Search Results (106)

Universal Design for Learning (UDL) has advanced inclusive education by positioning learner variability as an anticipated condition of instructional design and emphasizing the proactive reduction of barriers. Yet, structural accessibility alone does not fully explain how learners and educators experience belonging, construct identity, exercise agency, or translate lived experience into pedagogical decision-making. This study examines how these interpretive dimensions of learning may extend existing approaches to inclusive educational design. Using a Phase I exploratory Design-Based Research methodology, the study investigated the reflexive and pedagogical experiences of 20 leaders of learning working across educator preparation, professional learning, and school-based instructional contexts in the United States. Participants included 12 faculty leaders facilitating graduate-level or professional learning experiences and 8 teacher leaders engaged in school-based instructional practice. The inquiry was designed for conceptual development rather than intervention validation, examining how authentic professional experiences could inform the emergence of an identity-responsive framework for inclusive educational design. Prototypical Narration Surfacing and Synthesis served as the interpretive methodology through which lived experience was surfaced, interpreted, and synthesized across participant narratives, instructional artifacts, observation records, coaching documentation, and portfolio evidence. Narrative inquiry, thematic analysis, iterative coding, and cross-context interpretation supported the identification of recurring developmental patterns. Findings indicated that professional growth extended beyond the acquisition of discrete instructional competencies and was experienced as an interconnected process of identity development, belonging, self-efficacy, professional agency, and pedagogical reasoning. Across faculty leaders and teacher leaders, reflexive interpretation increasingly informed intentional instructional decision-making and more responsive approaches to learner variability. Cross-context synthesis further revealed recurring developmental orientations related to challenge, agency, belonging, identity, and transformation. These patterns contributed to the emergence of Archetypal Inquiry as a provisional, anti-reductionist interpretive lens rather than a predetermined participant classification system. The iterative synthesis of: (a) structural accessibility, (b) lived experience, (c) reflexive interpretation, (d) pedagogical reasoning, and (e) contextual responsiveness, subsequently informed Universal Access by Design, an emerging Phase I conceptual framework for identity-responsive inclusive education. The study suggests that inclusive educational design may be strengthened when UDL’s structural commitments are complemented by attention to how learners and leaders interpret experience, construct identity, and continually redesign educational environments in response to emerging evidence. Universal Access by Design is therefore offered not as a replacement for UDL or as a validated intervention, but as a provisional framework and foundation for continued Design-Based Research, implementation, and empirical refinement across diverse educational settings. Full article

Persistent challenges in Environmental Microbiology teaching include the mismatch between networked knowledge structures and linear instruction, insufficient support for open-ended engineering scenarios, the gap between blended formats and deep learning outcomes, and weak process-oriented assessment evidence. Guided by Outcome-Based Education (OBE), the course team constructed a four-dimensional curriculum graph integrating ability, problem, knowledge, and resource dimensions, and developed a progressive teaching model of graph-guided learning, intelligent inquiry, and data-driven evaluation. This article reports the design and implementation of a teacher–student–AI collaborative blended smart course and presents a descriptive evaluation of one implementation cycle. The course was implemented over a 16-week semester with 60 third-year environmental engineering undergraduates at Jiangsu University; the previous cohort, taught by the same instructors with conventional blended teaching, served as a historical reference. Data were collected from platform interaction records, blueprint-matched final examination questions, and a piloted questionnaire (58 valid responses; Cronbach’s α = 0.89), and were analyzed with descriptive statistics, independent samples t-tests, and effect sizes; classroom interaction was summarized descriptively because repeated student session observations were clustered within students. Using the module on biological nitrogen and phosphorus removal in wastewater treatment as an example, the article illustrates differentiated pre-class preparation, in-class problem-chain inquiry with AI-assisted scheme design, and post-class learning profiling. Compared with the historical cohort, the implementation cohort showed a descriptively higher classroom interaction rate (90.3% vs. 70.5%), a 15.2-percentage-point higher mean score rate on examination questions targeting microbial regulation (95% CI [10.2, 20.2]; Cohen’s d = 1.12), and positive student perceptions (91.4% reported that knowledge graphs supported systematic cognition and 84.5% reported increased confidence in analyzing engineering problems). The documented course architecture and implementation pathway may provide a practical reference for the smart transformation of core environmental engineering courses. Full article

Student engagement in developing open educational resources (OER; openly licensed materials without fees to access) may be critically important for sustainable higher education and for developing important skills. There has been substantial debate about the use of generative artificial intelligence (GenAI) for the sustainability of OER, but little empirical inquiry. In this quasi-experimental study in the United States, two sections of college students (N = 113) collaborated with their instructor to improve the sources cited in an OER textbook. In one section, students only used traditional library databases to find suitable sources (traditional; n = 55). In another section, students were instructed on how to use GenAI to locate and understand scholarly journal articles using Scite.ai and SciSpace (AI-enhanced; n = 58). Both sections of students reported improved source-finding skills based on pre- and post-semester questionnaires; however, there was no evidence of improved growth with AI enhancement. Students in the traditional section appeared to have better assignment scores. In contrast, students in the AI-enhanced section were more likely to successfully submit assignments. Findings are discussed in the context of how open pedagogy with or without AI tools may support the sustainability of OER as well as overall sustainable education goals in higher education. Full article

Artificial intelligence (AI) has the potential to support sustainable science teacher education by promoting inquiry, responsible technology use, and digital competence. This study examined the effects of an AI-supported guided inquiry intervention on pre-service science teachers’ artificial intelligence literacy (AIL), self-perceived computational thinking skills (SPCTS), and conceptual understanding of photosynthesis and cellular respiration. A quantitatively driven quasi-experimental pretest–posttest control group design with an embedded qualitative component was employed with 48 s-year pre-service science teachers in Türkiye. The experimental group participated in an eight-week AI-supported guided inquiry program integrating problem and design-based learning, whereas the control group received conventional instruction. Mixed-design ANOVA revealed significant group-by-time interactions for conceptual understanding of photosynthesis (F (1, 41) = 22.79, p < 0.001, ηp² = 0.357) and cellular respiration (F (1, 44) = 25.70, p < 0.001, ηp² = 0.369), whereas no significant effects were found for AIL or SPCTS (p > 0.05). Qualitative findings showed that participants reported perceived benefits and engagement in conceptual learning, inquiry, collaboration, critical evaluation of AI-generated outputs, and digital content creation. The findings suggest that AI-supported guided inquiry can strengthen disciplinary conceptual learning while fostering competencies associated with sustainable science teacher education, although longer interventions may be required to produce measurable gains in AIL and SPCTS. Full article

Project-based learning (PBL) holds significant promise as a student-centered instructional approach in secondary mathematics, yet teachers’ capacity to leverage it for diverse learners is deeply shaped by their affective experiences during implementation. This narrative inquiry examines the affective journeys of three high school mathematics teachers as they adopted PBL in classrooms characterized by varied student readiness levels and engagement profiles. We document teachers’ affective journeys as they experience initial PBL awareness, participate in active experimentation, and work toward forming emerging commitments and facilitator identities. Analysis of focus groups and interviews reveals three affective tensions: comfort versus transformative reflection, epistemic ideals versus ontological school realities, and career risk versus identity change. The findings demonstrate how teachers can navigate iterative methods of trial, how teacher educators can better support future teachers’ use of student-centered pedagogies, and how administrators can be aware of the impact that teacher affect can have on performance and pedagogy. Implications address how this broader education community can support differentiated, inquiry-based mathematics instruction. This support can be advanced through scope-controlled projects, micro-evidence portfolios, and incremental adoption pathways. These approaches honor teachers’ emotional labor while supporting their sustained use of student-centered learning strategies intended to broaden opportunities for participation and learning in mathematics classrooms. Full article

Promoting learners’ knowledge construction during inquiry-based learning has long been a central concern in the learning sciences. To support learners’ logical reasoning, this study developed an instructional system integrating generative AI-based dynamic scaffolding with a physical robotic arm. The system incorporates two logic reasoning tasks—the Bottle-Taking Game and the River-Crossing Game—to provide adaptive AI-assisted guidance through embodied interaction for problem-solving. A quasi-experimental nonequivalent pretest–posttest design was conducted with 64 sixth-grade students. The experimental group (n = 31) learned through an AI-assisted robotic interaction mode, whereas the control group (n = 33) received conventional hands-on instruction. The results showed that the experimental group achieved significantly better logical reasoning performance than the control group. ARCS-V motivation analysis revealed that high-achieving students in the experimental group scored significantly higher on the Attention, Relevance, Confidence, and Volition dimensions than their peers in the control group, whereas low-achieving students scored significantly lower on Relevance. No significant between-group differences were found in cognitive load, indicating that AI-assisted scaffolding did not impose additional cognitive burden. Furthermore, students perceived the proposed system as useful, easy to use, and satisfactory. Overall, the findings demonstrate that integrating AI-assisted scaffolding with embodied robotic interaction enhances logical reasoning performance while maintaining learning motivation and cognitive processing and fostering positive technology acceptance. These results provide empirical evidence supporting AI-assisted robotic game-based learning and contribute to STEM education. Full article

This study examines teachers’ acceptance of an inquiry-oriented, Crime Scene Investigation (CSI)-based teaching sequence supported by a Virtual Scanning Electron Microscope (Virtual-SEM) using an extended Technology Acceptance Model (TAM). While TAM has been widely used to explain technology adoption, its traditional focus on cognitive perceptions may not fully capture the pedagogical complexity of educational settings. To address this, the study integrates pedagogical and affective variables, namely Inquiry Engagement (INQ), Trust (TR), and Self-Efficacy (SE), into the TAM framework. Data were collected from 30 teachers who evaluated a teaching sequence designed according to constructivist principles and the 5E Instructional Model. Descriptive statistics, reliability analysis, correlation analysis, and multiple regression analyses were employed to examine the relationships among constructs. The findings indicate high perceived usefulness, positive attitudes, and strong behavioral intention to adopt the sequence. Inquiry Engagement was significantly associated with both Perceived Usefulness and Attitude Toward Use, while Trust was significantly associated with Perceived Ease of Use and attitudes. In contrast, Perceived Usefulness showed a weak and non-significant association with attitudes, suggesting that pedagogical factors may play a particularly important role in technology acceptance. Attitude Toward Use showed the strongest association with Behavioral Intention. The findings provide preliminary support for an extended, pedagogically enriched TAM and highlight the potential importance of instructional design in technology acceptance. Full article

In China’s latest mathematics curriculum, project-based learning (PBL) foregrounds mathematical problem solving (MPS) as student-led inquiry in authentic contexts. This study examines teachers’ beliefs about MPS within PBL, and how such beliefs are enacted in planning and teaching. Using a constant comparative approach, we drew on interviews, lesson plans, and reflective accounts from 14 mathematics teachers. Most teachers emphasised application and creativity, positioning themselves as guides/supporters who facilitate students’ exploration. Consistent with these beliefs, lesson plans commonly drew on personally and socially grounded contexts and featured challenging, open-ended tasks attending to cognitive breadth and depth. While espoused beliefs largely aligned with described implementation, a minority endorsed procedure-focused instruction, revealing tensions between exploration- and content-oriented approaches. Examining teachers’ beliefs can inform understanding of progress in curriculum reform. Sustained, long-term professional learning—supported by institutional resources and professional autonomy—is needed to help teachers navigate these tensions. Full article

This qualitative content analysis investigates how preservice teachers (PSTs) curate primary sources in early childhood and elementary social studies contexts, revealing the ideological implications of their instructional choices. Drawing on 347 selections submitted by 103 PSTs in a scaffolded, inquiry-based assignment, the study analyzes whether selections perpetuate dominant cultural narratives or reflect counternarratives and culturally sustaining practices. Findings indicate that while nearly half of all sources aligned with White, male, Eurocentric perspectives, a significant subset engaged historically marginalized voices, suggesting emergent but uneven commitments to inclusive representation. Selections varied in depth of reflection, often shaped by archival access, curricular constraints, and unexamined pedagogical habits. Grounded in Critical Educational Theory, Reflective Teaching Practices, and Culturally Sustaining Pedagogy, the study highlights the ideological weight of source selection and the need for teacher preparation programs to scaffold reflective, justice-oriented engagement with historical materials. These findings contribute to ongoing conversations about equity, civic responsibility, and culturally responsive teaching in early social studies education. Full article

Social media platforms increasingly function as informal education systems for programming learning, yet the systemic support structures these environments provide remain poorly understood. We analyzed 40,004 comments from programming tutorial videos on a major social media platform (2016–April 2025) to identify patterns of learner support needs at scale. Using BERTopic, we identified twelve discussion themes. We then consolidated these themes into a learner-needs typology based on their dominant support functions: instructional-oriented needs, operational support needs, and knowledge-constructionneeds. We mapped this typology onto the Community of Inquiry (CoI) framework to assess its explanatory coverage. This mapping revealed a critical systemic gap. Operational support needs, covering environment configuration, tool integration, dependency management, and technical troubleshooting, constituted the largest category (44.53% of theme-level discourse), exceeding both knowledge-construction needs (28.42%) and instructional-oriented needs (26.95%). Learners repeatedly described these infrastructure-level challenges as disrupting their attempts to engage with content, execute code for testing ideas, and coordinate with peers, yet these operational readiness needs are not fully specified by CoI’s traditional presences. Social presence did not emerge as a standalone theme at the topic-modeling level; rather, social cues were often embedded within task-oriented troubleshooting. Based on these findings, we propose Technical Presence as a context-sensitive extension to the CoI framework, defined as the extent to which a learning community enables operational readiness through accessible infrastructure support and collaborative troubleshooting. As an infrastructural support condition, Technical Presence supports operational readiness within tool-dependent, practice-based learning: when learners report infrastructure failure, the conditions for enacting instructional design, cognitive inquiry, and peer collaboration are correspondingly weakened. These findings carry implications for content creators, platform developers, and education system designers seeking to strengthen the infrastructural foundations of technology-enhanced learning at scale. Full article

Crab traps are commonly used tools in both commercial and recreational fisheries to capture crabs through baited enclosures. However, the existing conventional designs often suffer from reduced catch efficiency, high bycatch rates, and rapid bait deterioration, which undermine their effectiveness and environmental sustainability. This study evaluated the effectiveness of an innovative crab trap setup incorporating an attractor device, designed not only to enhance crab catch rates but also to serve as a localized laboratory simulator for Outcome-Based Education (OBE) in Industrial Arts. Utilizing a developmental research design, this study was conducted in Barangay Caloc-an, Magallanes, Agusan del Norte. The research involved commercial and recreational crab fishermen, as well as electrical and electronics experts, to assist in setting up and evaluating the innovative crab trap device. The key variables examined included the type of attractor device used, the dispersal rate of the liquid bait, and the trap’s overall effectiveness in capturing crabs. Four different bait dispersal intervals were tested: 40 min, 30 min, 10 min, and 30 s. Results showed that shorter dispersal intervals significantly increased catch rates, with the 30 s interval yielding the highest and most consistent results. The developmental research framework enabled iterative testing and refinement of the trap system, allowing for continuous improvement of its components. Importantly, this study’s broader educational aim was to provide students with a practical, culturally relevant, and outcome-focused learning experience, where technical skills and scientific inquiry are applied in real-world contexts. The crab trap device served not only as a fishing tool but also as a simulated laboratory apparatus for Industrial Arts instruction, fostering skill development and engagement. Overall, this study contributes valuable insights into both fisheries management and educational innovation, demonstrating that a well-designed crab trap device can support more effective and sustainable fishing practices while also enhancing Industrial Arts education through hands-on, localized learning experiences. Full article

Recent evidence indicates that many high school students continue to exhibit weak problem-solving skills and incomplete conceptual understanding of environmental change, although both are critical for addressing increasingly complex ecological challenges in the 21st century. This study aims to evaluate the effectiveness of the INSPIRE learning model in enhancing problem-solving skills and conceptual mastery of environmental change among high school students. The INSPIRE model integrates e-modules, guided inquiry-based learning (GIBL), and deep learning principles into a cohesive instructional framework. A quasi-experimental design with a non-equivalent control group pretest-posttest approach was employed, involving 108 Grade 10 students in three groups: an experimental group applying the INSPIRE model, control group 1 utilising discovery learning, and control group 2 implementing guided inquiry without e-modules. Data were collected through pretests and posttests assessing problem-solving skills and conceptual mastery of environmental change, complemented by observations of the learning implementation. The results showed that students in the INSPIRE group obtained higher mean posttest scores in both problem-solving skills and concept mastery than students in the two control groups, with statistically significant differences (p < 0.05). The findings suggest that the integration of e-modules, GIBL, and deep learning principles within the INSPIRE learning model supports a more meaningful learning experience and fosters 21st-century competencies, particularly problem solving in an environmental context. Practically, the INSPIRE learning model represents a promising option for biology instruction, especially for topics that require analytical thinking, investigation, and deep conceptual understanding. Full article

We propose an interactive approach to teaching Coulomb’s law and electrostatics in general, rooted in two complementary pedagogical methodologies: hyper-constructivism (H-C) and neo-realism. Unlike standard constructivism, our hyper-constructivist approach treats students’ prior ideas—even if incomplete or inconsistent—as essential “submerged logs” that teachers may use to guide students across the cognitive lake, toward the correct understanding. We implement a triadic model of cognitive didactics, balancing amusement (the ludic “hook”), formal teaching, and deepening scientific inquiry. Here, we present a hyper-constructivist path on electrostatics—Coulomb’s and Gauss’s laws. Through a sequential path of experiments involving plastic rods, “trained” aluminum cans, Volta’s electrophorus, and “Christmas” ornaments, we demonstrate how students can spontaneously formulate problems and bridge the gap between intuitive observations and complex effects of electrical polarization, going beyond the scholastic Coulomb’s law, via numerical modeling. The proposed interactive approach is rooted in phenomena-based learning and leverages discrepant events—surprising physical phenomena that challenge prior intuitions—as “ludic hooks” to trigger spontaneous inquiry and conceptual reconstruction. The main goal of our strategies is to trigger and develop young students’ interest in physics, which in many European countries is low. This method not only facilitates the acquisition of physical laws but also fosters “intellectual inquisitiveness” and social competencies, proving that well-rooted knowledge emerges from a synthesis of tangible experience and advanced scientific modeling. Our contribution constitutes a complex pedagogical proposal, iteratively developed and implemented in diverse didactical environments over several years. This paper presents a pedagogical proposal developed and refined through more than twenty years of educational practice. For teachers interested in implementing hyper-constructivist instruction, we provide a detailed teaching pathway on electrostatics, with didactical explanations and pedagogical notes. Full article

The growing centrality of data in contemporary society has intensified calls to expand data literacy across K–12 education, positioning teachers as key agents in this effort. This article traces the emergence of data literacy as a domain of educational research and reports findings from a systematic review of empirical studies on K–12 STEM teacher data literacy published between 2015 and 2025. Guided by the PRISMA framework, searches of Academic Search Complete, APA PsycINFO, and supplementary sources yielded a final sample of 26 studies. The review examines (1) what has been prioritized in research on teaching data literacy and (2) the conceptual models used to study data literacy in educational contexts. Findings indicate that existing research primarily emphasizes teachers’ knowledge, beliefs, and use of technological tools, with comparatively limited attention to classroom enactment and student learning. Conceptually, the field is characterized by the use of diverse and often disconnected frameworks, including competency-based, statistical reasoning, and pedagogical models, resulting in a fragmented knowledge base. We argue that this fragmentation stems from underlying epistemological, methodological, and contextual tensions that have yet to be theoretically reconciled. In response, we propose an integrative perspective that conceptualizes data literacy as a situated, practice-based, and socio-epistemic phenomenon. This framing highlights the dynamic interplay among interpretive reasoning, instructional design, mediational tools, and contextual conditions. Advancing the field requires moving beyond isolated lines of inquiry toward theoretically coherent approaches that connect teacher cognition, instructional practice, and student learning in order to support meaningful and equitable participation in a data-driven world. Full article

This study explored the effectiveness of the Phenomenon-Based Learning (PheBL) model in fostering students’ autonomous learning behaviors and metacognitive awareness as important dimensions of sustainable learning. Employing a quasi-experimental pre-test–post-test control group design, the study was conducted with 48 fifth-grade students in Türkiye. The experimental group participated in PheBL-based instructional practices structured around real-life phenomena, collaborative inquiry, student-generated questioning, reflective learning activities, and interdisciplinary problem-solving processes, whereas the control group received conventional teacher-centered instruction. Data were collected using the Autonomous Learning Scale and the Metacognitive Awareness Inventory and analyzed through ANCOVA and paired-samples t-tests. The findings revealed that students in the experimental group demonstrated significantly higher levels of autonomous learning and metacognitive awareness than those in the control group. Within-group analyses also indicated substantial improvements from pre-test to post-test across all measured dimensions. These findings suggest that PheBL may enhance students’ capacity for self-regulation, reflective thinking, and learner autonomy by engaging them in active, inquiry-oriented, and reflective learning processes. Furthermore, the results indicate that learning experiences grounded in authentic real-life phenomena may support the development of transferable competencies associated with lifelong and adaptive learning. Nevertheless, the findings should be interpreted cautiously due to the relatively small sample size, the short duration of the intervention, and the reliance on self-report measures. Despite these limitations, the study contributes to the growing body of research on learner-centered pedagogies by providing empirical evidence that autonomous learning and metacognitive awareness may be simultaneously fostered through phenomenon-based instructional practices. Future research is recommended to investigate the long-term effects and broader contextual applicability of PheBL across diverse educational settings and learner populations. Full article