Asean Journal of Engineering Education (AJEE) The ASEAN Journal of Engineering Education (AJEE) (eISSN: 2231-9433) welcomes papers that bridge the world of theory and practice in engineering education. It considers manuscripts focusing on theory as well as those focusing on practice, assessment and innovation in engineering education. Focus and Scope There are two sections in the journal where the first section focuses on rigorous research on engineering education, while the second section includes papers that offer scholarly experience sharing on the practice and innovation in engineering education strategies. Engineering Education comprises research areas of epistemology, teaching and learning, assessment, curriculum, accreditation, first-year experience, talent grooming from school level and others that can further improve engineering education to meet the challenges of the 21st century. Indexed by: MyJurnal
From STEM Identity to Engineering Identity: A Critical Review of Theoretical Development and Emerging Research Directions
Engineering identity has become an important construct in engineering education research because of its influence on student engagement, persistence, belonging, and professional development. However, its theoretical foundations remain dispersed across psychology, sociology, science education, STEM education, and engineering education. This paper presents a structured critical review of engineering identity research by tracing its development from foundational identity theories through science and STEM identity frameworks to contemporary engineering identity models. Drawing on 49 core publications published primarily between 2000 and 2026, the review shows that engineering identity has gradually consolidated around three core dimensions: interest, performance and competence, and recognition. Contemporary scholarship, however, has expanded beyond this tripartite structure to include agency, belonging, emotional experience, developmental perspectives, contextual variation, and professional readiness. The review identifies key challenges in the literature, including conceptual fragmentation, methodological concentration, Western-centred evidence, and limited longitudinal understanding. Based on these findings, the paper proposes future research directions that emphasise contextualisation, ASEAN and Global South perspectives, industry readiness and employability, longitudinal inquiry, and more integrated identity frameworks. This review contributes by consolidating the theoretical evolution of engineering identity and clarifying opportunities for future conceptual and empirical development.
Copyright (c) 2026 Asean Journal of Engineering Education
Exploring Student Learning Experiences in a PowerPoint-Based Open-Ended Virtual Laboratory for Environmental Engineering Education
Virtual laboratory technology can provide students with the same learning outcome through a simulated experiment without accessing a physical laboratory. It can also be designed to be open-ended, allowing students to develop the methodology to solve a given problem. This is in-line with Outcomes-Based Education as required by the Engineering Accreditation Council of Malaysia. Therefore, the development of an open-ended virtual laboratory and understanding of how it impacts learning outcomes and student engagement are important. This study developed an interactive, animated, open-ended virtual laboratory for an undergraduate environmental engineering water treatment course using the PowerPoint platform, and its effectiveness in delivering hands-on laboratory instruction was measured from students’ perspectives. Students’ attainment of the learning outcome was analysed through their laboratory assessment, and their engagement with the virtual laboratory was measured using a survey. The results showed that students successfully navigated the open-ended laboratory assessment and achieved the intended learning outcome. In terms of learning engagement, 90% of students agreed that the virtual laboratory was easy to operate and understand, flexible, stimulating, satisfying, and good for distance learning. However, only 20% of students agreed that they learned and understood more in a virtual laboratory than in a physical one, and only 10% reported gaining hands-on skills through the virtual laboratory.
On augmenting students’ learning in beam structures using numerical simulations
Virtual laboratories are seen as an alternative to the delivery of traditional laboratory activities. Additionally, it can be used to supplement or complement traditional teaching practices, especially for engineering topics that are typically assumed by students to be difficult to grasp. In this paper, the use of numerical simulations for a laboratory exercise on a major course in aerospace engineering will be discussed. Moreover, the influence of finite element analysis (FEA) on the learning process of students regarding beam profile and bending performance will be highlighted. SolidWorks program was used for the modeling and structural analysis of beam profiles under predetermined conditions. Numerical model verification and validation were made using established formulae and theories from engineering mechanics. This method was later implemented under the aerospace laboratory course for aerospace engineering students. Fourteen (14) students were asked to report the results of their simulations as well as observations on the structural performance of the beams through a laboratory report. Students' consent to perform content analysis of their reports was secured through Google survey. Applying FEA, students were able to establish connections between beam profile, moment of inertia and bending stiffness, which are often hard to explain in traditional teaching methods. Further, students better appreciate theories associated with beams and their application to aircraft structures. As we navigate a VUCA environment and rapid advancements in computing, numerical simulation programs can supplement or provide alternative avenues where students can learn topics that are conventionally perceived to be challenging.
Education in the Mirror of Institutions: A Systematic Review of Service Quality and Character
Transformation of higher education services demands the integration of digital services and institutional character in facing the challenges of accessibility, inclusion, and digitalization. This study examines the effectiveness of Service Quality and E-Service Quality models in academic and administrative services, the methodological challenges of using Analytical Hierarchy Process (AHP), Fuzzy Logic, and Importance Performance Analysis (IPA), and the role of institutional characteristics as mediators or moderators of student satisfaction and trust. This study uses a Population, Intervention, Comparator, Outcomes, and Context (PICOC) + Urgency of research and research motivation (UM) -based SLR approach to examine higher education services. Through the synthesis of 26 selected articles (2022–2025), multicriteria analysis such as AHP, Fuzzy, IPA reveals supporting factors, service effectiveness, and institutional contributions to its transformation. This study builds the Framework of Service Quality Impact in Higher Education Institutions (FSQIHEI) model to transform higher education digital services through the integration of AHP, Fuzzy, and IPA. Its contributions include literature mapping 2023–2025, emphasis on Service Quality, and differentiation of service strategies between public and private universities. Institutional characteristics are introduced as important variables in measuring student satisfaction and trust in a sustainable manner. This study includes an institutional characteristics-based FSQIHEI model, strengthening the Service Quality literature, and offering an evaluative approach to digital higher education services that is responsive, measurable, and contextual.
Cracking Engineering Physics through Crossword Puzzles: A Gamified Active Learning Approach to Enhance Engagement and Concept Retention
This study intends to examine how well gamified active-learning resources, more especially, crossword puzzles, improve student engagement, memory and conceptual understanding of physics topics in first year engineering students. This study offers a scalable, interactive teaching approach intended to close the gap between passive listening and active cognitive involvement in technical subjects, even though standard lecture-based engineering approaches frequently result in shorter attention spans and poor memory. The method uses gamification to turn rote memorizing of technical terms and difficult ideas into a fun, competitive and introspective experience that supports certain learning objectives based on the active learning principle. Crossword puzzles were used as tools for review and pre-assessment of about 300 undergraduate B. Tech students from different branches. A mixed-methods strategy was used to collect the data, measuring both quantitative gains and qualitative involvement through the use of pre- and post-quiz scores, mid-semester examination results, and structured student feedback. As per the results obtained, crossword puzzles are a useful addition to engineering education since they greatly increase conceptual clarity and technical language memory. These findings imply that the drawbacks of conventional physics instruction can be effectively addressed by incorporating gamified components.
Design-Based Learning (DBL) Under Contextual Constraints: A Framework for Form 3 Design and Technology Education in Rural Malaysia
Design‑Based Learning (DBL) has been widely promoted as a learner-centred pedagogy that engages students in creative, hands‑on, and problem‑solving tasks. In Malaysia, DBL aligns closely with the Design and Technology subject (Rekabentuk dan Teknologi – RBT) introduced under the Secondary School Standard Curriculum (KSSM). However, most DBL models are often conceptualised in well-resourced environments that assume access to specialised tools and digital technologies. Limited empirical research has examined how the approach is enacted in under-resourced rural settings. This qualitative study explores how DBL is enacted, adapted, and constrained in rural school contexts in three rural secondary schools in Kudat, Sabah. Drawing on semi-structured interviews with nine RBT teachers, including three school administrators who also teach RBT, and six Form 3 RBT students, alongside document analysis, the study employed inductive thematic analysis to examine classroom realities and contextual challenges. Four interrelated themes emerged: inadequate material and infrastructural resources, tensions in integrating theory and practice, difficulties in assessing design processes, and limited professional and community support. Guided by constructivist, place-based, and social learning perspectives, these findings were interpreted to develop a contextualised DBL framework that responds to the realities of under-resourced rural settings. The proposed framework emphasises pedagogical flexibility, process-oriented assessment, and enabling support structures to support more inclusive and sustainable DBL implementation. This study contributes to the literature by extending existing understandings of Design-Based Learning through an examination of how DBL is reshaped by contextual constraints in rural and under-resourced secondary school environments. The study contributes to ongoing efforts to reduce educational inequities in line with the Malaysia Education Blueprint 2013–2025 and aligns with Sustainable Development Goals 4, 5, 9, 10, and 17 by advancing equity, innovation, and collaborative learning in underserved communities.
Digital Twin driven classrooms: A case study of an AI-augmented conceptual framework for adaptive learning
The rapid expansion of digital education has improved access to learning but has also revealed persistent limitations related to personalization, real-time adaptability, scalability, and learner engagement. Many existing digital learning platforms and AI-based tools operate as isolated solutions, offering limited integration and treating learners as passive recipients of instruction. To address these challenges, this paper proposes a conceptual framework for AI-augmented Digital Twin classrooms (AIDTC) that reconceptualizes the classroom as an intelligent cyber-physical learning system. The framework was developed through a structured synthesis of interdisciplinary literature spanning Digital Twin theory, cyber-physical systems, artificial intelligence in education, and immersive learning. Drawing on advances in digital engineering and Industry 4.0/5.0 principles, the framework integrates Digital Twin modeling, artificial intelligence, immersive learning technologies, and human-in-the-loop orchestration within a layered architecture. Continuous synchronization between learner interactions and dynamic digital representations enables proactive instructional adaptation based on real-time behavioral, cognitive, and contextual data. The proposed architecture comprises four interconnected layers perception, cognition, immersion, and orchestration supporting data capture, intelligent reasoning, immersive learning delivery, and transparent pedagogical control. The study adopts a conceptual framework development approach supported by a single case study to demonstrate how the framework can be applied in a higher-education setting. While empirical generalization is beyond the scope of this work, the case demonstrates the internal coherence, feasibility, and applicability of the proposed framework. Overall, the AIDTC framework offers a future-ready blueprint for developing intelligent, ethical, and learner-centered digital classrooms that extend beyond conventional online and hybrid learning paradigms.
Bridging Gaps in Electronic Circuit Design Education: An Action Research Study
This paper presents an action research project aimed at improving the performance of second-year students in electronic circuit design, as part of their practice in the undergraduate module MEC104 at Xi’an Jiaotong-Liverpool University. Several issues have been identified through observations by module leaders and feedback from students, including gaps between lectures and lab sessions, safety concerns, and lengthy debugging periods. To address these challenges, this study proposed integrating the TinkerCAD simulation tool into the module, outlining a three-step action research plan. The results and analysis indicate a positive impact of the simulation-based approach on student learning and performance in electronic circuit design. The paper concludes with a discussion of future work in this area.
Student Performance Prediction Using the UCI Dataset: A Comparison of Interpretable and Ensemble Models
AI technologies have not only transformed teaching methods but have also provided novel solutions for education management, assessment, and personalized learning. This study examines whether complex machine learning models consistently outperform simple interpretable approaches in predicting student outcomes. Using the UCI Student Performance dataset, five key predictors: First period grade (G1), Second period grade (G2), Number of past class failures (Failures), Mother's education level (Medu) and Higher education aspiration (Higher), were extracted from 32 original attributes. Three models, including Linear Regression (LR), Random Forest (RF), and an Ensemble Model (EM), were evaluated across Mathematics and Portuguese subjects using MSE, RMSE, MAE, and , with five-fold cross-validation to assess robustness. Experimental results demonstrate that Linear Regression achieved the best overall performance in both subjects, with = 0.779 for Mathematics and = 0.862 for Portuguese , whereas RF and EM did not yield consistent gains. Portuguese is generally more predictable than Mathematics under the same pipeline. Feature influence analysis indicates that early-term grades (G1 and G2) dominate predictive power, suggesting that the approach supports mid-semester/operational prediction rather than start-of-term early-warning. Overall, the findings highlight the practical value of interpretable models for educational analytics when transparency and deployability are important.
Improving Learning Experiences with Project Development and Problem-Solving Using Microcontroller – A Case Study
This paper presented an innovative teaching practice to promote problem-based learning via an Internet of Things (IoT) and Arduino microcontroller workshop. This educational research evaluates the participants’ improvements in terms of the knowledge, confidence level and motivation. The participants included multi-disciplinary engineering students, who have enrolled in Electrical Systems (ELEN1000), whereby they completed all given tasks in teams and within a limited time. At the end, total of 91 respondents’ feedback was accumulated and analyzed via descriptive, T-test and ANOVA analysis. T-test 1 (p = 0.08135) found that the workshop improved participants’ excitement. T-test 2 (p = 0.1323) explained that the workshop activities help to visualize the learned knowledge. Nevertheless, T-test 3 (p = 0.02) implied that the developed confidence level did not improve respondents’ capability to generate spontaneous ideas. T-test 4 (p = 0.15999) highlighted that respondents are impressed with their capabilities after viewing the results. ANOVA Test 1 revealed that knowledge visualization significantly enhanced participants’ confidence levels; however, it was insufficient to substantially improve their ability to generate spontaneous ideas for problem-solving. These findings suggest the need for additional activities that expose participants to a broader range of IoT applications. Overall, all respondents reported highly positive perceptions of the workshop and expressed inspiration to utilize microcontrollers in their future projects.
Unlocking Learning Potential in Advanced-level Mathematics: AI-Driven Spaced Retrieval for Enhanced Pedagogy
Retrieval practice is an effective learning approach that involves students actively retrieving knowledge from memory after completing the lesson (like lectures, workshops, and labs), which improves memory retention and fosters long-term learning. In short, this study underpins Retrieval Practice Theory. Unlike the pre-test, which involves taking practice tests before learning new information as opposed to afterward, retrieval practice is a strategy where students are tested on questions about unit materials that they have already learned. However, a more interactive spaced retrieval practice using a new platform, such as the highly recommended AI-powered question generators like Edapp, is still limited. This new spaced retrieval practice was implemented two times per semester for mid-semester tests, and then the data was collected for analysis. Based on an engineering first-year unit, namely MATH1020 Calculus for Engineers, after implementing spaced retrieval practices in the first semester of 2024, a significant increase in the passing rate was observed, up to 20.33%. The 95% confidence intervals for the passing rates further reinforce this improvement, showing that the post‑intervention cohort’s performance was not only higher but also statistically more precise compared to the pre‑intervention groups. This substantial improvement demonstrates the effectiveness of the newly proposed intervention.
This paper introduces AI-Marking Assistant (AI-MA), a prototype application that aims to improve the efficiency and consistency of grading and grading feedback by allowing educators to integrate Generative Artificial Intelligence (GAI) assistance into the grading process. While automated grading has the advantages over traditional human marking of being efficient, timely, consistent, scalable, and objective, there are also known limitations and potential issues associated with process. Grading and feedback can lack the nuance and context that would normally come from an expert marker. Results can also be biased by the training data and there are significant ethical and legal implications of allowing a machine to grade assignments without human oversight. AI-MA aims to overcome these limitations by offering a human-in-the-loop GAI assisted interface that allows educators to leverage the power of GAI while keeping an active oversight and interactive role in the marking process. AI-MA allows human graders to manually mark assignments, or edit the output of a GAI model with results fed back to the model in order to improve its performance. A pilot study with the application demonstrates its potential to significantly improve grader performance while maintaining the quality of marking and grade feedback for students.
Copyright (c) 2025 Asean Journal of Engineering Education
Process Eye-Tracking Data with Machine Learning Approach in Context of Fundamentals of Electrical Engineering
In this research study, first-semester students solved tasks in the context of the fundamentals of electrical engineering. They were wearing eye-trackers while solving the tasks. The collected data is used to train a machine learning model per task, that predicts based just on eye-tracking data, if a student is about to succeed in solving a specific task or if the student is about to fail. The trained models reach an accuracy of 85% respectively 91% depending on the task. In the future, this model will be integrated into a virtual environment where eye-trackers are present, to assist those students who might fail.
Digital Transformation of Primary and Secondary Education Institutions: A Case of the Czech Republic
Digital transformation (DT) of primary and secondary (P&S) education in the Czech Republic has accelerated over the past decade, yet research on its impact and digital maturity (DM) remains limited. This gap is significant given the global emphasis on technology-driven learning environments and the evolving role of students, teachers, and parents. This study investigates how DT influences the quality of the education process and stakeholder interactions in Czech P&S institutions. Three research questions guide the analysis: students’ perception of DT, their need for increased IT integration, and whether DT affects communication between students, teachers, and parents. An exploratory survey was conducted among 65 students aged 6–19 across all Czech regions. Findings indicate that DT is generally perceived positively, though attitudes toward increased IT use remain neutral, and its influence on communication is inconclusive. The study contributes by providing empirical evidence on DT and DM in Czech P&S education, highlighting regional disparities and offering a basis for future comparative research.
The Implementation of Book-end Division Approach using ClassPoint in Digital Electronics Courses
This paper explores the integration of the Book-End Division Approach with ClassPoint within the Technology-Enhanced Learning (TEL) framework to enhance student engagement in Digital Electronics courses at the Faculty of Electrical and Electronics Engineering Technology (FTKEE), Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA). Conventional teaching methods frequently face challenges to engage students, particularly in technical disciplines like electrical and electronic engineering. The study leverages a student engagement framework to foster an interactive learning environment, utilizing ClassPoint's interactive features to promote active participation, and collaboration among students. The Book-End Division Approach divides class sessions into advanced organizing, intermittent discussions, and closure. Results indicate significant impacts in student participation and motivation, with over than 90% of the students agree ClassPoint TEL made the classroom environment more motivating.
A Scoping Review of Diversity, Equity, and Inclusion in Energy Engineering Education
A diversity, equity, and inclusion (DEI) problem persists in undergraduate programming, despite energy engineering receiving increasing attention as a critical field in addressing sustainability and global energy challenges. This paper examines the current situation of energy engineering education on DEI worldwide based on the areas of gender, race, and socioeconomic inclusion. This discussion examines the challenges and explores inclusive pedagogy, curriculum structure, faculty development, student mentoring, and institutional commitment. The review concludes that, although some of these initiatives are promising, integration is cursory and inconsistent. Embedding DEI in teaching pedagogy, institutional frameworks, and policy to enhance the undergraduate students' learning outcomes and equity in energy engineering is recommended.
Designing Better Engineering Education Through Assessment: A Book Review
Designing Better Engineering Education Through Assessment: A Practical Resource for Faculty and Department Chairs on Using Assessment and ABET Criteria to Improve Student Learning, edited by Joni E. Spurlin, Sarah A. Rajala, and Jerome P. Lavelle, provides a comprehensive guide to enhancing engineering education through effective assessment practices aligned with ABET accreditation standards. Aimed at faculty members and department chairs, this book focuses on the practical application of assessment methods to improve student learning and meet accreditation criteria. It explores the role of both formative and summative assessments in evaluating student outcomes at various stages of the engineering curriculum, from introductory courses to capstone projects and graduate education. The book is divided into four main parts: the basics of assessment, barriers and challenges to effective implementation, assessing student learning across the educational continuum, and the future of assessment in engineering education. The first part introduces fundamental assessment concepts and the importance of aligning assessments with desired learning outcomes. The second part addresses common obstacles, such as faculty resistance and institutional inertia, and provides strategies for overcoming these challenges. Part three discusses the integration of assessment throughout the engineering education experience, emphasizing methods used at different educational stages. The final part looks ahead, examining emerging trends and technologies that could transform the future of assessment. Through its practical examples, case studies, and expert insights, this book serves as a valuable resource for those seeking to improve engineering programs by ensuring that student learning is effectively measured and continuously enhanced. It offers actionable strategies for creating a culture of assessment that supports the ongoing improvement of engineering education.
Between ABET and EUR-ACE Accreditation: A Decision-Oriented Framework for Engineering Programs Outside the U.S. and Europe
Engineering program accreditation plays a critical role in assuring educational quality, supporting graduate mobility, and enhancing institutional credibility in an increasingly globalized higher education landscape. Among the most influential accreditation systems worldwide, ABET and the EUR-ACE® label represent distinct accreditation paradigms shaped by different professional, academic, and governance traditions. While both frameworks are widely adopted beyond their regions of origin, institutions outside the United States and Europe face limited guidance in selecting the accreditation pathway that best aligns with their mission, graduate trajectories, and external environment. This study addresses this gap through a qualitative, document-based comparative analysis of ABET and EUR-ACE accreditation frameworks. Official accreditation criteria, policy documents, and peer-reviewed literature are systematically analyzed to examine differences in accreditation philosophy, student outcome structures, recognition mechanisms, and mobility pathways. Rather than ranking the two systems, the study develops a decision-oriented analytical framework that supports strategic accreditation choice based on institutional objectives, labor-market orientation, and academic mobility considerations. The analysis shows that while ABET is strongly aligned with professional practice and industry recognition, EUR-ACE is more closely embedded in academic mobility and qualification transparency within the European Higher Education Area. The proposed framework provides institutional leaders and policymakers with a structured tool to align accreditation decisions with regional context and long-term strategic goals.
The Doctor of Efficiency: Philosophical Reflections on Knowledge and Meaning in the Age of AI
Artificial intelligence has accelerated knowledge production while quietly redefining what counts as knowing. Within universities, this transformation is most visible in the PhD; traditionally a Doctor of Philosophy devoted to slow inquiry and reflective understanding. As AI systems generate research outputs, structure arguments, and even simulate reasoning, the doctoral identity risks mutating into that of a Doctor of Efficiency: a figure of technical productivity optimized for metrics rather than meaning. This essay traces the philosophical genealogy of that shift, from Weber’s instrumental rationality to contemporary algorithmic epistemology, arguing that AI represents the culmination, not the cause, of a long drift from wisdom to calculation. Drawing on Arendt, Simondon and Floridi, it diagnoses how automation displaces comprehension and how academia’s fixation on speed undermines intellectual responsibility. The paper concludes by proposing an alternative ethos for the digital university grounded in cognitive authenticity, epistemic humility and reflective effort; the virtues through which intelligence regains its human depth.
Emotional Intelligence in Engineering Problem-Solving: A Phenomenological Study Among Manufacturing Engineers
Engineering graduates often enter the workforce with underdeveloped emotional intelligence (EI), leading to challenges in emotional regulation, decision-making, and social interactions that subsequently impact their employability and job performance. Despite its recognized importance for professional success, the integration of EI into engineering education remains inconsistent. This study aims to identify the essential Emotional Intelligence competencies required for successful engineering problem-solving. Using a phenomenological approach, semi-structured interviews were conducted with practicing engineers in a manufacturing setting. The findings reveal three key EI competencies frequently demonstrated by engineers, which are now formulated as empirical insights: (1) Initiative – Taking proactive steps to address issues and empirically validate assumptions; (2) Adaptability – Strategically adjusting to changes and collaborating across departments to manage uncertainty; and (3) Self-Recognition – Deep awareness of one's strengths, limitations, and the impact of one's behaviour on the team. These findings offer clear empirical insights into the critical role of Emotional Intelligence within the manufacturing engineering context, suggesting that engineering education programs should explicitly teach these skills.
ABET and Global Quality in Engineering Education
A strong commitment to educational quality and continuous improvement is essential in the development of any engineering program seeking international recognition. Through a comprehensive process of self-assessment, documentation, and external evaluation, such programs demonstrate compliance with global standards of engineering education. International accreditation validates the academic, curricular, and formative strength of a program, ensuring that graduates are well-equipped to address complex challenges in a globalized professional environment. The integration of best teaching practices, industry collaboration, and an outcome-based educational model are critical to achieving and sustaining excellence. This achievement reflects the institution’s dedication to delivering a comprehensive, relevant, and globally aligned education that meets both current market needs and international expectations in higher education. This study addresses this challenge by documenting and analyzing the specific institutional experience of one engineering program during its latest ABET accreditation cycle. The work details the chronology of the procedures and efforts required, including the development and documentation of compliance with the eight ABET criteria, the preparation of the self-study report, and the external evaluation. The findings provide a practical methodological blueprint for other institutions and emphasize the critical necessity of integrating an Outcomes-Based Education model and sustained continuous improvement practices to achieve and maintain global quality.
Development and Validation of an Instrument Assessing Biomedical Engineering Competencies, AI Readiness, and Organisational Support
This study presents the development and validation of a survey instrument designed to assess the competence of biomedical engineers in AI-integrated healthcare settings. Based on the KSAA (Knowledge, Skills, Abilities, and Attitudes) framework, the instrument incorporates AI readiness and perceived organisational support (POS) as mediators of job performance. The items were adopted and adapted from established studies and refined through expert opinion analysis involving five experts from academia and industry, followed by feedback from 10 postgraduate reviewers. A pilot study was conducted with 40 biomedical engineers in this study group using the same criteria as the intended full-scale study. Data were analysed using SPSS version 30.0, focusing on internal consistency through reliability analysis. Results showed strong reliability across all dimensions, with Cronbach's alpha values ​​ranging from 0.823 to 0.897. This paper only reports the validation phase of the instrument; testing of the mediation hypothesis will be conducted in a subsequent full-scale study. Validated instruments provide a reliable foundation for future workforce development, training programmes, curriculum enhancements, and large-scale data collection in AI-driven healthcare environments.
Impact of Workplace Support on Career Advancement of Electrical Trade Teachers in Technical Colleges
One of the key factors for employee to reach the peak of their career is the level of support from colleagues or those around them. This is crucial for professional development and career progress. Hence, this study examines the impact of workplace support on the career advancement of electrical trade teachers in technical colleges in Ogun State, Nigeria. Descriptive survey research design was adopted for the study. The population for the study comprised all the thirty (30) electrical trade subject teachers across the 8 technical colleges in Ogun State. Structured questionnaire was used for data collection. Data were analyzed using mean and standard deviation, correlation and regression. The findings of the study revealed that no significant relationship exist between workplace support and career advancement of electrical trade teachers (r=.033; p˃0.05). Also, workplace support significantly influences career advancement of electrical trade teachers (β= .312; p<0.05) in technical colleges in Ogun State. It was concluded and recommended that workplace support plays a crucial role in shaping professional growth and career progression of electrical trade teacher’s. Therefore, educational stakeholders should collaborate with industries for regular workshops, training sessions, and certification programs to keep teachers updated with the latest industry trends and teaching methodologies.
Integrating SOLO Taxonomy with Active Learning in Chemical Engineering Process Simulation
This study presents a structured pedagogical intervention that integrates Active Learning strategies with the Structure of the Observed Learning Outcome (SOLO) Taxonomy to enhance cognitive development and technical competency in a Process Simulation and Integration course for third-year chemical engineering students. The course was redesigned to align weekly learning activities with SOLO’s five hierarchical levels, progressing from basic unit operations to advanced process optimization using tools such as Aspen HYSYS. Active learning techniques including hands-on simulations, team-based problem-solving, reflective journals, and gallery walks were implemented during Semester 2 of the 2022/2023 session at Universiti Malaysia Sabah (UMS), engaging 50 students in a scaffolded learning journey. Assessment data showed a 48% improvement in problem-solving proficiency, alongside enhanced software fluency and teamwork. Reflective journals and peer evaluations confirmed gains in conceptual understanding and confidence in tackling complex engineering problems. The findings underscore the value of aligning cognitive taxonomies with active pedagogical strategies to support deep learning, engagement, and real-world application. This approach offers a replicable model for engineering educators aiming to foster 21st-century skills in simulation-based courses.
ABET Accreditation in Europe: A Comparative Analysis
Accreditation serves as a critical marker of educational quality, with ABET representing a global benchmark in engineering and technology. While European nations maintain robust national accreditation systems, a strategic pursuit of ABET accreditation by select institutions persists. This study presents the first comprehensive, quantitative analysis of ABET-accredited programs across eight European nations, employing a structured benchmarking framework to move beyond descriptive counts. Our analysis reveals that ABET adoption in Europe is a targeted strategy for international differentiation rather than a broad quality assurance measure. This is evidenced by the overwhelming dominance of Engineering Accreditation Commission (EAC) programs (94.34%), a complete absence of Engineering Technology Accreditation Commission (ETAC) accreditation, and a high concentration of programs in elite technical universities in Turkey and Spain. Furthermore, historical data underscores the challenge of sustaining accreditation, highlighting the long-term resource commitment required. The European experience offers valuable lessons for global stakeholders, particularly in emerging educational hubs in the Association of Southeast Asian Nations (ASEAN) region, demonstrating that ABET functions most effectively as a complementary, top-tier credential within a multi-layered quality assurance ecosystem.
Artificial Intelligence Integration For Shaping Future Engineering Education At Higher Colleges of Technology, UAE
Artificial intelligence (AI) continues to influence and reshape the field of higher education, offering new opportunities to enhance teaching and learning in engineering programs. This case study examines the integration and impact of AI tools, specifically ChatGPT and MATLAB Simulink, in supporting constructivist instructional approaches within typical undergraduate chemical engineering courses at the Higher Colleges of Technology in the United Arab Emirates (UAE). Grounded in Constructivist Learning Theory (CLT) and guided by the Technological Pedagogical Content Knowledge (TPCK) framework, the study explores how AI tools support student engagement, independence, and deep understanding of complex chemical engineering concepts. Data were collected through two focus group discussions with instructors and students, respectively, and complemented by document analysis of course materials and AI-generated student work. The findings indicate that AI integration contributes to personalized learning, improved academic performance, and increased student engagement. However, the study also identifies significant challenges, including academic integrity concerns, limited technical knowledge among educators and students, students' excessive reliance on AI, occasional inaccuracy of AI-generated content, restricted access to advanced AI tools, and the cost of implementation. These insights highlight both the promise and the challenges of integrating AI into engineering education.
A Review of SoTL Research Methodologies: A Guide to Conceptualizing and Conducting the Scholarship of Teaching and Learning
Research Methodologies: A Guide to Conceptualizing and Conducting the Scholarship of Teaching and Learning is a comprehensive and practical guide for educators, researchers, and graduate students engaged in the Scholarship of Teaching and Learning (SoTL), with relevance to those in engineering education. Authored by Michelle Yeo, Janice Miller-Young, and Karen Manarin, the book provides a structured approach to conceptualizing, conducting, and disseminating SoTL research. With a focus on both theoretical frameworks and practical applications, this resource addresses diverse research paradigms, from positivist and interpretive to transformative methodologies. It highlights a range of data generation methods, including quantitative surveys, qualitative interviews, focus groups, and artifacts, ensuring a balanced approach for both the theoretical and practical aspects of SoTL. The authors emphasize the importance of research-based assessment and innovation in teaching practices, offering guidance on research design and analysis that directly relate to improving educational outcomes in engineering programs. Ethical considerations are woven throughout the text, ensuring that SoTL research in engineering education maintains a focus on social justice and inclusivity. With sections dedicated to theoretical frameworks, data generation, and the dissemination of research, this book provides the essential tools for advancing both theoretical understanding and innovative practices in engineering education. It serves as a vital resource for those seeking to enhance their teaching through research and contribute to the development of engineering education through evidence-based innovation and assessment. Hence, this book review evaluates the book’s key themes on methodological approach, theoretical foundations as well as implications for STEM Educators.
Optimizing Industrial Training in Industry 4.0: A Mixed-Methods Validation of an Integrated LMS and Six Sigma 4.0 Framework
Industrial training programs face persistent challenges due to the lack of industry-specific contextualization in Learning Management Systems (LMS) and the digital disconnect in Six Sigma methodologies, limiting their effectiveness in Industry 4.0 environments. This study addresses this gap by proposing a novel integration of LMS with Six Sigma 4.0, aiming to enhance knowledge retention, project outcomes, and operational efficiency through data-driven training optimization. Employing a mixed-methods quasi-experimental design, the research combines quantitative pre-/post-intervention assessments (n = 110 trainees) with qualitative interviews (n = 8 trainers), analyzed via statistical testing (paired t-tests) and thematic coding. Results demonstrate statistically significant improvements in knowledge retention (34%, p < 0.001) and project outcomes (27%, p < 0.001), alongside two key qualitative benefits: real-time analytics enabling agile corrective actions, and a 40% reduction in manual audits through automated Six Sigma tools. The study concludes by validating a scalable framework for industrial training innovation, contributing actionable insights for workforce development in the industry 4.0 era.
Seeing Growth Through Service Learning: My Journey with Separation Processes
This narrative inquiry explores the integration of service learning into the undergraduate Separation Processes course at the Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia (UTM), from its inception in 2019 to its current implementation in 2024. Through personal reflection and pedagogical documentation, the paper traces the evolution of teaching practices, student engagement, and institutional response to service learning - a component now contributing 10% of the course’s total assessment. Drawing from experiential learning theory, the study illustrates how service learning activities - ranging from school outreach programs and video production to public exhibitions - cultivate not only technical understanding but also communication, leadership, and organizational skills among chemical engineering students. The paper also reflects on the author's first year as course coordinator, revealing insights into curriculum management, staff development, and the broader impact of reflective practice in engineering education. By situating service learning within the scholarship of teaching and learning, the paper advocates for its continued growth as both a pedagogical tool and a catalyst for holistic student development.
Evaluating the Effectiveness of an Intensive CCIE Bootcamp: A Case Study from Indonesia
This study examines the instructional design, delivery, and educational impact of the Cisco Certified Internetwork Expert (CCIE) Bootcamp organized by IDN Networkers Indonesia. The problem addressed is the limited access to affordable, intensive CCIE certification preparation in Southeast Asia, where traditional training costs (USD 2,000-7,000) remain prohibitive for many professionals. Held over six consecutive days with training hours extending from 8:00 AM to 12:00 AM, the program represents an ultra-intensive technical training model. Using a qualitative case study approach with document analysis and thematic coding of participant testimonials (n=25), official program documentation, and autoethnographic observations, we evaluate the extent to which the bootcamp supports learning outcomes relevant to Cisco's CCIE certification through experiential learning theory (Kolb) and constructive alignment (Biggs frameworks. Data collection included structured interviews, participant feedback surveys, and systematic observation protocols. Our findings show that comprehensive content, immersive learning, and aligned support mechanisms significantly enhance participants' skill readiness and confidence with initial certification success rates of 12% (3 of 25 participants) within six months post-training. This paper contributes recommendations for integrating bootcamp models in formal engineering curricula in ASEAN.