Search Results (5)

Most adaptive learning systems personalize around content sequencing and difficulty adjustment rather than transforming instructional material within the lesson itself. This paper presents the STREAM (Semantic Transformation and Real-Time Educational Adaptation Multimodal) framework. This modular pipeline decomposes multimodal educational content into semantically tagged, pedagogically annotated units for regeneration into alternative formats while preserving source traceability. STREAM is designed to integrate automatic speech recognition, transformer-based natural language processing, and planned computer vision components to extract instructional elements from teacher explanations, slides, and embedded media. Each unit receives metadata, including time codes, instructional type, cognitive demand, and prerequisite concepts, designed to enable format-specific regeneration with explicit provenance links. For a predefined visual-learner profile, the system generates annotated path diagrams, two-panel instructional guides, and entity pictograms with complete back-link coverage. Ablation studies confirm that individual components contribute measurably to output completeness without compromising traceability. This paper reports results from a tightly scoped feasibility pilot that processes a single five-minute elementary STEM video offline under clean audio–visual conditions. We position the pilot’s limitations as testable hypotheses that require validation across diverse content domains, authentic deployments with ambient noise and bandwidth constraints, multiple learner profiles, including multilingual students and learners with disabilities, and controlled comprehension studies. The contribution is a transparent technical demonstration of feasibility and a methodological scaffold for investigating whether within-lesson content transformation can support personalized learning at scale. 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

Science, technology, engineering, and mathematics (STEM) are crucial for economic development and play a significant role in achieving sustainable development goals. Despite this, there is a shortage of skilled STEM professionals and a declining interest in STEM education and careers. The Saudi Vision 2030 goal of economic diversification and sustainable development aims to transform Saudi Arabia into a knowledge-based economy driven by innovation and sustainability. This study investigates factors influencing adolescents’ attitudes toward STEM careers in Saudi Arabia, with comparative insights from Bahrain and Singapore. Structural equation models (SEM) were constructed for each country to analyze the influence of scientific self-concept, school belonging, and teacher effectiveness on students’ choices of science careers. Mediation analysis examined the interest and value of science as mediators in these relationships. Confirmatory factor analysis was conducted to validate model constructs before building SEM models. Data from TIMSS 2019 for eighth-grade students was used to develop model constructs based on relevant items from the student questionnaire. Findings reveal that students’ interest in and value of science significantly influence career decisions, with self-concept and teacher engagement playing crucial roles. Teacher effectiveness had the strongest impact on science interest in Saudi Arabia and Bahrain, while self-concept was most influential in Singapore. These results highlight the importance of fostering teacher engagement and self-concept to encourage students’ career paths in science. To support this, Saudi Arabia should enhance teacher training programs by integrating mentorship, active learning strategies, and technology driven instruction to improve student engagement. Adopting Singapore’s blended learning model can foster self-confidence and independence in STEM education, while hands-on learning and career exposure programs can strengthen students’ self-concept and long-term commitment to STEM fields. Additionally, expanding extracurricular STEM initiatives and industry partnerships will help connect classroom learning to real-world applications. By aligning STEM education reforms with these insights, Saudi Arabia can cultivate a skilled workforce that supports its economic transformation under Vision 2030. Full article

Solving a problem requires and promotes a diversity of competencies, which include conceptual knowledge, technical and methodological knowledge, and transversal competencies. Everyday STEM-relevant problems are contextualized, ill structured, and multidisciplinary in nature. By focusing on daily life issues, they promote students’ engagement in the problem-solving process and enable them to perceive how science relates to their lives. This paper aims to characterize the processes followed by prospective primary school teachers when solving three STEM-relevant problems that have different features. The qualitative analysis of 77 participants’ answers showed that complete problem-solving pathways were one among a variety of other paths identified. Most strategies adopted by the participants led them to ignore the contextual conditions of the problem and to reach solutions that did not attend to them. The affective relationship with the object may increase the problem solver’s tendency to ignore the contextual conditions, but this issue deserves further research. The results shed some light on the features of the problems that teacher educators should select if they wish for their prospective teachers to learn and succeed in solving everyday STEM-relevant issues. This is required to promote their future students’ engagement in problem-based learning processes. Full article

Striving toward goal completion and achieving objectives is one of the motors of personal advancement. The path to goal completion is fueled by many reasons, among which motivation stands out as one of the core impulses. Motivation acquires a particularly high relevance in learning, prompting educators to mind its substance when designing not only the material to be imparted but also the approach and the mechanisms to assess knowledge acquisition. The intrinsic nature of motivation might stem from self-realization, thriving in specific goals, or even exploring unknown ground. One of the main teacher–student interactions is the provision of adequate tools to achieve learning outcomes. One of the tools available to teachers is the exercise of extrinsic motivation. This paper proposes and assesses the initial implementation of a student-involved extrinsic motivation method. A pilot group in the Junior year of a Bachelor in Mechanical Engineering program was selected, in which the evaluation system was slightly modified with respect to the system that is normally used. The course selected for the study was a compulsory six European Credit Transfer and Accumulation System (ECTS) course covering production and manufacturing technology. Students were asked to partake in the drafting of questions to assess their own knowledge, hence indirectly increasing their motivation to learn the content. The tentative results obtained with the pilot group appear to be positive and relevant. Students showed a higher engagement during class and reported needing fewer hours of preparation at home (32% reduction). In addition, global satisfaction with the course was improved. Full article