Search Results (1,361)

This study explores the application of artificial intelligence (AI) in higher education to enable the early identification of at-risk students using only engagement data from learning management systems (LMS). Unlike many existing early-warning models that are limited to single disciplines or rely on sensitive demographic and prior academic records, the proposed approach offers a privacy-conscious and highly generalizable predictive framework suitable for diverse higher education contexts. The dataset includes over 1.7 million LMS interaction records from 236 undergraduate subjects spanning four academic divisions. These subjects encompass a wide variety of instructional designs and assessment structures. To address cross-subject heterogeneity, this study employs rank-based engagement features that represent students’ relative behavioral patterns within each course, facilitating meaningful comparison across disciplines without reliance on absolute activity levels. Using standard machine learning classifiers, the model achieves over 90% prediction accuracy for final subject performance by Week 3 of the semester, demonstrating that reliable early detection of at-risk students is feasible at an early stage of teaching and learning. Rather than claiming intervention effectiveness, the study positions AI-enabled early prediction as a scalable foundation for proactive student support and enhanced teaching responsiveness, with the potential to inform timely pedagogical actions such as targeted outreach and academic advising. By emphasizing generalizability, ethical data use, and privacy protection in AI-enabled learning analytics, this research contributes practical insights into how predictive AI can responsibly support teaching and learning in higher education. Full article

The integration of digital formats into undergraduate medical education offers a promising approach to enhance procedural skill acquisition. This study investigates the efficacy of a short, structured instructional video as part of a blended learning curriculum for teaching radial artery puncture to final-year medical students. A single-center, randomized, cross-over trial was conducted at the University Medical Center Mainz. Seventy-eight final-year medical students were randomized into an exposure group (instructional video based on Peyton’s four-step approach) and a control group. Performance was assessed using a 14-item checklist (maximum 16 points; pass threshold: 60%). At T1, the exposure group achieved significantly higher scores (p < 0.001, r = 0.735). Only 2.5% of the exposure group failed compared to 26.3% in the control group. After one week, the exposure group showed no significant performance decline (p = 0.101). The control group improved significantly after viewing the video (p < 0.001). At T2, no statistically significant difference remained between groups (p = 0.013, adjusted α = 0.0125). A short, structured instructional video significantly enhances initial performance and short-term retention of radial artery puncture skills in a blended learning setting. Full article

The integration of Generative Artificial Intelligence (GenAI) into programming education has introduced new opportunities and challenges for the teaching–learning process in higher education. While GenAI tools can support personalized learning and immediate feedback, their effectiveness depends on how they are pedagogically integrated into instructional environments. This study analyzes the relationship between GenAI-supported instructional strategies, academic context, affective factors, and demographic variables on normalized learning gain in undergraduate introductory programming courses. A multi-group quasi-experimental pre-test–post-test design was conducted involving 648 engineering students distributed across 53 course groups taught by 32 professors from 10 campuses. Four GenAI-supported instructional strategies were implemented and compared with traditional instructional conditions. Learning gains were analyzed through a linear mixed-effects model considering instructional strategy, academic program, student frustration, future intention to use GenAI, student gender, and professor gender as fixed effects, while group/professor was modeled as a random effect. Results showed that instructional strategy was the strongest predictor of learning gain, followed by academic program and student frustration. In contrast, demographic variables and future intention to use GenAI did not show significant associations with learning outcomes. The findings suggest that learning gains in programming education depend primarily on instructional design and pedagogical mediation rather than on students’ demographic characteristics or technological predisposition. Full article

Understanding teachers’ attitudes towards statistics is essential, as these attitudes influence both teaching practices and students’ learning outcomes. This study examines attitudes toward statistics among Chilean teachers, comparing pre-service and in-service teachers across emotional, cognitive, and behavioral dimensions. Using quantitative methods, data were collected from 111 teachers through a modified version of the Attitudes Toward Statistics and Its Teaching Scale survey. The results show that in-service teachers display more positive attitudes toward statistics than pre-service teachers, suggesting that professional experience and continuous development contribute to greater confidence and competence in teaching statistics. Positive emotional experiences, such as enjoyment and interest in statistics, are strongly associated with higher engagement in both learning and teaching the subject. Additionally, perceiving statistics as valuable has a positive effect on teachers’ instructional behavior. These findings have important implications for teacher education. They highlight the need for targeted professional development initiatives that strengthen statistical knowledge while addressing emotional and attitudinal barriers. Furthermore, integrating real-world statistical applications into teacher training programs can enhance relevance and engagement. Overall, promoting positive attitudes toward statistics among teachers is key to improving the quality of statistics education and preparing students to function effectively in an increasingly data-driven society. Full article

Recent advancements in Large Language Models (LLMs) hold significant promise for reshaping programming education. However, critical instructional challenges such as high failure and dropout rates, insufficient feedback, and inadequate support for students’ independent analytical thinking remain prevalent. Addressing these gaps, this study introduces the Guided Programming and Analysis System (GPAS), an innovative educational approach leveraging LLM-based technology to enhance programming instruction. GPAS is designed to support autonomous learning processes by integrating multi-turn interactive thought guidance, code polishing, semantic annotation generation, and structured scoring mechanisms across multiple programming languages. Experimental results demonstrate significant effects were observed in correlation analysis with expert evaluations ($r=0.668$, $p=6.84\times {10}^{-12}$) and paired-sample tests on code and report-level improvements (effect sizes Cohen’s $d=0.92$ and $1.56$, respectively, $p=3.56\times {10}^{-6}$ and $p=1.64\times {10}^{-10}$). Additionally, findings revealed that the GPAS platform significantly improved code quality, particularly benefiting lower-achieving students, and effectively captured nuanced improvements in readability, structure, and boundary handling. Moreover, GPAS emphasizes the supportive role of educators, enabling them to focus more effectively on higher-order teaching tasks while the platform handles routine instructional feedback. Collectively, these results suggest that GPAS provides a promising framework for supporting learner-centered programming education and independent problem-solving processes. Full article

Background: Virtual reality (VR) has attracted increasing attention in architectural design education because of its potential to support spatial cognition and embodied understanding of architectural space. Compared with conventional two-dimensional (2D) drawings and screen-based three-dimensional (3D CAD) tools, VR enables learners to experience space at a realistic scale through binocular disparity and motion parallax, which may reduce cognitive load and facilitate experiential learning. However, previous studies have mainly relied on subjective evaluations, such as questionnaires and observations, and have not sufficiently examined differences in educational effectiveness among design tools or among students with different learning levels. Objective and Methods: This study aimed to identify effective teaching tools for facilitating students’ understanding at different learning levels and to propose appropriate methods for applying VR to improve educational effectiveness. To achieve this, we proposed an objective experimental method for evaluating the effectiveness of VR in architectural design education based on students’ ability to identify incorrect content in architectural design plans. The experiment compared the performance of students using 2D drawings, 3D CAD, and VR environments and examined differences according to student grade levels (higher- and lower-year students) objectively. Results: The results revealed that both higher- and lower-year students identified more incorrect content items related to “Fitting” (such as door layouts) when using 2D drawings (finding rates were 43.8%~53.3% higher than those with 3D CAD or VR), whereas more incorrect content items related to “Furniture” size were identified when using VR (finding rates were 18.8%~56.3% higher than those with 2D drawings or 3D CAD). In addition, items related to sectional and elevation design, such as “Opening,” as well as issues concerning the size of “Space,” were identified by higher-year students regardless of the tool used. In contrast, lower-year students identified approximately twice as many of these items when using VR as when using 2D drawings. Conclusions: Based on the above results, the effectiveness of VR varied depending on both the type of design knowledge and the students’ learning levels. VR improved lower-year students’ understanding of spatial dimensions, furniture and fitting compared with conventional tools. Furthermore, VR encouraged more detailed consideration of spatial and design-related issues during architectural design tasks. These findings suggest that VR can reduce the cognitive load associated with learning architectural spatial concepts and promote experiential learning close to real spatial perception. Implications: This study supports the appropriate use of VR in architectural design education. The experimental method proposed in this study can also be used to objectively evaluate the effectiveness of educational tools other than VR before their implementation in architectural design education. Applying this method in architectural education is expected to enhance students’ awareness of architectural spatial issues and promote more comprehensive spatial understanding during the design process. Full article

Digital technologies are increasingly transforming teaching and learning, particularly through technology-enhanced assessment and feedback systems. This study examines the feasibility and pedagogical utility of the Kit-Build Concept Map (KBCM) system as a technology-supported approach for systematizing serial concept mapping in a human–computer interaction course. A three-week study was conducted with 258 undergraduate students, integrating a re-composition framework with real-time feedback to support continuous refinement of students’ externalized conceptual representations. Pre-tests, post-tests, and concept map analytics were used to evaluate learning gains and concept map structures across instructional sessions. The results show that the KBCM system enabled lecturers to identify individual and class-level map gaps and provide timely, data-informed feedback to support instructional monitoring and pedagogical decision-making. Students showed statistically significant improvements in learning outcomes, consistent progress across instructional weeks, along with a measurable reduction in discrepancies between student-generated maps and the expert map. These findings suggest that serial concept mapping with re-composition and feedback support may help students refine their externalized conceptual representations to become more closely aligned with target knowledge over time. Overall, this study highlights the potential of technology-enhanced concept mapping systems to support continuous instructional feedback, assessment, and data-informed pedagogical practices in higher education. The findings should be interpreted within the context of a short-term, three-week implementation focusing on changes in externalized conceptual representations rather than direct measurement of internal cognitive processes. Full article

Artificial intelligence (AI) is increasingly being integrated into higher education. Among these innovations, AI teaching assistants have emerged as tools that can provide immediate academic support, personalized feedback, and improved access to learning resources. Despite the growing adoption, limited research has explored students’ knowledge, attitudes, and acceptance of AI teaching assistants in African higher education contexts. The Technology Acceptance Model was adopted as a theoretical lens to explore South African university students’ Knowledge, Attitudes and Acceptance of AI teaching assistants in a clinical learning environment. A qualitative study design within an interpretivist paradigm was employed. Data were collected through semi-structured interviews with six undergraduate students who had experienced both traditional teaching approaches and AI-assisted learning. The data were analysed using thematic analysis. The findings revealed three key themes: students’ understanding of AI teaching assistants, attitudes toward AI-assisted learning, and acceptance and concerns regarding AI in clinical education. The results indicate that students generally demonstrate positive attitudes toward AI teaching assistants and recognize their usefulness for supporting independent learning. However, participants also expressed concerns regarding the accuracy of AI-generated information and emphasized the continued importance of human educators in clinical training. The study contributes context-specific insights into technology acceptance in African higher education, highlighting how perceived usefulness may remain strong even in resource-constrained environments. Full article

This study analyzes formative research as a pedagogical resource for teaching scientific logic in higher education from a constructivist perspective. The purpose of the article is to examine how formative research contributes to the development of scientific reasoning, critical thinking, and analytical skills among university students through active, reflective, and contextually grounded learning processes. The study is an exploratory narrative/documentary literature review. The initial bibliographic search identified 105 scientific documents published between 2000 and 2025 in indexed databases such as Scopus, Web of Science, SciELO, Taylor & Francis, MDPI, ResearchGate, Redalyc, and RENATI. After duplicates were removed and inclusion and exclusion criteria were applied, 54 studies were selected for the final analysis. A two-way documentary analysis matrix was used to identify conceptual relationships among constructivism, reflection-in-action, mental representations, induction and deduction, and their contributions to scientific logic. The findings show that formative research strengthens scientific logic by promoting active knowledge construction, critical reflection, problem-solving, and argumentative reasoning. The contributions of Piaget, Vygotsky, Bruner, Schön, and Fosnot demonstrate that scientific thinking develops through interaction, inquiry, contextualized learning, and reflective practice. Inductive and deductive reasoning were also identified as complementary mechanisms for developing analytical and interpretive competencies in university education. The study proposes that formative research should be considered a central pedagogical strategy in higher education because it facilitates the integration of scientific reasoning, reflective learning, and research-based teaching. Finally, an operational formative research program based on a holistic student development approach is proposed to foster scientific reasoning, intellectual autonomy, and the formation of more critical, reflective, and scientifically competent university students. Full article

Over the past decade, educators and administrators in higher education have taken steps toward improving accessibility in teaching and learning. Yet research on supporting students with disabilities in experiential pedagogies, such as community-engaged learning, remains limited, particularly regarding best practices for inclusive instruction. The present study addresses this gap by exploring the perceptions and experiences of students with disabilities in community-engaged learning opportunities, as well as the support mechanisms that may contribute to their meaningful participation in these experiences. Forty-three students with disabilities participated in this qualitative study. Drawing on focus groups, individual interviews, and written responses, the study identifies themes for more inclusive design and delivery, including clearly outlining the physical and digital demands of engagement activities well in advance, designing courses with flexibility in mind, protecting students’ privacy, and including an accessibility statement in the syllabus. While the thematic analysis offers practical recommendations for educators and administrators, aimed at reducing barriers and fostering meaningful participation, the study also advocates for greater theoretical engagement with the personal and relational dimensions of experiential education. Full article

This paper examines how historic wooden-built environments and open-air museums can function as pedagogical settings for craft education. Drawing on teaching experiences from higher education in Norway, it analyses how students develop knowledge through guided engagement with tools, materials, and traditional practices in situated learning environments. Two teaching cases, spoon carving in a museum workshop and the investigation of a historic log-built structure, are presented as pedagogical designs. The analysis focuses on how learning is structured and develops through relational and responsive engagement with materials, tools, and professional guidance, rather than solely on learning outcomes. The cases demonstrate how teaching can be organised to support the development of embodied and practice-based knowledge. The paper develops a theoretical framework grounded in 4E cognition (embodied, embedded, extended, and enactive cognition) and Tim Ingold’s concepts of meshwork and wayfaring. These perspectives are applied as analytical tools to examine how learning emerges through action, feedback, and iterative engagement within specific learning environments. Historic workshops, tools, and buildings are approached as pedagogical resources that shape the conditions for learning. While such environments carry historical and material depth, the focus here is on how they structure students’ engagement and influence learning processes in practice. The paper argues that craft pedagogy involves the design of learning situations where material engagement, reflection, and professional guidance are integrated. It proposes an understanding of learning as a situated and relational practice, in which knowledge develops through participation in practice rather than through transmission alone. Full article

Engaging students in sustainability challenges is often easier in theory than in practice. This study examines first-year French undergraduates’ patterns of engagement with the TEDS module (Transition Ecologique pour un Développement Soutenable), a nationwide programme developed in France to promote ecological transition and sustainable development. Data were collected through an online questionnaire comprising 24 closed- and open-ended questions exploring students’ self-reported familiarity with, understanding of, concern about, and self-reported intentions to engage in sustainability-related actions, as well as perceived learning needs and background characteristics. Only 18 questions (143 items) were included in the present analysis, covering all dimensions except those related to the evaluation of the training programme. Results indicate that environmental concern is the factor most strongly associated with self-reported engagement intention, despite persistent gaps in conceptual understanding, particularly regarding the Anthropocene and alternative socio-economic models. Knowledge score and concern are structured hierarchically according to issue visibility, with climate change ranking highest. Engagement depends not only on concern but also on perceived opportunities for action, yet students struggle to identify concrete pathways. The absence of significant differences across gender and disciplines points to a strong generational convergence that reshapes the determinants of environmental engagement. Overall, the key challenge for sustainability education is linking systemic knowledge to concrete contexts of learning and everyday life. Full article

Higher education increasingly addresses topics that are complex, interdisciplinary, and context-dependent, creating challenges for traditional lecture-based instruction. This study explores the potential of AI-assisted interactive storytelling as a pedagogical approach for such learning contexts, using healthy buildings as an instructional case relevant to architecture, engineering, and construction (AEC) education. Grounded in constructivist learning theory, a set of interactive stories was developed using generative AI and implemented in Twine to create a decision-based learning experience. The intervention was tested in a class using a pretest–posttest design along with a student perception survey. The results showed a significant improvement in knowledge following the intervention. Student feedback was also positive across all measured dimensions, including perceived learning, cognitive engagement, emotional engagement, motivation to learn, and comparison with traditional lectures. These findings suggest that interactive storytelling can support both learning and engagement when teaching complex, multidimensional topics. This study further indicates that generative AI can serve as a practical development partner by reducing the time and technical effort required to create interactive educational materials. Overall, this paper contributes to higher education research by positioning and demonstrating AI-assisted interactive storytelling as a promising instructional approach for complex learning areas. Full article

This paper describes design, implementation and initial evaluation of Digital Twin Metaverse Classroom for higher education. Digital Twin Metaverse Classroom refers to highly realistic digital replicas or virtual replicas or prototypes of university classrooms or learning spaces. This paper focuses on creating high-fidelity digital replica of typical university lecture room. The main purpose of the Digital Twin Metaverse Classroom is to support teaching and learning in addition to traditional videoconferencing. The pilot involved thirty-two undergraduate students. A single-group pre-test/post-test quiz measured short-term learning, while the Technology Acceptance Model (TAM) measured acceptance through perceived usefulness, perceived ease of use, attitude toward use, and behavioral intention. A single session raised the mean quiz score from 6.41 to 9.19, a within-session gain that reached statistical significance, while all four TAM constructs scored highly. Because the sample was small and confined to one institution, with neither a control group nor a follow-up, these findings are best read as early evidence of feasibility, short-term improvement, and favorable acceptance rather than as proof of comparative effectiveness. Full article

Mindful pedagogy integrates a mindful approach in the classroom to support learning, creativity, and wellbeing using formal meditative practice or informal subject-related mindful practice or both. Since 2019, Mindful Kitchen Health and Wellbeing for Chefs, a globally unique module, has been delivered within year 1 of an undergraduate culinary arts programme. It uses a mindful pedagogical approach in a teaching kitchen setting promoting student self-care, mindfulness with food and positive kitchen culture. This qualitative single-case study explores its impact on the wellbeing of chefs in a real-world context and the process that creates that impact. The case study database includes interviews with graduates (n = 11), students (n = 7), module artefacts, co-creation workshops, and researcher reflection on class observations. Four themes emerged: stepping into wellbeing using the breath builds self-awareness, a mindful classroom builds creative confidence, calm minds empower the self for the workplace and informal mindful pedagogy creates “spacious applied learning” in Higher Education (HE). These unique insights can inform wellbeing-focused pedagogical practice in HE settings. Students’ experiences are easily transferable into other disciplines; however, further research should investigate nuances in transferability. Recommendations on integrating this approach into educators’ practice to strengthen wellbeing-focused teaching are presented. Full article