Search Results (126)

Astronomy provides an exceptional context for developing data literacy, critical thinking, and computational skills in education. This paper presents a project-based learning (PBL) framework that integrates exploratory data analysis (EDA), fuzzy logic, and explainable artificial intelligence (XAI) to teach students how to extract and interpret scientific knowledge from real astronomical data. Using open-access resources such as NASA’s JPL Horizons and ESA’s Gaia DR3, together with Python libraries like Astroquery and Plotly, learners retrieve, process, and visualize dynamic datasets of comets, asteroids, and stars. The methodology follows the full data science pipeline, from acquisition and preprocessing to modeling and interpretation, culminating with the application of the FAS-XAI framework (Fuzzy-Adaptive System for Explainable AI) for pattern discovery and interpretability. Through this approach, students can reproduce astronomical analyses and understand how data-driven methods reveal underlying physical relationships, such as orbital structures and stellar classifications. The results demonstrate that combining EDA with fuzzy clustering and explainable models promotes deeper conceptual understanding and analytical reasoning. From an educational perspective, this experience highlights how inquiry-based and computationally rich activities can bridge the gap between theoretical astronomy and data science, empowering students to see the Universe as a laboratory for exploration, reasoning, and discovery. This framework thus provides an effective model for incorporating artificial intelligence, open data, and reproducible research practices into STEM education. Full article

The integration of large language models (LLMs) into project-based learning (PBL) holds significant potential for addressing enduring pedagogical challenges in engineering education, such as providing scalable, personalized support during complex problem-solving. Grounded in Self-Determination Theory (SDT), this study investigates how different LLM usage strategies impact student learning within a blended engineering geology PBL context. A one-semester quasi-experiment (N = 120) employed a 2 (usage mode: individual/shared) × 2 (interaction restriction: restricted/unrestricted) factorial design. Mixed-methods data, including surveys, interaction logs, and reflective reports, were analyzed to assess learning engagement, psychological needs satisfaction, cognitive interaction levels, and project outcomes. Results demonstrate that the individual use strategy significantly outperformed shared use in enhancing engagement, needs satisfaction, higher-order cognitive interactions, and final project scores. The restricted interaction strategy effectively served as a metacognitive scaffold, optimizing the learning process by promoting deliberate planning. Notably, individual autonomy did not undermine collaboration but enhanced it by improving the quality of individual contributions to group work. Students also developed robust critical verification habits to navigate LLM “hallucinations.” This research identifies “individual autonomy” as the core mechanism and “moderate constraint” as a crucial design principle for LLM integration, providing an empirically supported framework for harnessing generative AI to foster both motivational and cognitive outcomes in engineering PBL. Full article

This paper explores the history of evolving teaching techniques in Digital Signal and Image Processing (DSIP) education with a focus on integrating Artificial Intelligence (AI) tools to close the continuing gap between theory and practice. Since DSIP has been at the center of Telecommunication, Medical Imaging, Robotics and AI, this paper examines active and student-centered learning paradigms, like collaborative, situation-based, and project-based learning (PBL) as viable pedagogical methods. The research methodology includes analyzing a survey using Data Visualization Tools in Python-3.12, 2023. This paper overviews the application of digital tools including MATLAB-R2024a, Python, Cloud-based systems, and AI-based learning analytics to promote experiential and adaptive learning to enable students to test complex signal and image processing systems. The findings emphasize the fact that these practices contribute to developing conceptual knowledge, critical thinking, and solving problems through engaging learners in real-life and data-driven scenarios. The results also indicate how the teachers can upgrade their instructional approach to technological innovations in teaching. Finally, this paper highlights the nature of AI-enriched pedagogies and practical experience to build the skills needed to operate in a more data-intensive, technologically advanced and sustainable engineering environment. Full article

Material degradation in the form of corrosion is an important industrial problem that affects asset integrity, reliability, and sustainability in various industries. To equip engineering professionals with the knowledge required for appropriate material selection and corrosion-mitigation design, this subject forms an essential part of the engineering curriculum at both undergraduate and graduate levels across multiple disciplines. This paper presents the design, implementation, and evaluation of an active learning (AL)-based course framework to teach a corrosion science and engineering course at the mechanical engineering department, KFUPM. A combination of AL strategies, including project-based learning (PBL), case-based inquiries, peer instruction, and think–pair–share activities, etc., was systematically integrated into the course to promote collaborative learning, conceptual enrichment, and critical thinking. Positive student feedback (>90% for most of the survey questions) with a response rate of 89% indicated increased motivation, improved understanding of complex corrosion mechanisms, and increased confidence in applying knowledge to solve engineering problems. A Cronbach’s alpha coefficient of 0.75 was obtained, reflecting strong internal reliability of the instrument. These findings suggest that integrating AL pedagogies in the corrosion course contributed towards enhanced learning outcomes and student preparation to support sustainable industrial practices using informed materials selection and corrosion management. Full article

This study examines the motivational and sustainability effects of an Anki-based, individualized project-based learning (PBL) model in an elementary Hindi language course. Conventional PBL approaches in language education typically rely on collaborative, production-focused tasks that can be demanding for novice learners and usually conclude when the final project is submitted, leaving little structured support for continued practice. In this study, script, vocabulary, expression, sentence patterns, and pronunciation are not treated as background work but defined as the core pedagogical problem. Over the semester, each learner builds and refines a personalized Anki deck—a multimedia flashcard system based on spaced repetition—designed to support Devanagari word and sentence recognition, pronunciation practice, listening comprehension, and vocabulary retention. Each student constructed an individual deck aligned with course content, selecting vocabulary items, creating example sentences, and developing personalized memory cues that matched their learning pace and needs. Motivation was measured with a modified Instructional Materials Motivation Survey (IMMS) using only positively worded items to enhance reliability. Results showed consistently high scores across all ARCS domains, particularly for Confidence (M = 3.86) and Satisfaction (M = 3.93). Female students reported higher average scores, but gender showed no association with motivational grouping. Strong correlations among ARCS dimensions indicated consistent engagement across motivational components. Cluster analysis identified two groups of learners: highly motivated learners who treated deck creation as an ongoing learning resource, and less motivated learners who still maintained scores above the neutral midpoint—engaged enough to manage typical beginner challenges. The findings suggest that Anki-based PBL can make project-based learning workable at the novice level. By positioning deck creation as both the problem students solve and the tool they build, the model integrates continuous, self-paced practice into the project structure rather than treating it as a one-time deliverable. This design responds to a familiar gap in beginner language instruction: what happens when formal scaffolding ends. Unlike conventional PBL, which concludes with project submission, this approach creates a resource learners can use independently over time, embedding ongoing vocabulary retention and autonomous practice into the learning experience itself. Full article

The integration of project-based learning (PBL) in primary education has proven effective in fostering students’ critical thinking, creativity, collaboration, and problem-solving abilities. When implemented through eLearning platforms, PBL can be enhanced by digital environments that combine pedagogical and technological characteristics supporting interactive learning, personalization, and continuous formative assessment. This study aimed to evaluate the pedagogical-technological characteristics of e-learning platforms relevant to the implementation of PBL in Lithuanian primary education. A multi-stage Delphi study was conducted involving 22 primary school teachers experienced in applying educational technologies and project-based learning. In the initial stages, the research team developed and validated a PBL-oriented evaluation instrument, followed by an expert-based selection and in-depth assessment of eight e-learning platforms available for Lithuanian educational practice. The findings revealed substantial differences in how platforms support the main phases of the PBL process. The highest evaluations were given to LearnLab and SMART Lumio, which demonstrate a balanced integration of pedagogical and technological characteristics aligned with PBL logic, whereas content-oriented platforms such as Moodle showed limited adaptability. The final Delphi round generated expert-informed recommendations for enhancing platform design and pedagogical functionality. The study contributes to the understanding of how e-learning platforms can operationalize project-based learning principles and provides an empirically grounded framework for improving technology-enhanced PBL in primary education. Full article

This article explores the potential of an integrated pedagogical approach that combines project-based learning (PBL) with Internet of Things (IoT) technologies to achieve the United Nations’ Sustainable Development Goals (SDGs). Within the context of Education for Sustainable Development (ESD), this model transforms students from passive consumers of information into active agents of change. The study demonstrates that leveraging IoT sensors enables students to tackle pressing and complex sustainability challenges by engaging them in a comprehensive problem-solving cycle—from collecting real-world data to developing innovative solutions. By analysing the existing scientific literature, the approach is shown to significantly improve critical thinking skills, systems thinking, creativity, and teamwork. The study also proposes a new conceptual framework (hypothesis), the EcoHabits model, whose effectiveness remains to be empirically validated. This model demonstrates IoT’s potential to enhance sustainability competencies, improve health literacy, and promote individual and collective behaviour change. Despite its significant pedagogical benefits, the article identifies key implementation challenges, including the need for adequate teacher training and community collaboration. In conclusion, this innovative framework offers a promising solution for preparing future generations to address global issues and become active, responsible citizens of the 21st century. Full article

This study presents the HISTOESE (History Education for Sustainable Environments) Model, an empirically grounded and practice-based framework for cultural heritage education and sustainability. Developed through a qualitative, design-based research approach, it analyzes a longitudinal corpus of 50 master’s dissertations and supervised teaching reports (2008–2025) from the Polytechnic Institute of Viana do Castelo, Portugal. Although the empirical basis derives from teacher education, the HISTOESE model fosters school–community partnerships that indirectly support cultural tourism and sustainable, place-based recovery. Using inductive thematic analysis, the study traced how project-based learning (PBL) activities mobilised local heritage, community collaboration, and sustainable pedagogical practices. Three key findings emerged: (1) local-context pedagogies strengthened children’s historical consciousness and heritage literacy; (2) inclusive, low-cost and upcycling strategies fostered community participation; and (3) partnerships with museums, tourism offices, and cultural associations generated visible cultural events that reinforced post-COVID resilience. The HISTOESE framework synthesises these insights into four interrelated pillars—Proximity and Contextualization, Inclusive and Sustainable Practices, Recognition and Valorisation and Active Citizenship and Collaboration—providing a transferable model for teacher education and community-based cultural sustainability. Practical implications concern curriculum design, heritage–tourism interfaces, and collaborative strategies for sustainable development. Full article

Building Information Modeling (BIM) is a transformative tool in Sustainable Design (SD), providing measurable benefits for efficiency, collaboration, and performance in architectural, engineering, and construction (AEC) practices. Despite its growing presence in academic curricula, a gap persists between students’ recognition of BIM’s sustainability potential and their confidence or ability to apply these concepts in real-world practice. This study examines students’ understanding and perceptions of BIM and Sustainable Design education, offering insights for enhancing curriculum integration and pedagogical strategies. The objectives are to: (1) assess students’ current understanding of BIM and Sustainable Design; (2) identify gaps and misconceptions in applying BIM to sustainability; (3) evaluate the effectiveness of existing teaching methods and curricula to inform future improvements; and (4) explore the alignment between students’ theoretical knowledge and practical abilities in using BIM for Sustainable Design. The research methodology includes a comprehensive literature review and a survey of 213 students from architecture and construction management programs. Results reveal that while most students recognize the value of BIM for early-stage sustainable design analysis, many lack confidence in their practical skills, highlighting a perception–practice gap. The paper examines current educational practices, identifies curriculum shortcomings, and proposes strategies, such as integrated, hands-on learning experiences, to better align academic instruction with industry needs. Distinct from previous studies that focused primarily on single-discipline or software-based training, this research provides an empirical, cross-program analysis of students’ perception–practice gaps and offers curriculum-level insights for sustainability-driven practice. These findings provide practical recommendations for enhancing BIM and sustainability education, thereby better preparing students to meet the demands of the evolving AEC sector. Full article

Engineering education in developing countries faces critical challenges that hinder progress toward achieving the United Nations Sustainable Development Goals (SDGs). In the Democratic Republic of Congo (DRC), students entering engineering programs often exhibit significant apprehension toward foundational sciences, creating barriers to developing the technical competencies required for sustainable development. This paper introduces the AI-Integrated Practical Learning in Engineering (AIPLE) Framework, an innovative pedagogical model that synergizes Problem-Based Learning (PBL), hands-on experimentation, and strategic Artificial Intelligence (AI) integration to transform engineering education for sustainability. The AIPLE framework employs a five-stage cyclical process designed to address student apprehension while fostering sustainable engineering mindsets essential for achieving SDGs 4 (Quality Education), 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure), and 11 (Sustainable Cities and Communities). This study, grounded in qualitative surveys of engineering instructors at Université Loyola du Congo (ULC), demonstrates how the framework addresses pedagogical limitations while building technical competency and sustainability consciousness. The research reveals that traditional didactic methods inadequately prepare students for complex sustainability challenges, while the AIPLE framework’s integration of AI-assisted learning, practical problem-solving, and sustainability-focused projects offers a scalable solution for engineering education transformation in resource-constrained environments. Our findings indicate strong instructor support for PBL methodologies and cautious optimism regarding AI integration, with emphasis on addressing infrastructure and ethical considerations. The AIPLE framework contributes to sustainable development by preparing engineers who are technically competent and committed to creating environmentally responsible, socially inclusive, and economically viable solutions for developing countries. Full article

This study investigates the utilisation of AI tools, including Grammarly Free, QuillBot Free, Canva Free Individual, and others, to enhance learning outcomes for 180 s-year telecommunications engineering students at Universidad Politécnica de Madrid. This research incorporates teaching methods like problem-based learning, experiential learning, task-based learning, and content–language integrated learning, with English as the medium of instruction. These tools were strategically used to enhance language skills, foster computational thinking, and promote critical problem-solving. A control group comprising 120 students who did not receive AI support was included in the study for comparative analysis. The control group’s role was essential in evaluating the impact of AI tools on learning outcomes by providing a baseline for comparison. The results indicated that the pilot group, utilising AI tools, demonstrated superior performance compared to the control group in listening comprehension (98.79% vs. 90.22%) and conceptual understanding (95.82% vs. 84.23%). These findings underscore the significance of these skills in enhancing communication and problem-solving abilities within the field of engineering. The assessment of the pilot course’s forum revealed a progression from initially error-prone and brief responses to refined, evidence-based reflections in participants. This evolution in responses significantly contributed to the high success rate of 87% in conducting complex contextual analyses by pilot course participants. Subsequent to these results, a project for educational innovation aims to implement the AI-PBL-CLIL model at Universidad Politécnica de Madrid from 2025 to 2026. Future research should look into adaptive AI systems for personalised learning and study the long-term effects of AI integration in higher education. Furthermore, collaborating with industry partners can significantly enhance the practical application of AI-based methods in engineering education. These strategies facilitate benchmarking against international standards, provide structured support for skill development, and ensure the sustained retention of professional competencies, ultimately elevating the international recognition of Spain’s engineering education. Full article

This study presents a vertically integrated Project-Based Learning (PBL) and Community-Based Learning (CBL) framework that connects postgraduate and undergraduate programs in Applied Chemistry and Agricultural Engineering. Postgraduate students synthesized zeolite-based materials for nutrient recovery, which were subsequently applied by undergraduate students in field trials conducted in collaboration with rural farming communities. The project was evaluated using rubrics, surveys, focus groups, and reflective journals. Results demonstrated substantial development of technical, communication, and critical thinking skills, with students highlighting the value of linking theory to practice. Community feedback confirmed the perceived benefits of the material for soil improvement and fertilizer efficiency, while also underscoring the need for sustained engagement. Despite challenges such as curricular coordination and resource constraints, the model effectively fostered interdisciplinary learning and social impact. These findings highlight the contribution of this sequentially instructional design to STEM education by connecting research, teaching, and outreach within a constructivist, sustainability-oriented approach. Full article

Digital portfolios have become an essential assessment tool in project-based and student-centered learning environments. Unfortunately, students exert minimal effort in creating digital portfolios because they find the writing component unchallenging. This issue is concerning since existing research predominantly focuses on the use of pre-existing platforms for building digital portfolios. With this concern, there is an opportunity to explore more challenging approaches to digital portfolio creation. Consequently, this study employs a project-based learning (PBL) approach within a website design and development course, where 176 undergraduate students completed weekly coding tasks culminating in a self-coded digital portfolio. Using a one-group posttest-only research design, data were collected through a structured questionnaire that included demographic items and validated scales measuring learning effectiveness and ownership of learning. The survey was administered electronically after students submitted their digital portfolio projects. The results reveal that device ownership shows only weak associations with students’ perceptions, while internet connectivity and self-reported academic performance demonstrate stronger relationships with engagement and ownership of learning. Additionally, prior experience with digital portfolios positively influences students’ engagement, motivation, and ownership of learning. Implications of these findings are discussed for supporting the integration of digital portfolios into technical disciplines. Overall, this study contributes to the literature on PBL methodology, expands our understanding of digital portfolio integration, and underscores the significance of student-centered pedagogies. Full article

This study investigates Project-Based Learning (PBL) to boost student engagement in a Transport Phenomena course at the Federal University of Mato Grosso do Sul (UFMS). Through a hands-on project involving Floating Treatment Islands (FTIs) for water quality improvement, PBL was hypothesized to enhance student involvement and analytical skills. Students designed and optimized FTIs, experimenting with configurations like root length and plant type. Quantitative outcomes reveal a standard deviation of 1.5 in project scores among top performers (course average > 6), reflecting diverse problem-solving strategies, while a standard deviation of 0.8 near the passing threshold (course average ≈ 6) indicates consistent efforts to improve grades. Additionally, 80% of students rated their experience ≥ 4 on a 5-point scale, signaling high satisfaction, although 40% identified data interpretation as a challenge requiring targeted support. Outcomes were assessed by analyzing score variability, revealing higher standard deviations among top performers, indicating diverse problem-solving approaches, while lower deviations near the passing threshold suggested uniform efforts to improve grades. Despite general satisfaction, some students faced data interpretation challenges, highlighting areas for instructional refinement. The results affirm PBL’s effectiveness in fostering engagement and practical skills but suggest that adaptive teaching methods are essential to support comprehension and maintain engagement across different performance levels. Full article

This study investigates the integration of LTspice simulations and structured reflective practices within a project-based learning (PBL) framework in a Microelectronic Circuits course. The course was designed to improve students’ conceptual understanding, problem-solving abilities, and engagement by embedding simulation-based assignments and guided reflections within a final design project. A qualitative case study was conducted with 49 third-year undergraduate electrical engineering students. The data sources included structured reflection submissions, researcher observations, and evaluations of project presentations. Thematic analysis identified five recurring themes: linking theory to practice, iterative problem-solving strategies, metacognitive awareness, peer engagement, and reflections on integration challenges and benefits. The results indicate that the LTspice simulations enabled the students to visualize circuit behavior, experiment with design parameters, and observe the effects of design trade-offs. The integration of structured reflection prompted deeper learning by helping the students recognize misconceptions, articulate troubleshooting strategies, and build confidence in circuit analysis. Although some students initially struggled with the complexity of the simulation software, the iterative and collaborative nature of the PBL process increased their motivation and promoted meaningful engagement. This study contributes to the growing body of research on active learning in engineering education and offers practical recommendations for implementing simulation-based learning environments that promote critical thinking, metacognition, and technical competence. Full article