. Eligible studies examined serious games, simulation-based platforms, or immersive and non-immersive virtual reality interventions designed to support clinical skills development. Outcomes were classified using a predefined hierarchical framework aligned with Miller’s pyramid, distinguishing performance-based clinical competence, clinical reasoning, and secondary educational outcomes. Owing to substantial heterogeneity in interventions, comparators, and assessment methods, a narrative synthesis was performed. Results: Thirteen studies involving 892 participants were included. Serious games and virtual reality-based interventions were associated with generally favorable outcomes for knowledge acquisition, self-efficacy, motivation, satisfaction, and anxiety reduction. Improvements in clinical reasoning were reported in several studies, and some studies demonstrated benefits in performance-based clinical competence, particularly in simulation and virtual reality settings. However, findings for objective performance-based outcomes were mixed, with some studies reporting no statistically significant between-group differences. Heterogeneity in outcome definitions and limited reporting of standardized effect sizes reduced cross-study comparability. Conclusions: Serious games, including virtual reality-based interventions, may serve as complementary, scenario-based learning strategies in health sciences education. The most consistent effects were observed for cognitive and learner-centered outcomes, whereas evidence for objective gains in performance-based clinical competence remains variable. Further high-quality studies using standardized outcome frameworks, validated performance-based assessments, effect sizes, confidence intervals, and longer follow-up are needed. Full article

This experimental study investigated the impact of embedding social and emotional learning (SEL) in science instruction on the academic and social–emotional outcomes of Arabic-speaking sixth graders, including those with reading difficulties (RD). Children from two schools in northern Israel (n = 101) were randomly assigned to either an intervention group, which received SEL-enriched science lessons featuring collaborative, reflective activities over 30 sessions, or a control group receiving traditional instruction. Pre- and post-tests assessed SEL competencies, motivation towards science, and academic achievements in science and mathematics. Results showed significantly greater gains in SEL skills, and in science motivation and science achievement in the intervention group compared to controls, whereas mathematics outcomes remained unchanged. Typically developing students and those with RD benefited similarly. Integration of SEL into science curricula thus enhances cognitive and social–emotional learning dimensions, particularly in linguistically and socio-economically marginalised populations. Implications for inclusive pedagogy and future research directions are discussed. Full article

This study is set against a backdrop of interest in understanding how secondary school pupils perceive learning experiences based on Augmented Reality (AR) and digital assessment, with the aim of designing a useful tool for comparative and replicable research in AR-STEM contexts. To this end, an attitudinal questionnaire was developed and preliminarily validated through a quantitative study conducted with a sample of 199 students from various schools who worked on science curriculum content using an AR application created and validated for the explanation of key concepts. The instrument, designed ad hoc based on the TAM and IMMS models and peer-reviewed, comprised 35 items. Its reliability and construct validity were analysed using Cronbach’s alpha and exploratory and confirmatory factor analysis. The results showed favourable scores for motivation, technological acceptance and the evaluation of digital assessment, alongside high internal consistency and a stable three-factor structure. In conclusion, the instrument presented in full in this study provides preliminary evidence that it is a valid, reliable and useful tool, although the digital assessment dimension remains emerging and will require further validation with independent samples. Full article

Questioning is widely recognised as a key dimension of learning in science education, yet learner questioning has often been treated as a secondary aspect of classroom participation rather than as a central pedagogical and epistemic practice. This article offers a conceptual examination of questioning in relation to science education for sustainability, informed by a critical interpretive engagement with literature on questioning, participation, classroom dialogue, engagement, and science education. It argues that science education for sustainability requires more than the transmission of scientific knowledge, calling instead for pedagogical spaces in which learners can engage with complexity, uncertainty, interpretation, and the ethical and social dimensions of socio-scientific issues. The article’s main contribution lies in repositioning learner questioning as a central condition of science education for sustainability and in showing that questioning is shaped not only by knowledge and motivation, but also by participation, hesitation, silence, and broader dynamics of voice, legitimacy, and power. In this perspective, fostering questioning becomes essential to more inclusive, dialogic, reflexive, and transformative approaches to science education for sustainability. The article further argues that fostering questioning in this way contributes directly to the educational ambitions embedded in SDG 4, SDG 13, and SDG 16—making questioning-centred pedagogy not merely a methodological choice, but a condition for more democratic, just, and transformative science education for sustainable development. Full article

Digital gamification may function as motivational scaffolding within situated course designs when it helps learners perceive progress, participate actively, and connect course activities with meaningful professional goals. This article examines how motivational scaffolds were designed and refined through digital gamification in a fourth-year science course in early childhood teacher education. Using a two-cycle design-based research approach, the study analyzed an initial FantasyClass-supported implementation and a subsequent redesigned version. In Cycle 1, broad affective outcomes, feature ratings, and open responses were associated with more favorable recent learning experiences, somewhat more favorable current views of science and its relevance, and higher perceived science-teaching capability and preparedness. Feature-level evidence identified progression, collaborative work, and narrative coherence as central motivational supports. These findings informed Cycle 2, which recalibrated selected mechanics and strengthened the narrative structure. Post-course Intrinsic Motivation Inventory results were descriptively consistent with above-midpoint enjoyment, perceived competence, and perceived choice, with enjoyment positively associated with competence and choice. Qualitative evidence highlighted active participation, progress awareness, and perceived relevance for future teaching. The findings suggest that, under the design conditions examined here, digital gamification may support motivationally meaningful course design when treated as motivational scaffolding rather than as an isolated reward system. Full article

Generative artificial intelligence (GenAI) is reshaping learning in higher education, with particularly pronounced implications for the humanities and social sciences (HSS), where learning outcomes are commonly expressed through written and interpretive forms that align closely with GenAI’s capabilities. Yet, systematic evidence on the educational impacts of GenAI on HSS students remains limited. Addressing this gap, this study draws on a large-scale survey of HSS students in China to examine its role in academic development. Guided by relevant learning theories, this study focuses on four dimensions: patterns of use, effects on learning processes and academic performance, challenges associated with GenAI use, and preferred approaches to curricular integration. We found that more than half perceived enhanced learning motivation, independent thinking and creativity, although a substantial minority reported little change or even decline. Comparatively, a notably larger majority reported academic performance gains, although these gains may partly reflect limitations in conventional assessment practices. The study identifies variations in perceived learning and performance improvements among students with differing durations of GenAI experience, along with observable disciplinary differences and modest gender differences. While an overwhelming majority valued the importance of ethical considerations, only slightly more than half were satisfied with privacy protection. Limited accuracy and overreliance emerged as the most pressing concerns reported by students. Students favored partial or optional curricular integration supported by practice-oriented training, and widely recognized GenAI’s significance for their future professional development. Grounded in student perspectives, this study offers evidence-based recommendations for the responsible and pedagogically meaningful integration of GenAI. Full article

Despite the growing use of artificial intelligence (AI) in science education, little is known about the motivational value of AI-supported digital tools in upper-primary ecosystem science learning. This quasi-experimental study examined whether participation in a teacher-guided digital ecosystems unit integrating AI-supported elements and interactive non-AI tools was associated with sixth-grade students’ ecosystem achievement, interest in science, attitudes toward science, and science self-efficacy. Four sixth-grade classes in an Israeli elementary school (123 students) participated. The experimental group completed six 45-min lessons; the control group studied the same content without the AI-supported components and integrated digital sequence. Students completed pretest and posttest questionnaires and an ecosystem achievement test; the experimental group also completed a satisfaction questionnaire. Semi-structured interviews were conducted with 10 students from the experimental group. Baseline-adjusted analyses indicated higher post-intervention achievement and motivational outcomes in the experimental group. Boys reported higher interest and self-efficacy than girls, and mothers’ education was positively associated with interest and attitudes. Within the experimental group, satisfaction was positively related to all motivational outcomes and significantly predicted self-efficacy. Interview themes highlighted visualization, feedback, collaboration, and occasional cognitive and technical challenges. Overall, this teacher-guided instructional package was associated with more favorable outcomes under classroom conditions in schools. Full article

This review paper presents a comprehensive and system-oriented analysis of advanced non-destructive testing (NDT) technologies for metal additive manufacturing (AM), including X-ray computed tomography (XCT), ultrasonic testing (UT), infrared thermography, acoustic emission (AE), and electromagnetic techniques. While the existing literature often focuses on the physical principles of individual NDT methods, this work addresses a critical knowledge gap by analyzing NDT as a digitally integrated “quality intelligence layer” rather than a standalone post-process inspection tool. The primary motivation is to bridge the disconnect between raw inspection data and cyber–physical production systems. Particular focus is given to NDT data analytics and digitalization, where machine learning (ML) and digital twin (DT) integration are discussed as fundamental enablers of intelligent manufacturing. The review systematically examines image and signal processing pipelines required for quantitative defect characterization, highlighting challenges related to voxel resolution, signal-to-noise ratio, anisotropic microstructures, and operator dependency. It further analyzes supervised learning, deep learning, and multi-sensor data fusion approaches for automated defect classification and predictive quality assessment. Furthermore, the role of digital twins in coupling in situ monitoring data, ex situ NDT results, and physics-based models is discussed as a transformative pathway toward closed-loop process control and evidence-based certification. By synthesizing NDT science with digital manufacturing architectures, this review contributes a unique framework for transitioning from traditional inspection-centric quality control to a predictive, adaptive, and digital twin-enabled quality assurance paradigm. The work concludes by identifying key research gaps in data standardization and computational scalability, providing a strategic roadmap for the future of smart AM production. Full article

Celestial bodies in the solar system have long been of particular interest in space science. Some questions, e.g., those concerning the origin of life, require on-site landing and exploration. Due to signal delay, some degree of autonomy provided by artificial intelligence (AI) is needed. Motivated by planetary exploration missions, the German Research Center for Artificial Intelligence (DFKI) has developed methods for (semi-)autonomous control of vehicles and robots on extraterrestrial bodies. To validate the software, we conduct extensive field tests in terrestrial analog environments. Field tests can be seen as an intermediate step between development and laboratory testing and real-world deployment in an extraterrestrial environment. This paper describes the challenges of testing AI and robotic systems in analog environments, with a focus on the additional dependencies that arise during the preparation and execution of such field tests. The robots and software tested in these field tests are based on more than a decade of development across various projects, covering a wide range of AI systems and applications, including geometric planning, probabilistic perception, deep learning, and robot construction for open challenges in planetary exploration. Full article

Immersive technologies—such as virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR)—are increasingly adopted in cultural heritage settings to support education, public engagement, and digital preservation. This scoping review systematically maps existing research on immersive learning within cultural heritage contexts, identifying major trends, pedagogical approaches, and reported outcomes. Following the PRISMA-ScR framework, nineteen studies were selected from 235 publications published between 2016 and 2025 across four databases: ACM Digital Library, Web of Science, ProQuest, and Scopus. Findings reveal a predominant focus on enhancing learner motivation, engagement, and the perceived authenticity of immersive experiences. However, empirical validation of learning outcomes—particularly regarding sustained knowledge retention, critical reflection, and inclusive participation—remains scarce. Persistent gaps are also evident in accessibility and scalability, alongside ethical concerns related to cultural sensitivity, power asymmetries, and the representation of diverse heritage voices. By foregrounding participatory and co-creation approaches, this review highlights how collaborative design processes can enhance learner engagement and support the sustainable digital preservation of cultural heritage. Full article