Higher education programs are embracing curricular models that incorporate active teaching-learning methodologies to foster students’ active participation in knowledge building, based on competency-based training. Research-based learning (RBL) stands out as an active methodology that can be used at various academic levels, including undergraduate. In this context, the present research explores the contribution of undergraduate research training to the process of developing generic competencies in engineering students. The study focuses on the perceptions of a group of employers and graduates from a Peruvian higher education institution. A mixed-methods approach was adopted, as interviews and surveys were applied. The study had a descriptive purpose with a concurrent design. The findings suggest that undergraduate research training is perceived as supporting the development of generic competencies such as research, teamwork, effective communication, analytical and critical thinking, adaptability, digital literacy, intellectual curiosity, and lifelong learning (LL). Overall, the results highlight undergraduate research training, implemented through RBL, as an effective strategy associated with the development and strengthening of generic competencies and the alignment of Science, Technology, Engineering, and Mathematics (STEM) education with labor market demands, while underscoring the importance of consolidating an institutional research culture within competency-based curricula.
This paper examines the strategic importance of cybersecurity education as a pedagogical and managerial mechanism for strengthening organisational resilience. Responding to the need for practice-orientated engineering pedagogy, the paper formulates a guiding research question: How can role-specific cybersecurity education be selected, justified, and evaluated so that it supports resilient behaviour across organisational levels? The study combines a structured narrative review of cybersecurity education and awareness approaches with a transparent SWOT-based analytical framework. SWOT is used as a managerial self-assessment tool for identifying strengths, weaknesses, opportunities, and threats in both the general cybersecurity environment and the human-factor dimension. The paper distinguishes gamification from games, explains the rationale for selecting educational approaches, and proposes operational criteria for translating SWOT findings into training requirements. The contribution is intended for educators, cybersecurity managers, and organisational leaders who design or evaluate cybersecurity awareness programmes in engineering-orientated, technical, and socio-technical environments.
This study aimed to develop and evaluate a flipped, microlearning, and augmented reality model to enhance undergraduate engineering students’ conceptual understanding and problem‑solving skills in an electrical circuit laboratory course. The participants consisted of 43 first‑year engi‑ neering students, divided into an experimental group (n = 21) and a control group (n = 22). The experimental group was instructed using the integrated model, while the control group received traditional instruction. Research instruments included a learning achievement test, a problem‑solving skills rubric, and a satisfaction questionnaire, all of which demonstrated acceptable validity and reliability. Data were analyzed using multivariate analysis of variance (MANOVA) and mixed ANOVA. The findings indicated that students in the experimental group significantly outperformed those in the control group in both learning achievement (p < .05) and problem‑solving skills (p < .01). In addition, the experimental group demonstrated greater learn‑ ing retention at two weeks after instruction. These results suggest that integrating augmented reality and microlearning within a flipped classroom framework effectively supports conceptual understanding and enhances problem‑solving skills in engineering education. The integrated model provides a practical instructional approach for improving laboratory‑based learning in science and engineering contexts. This study extends existing research by providing an instruc‑ tional framework that supports both cognitive and experiential learning in higher education.
Engineering students struggle with abstract concepts and theory-practice integration, yet few studies systematically examine how to design virtual reality (VR) learning environments that sustain engagement beyond initial novelty effects. Multi-modal approaches that strategically integrate different technological affordances offer promising but underexplored solutions. This design case study demonstrates the development and implementation of a multi-modal VR learning environment integrating immersive Cave Automatic Virtual Environments (CAVE), non-immersive MATLAB simulations, and artificial intelligence (AI) motion tracking within project-based learning (PjBL). We investigate how different technological modalities can be strategically orchestrated to support situational interest development in undergraduate engineering education. We designed and implemented a four-week “Biomechanics of a Pitch” project in a Strength of Materials course, engaging 20 undergraduate mechanical engineering students. Using an exploratory case study approach with convergent mixed-methods data collection, we measured presence, representation fidelity, and situational interest through validated instruments (α = 0.92–0.93) and focus groups. Data was analyzed through reliability analyses, descriptive statistics, and thematic analysis to understand design effectiveness and student experiences. The multi-modal design enabled distinct complementary technological affordances: CAVE excelled in spatial presence (α = 0.93) and immersive understanding (M = 4.2, SD = 0.8), MATLAB supported analytical thinking and pedagogical usefulness, while AI motion tracking created personalized connections. Student interest evolved from pre-experience curiosity through maintained engagement during multi-modal experiences to post-experience learning motivation. Qualitative data revealed how strategic modality transitions sustained engagement beyond novelty effects. We present an integrated framework synthesizing interest development theory with multi-modal VR design principles, demonstrating how theoretically grounded VR implementations move beyond novelty effects through strategic technological orchestration. The study contributes a design framework, evidence-based design checklist, and practical implementation guidelines for engineering educators seeking to create effective VR-enhanced learning experiences.
This study designed an AI-integrated collaborative problem-based learning (CPBL) course aimed to bolster programming self-efficacy among undergraduate and to elucidate the underlying psychological mechanisms that drive self-efficacy. A total of 179 Taiwanese undergraduates participated in an 18-week intervention that integrated AI toolkits, CPBL frameworks, and instructional scaffolding to facilitate interdisciplinary application. To achieve our goals, two instruments were developed to measure programming-specific achievement goals and mindsets. The results indicated that the AI-supported CPBL environment effectively fostered a growth mindset, mastery experiences, and self-efficacy in programming. Mediation model analysis revealed that growth mindset and mastery experience functioned as dual mediators linking achievement goal orientation to self-efficacy. Notably, mastery goals exerted a markedly stronger influence on self-efficacy compared to performance goals. The findings highlight the necessity of prioritizing mastery-oriented pedagogy in the design of AI-integrated programming curricula.
