ABSTRACT Background Science, Technology, Engineering and Mathematics (STEM) youth interest and enrollment is experiencing a globally extended global decline. The capabilities of K-6 educators to motivate every learner towards pursuing STEM careers have been considered a focus of interest to revert the trend. Purpose This study examined the professional development process of K-6 pre-service educators participating in an online course centered on the curricular and pedagogical integration of STEM via educational robotics. The course was structured following the Technological Pedagogical Content Knowledge (TPACK) framework. Sample A total of n = 679 K-6 pre-service STEM teachers participated in this study. Design and Methods A pre-experimental study design was followed. Data included self-reported quantitative measures pertaining to STEM disciplinary knowledge, pedagogical knowledge and the attainment of the often STEM-related 21st century skills, alongside ad-hoc indices reflecting perceived barriers to STEM education. The course was administered following a MOOC-like format: students were able to freely access course materials on demand. Results The findings reveal improvements in all areas, as well as underlying gender and degree-based gaps in baseline attainment and professional development. Males showed better baseline levels and development throughout the intervention of STEM knowledge. Females showed a similar trend with regards to attainment of 21st century skills, as well as a higher increase in perceived barriers to STEM education. Early childhood pre-service educators tended to show less development and improvement of STEM disciplinary knowledge and didactic barriers to STEM education. Conclusion The online course showed satisfactory results regarding the attainment of knowledge and skills pertaining to STEM education. Nonetheless, the interiorization of barriers to STEM education amongst prospective teachers, as well as the varying profiles based on sex and enrolled degrees, needs to be taken into consideration to define an initial teacher training curriculum that fulfills the needs of every enrolled profile.

Social determinants of health (SDOH), the nonmedical factors influencing patients across individual and systematic levels, are essential to comprehensive healthcare. However, there is varied guidance in exactly how it should be taught or assessed in physician assistant (PA) programs, as well as what methodologies are effective or preferred by students. A between-and-within groups study was designed for first-year PA students to evaluate their opinions, confidence levels, and comfort regarding SDOH delivered by 2 brief educational modules (one using an expert panel and the other a gamified approach). A total of 48 students participated in the study. Results found that students appreciated the importance of SDOH to patient care and valued the application of clinical and public health resources. Students' confidence and comfort levels regarding SDOH improved following each educational module (P < .05 pre vs. post comparisons). Students valued modular approaches to learning SDOH and equally prefer the panel and game formats. Students ranked direct clinical care as their highest preference in how they would prefer SDOH principles to be taught, followed by case-based learning, panel-based, and gamified-based approaches. Online learning was the least preferred teaching method. These results suggest (1) modular approaches may be an effective means to teach SDOH, (2) SDOH could be taught longitudinally across the curriculum to reinforce understanding, and (3) delivery of SDOH curricula in PA education could consider nontraditional formats that promote interactive learning.

The digital transformation of e-commerce has dramatically reshaped Indonesia’s business landscape, with transaction values projected to reach USD 80 billion by 2025. Nevertheless, this rapid expansion has simultaneously produced critical ethical challenges, including price manipulation, exploitation of personal data, and structural injustice that disadvantages MSME actors. This study aims to analyze the relevance of Islamic business ethics norms from Al-Ghazali’s perspective within the context of the Shopee platform and to formulate applicable strengthening strategies. Utilizing a qualitative method through a literature-based approach examining Al-Ghazali’s works and 45 contemporary studies (2015–2025), this research investigates four fundamental principles of Islamic business ethics: mashlahah (public benefit), niyyah (sincere intention), sidq (honesty), and ‘adl (justice). The findings reveal that the implementation of these principles through features such as rating systems, product reviews, and dispute-resolution centers can enhance consumer protection by up to 65%. However, significant obstacles remain, including uneven product transparency (40%), misuse of reviews (15–20%), and the dominance of profit-driven motives (70%). The study proposes five key strategic recommendations: digital ethics education, AI-Blockchain-based verification systems, integration of mashlahah into recommendation algorithms, multi-stakeholder collaboration, and the development of an Islamic Business Ethics Index (IBEI). Consistent implementation of Al-Ghazali’s ethical principles is expected to foster an e-commerce ecosystem that is equitable, transparent, and oriented toward collective welfare.

The article examines the development of the concept of pedagogical support in domestic pedagogy. It presents a broad historical and social context in which this concept emerged. The aim of the article is to investigate the origins of the ideas about supportive activities in our country, various approaches to defining its content, and the prospects for further development. Methodology and research methods. The article employs an analysis of the emergence and development of ideas about supportive activities in domestic pedagogy, their current state, and prospects for further development. Results of the research. It is demonstrated that the idea of supportive activities is reflected in the works of many classics of world and domestic pedagogy. In Russia, the emergence of the concept of pedagogical support in its modern form can be traced back to the late 20th century and is associated with the works of O. S. Gazman. The article discusses the further development of the concept, related to the clarification of its subject matter, as well as the emergence of ideas about tactics, principles, and stages of pedagogical support. The transformation of supportive activity practices in relation to the digitalization of education, the spread of distance online education, and restrictions caused by the pandemic is investigated. An analysis of various approaches to understanding pedagogical support is conducted. In conclusion, it is demonstrated that despite the variety of approaches, the central principles for this concept remain: the humanistic position of the educator, assistance to the child in the process of individualization, and collaboration between the educator and the child. The prospects for the further development of ideas about pedagogical support are considered.

Massive open online courses (MOOCs) are well-known for offering flexible learning; however, they also pose challenges for English-as-a-foreign-language (EFL) learners, particularly in maintaining motivation and engagement in such self-paced learning online courses. This study explored the factors influencing EFL students' participation in a MOOC through the lens of Expectancy-Value Theory and Socio-Cognitive Theory. Employing a qualitative design, involving 31 EFL students from a private university in the Mekong Delta enrolled in a public speaking MOOC, the study collected data of 20 reflective journals and 12 semi-structured interviews from these participants. The data was analyzed using reflexive thematic analysis. The findings revealed that student engagement increased when learners expected success, perceived the course as valuable, and employed self-regulated learning strategies. Motivation was sustained through goal setting, time management, and persistence; however, language barriers, technological issues, and social isolation impeded learning. Despite these obstacles, students use goal setting, time management, and persistence to sustain motivation. Expectancy–value theory (EVT) explains how perceived value and expectations of success shape engagement, whereas social cognitive theory (SCT) emphasizes self-efficacy and self-regulation as key drivers of motivation. These findings can inform educators, curriculum designers, and policymakers in developing more supportive online learning environments. Alongside recommending inclusive instructional strategies, including linguistic support, interactive content, and community-building, the study urges research into the long-term effects of SRL strategies and the effectiveness of SRL-based training for EFL learners in varied MOOC contexts.

In the context of the accelerating digital transformation of higher education worldwide, Artificial Intelligence (AI) has emerged as a pivotal driver for innovating online learning models, enhancing teaching quality, and optimizing learners’ experiences. In Vietnam, private universities - characterized by institutional flexibility, intense competitive pressure, and a high degree of financial and academic autonomy - are increasingly required to adopt AI as a strategic instrument to improve educational quality and institutional competitiveness. Despite its significant potential, the implementation of AI in online training across Vietnamese private universities remains fragmented, unsystematic, and constrained by multiple challenges related to technological infrastructure, human resources, financial capacity, governance mechanisms, as well as ethical and legal frameworks. This study aims to provide a comprehensive examination of the current state of AI application in online education at private universities in Vietnam, to identify key barriers hindering effective implementation, and to propose strategic solutions tailored to the national and institutional context. Employing a mixed-methods research design, the study integrates quantitative survey data with qualitative insights derived from in-depth interviews with university leaders, faculty members, and students. The findings indicate that AI has been preliminarily applied in areas such as intelligent learning management systems, personalized learning pathways, AI-powered chatbots, and learning analytics. However, the depth and effectiveness of these applications remain limited, and their transformative potential has yet to be fully realized. Drawing on empirical evidence and international best practices, the paper proposes a strategic framework encompassing institutional governance reform, digital and AI-oriented capacity building, investment in data-driven infrastructure, and the development of a sustainable AI-enabled educational ecosystem for private higher education institutions. This study contributes to the growing body of literature on AI in higher education within developing country contexts, while also offering practical managerial and policy implications for advancing the digital transformation and long-term sustainability of Vietnam’s private university sector

Artificial Intelligence (AI) has become integral to education, transforming the way students approach mathematics. This qualitative study examines the perceptions, experiences, and usage patterns of BS Applied Mathematics students in using AI tools such as ChatGPT, Gemini, Meta AI, and Cici for solving mathematical problems within the context of Technology-Enhanced Learning (TEL). Grounded in the Technology Acceptance Model (TAM), it explores five dimensions: usefulness, ease of use, attitude toward use, behavioral intention, and actual use. Data was analyzed using both phenomenological and thematic approaches, incorporating interviews, focus group discussions, and observations. Students primarily used AI tools for speed, convenience, and quick solutions under time pressure. While most preferred AI as a complement to traditional learning, they expressed concerns about overreliance, limited understanding, and reduced motivation. Nonetheless, students demonstrated digital literacy by validating AI outputs and using multimodal resources, such as YouTube tutorials, to enhance comprehension. The study advocates for balanced AI integration in education, emphasizing digital literacy, responsible use, and the development of improved AI-based platforms to strengthen multimodal and explainable learning within TEL frameworks.

This study examines the effects of digital books and interactive instructional videos on students’ learning outcomes in Islamic Religious Education (IRE). Employing a quantitative approach with a quasi-experimental nonequivalent control group design, the study involved 68 eleventh-grade students selected through purposive sampling from a population of 209 students. Data were collected using achievement tests and questionnaires and analyzed through descriptive and inferential statistics. The findings reveal that the use of digital books resulted in a mean score of 42.53 and demonstrated a significant effect on IRE learning outcomes (t = 2.140 &gt; 2.037; R² = 0.250), indicating a 25% contribution to learning improvement. In contrast, interactive instructional videos produced a higher mean score of 55.24 and showed a stronger significant effect (t = 2.631 &gt; 2.037; R² = 0.770), contributing 77% to the variance in learning outcomes. Furthermore, the independent samples test indicated a statistically significant difference between the two groups (p = 0.000 &lt; 0.05), with interactive video instruction outperforming digital books. These findings demonstrate that interactive digital media characterized by audiovisual integration and learner engagement provide greater pedagogical impact in IRE instruction compared to text-based digital resources. The study contributes to the development of digital Islamic education by providing empirical evidence on the comparative effectiveness of structured digital textbooks and interactive multimedia approaches. It offers a data-driven foundation for integrating adaptive and interactive technologies into IRE classrooms to enhance academic achievement and promote more effective technology-supported religious education.

ABSTRACT Personalized Learning through Cognitive State Analysis is an intelligent web-based learning system that monitors a learner’s attention level using real-time webcam analysis. The system detects facial presence and eye activity using OpenCV and Haar Cascade algorithms to determine whether the learner is attentive or distracted. Based on the detected cognitive state, the system dynamically adapts the learning content. If the learner is attentive, video-based learning continues. If the learner is distracted multiple times, the system recommends alternative learning modes such as text-based content or quizzes. The platform also provides a dashboard to analyze attentive time, distracted time, and overall performance. This system aims to improve learning efficiency, engagement, and personalization in digital education environments. Keywords: Personalized Learning, Cognitive State Analysis, Haar Cascade, OpenCV, Adaptive Learning, Attention Detection, E-learning.

Comment on “Perspectives on the Teaching and Learning of Non-Verbal Communication Skills: Tutor, Simulated Patient and Student Experiences of a Rapid Transition to Online Learning”

Purpose of the study: This study investigates the transformative role of Meaning Reconstruction (MR) in mediating the relationship between Post-Purchase Dissonance (PPD) and Eudaimonic Well-Being (EWB) in the context of digital education service consumption in Indonesia. Methodology: This study employs a quantitative explanatory design using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Data were collected through web scraping from 500 publicly accessible posts on Twitter (X), Reddit, and TikTok discussing post-purchase experiences with digital education services in Indonesia (2020–2024). Computational text analysis using a fine-tuned IndoBERT model was applied to derive construct scores for PPD (X1–X3), MR (M1–M4), and EWB (Y1–Y4). Indicators were quantified using algorithmically normalized NLP-based semantic intensity scores ranging from 1 to 7, representing computational estimations of construct magnitude rather than self-reported NLP-based normalized semantic score (1–7) responses. Main Findings: Results confirm that PPD significantly influences MR (β=0.446, p&lt;0.001) and MR strongly predicts EWB (β=0.481, p&lt;0.001). The direct path PPD→EWB is significant (β=0.176, p&lt;0.001), while the indirect effect via MR is also significant (β=0.214, t=8.248, p&lt;0.001), with a Variance Accounted For (VAF) of 54.8%, indicating partial mediation. R²(MR)=0.199 and R²(EWB)=0.338. All measurement model criteria are satisfied: outer loadings &gt;0.70, AVE &gt;0.50, CR &gt;0.70, and HTMT &lt;0.85. Novelty/Originality of this study: Reconstruction as a critical transformative mechanism, reframing post-purchase dissonance from a purely negative outcome into a catalyst for consumer psychological growth. The use of computational text analysis (NLP + web scraping) as an alternative to conventional surveys further contributes methodological novelty.

Purpose This study aims to explore how Mentimeter, a student response system (SRS), fosters agentic and emotional engagement in undergraduate TESOL courses at an English-medium instruction (EMI) university in China. It addresses specific challenges related to student passivity and language anxiety to bridge the theory–practice gap in teacher education. Design/methodology/approach Data were collected from 47 undergraduate students via pre- and post-intervention surveys and analyzed using paired-samples t-tests to measure changes in engagement. To explain quantitative trends, focus group discussions (n = 12) were conducted and analyzed thematically, providing deeper insights into student perceptions of specific interactive features. Findings Quantitative results revealed a statistically significant increase in agentic engagement, while emotional engagement showed slight, non-significant improvement. Qualitative findings revealed four themes: creating a safe environment, acknowledging individual agency, enhancing interaction and participation and promoting cognitive depth. These themes suggest a pedagogical progression: Mentimeter’s anonymity first fosters psychological safety, serving as a necessary foundation for students to subsequently exercise agency and engage in deeper cognitive learning. Practical implications Educators should integrate SRS tools strategically, beginning with low-stakes, anonymous activities (e.g. quiz games, word clouds) to establish emotional safety before scaffolding toward cognitively demanding tasks (e.g. open-ended critiques or reflections). This staged progression from foundational conditions to active engagement to cognitive outcomes provides a practical framework for sequencing technology-enhanced activities in contexts characterized by language anxiety or student passivity. Originality/value This research contributes a nuanced understanding of technology-enhanced learning in EMI contexts by distinguishing between emotional and agentic dimensions. It proposes a staged engagement framework arguing that SRS tools are essential for reducing language anxiety and establishing the psychological safety required for developing learner agency and critical thinking.

Background/Objectives: Stroke frequently leads to balance deficits. Vestibular physical therapy (VPT) may enhance postural control through neuroplastic mechanisms. Virtual reality (VR) can provide ecologically valid environments for rehabilitation, increasing patient engagement. Methods: In this randomized feasibility study, nine individuals with chronic stroke were randomized to either a Real visuo–vestibular rehabilitation group (n = 6) or a Sham VR group (n = 3) to explore the feasibility of the protocol and randomization procedures rather than to compare clinical efficacy. Both groups were trained in immersive VR environments for 12 sessions. The Real group experienced visuo–vestibular stimuli requiring sensorimotor integration; the Sham group trained in the same environments without such stimuli. Feasibility was assessed through attendance, participation (Pittsburgh Rehabilitation Participation Scale, PRPS), and user satisfaction (USEQ). Safety and acceptability were monitored through adverse event reporting. Secondary exploratory outcomes included measures of balance—the Mini Balance Evaluation Systems Test (MiniBESTest), the Berg Balance Scale (BBS), and the Performance-Oriented Mobility Assessment (POMA)—as well as functional independence (Barthel Index), health-related quality of life (Stroke-Specific Quality of Life Scale, SSQoL), and a set of spatiotemporal and gait quality parameters derived from inertial measurement unit (IMU) data collected during the 10-Meter Walk Test and the Figure of 8 Walk Test. Results: All participants completed the protocol without adverse events. Participation, as measured by the PRPS, remained consistently high across sessions (mean ≥5.7/6), while USEQ scores indicated excellent user satisfaction (mean ≥28/30). Exploratory analyses revealed improvements in MiniBESTest and BBS scores for the Real group. Instrumental measures derived from IMUs demonstrated improvements across groups. Conclusions: Exploratory outcomes suggested positive trends in balance improvements, and the integration of clinical scales with wearable sensors proved feasible and informative.

Rapid Discrimination and Quantification of Adulterants in High-Value Yak Milk Using Electronic Nose and Machine Learning

Nursing students tend to have negative feelings toward taking statistics courses. In an attempt to address these feelings, a nursing professor and a mathematics professor formed a partnership to reimagine and teach the required online, asynchronous statistics course for nursing graduate students. The backward design approach was used to create effective learning experiences for students to meet learning outcomes. Evidence-based teaching strategies were utilized to ensure the course was inclusive and met best practices for online teaching. The perspectives of both a mathematician and nurse were vital in determining what would constitute evidence students had achieved the learning outcomes; statistical rigor was balanced with real-world applicability. Students in the pilot group reported enjoying the course more than expected and also successfully met the learning outcomes. This interdisciplinary partnership provided a multitude of benefits to student learning. We recommend nursing programs pilot coteaching required statistics courses.

Inquiry Based Learning (IBL) has emerged as a transformative pedagogical approach in mathematics education, emphasizing student-centered exploration and critical thinking. This study conducts a bibliometric analysis to explore trends, influential contributors, and research themes in IBL within mathematics education. A total of 82 publications were retrieved from the Scopus database, covering the period from 2008 to 2024. Analytical tools such as biblioMagika® were employed for metric calculations, OpenRefine for data cleaning, and VOSviewer for network visualization. The analysis reveals a notable increase in IBL research after 2016, with a peak in 2024, driven by the integration of digital tools and the growing emphasis on problem-solving skills in mathematics education. The leading contributors include countries such as the United States, Australia, and the Netherlands, with institutions like the University of California and Utrecht University playing pivotal roles. Highly cited publications from authors such as Katja Maass and Sandra L. Laursen underscore the field’s academic impact. Core research themes identified include constructivism, technology-enhanced learning, and mathematical modeling, with frequent keywords being "inquiry based learning," "mathematics education," and "problem-solving." Citation metrics indicate an h-index of 17 and an average citation rate of 11.38 per publication, reflecting the scholarly influence of IBL research. This comprehensive analysis offers valuable insights for educators, researchers, and policymakers, advocating for continued exploration of IBL's potential to enhance mathematical understanding and inquiry-driven learning outcomes.

Embracing the challenge: Predicting self-testing in non-formal online courses using machine learning

Online learning with a hedge-based random vector functional link network using multi-forgetting factors

Machine learning methods for small data and upstream bioprocessing applications: A comprehensive review.

Understanding cyberloafing in video-conferencing-enabled online learning: A resource-based perspective