Search Results (327)

Modification to a thin beverage consistency is frequently recommended when swallowing is impaired, but proper thickening during preparation is essential. Contemporary technologies provide innovative ways of addressing quality control due to ongoing challenges in the accuracy of beverage preparation. This study explored two-dimensional (2D) and three-dimensional (3D) methods for visualizing beverages representing different levels of consistency (thin, mildly thick, or moderately thick). A total of 48 adults with limited knowledge about swallowing and no experience with thickened beverages participated. They learned about levels of modification and then viewed 2D images (photos) and 3D virtual models of beverage content. Results showed that their ability to recognize beverage consistency and their decision confidence was generally similar across dimensions even though study participants conveyed a strong preference for viewing 3D models. Qualitative findings underscored the importance of beverage attributes, especially color. Participants differed in their perceptions in using a constant (2D) or multiple angles (3D) when evaluating visualizations. Results help inform about the potential role of visual content in developing instructional resources about thickened beverages prescribed for patients with special medical needs. Full article

Proportional reasoning is a crosscutting concept identified as necessary for student success in upper-level mathematics as well as science, technology, and engineering. Research on middle-grade mathematics learning shows that students tend to develop stronger understandings of mathematical concepts when they learn through constructionist real-world projects that are relevant and meaningful to them. In this qualitative exploratory research study, we developed and implemented a Challenge-Based Learning through Making project for a middle school engineering class to investigate how students demonstrate their understanding of proportional reasoning through designing and making physical and digital artifacts, mentored by industry experts, and within the context of a school makerspace. Our findings showed that students accurately represented their understanding of proportionality through their digital artifacts more than any other modality available, contrasting previous findings in the relevant literature. Findings regarding the integration of professional technology for digital 3D modeling, mentorship of industry experts, and the prevalence of mathematical estimation in digital modeling provide avenues for further research vis-a-vis the role of expert mentorship in middle school STEM design challenges and mathematical estimation in spatial reasoning for design. Implications for the practice and the field of STEM learning are discussed. Full article

Following the significant disruption of traditional teaching by the COVID-19 pandemic, gamified education—an approach integrating technology and cognitive strategies—has gained widespread attention and use among educators and learners. This study explores how game-based learning, supported by situated learning theory and game design elements, can boost learner motivation and knowledge construction. Using 20,293 user comments from the Chinese video platform Bilibili, the study applies sentiment analysis and LDA to uncover users’ sentimental tendencies and cognitive themes. The analysis identifies four core themes: (1) The application of contextual strategies in language learning, (2) Autonomous exploration and active participation in gamified learning, (3) Progressive enhancement of logical thinking in gamified environments, and (4) Teaching innovation in promoting knowledge construction and deepening. Building on these findings, the study further develops a cognitive scaffolding model integrating “contextualization–procedural logic–active construction” to explain the mechanisms of motivation–cognition interaction in gamified learning. Methodologically, this study innovatively combines LDA topic modeling with sentiment analysis, offering a new approach for multidimensional measurement of learner attitudes in gamified education. Theoretically, it extends the application of situated learning theory to digital education, providing systematic support for instructional design and meaning-making. Findings enrich empirical research on gamified learning and offer practical insights for optimizing educational platforms and personalized learning support. Full article

Digital transformation (DT) is rapidly reshaping education at multiple levels, including curriculum, instructional practices, and institutional culture. Within this context, entrepreneurship education has become a key field for preparing individuals to navigate uncertainty and generate social and economic value in a digital society. Entrepreneurial competencies are increasingly conceptualized as a multidimensional construct that encompasses creativity, problem-solving, critical thinking, collaboration, and digital literacy. This study aims to identify core entrepreneurial competencies relevant to the digital era and examine how technology-integrated instructional strategies contribute to their development. A systematic literature review was conducted in accordance with PRISMA 2020 guidelines, analyzing 72 peer-reviewed journal articles published between January 2021 and June 2025. The findings indicate that DT drives structural changes in education beyond tool adoption, with technologies such as artificial intelligence (AI), data analytics, and digital collaboration platforms serving as catalysts for innovative thinking and entrepreneurial behavior. These technologies are not merely supportive tools but are embedded in competency-based learning processes. This review provides a comprehensive competency framework integrating three domains, AI-collaborative pedagogy validation, and implementation strategies, enabling educators, curriculum developers, and policymakers to redesign entrepreneurship education that aligns with the realities of digital learning environments and fosters future-ready entrepreneurial capabilities. This conceptual framework theoretically systematizes the integration of innovative thinking and ethical execution capabilities required in the digital era, contributing to defining the future direction of entrepreneurship education. Full article

Educational reforms increasingly require teachers to implement innovations, yet these efforts often remain unsustainable. Effective implementation is closely tied to continuous professional development and learning (CPDL). This study explores how a CPDL path supports the transition from current teaching practices to enhanced instructional methods that integrate a STEM innovation focused on improving students’ spatial ability—a critical cognitive skill linked to STEM success, especially in early education. While professional development (PD) can foster practices that support spatial thinking, few studies have examined how teacher learning translates into measurable student gains. This study evaluates the impact of a CPDL program that combined expert-led workshops with Lesson Study (LS), a collaborative and reflective approach. The program was tailored to 24 female STEM teachers whose profiles showed limited cognitively active learning opportunities for students. Pre- and post-intervention assessments measured changes in student performance across three spatial components: visualization, mental transformation, and orientation. Students in Grades 1–3 showed statistically significant gains (p < 0.00001), with the strongest improvement in spatial visualization. Grade 3 students made the largest relative gains, indicating developmental readiness. Findings highlight the value of stepwise preparation and leadership support in innovation implementation, offering strong empirical evidence that LS-based CPDL improves both teaching and student cognitive outcomes. Full article

This paper explores how primary school teachers integrate digital technologies into their classroom practice, with a particular focus on the extent to which their stated intentions align with what actually takes place during lessons. Drawing on data from the Bulgarian SUMMIT project on digital transformation in education, the study employed a mixed-methods design combining semi-structured interviews, structured lesson observations, and analysis of teaching materials. The sample included 44 teachers from 26 Bulgarian schools, representing a range of educational contexts. The analysis was guided by the Digital Technology Integration Framework (DTIF), which distinguishes between three modes of technology use—Support, Extend, and Transform—based on the depth of pedagogical change. The findings indicated a strong degree of consistency between teachers’ accounts and observed practices in areas such as the use of digital tools for content visualisation, lesson enrichment, and reinforcement of knowledge. At the same time, the study highlights important gaps between teachers’ aspirations and classroom realities. Although many spoke of wanting to promote independent exploration, creativity, collaboration, and digital citizenship, these ambitions were rarely realised in observed lessons. Pupil autonomy and opportunities for creative digital production were limited, with extended and transformative practices appearing only occasionally. No significant subject-specific differences were identified: teachers across disciplines tended to rely on the same set of familiar tools, while more advanced or innovative uses of technology remained rare. Rather than offering a definitive account of progress, the study raises critical questions about teachers’ digital pedagogical competencies, contextual constraints and the depth of technology integration in everyday classroom practice. While digital tools are increasingly present, their use often remains limited to supporting traditional instruction, with extended and transformative applications still aspirational rather than routine. The findings draw attention to context-specific challenges in the Bulgarian primary education system and the importance of aligning digital innovation with pedagogical intent. This highlights the need for sustained professional development focused on learner-centred digital pedagogies, along with stronger institutional support and equitable access to infrastructure. Full article

Artificial Intelligence (AI) is reshaping higher education by enabling personalized learning (PL) and enhancing teaching and learning practices. To examine global research trends, pedagogical paradigms, equity and sustainability considerations, instructional strategies, learning outcomes, and interdisciplinary collaboration, this study systematically reviewed 29 articles indexed in the Social Sciences Citation Index (SSCI) Q1, representing the top 25% of cited articles, published between January 2020 and December 2024 in the Web of Science database. Results indicate that AI-PL research is concentrated in Asia, particularly China, and predominantly situated within education and computer science. Quantitative designs prevail, often complemented by qualitative insights, with supervised machine learning as the most common algorithm. While constructivist principles implicitly guide most studies, explicit theoretical grounding improves AI-pedagogy alignment and educational outcomes. AI demonstrates potential to enhance instructional approaches such as PBL, STEAM, gamification, and UDL, and to foster higher-order skills, yet uncritical use may undermine learner autonomy. Systematic attention to equity and SDG-related objectives remains limited. Emerging interdisciplinary collaborations show promise but are not yet fully institutionalized, constraining integrative system design. These findings underscore the need for stronger theoretical framing, alignment of AI with pedagogical and societal imperatives, and professional development to enhance educators’ AI literacy. Coordinated efforts among academia, industry, and policymakers are essential to develop scalable, context-sensitive AI solutions that advance inclusive, adaptive, and transformative higher education. Full article

Post-monolingual circumstances are increasing reflecting the growing occurrence of multilingualism, migration, and advancing communication technologies. Cultural groups value maintaining heritage languages while also learning the ones in their new life environments. Heritage language maintenance is, for example, promoted by immigrant parents and grandparents in the Northern Netherlands, as well as in other locations. Maintaining cultural heritage language also needs innovative instructional approaches and pedagogy. This article presents a study exploring the role of peer collaboration in supporting children’s Chinese heritage language use and learning in New York City. Drawn from sociocultural theory and extended in prior research examining peer collaboration in writing development, we focused on understanding the role of peer collaboration in Chinese immigrant children’s Chinese heritage language use in an after-school (Sunday school) program. In collaboration with organizers of the school, our study involved a 30 min peer collaboration writing activity. The activity invited children to collaborate with a peer to write a letter about the fun experiences they had in the Chinese language school. Interaction processes and products were collected and analyzed to address two primary research questions including the following: What are the languages and peer collaboration processes that children in this Chinese language school used in their conversations and in the text of the letters they created together? How did children’s use of Chinese and English during peer collaboration relate to language in the texts they wrote? Results indicated that children played diverse, mutually supportive roles during their collaboration, such as suggesting narrative sequences for the letter, including confirming/agreeing, and correcting and clarifying, although different pairs balanced such strategies somewhat differently. Among numerous findings is that children used Mandarin most frequently when narrating events that they found enjoyable at the Chinese language school. The findings fill a gap in research on multilingual peer collaboration, in particular with Chinese and English in the United States. In addition to those findings, research in an after-school heritage language program provides a model for innovative research in practice. Full article

This study investigates the impact of a gamified educational experience on the training of future teachers, focusing on a visit to the Natural History Pavilion at the University of Almería, compared to a traditional instructional approach. A quasi-experimental pre-test–post-test design was employed with both undergraduate and master’s degree teacher education students, combining quantitative analysis with complementary data. The findings indicate that participants in the gamified groups demonstrated significant gains in knowledge acquisition following the visit, as well as higher levels of appreciation for the activity itself. This study concludes that gamification cognitively enriches the museum learning experience and stands out as an innovative and pedagogically relevant strategy in teacher education. Full article

The creation of digital educational games often lacks strong user-centered design despite available frameworks, which tend to focus on technical and instructional aspects. This paper presents the Empathic Design Thinking Framework (EDTF), a structured methodology tailored to digital educational game creation. Rooted in human–computer interaction (HCI) principles, the EDTF integrates continuous co-design and iterative user research from ideation to deployment, involving both learners and instructors throughout all phases; it positions empathic design (ED) principles as an important component of HCI, focusing not only on identifying user needs but also on understanding users’ lived experiences, motivations, and frustrations. Developed through design science research, the EDTF offers step-by-step guidance, comprised of 10 steps, that reduces uncertainty for novice and experienced designers, developers, and HCI experts alike. The framework was validated in two robust phases. First, it was evaluated by 60 instructional game experts, including designers, developers, and HCI professionals, using an adapted questionnaire covering dimensions like clarity, problem-solving, consistency, and innovation, as well as standardized scales such as UMUX-Lite for perceived ease of use and usefulness and SUS for perceived usability. This was followed by in-depth interviews with 18 experts to understand the feasibility and conceptualization of EDTF applicability. The strong validation results highlight the framework’s potential to guide the design and development of educational games that take into account HCI principles and are usable, efficient, and impactful. Full article

Traditional lecture-based teaching often struggles to foster student engagement, active participation, and deep learning in large-class general education courses. As class sizes grow, students may become passive learners, limiting their ability to develop essential skills such as self-directed learning and teamwork. Innovative instructional strategies are needed to address these challenges and create a more interactive, student-centered learning environment. Team-Based Learning (TBL) has emerged as a practical pedagogical approach that promotes collaboration, critical thinking, and student accountability. This study investigates the influence of TBL on Self-Directed Learning (SDL) and Team Dynamics (TD) through a quasi-experimental design. One class was classified as the experimental group (TBL), while the other was classified as the control group (traditional lecture-based teaching). Data were analyzed using independent-samples one-way ANCOVA and the Johnson–Neyman method to examine the impacts of TBL on SDL and TD. The results indicate that the experimental group adopting TBL outperformed the control group in both SDL and TD. The ANCOVA results revealed that TBL had a significant positive impact on the self-monitoring factor of SDL after controlling for pre-test scores. Furthermore, the Johnson–Neyman analysis demonstrated that the effect of TBL varied across different pre-test levels, suggesting that the influence of TBL on SDL and TD was more pronounced under certain conditions. Overall, this study supports the effectiveness of TBL as a pedagogical strategy in large-class general education courses, highlighting its potential to enhance students’ SDL and TD. These findings provide valuable insights for future teaching practices and curriculum design, emphasizing the need for more interactive, student-centered learning approaches in higher education. Full article

The development of online courses aligned with sustainable education principles is crucial for equipping learners with 21st-century skills essential for a sustainable future. As online education expands, predicting achievers (in this research, students with a final grade of seven or higher) becomes essential for optimizing instructional strategies and improving retention rates. This study employs a Linear Discriminant Analysis (LDA) model to predict academic performance in an online theatre course rooted in sustainable education principles. Engagement metrics such as total logins and collaborative assignment completion emerged as decisive predictors, aligning with prior research emphasizing active learning and collaboration. The model demonstrated robust performance, achieving 90% accuracy, 80% specificity, and an 88% correct classification rate. These results underscore the potential of machine learning in identifying achievers while highlighting the significance of sustainable pedagogical components. Future research should explore emotional engagement indicators and multi-course validation to enhance predictive capabilities. By utilizing the e-learning system information, the presented methodology has the potential to assist institutional policymakers in enhancing learning outcomes, advancing sustainability goals, and supporting innovation across the educational and creative sectors. Full article

The significance of children’s mathematical competence during the early years is well established; however, the methods for developing such competencies remain less understood. Specifically, there is a need to identify what constitutes high-quality educational environments and effective instruction. Both the study and promotion of high-quality educational environments and teaching, through coaching and other professional development initiatives, necessitate the use of observational instruments that are reliable, efficient, and valid, including content, internal, external, and consequential validity. Moreover, domain-specific measures are essential, as general quality measures often fail to adequately assess curriculum content, scope, or sequence, and they do not reliably predict improvements in children’s learning outcomes. This study employed innovative analytical techniques to evaluate the scoring and interpretation of an existing domain-specific observational measure: the Classroom Observation of Early Mathematics Environment and Teaching (COEMET). We applied non-linear modeling approaches (i.e., Random Forest [RF] and Generalized Additive Models [GAMs]) to investigate and provide a comprehensive overview of the relationships between COEMET’s measures—at both the scale and item levels—of teachers’ practices and children’s mathematical competencies. The study first employed the RF machine learning method to identify the most important COEMET items for prediction, followed by the use of GAMs to depict the non-linear relationships between COEMET predictors and the outcome variable. The analysis revealed that certain teaching practices, as indicated by the COEMET items, exhibited non-linear and even non-monotonic associations with children’s mathematical competencies. Full article

This systematic review investigates the integration of artificial intelligence (AI) and information and communication technologies (ICT) in physical education across all educational levels. Physical education is uniquely centered on motor skill development, physical activity engagement, and health promotion—outcomes that require tailored technological approaches. Through the analysis of recent empirical studies, the main areas where digital technologies contribute to pedagogical innovation are highlighted—such as personalized learning, real-time feedback, student motivation, and educational inclusion. The findings show that AI-assisted tools facilitate differentiated instruction and self-regulated learning by adapting to students’ individual performance levels. Technologies such as wearables and augmented reality (AR)/virtual reality (VR) systems increase engagement and support the participation of students with special educational needs. Furthermore, AI contributes to more efficient and objective assessment of motor performance, coordination, and movement quality. However, significant structural and ethical challenges persist, such as unequal access to digital infrastructure, lack of teacher training, and concerns related to personal data protection. Teachers’ perceptions reflect both openness to the educational potential of AI and caution regarding its practical implementation. The review concludes that AI and ICT can substantially transform physical education, provided that coherent policies, clear ethical frameworks, and investments in teachers’ professional development are in place. Full article

Problem-based learning (PBL) has been recognized for enhancing student motivation and key competencies. However, its integration with emerging topics such as ESG (Environmental, Social, and Governance) in general education remains underexplored. This study implemented a PBL-based instructional design in a general education course titled “Organizational Greenhouse Gas Inventory and Net-Zero Transition,” integrating practical tasks and ESG case studies to enhance students’ sustainability literacy and core competencies. Pre- and post-course assessments were conducted using the University Career and Competency Assessment Network (UCAN) questionnaire, analyzed through paired sample t tests and Wilcoxon signed rank tests. Results showed significant improvements in the innovation and communication aspects, with upward trends observed in other domains. Students also demonstrated strong engagement and learning motivation through tasks such as carbon footprint estimation, data integration, and field-based assessments. The findings support the feasibility of embedding ESG and PBL frameworks in general education. Future course iterations will consider differentiated instructional design and the incorporation of qualitative methods to accommodate diverse student backgrounds and enhance learning outcomes, contributing to the advancement of sustainability education in higher education. Full article