Journal of Engineering Research and Education (JERE)
Journal of Engineering Research and Education (JERE) is an annually engineering journal, scholarly open access and published by the publication of Universiti Malaysia Perlis (UniMAP). JERE is focusing on theories, methods, and applications in Engineering Research and Education. JERE covers all areas of Engineering Research and Education, publishing refereed original research articles. Articles preferably should focus on new methods, report or research, review or research, latest research findings and innovative practices in the engineering field.
Islamic Ethics in Student-Led Stingless Beekeeping
This paper presents a faith-integrated, student-led stingless beekeeping initiative at the International Islamic University Malaysia (IIUM), illustrating how Islamic ethical principles can enrich sustainability education and entrepreneurship. Conducted under the Mahallah Ruqayyah Representatives Committee (MRC) with guidance from interdisciplinary mentors, the project has been successfully sustained for six years (2019-present), providing students with experiential learning in hive management, product innovation, and ethical entrepreneurship. Core Islamic values, ihsan (excellence), amanah (moral responsibility), barakah (multiplication of goodness), and khalifah (environmental stewardship) were embedded throughout the learning process. Data triangulated from project documentation, reflective journals, and mentor evaluations indicated that 85% (n = 34) of participants affirmed the project’s effectiveness in linking scientific knowledge with Islamic ethics. Mentor feedback identified five key challenges: inconsistent student motivation (M = 4.1), lack of technical competency (M = 4.0), and environmental variability (M = 3.8) were rated as the most significant, while limited training time (M = 3.0) and communication gaps (M = 2.6) were of moderate concern. Despite these constraints, the initiative demonstrated that integrating Qur’anic principles into experiential learning fosters holistic character development, sustainability awareness, and ethical entrepreneurship among students.
Copyright (c) 2026 Journal of Engineering Research and Education (JERE) https://creativecommons.org/licenses/by-nc-sa/4.0
Pentahelix Collaboration in Aquagreen Sustainable Engineering
The increasing global demand for sustainable solutions to environmental challenges has spurred interest in multi-stakeholder approaches such as the pentahelix collaboration. While widely promoted as a transformative pathway for sustainability, there is limited empirical evidence on its practical application in indigenous and resource-constrained contexts. Challenges such as reconciling diverse stakeholder priorities, addressing language and cultural barriers, and ensuring equitable participation often hinder effective implementation, risking the framework remaining more conceptual than operational. To explore these challenges, the Aquagreen initiative was introduced in Kampung Sungai Relang through a partnership among the International Islamic University Malaysia (IIUM), CIMB Foundation, Jabatan Kemajuan Orang Asli (JAKOA), the Malaysia Institute of Sustainable Agriculture (MISA), and the Orang Asli community. By establishing an integrated aquaculture–hydroponics system powered by solar energy, the project provides insight into the process, considerations, and the practical challenges of translating the pentahelix approach into practice in indigenous, resource-constraint settings. Its recognition with the 2024 RCE Award for Outstanding Flagship Project by the United Nations University – Institute for the Advanced Study of Sustainability (UNU-IAS) highlights its contribution to advancing collaborative sustainability initiatives in marginalised communities.
A Systematic Literature Review on the Role of Engineering Education in an Evolving Educational Landscape
This systematic literature review (SLR) examines the evolving role of engineering education in the face of rapid technological disruption, shifting industry demands, and societal expectations for sustainability. Drawing on 2019–2025 literature, four converging themes are identified: (1) digital and online learning, (2) industry–academia collaboration, (3) future-ready competencies, and (4) sustainability and ethics. Digital platforms such as Massive Open Online Course (MOOCs), flipped classrooms, and AI-driven tools are transforming pedagogy, while collaborations with industry enhance authentic problem-solving and employability. At the same time, new competency frameworks emphasise interdisciplinary skills, adaptability, and AI literacy. Sustainability and ethics are increasingly embedded into curricula, yet inconsistently operationalised. Persistent challenges include faculty readiness, unequal digital access, and limited assessment tools for complex competencies. This review highlights best practices and gaps, concluding with recommendations for integrated curriculum design, stronger policy support, and robust measurement frameworks. It argues for a holistic, adaptive model of engineering education capable of preparing graduates as technologically proficient, socially responsible, and globally adaptable professionals.
Evaluating Professional Development through Mechatronics Engineering Internship: A Feedback-Based Analysis
This paper evaluates the professional development of Mechatronics Engineering students (n=56) at the International Islamic University Malaysia (IIUM) through a feedback-based analysis of industrial training collected in Semester 3, 2023/2024. The study incorporates feedback from two perspectives: company supervisors and academic examiners, focusing on targeted Program Outcomes (PO): PO8 (ethics), PO9 (individual and teamwork), and PO10 (communication). Quantitative analysis revealed that company supervisors rated students highest for ethics (PO8, mean = 93.46%), followed by teamwork (PO9, mean = 90.75%), and communication (PO10, mean = 88.69%), with statistically significant differences between groups (p < 0.001). In contrast, marks assessed by IIUM lecturers showed similar averages across PO groups (PO8 = 87.74%, PO9 = 86.83%, PO10 = 86.46%) and no significant differences (p = 0.495). A paired samples t-test further demonstrated that company supervisors awarded significantly higher marks overall than academic lecturers (mean difference = 3.96, t(167) = 4.104, p < 0.001, Cohen’s d = 0.32), with a weak correlation between the two assessor groups (r = 0.334, p < 0.001). Preliminary observations suggest that while students generally demonstrate strong ethical behaviors and teamwork, communication skills vary depending on the placement environment. The weak correlation indicates differing assessment perspectives, likely reflecting the contrast between practical, real-time evaluation and more standardized academic appraisal.
Systematic Literature Review on Students’ Perceptions of Ethical AI: Fairness, and Regulatory Understanding
The increasing demand of Artificial Intelligence (AI) in academia has intensified debate over ethical implications and establishment of regulations. While extensive research focuses on AI technicalities such as algorithm development, algorithmic accountability, and regulatory frameworks, insufficient attention has been given to how students perceive these ethical dimensions. This study presents a systematic literature review (SLR) on students’ perceptions of ethical AI, focusing on awareness, fairness, and knowledge of regulatory systems. This SLR adheres to the PRISMA 2020 guidelines and consolidates findings from four academic databases: Scopus, ScienceDirect, IEEE Xplore, and ERIC. The findings reveal that while students generally acknowledge the importance of using AI tools ethically, their understandings are influenced by the Perceived of Usefulness (PoU), Perceived Of Ease of Use (PoEU) and Social and Cultural Perceptions. Students are concerned about the fairness of evaluations, as well as the potential of bias and discrimination, when AI techniques are employed without appropriate regulations or policies. This review highlights the importance of transparency in AI systems, the mitigation of prejudice, the assurance of justice, the reform of the educational paradigm, and the establishment of a comprehensive ethical AI framework and policy. The paper signifies the need to revolutionize teaching and learning while empowering learners with robust ethical foundations, which is critical in developing responsible AI practitioners.
Automating Co-curricular Management: An NFC-Based System for Streamlining Student Engagement at IIUM
In today’s educational systems, academic excellence alone is insufficient for a holistic development approach. Equally important is the active participation of students in co-curricular activities, which contribute significantly to their overall growth and skill development. Managing student co-curricular activities without an automated system often leads to significant administrative burdens, data inaccuracies, and inefficient use of resources due to reliance on manual processes like paper-based sign-ins and spreadsheets. Furthermore, the accurate recording of these activities is necessary not only for validating student participation and awarding credits but also for providing data-driven insights into engagement patterns and the overall effectiveness of university programs. To improve the tracking of student involvement in co-curricular activities, this study proposes integrating Near-field Communication (NFC) technology into IIUM's existing Starpoint system, thereby addressing its current operational challenges. The current system at IIUM faces several challenges, including delays in record updates, data loss, and human errors. These issues not only affect the accurate tracking of student engagement but also affect the timely acknowledgment of their efforts. The proposed NFC-based system seeks to address these problems by employing NFC tags, transceivers, readers, and microcontrollers to automatically and instantaneously collect and update Starpoint data. The system also introduces a Starpoint bank that allows students to collect Starpoints and use them as a form of currency within the university to gain various incentives including access to special events, or priority in certain university services. The paper reviews previous works that have explored the use of NFC technology in educational settings, highlighting their successes and limitations. It then explains the proposed design, implementation, and evaluation of the system. The results from the pilot project indicate significant improvements in the speed and reliability of recording student participation.
Measuring Students’ Level of Interest in Learning Embedded Systems Course: Instrument Development and Validation using Rasch Analysis
Increasingly essential to several industries, including consumer electronics, medicine, and automobiles, are embedded systems. But students are frequently frightened by their complexity, which presents difficulties in schooling. This research solves these problems by using Rasch analysis to create and check a scale gauging students' interest in Embedded Systems Design courses. Following content validation by an expert panel, a theoretical framework for the scale was created using a thorough literature analysis. In a pilot study with 40 people, the dependability of the scale was assessed. A bigger survey including 365 students from several colleges produced a diverse sample for study using WINSTEPS 5.7.4 to evaluate the dimensionality of the scale items, which resulted in high reliability scores (0.70 for people and 0.97 for items). The results, nevertheless, showed an alarming pattern: embedded systems design attracted little interest from students, which may impede academic performance and knowledge. This absence of involvement emphasizes the pressing need for educational institutions to update their curricula and teaching methods to stimulate more interest and provide students with vital abilities for technology-driven labor. Overall, the research offers helpful tips for measuring interest in embedded systems of education and emphasizes the importance of addressing these challenges.
Building Cyber Defense Skills: The CipherQuest Educational CTF Framework
As cyber threats grow increasingly sophisticated, equipping the next generation of cybersecurity professionals with practical, engaging training methods has never been more critical. Current cybersecurity education approaches face three key limitations: (1) traditional open-source CTF platforms often lack pedagogical alignment with academic curricula and lack institutional-grade user management and assessment tools, (2) game-based learning tools frequently sacrifice technical depth for accessibility, and (3) simulation environments may fail to foster competitive engagement crucial for skill retention. This paper evaluates three innovative approaches for cybersecurity education: Capture-the-Flag (CTF) competitions using the Ionian CTF model, which develops practical skills through challenge-based learning; CyberMoraba, an adaptation of the traditional African strategy game Morabaraba redesigned for cybersecurity instruction; and Cyberattack Simulator, offering realistic threat defense scenarios. Comparative analysis identified CTF as the most effective method for university students, combining technical skill development with competitive learning dynamics. Therefore, CipherQuest was developed, a CTF platform that synthesizes best practices from established systems (picoCTF, CryptoHack, HackTheBox) while incorporating IIUM curriculum-aligned challenges. The platform features jeopardy-style challenges across security domains with real-time feedback and progress tracking. Preliminary results show 90% of participants demonstrated improved cybersecurity knowledge and skills transferable to real-world scenarios. This research establishes that structured CTF platforms can effectively bridge theoretical cybersecurity education and practical application while maintaining academic consistency. The CipherQuest platform can provide universities with an evidence-based model for implementing engaging cybersecurity training that meets both educational objectives and industry needs.
Embedding Tawhidic Epistemology in Engineering Education Aligned with IEA 2021 Graduate Attributes
Integrating Tawhidic Epistemology (TE) into engineering education offers a transformative, faith-based framework. It unifies technical competence with spiritual, ethical, and societal responsibility. Rooted in the Islamic worldview of Tawhid, i.e., the Oneness of God, TE affirms that revelation (wahy) and reason ('aql) are complementary sources of knowledge, guiding all inquiry toward ethical objectives aligned with Maqasid al-Shari'ah. This paper proposes a structured, scalable model for embedding TE within engineering curricula, explicitly aligned with the International Engineering Alliance (IEA) Graduate Attributes Version 4 (2021), which emphasizes ethics, sustainability, societal impact, and inclusive professionalism. The framework differentiates between Primary and Supportive TE Courses, enabling targeted curriculum enhancements without compromising technical rigor. TE integration strategies include reflection-based learning, project design with ethical framing, structured rubrics, lecture infusion, and case-based reasoning, all of which are applied across design projects, industrial training, and technical courses. These strategies are mapped to IEA attributes, including WA6 (Engineer and the World), WA7 (Ethics), WK5 (Sustainable Design), WK7 (Role in Society), and WK9 (Inclusive Behavior). This alignment ensures compatibility with global accreditation standards. By situating engineering education within a Tawhidic framework, this model fosters engineers who are technically proficient, spiritually anchored, and ethically conscious. It addresses identity gaps in Muslim academia while responding to global demands for more responsible, inclusive, and human-centered technological development.
Exploring Julia for Statistical and Numerical Techniques in Electrical Engineering: Case Studies Aligned with EAC Standard 2024
In response to the Engineering Accreditation Council (EAC) Standard 2024, which mandates the integration of numerical and statistical techniques into engineering education, this paper advocates the adoption of the Julia programming language as a modern computational platform. Julia combines the speed of low-level languages with the intuitive syntax of high-level mathematical tools, making it ideal for electrical engineering curricula. This study presents practical case studies that illustrate Julia's application in solving circuit equations, performing frequency-domain signal analysis, and conducting data-driven modeling, key skills that directly map to Programme Outcomes (PO1, PO2, PO5). Julia's robust ecosystem, including packages such as DifferentialEquations.jl, Plots.jl, and Makie.jl support simulation, analysis, and high-quality visualization, enabling students to translate mathematical models into computational solutions effectively. Early pilot feedback suggests enhanced student engagement, deeper conceptual understanding, and stronger computational literacy. Rather than prescribing Julia, this paper offers a framework and encouragement for its integration wherever appropriate within engineering programs. Embedding Julia in labs, numerical courses, and final-year projects not only aligns with OBE and EAC standards but also equips graduates with industry-relevant skills for solving complex, data-driven engineering problems in a sustainable and accessible way.
Transforming Emergency Departments through AI: A Review of Predictive and Operational Schemes
The primary goal of emergency departments (EDs), which are vital healthcare facilities, is to provide urgent medical necessities for serious medical issues. In emergency rooms, overcrowding issues, a lack of resources, and long waiting times lead to delayed medical care, which raises patient disease severity and burns healthcare professionals. For conventional triage operations, the subjective human-based approach is inadequate for both attaining consistent outcomes and operating at peak efficiency. To improve healthcare outcomes, optimize care sequences, and increase triage precision, artificial intelligence (AI) is applied through machine learning (ML), natural language processing (NLP), and predictive analytics. With emphasis on AI-driven triage, predictive analytics, resource allocation, and clinical decision support, this paper examines how AI is transforming emergency department operations. The study emphasizes AI's potential to improve emergency healthcare delivery, decrease errors, and streamline patient flow through case studies and comparative analyses. Notwithstanding its advantages, integrating AI into EDs has drawbacks, such as algorithmic bias, data privacy issues, and the requirement for clinician training and trust. Ethical frameworks, practical AI tool validation, and smooth clinical workflow integration are necessary to address these concerns
AI-Powered and Conventional Malware Detection Approaches: Challenges and Future Trends
The continuous increase in users on the internet and online services provisioning such as shopping and banking causes many cyber criminals with a massive number of hackers sniffing users’ data. Malware is increasingly evolving, and the growth of worms, viruses, spyware, trojan horses, and other developments of malicious code requires improved detection techniques which are directed to the use of dynamic malware detection techniques. As a result, there is a growing need for anti-malware methods for protection of internet users’ privacy. Conventional mechanisms, such as behavior-based and signature-based approaches, have been broadly used but face great challenges compared to the growing malware threats. Artificial Intelligence AI-driven methods, leveraging Deep Learning (DL) and Machine Learning (ML), offer better adaptability and detection rates. This article serves as a survey, which investigates conventional and AI-powered malware detection techniques. Also, it offers a comparative analysis model, such as adaptability, accuracy, scalability, resource requirements, cost and more to signal their strengths and weaknesses. Finally, the study highlights future developments to mitigate the limitations of both approaches and improve overall cybersecurity resilience.
Coping with AI: Islamic Principles for New Education Policy
Artificial intelligence (AI) is reshaping the landscape of higher education by influencing how knowledge is produced, transmitted, and evaluated. While AI promises efficiency and personalisation, it also generates ethical dilemmas related to privacy, autonomy, bias, and accountability. These concerns become more profound when considered through an Islamic lens that connects knowledge to morality, faith, and social responsibility. This policy brief develops an Islamic framework for coping with the challenges of AI in education policy by drawing on the higher objectives of Islamic law (Maqāṣid al-Sharīʿah). The discussion revisits classical jurisprudential tools—maṣlaḥa (public welfare), qiyās (analogy), istihsān (juristic preference), and sadd al-dharaʿi (prevention of harm)—to reinterpret responsible innovation for the digital era. It argues that the integration of AI into education policy must preserve justice, compassion, and human dignity while advancing inclusive learning. The proposed framework highlights the potential of Islamic ethics to enrich global AI discourse by embedding spiritual accountability within educational governance.
Reimagining Constructive Alignment for Artificial Intelligence Integrated Learning – Looking into Agency
Artificial intelligence (AI) tools have been at the forefront of technology, redefining higher education teaching and learning, including engineering education. Since the introduction of AI, concerns have grown about its impact on learner agency and the fairness of assessments. The traditional teaching and learning approach have since been reviewed and redesigned to incorporate AI and to ensure its ethical use. This thematic review explores two main themes: learner agency and AI in engineering education. Two strings of theme-related keywords were used for the database search. This review examines the effects of integrating AI in teaching to provide learners with greater control over their learning process. It argues that AI usage will not lower the quality of teaching if assessments are reasonably adjusted. Constructive alignment was identified as the central focus for evidencing learners' agency, and a reverse-engineered constructive alignment can preserve agentic engagement. Learners' contributions were most evident in the assessment element. Hence, assessment becomes essential, suggesting that it should serve as the starting point for constructive alignment. By involving learners in the process, teaching and learning will be more learner-focused. Strategies are suggested for creating assignments that are AI-integrated, encourage meaningful participation, and mastery of the subject.
A Low-Cost Traffic Generation System Using Open-Source Software for Accessible Cyber Ranges
This project implements a comprehensive open-source traffic generator designed for cyber ranges and network defence labs. The project addresses the growing demand for advanced cybersecurity training tools that can simulate real-world network traffic and attack scenarios. By providing a hands-on laboratory environment, the tool directly enhances cybersecurity education by allowing students to interact with and analyse dynamic network conditions and malicious traffic patterns. Traditional traffic generators often lack the flexibility and usability required for educational and research applications, creating a gap that this project seeks to fill. The developed traffic generator features an intuitive configuration and control interface, a robust traffic generation engine capable of simulating diverse network traffic patterns, and support for various protocols, including TCP, UDP, ICMP, and HTTP. Prepackaged attack scenarios, such as DDoS, ransomware, and reconnaissance, enhance realistic cybersecurity training. The tool prioritizes customization options and comprehensive reporting to maximize its functionality and adaptability to different use cases. By offering an effective and accessible solution, this project significantly enhances the training and preparedness of cybersecurity professionals, contributing to the development of secure and resilient network infrastructures.
A Theoretical Guide to Developing Learner Agency in Chemical Engineering Curricula
This investigation was completed to understand the key themes and foundations surrounding learner agency culture for the benefit of student learning. An online literature search was conducted, with 36 selected papers forming the literature matrix that enabled the themes and trends to be spotted in the relevant literature. The key themes were fundamental skills and knowledge, learning environment, learner attitude and self-determination theory congruency. The important message emerging from these themes was the close relationship between environment and attitude for a learner, along with students using their past skills and knowledge in an environment to develop new skills and expertise, with fulfilling self-determination theory criteria enabling this to be repeated through the development of intrinsic motivation. These themes enabled the development of a theoretical framework, including a cycle and an interlinking process route that shows how learner agency could be nurtured in this scenario. To complete the aims of this investigation, this framework will be tested against first-year chemical engineering students and modified if any issues arise.
Perceptions and Insights on Industrial Training: A Study of IIUM Mechatronics Engineering Students
Industrial training plays a pivotal role in providing students with experiential learning opportunities that enhance their technical competence and professional readiness. This study presents an analysis of Mechatronics Engineering students’ perceptions of the industrial training programme at the International Islamic University Malaysia (IIUM). A total of 56 students participated in a survey evaluating the quality of training in the host company, ability to apply knowledge, career awareness, and faculty coordination. Quantitative data was complemented by qualitative insights derived from open-ended student reflections. Survey results reveal high satisfaction with supervision quality, mentorship, and work environment. Findings indicate that most students acknowledged that the internship is instrumental in bridging theoretical knowledge with real-world applications and in clarifying their career aspirations. Suggestions for improvement include extending the internship period and enhancing placement support through stronger university–industry partnerships. Overall, the findings revealed the effectiveness of the industrial training programme in fostering professional competencies while highlighting areas for improvement for enhanced experiential learning.
On the Operationalisation of Values, Flexibility and Sustainability in Curricula Adhering to MQF 2.0 2024
The Malaysian Qualifications Framework (MQF) 2.0 Addendum 2024 emphasises Values-Based Education (VBE), Flexible Learning Pathways (FLP), the Global Sustainability Agenda (GSA), and harmonisation with sectoral frameworks to strengthen graduate readiness and institutional compliance. As the 2026 compliance audit approaches, programme owners at undergraduate and postgraduate levels require a systematic approach to integrate these emphases into curricula. This paper analyses the evolution of the MQF, comparing MQF 1.0, MQF 2.0 (2017), and MQF 2.0 Addendum (2024), while contextualising global frameworks such as UNESCO's Education for Sustainable Development, the ASEAN Qualifications Reference Framework, and the Washington Accord. We propose a structured operationalisation framework aligning Programme Learning Outcomes (PLOs), Course Learning Outcomes (CLOs), and curriculum delivery with MQF's four emphases, while embedding SDG targets and IR4.0 competencies within teaching, learning, and assessment strategies. The framework is designed to be adaptable across disciplines, enabling institutions to implement policy-driven curriculum transformation regardless of programme type. Challenges in values assessment, curriculum flexibility, and staff readiness are discussed, alongside strategies for audit documentation and stakeholder engagement. This paper presents a practical and scalable model to guide Malaysian higher education institutions in aligning their curricula with MQF 2.0 Addendum 2024, ensuring audit-readiness and supporting the development of holistic, industry-ready graduates aligned with national and global policy aspirations.
Artificial Intelligence Tools in Arabic Learning Content Creation: Evaluating the Benefits and Overcoming the Challenges
The integration of artificial intelligence (AI) into content creation offers transformative potential for education, particularly in streamlining the production of animated learning materials. While educational animation is highly effective for simplifying complex subjects, its traditional production is often resource intensive. This paper explores the application of AI tools in creating an animated video to explain Hadith terminology to school students. It documents the end-to-end production process, from AI-assisted script generation to voice synthesis, to evaluate the practical benefits and challenges. The findings reveal that while AI significantly accelerates production, its use for Arabic-language Islamic content presents significant hurdles. These include cultural and stereotypical biases in datasets, inaccurate Arabic linguistic processing, inappropriate visual representations, and flawed text-to-speech pronunciation. The study concludes that while AI is a powerful tool for efficiency, its effective use in this context requires careful oversight and underscores the urgent need for developing culturally and linguistically nuanced AI models designed to Arabic Islamic education.
Prompt Quality Analysis in AI-Assisted Learning of Database Programming: Pedagogical Insights from a University-Level Intervention
Integration of Artificial Intelligence (AI) tools in higher education has transformed the teaching and learning strategy, especially in technical domains such as database programming. This study investigates the relationship between the quality of student-generated AI prompts and traditional database programming proficiency in higher education. Through quantitative analysis of 20 student submissions, we evaluate prompt quality across three dimensions—Specificity, Clarity, and Context—and examine their correlation with conventional assessment performance. Our findings reveal that Specificity in prompt writing shows the strongest association with traditional database skills (r = 0.51, p < 0.05), suggesting that students who craft more precise AI instructions also demonstrate stronger technical competencies. Clarity emerges as the most challenging aspect for learners (M = 1.85/4), highlighting gaps in technical communication. The study provides actionable insights for integrating prompt engineering into database education while maintaining focus on foundational knowledge. We discuss implications for curriculum design, including the need for explicit writing instruction and ethical considerations in AI-augmented learning. Limitations and future research directions are outlined, particularly regarding longitudinal effects of prompt-writing training and ethical dimensions of educational AI use. This work contributes to emerging scholarship on AI's role in computing education by demonstrating how prompt quality reflects and potentially enhances traditional learning outcomes.
Responsible Utilisation of AI in Academic Research Strategies for Preserving Scientific Integrity and Quality
This article aims to investigate the impact of artificial intelligence (AI) tools on scientific research and their effect on its integrity and quality. It also aims to determine the most effective strategies for promoting the responsible utilization of AI tools in scientific research. To achieve these objectives, a qualitative exploratory design was employed to provide a comprehensive description and explanation of the practices and challenges faced by researchers and scientists. Data were collected using relevant literature reviews, and thematic analysis was used to achieve the research objectives. The findings indicate that while AI is effective and capable of improving the efficiency and quality of academic research, its misuse poses risks to research integrity and quality. Among the terribly significant dilemmas are over-reliance on AI and the fabrication and falsification of information. Therefore, universities need to establish clear guidelines to ensure the responsible use of AI, promote a culture of integrity in scientific research, and train researchers in AI ethics. Develop more specialized AI tools tailored to research and contexts. Prompt engineering is fundamental for researchers to achieve accuracy and obtain reliable results for their research. Finally, AI tools cannot replace humans in the field of research, but they can help produce high-quality research.
Addressing Energy Challenges in Low-Income Communities via Solar PV and Thermal Management Approach
This study shows how important temperature control is for improving solar panel performance and supporting clean energy goals. It tested an active evaporative cooling system for photovoltaic (PV) panels under the hot and dry conditions of Atbara City, Sudan. Using MATLAB/Simulink, a water-based cooling setup was added to the back of a JKM400M-72HL-V solar panel to study how it affects temperature and electricity generation during the day. The cooled panel stayed much cooler—between 22°C and 30°C, compared to 67°C for the uncooled one. As a result, total daily power increased from 1,553 W to 2,235 W, a 44% improvement in efficiency (from 11.6% to 16.7%). The system also used very little water, about 2–5.2 liters per day for a 12-panel array. These results show that active evaporative cooling is a simple, practical, and eco-friendly way to boost solar panel performance and lifespan in hot, dry regions like northern Sudan, especially in low-income or off-grid areas.
Engineering Education for Sustainable Futures through Curriculum Renewal Aligned with the EAC Manual 2024
Engineering education is undergoing rapid transformation driven by Industry 5.0, digitalisation, sustainability imperatives, and growing expectations for ethical and human-centred practice. This structured review examined how global curriculum-renewal trends align with the Engineering Accreditation Council (EAC) Manual 2024. A systematic search of Scopus, Web of Science, and Google Scholar covering 2015–2025 identified 423 records, of which 92 full-text articles were screened and 48 met the inclusion criteria for thematic synthesis. Five dominant domains emerge, namely digital and artificial intelligence fluency, sustainability and ethics, human-centred learning, interdisciplinary and entrepreneurial mindsets, and flexible micro-credential pathways. Mapping these domains to the eleven Programme Outcomes in the EAC Manual 2024 revealed strong alignment in sustainability, ethics, teamwork, and societal responsibility, but weaker integration of digitalisation, AI-enabled problem solving, and lifelong-learning structures. The review proposes guiding principles for strengthening curriculum renewal, emphasising ethical integration, sustainability orientation, digital empowerment, human-centred learning, interdisciplinary synergy, and reflective quality management. These insights provide an evidence-based foundation for Malaysian engineering programmes seeking coherent, future-ready curriculum transformation consistent with global developments and accreditation expectations.
A Bibliometric Analysis of Religion and Culture based AI Framework
The implications of Artificial Intelligence (AI) development and deployment have become ethically significant in our modern lives. While the majority of contemporary AI ethics frameworks are based on secular and Western norms, there is an increasing number of works related to religion-culture in the frameworks. The focus of this bibliometric study is on the global research that surrounds religion and culture as the foundation for ethical AI frameworks, with an emphasis on Islamic ethical principles. By using the Scopus database, a total of 63 publications from 2015 to 2025 were analyzed through Biblioshiny and VOSviewer. The analysis includes trends in publication output, leading authors, collaborative networks, etc. Results indicate an increase in scholarly output since 2022, with Southeast Asia, notably Malaysia and Indonesia, and the Middle East as the key contributors. Core themes include ethics, religion, language model, and ethical design, while religious values, such as Islamic ethics and maqasid al-shariah, are increasingly integrated into AI ethics discourse. Keyword co-occurrence and thematic mapping reveal three dominant clusters: (1) core ethical AI principles, (2) ethics technology, and (3) religion-informed value systems. While terms like “artificial intelligence,” “ethics,” and “language models” remain central, faith-based constructs are transitioning from peripheral to foundational in shaping future AI frameworks. This study demonstrates the growing intellectual momentum behind culturally and spiritually responsive AI ethics also the potential of Islamic epistemology to enrich global AI governance.
Demographic Influences on Secondary School Students’ Interest and Educational Intentions in STEM
Enhancing student engagement in Science, Technology, Engineering, and Mathematics (STEM) requires understanding how demographic factors shape their perspectives and aspirations. This study examines the influence of gender, parental education, and socioeconomic status on students’ interest in STEM and their intention to pursue STEM subjects at Form 4. In this context, ‘interest’ refers to motivation and enjoyment derived from STEM activities, while ‘intention’ represents a concrete commitment to advanced enrolment in upper secondary education. Using a quantitative survey and descriptive analysis, data were collected from 142 secondary school students aged 13–15 in Kuala Lumpur and Selangor. The results revealed a high level of interest in STEM (M = 3.70), but only a moderate intention to pursue STEM at Form 4 (M = 3.32), indicating a gap between interest and subject selection. While demographic factors were not significant predictors of STEM interest, household income and parental education significantly influenced students’ intention to continue in STEM. These findings highlight the need for targeted educational support and interventions, particularly for students from lower socioeconomic backgrounds, to bridge the interest-intention gap and promote equitable access to STEM pathways.
A Bibliometric Study on Ethics in Stress Data Collection for Children Utilizing Speech or Video Recordings: A Focus on Islamic Perspective and Maqasid Al-Shariah
The main objective of this study is to determine relevant publications on general ethical guidelines for collecting data involving children. The study identified ethical guidelines for collecting stress data from children through speech or video recordings and explored their alignment with the principles of Maqasid Al- Shariah. The analysis utilised documents retrieved from the Web of Science (WoS) digital database, and the analysis of the results using Bibliometrix and Biblioshiny and Harzing’s Publish or Perish softwares. From the study, we found a total of 53 relevant publications are retrieved from the WoS digital database. Five key principles emerged for ethically collecting stress data from children through speech or video recordings: anonymization and confidentiality, secure data storage, transparency, voluntary participation, and institutional oversight. These principles align with the Maqasid Al-Shariah (i) Hifz al-Nafs: secure data storage and transparency, (ii) Hifz al-‘Aql: transparency and institutional oversight, (iii) Ḥifẓ al-Karāmah: anonymization and confidentiality, voluntary participation, (iv) Al-‘Adalah/’Adl: transparency and institutional oversight. This research is only focusing on non-clinical research studies and children. This is the first bibliometric analysis investigating the ethics of collecting stress data from children through speech or video recordings, with a specific focus on Islamic perspectives and the principles of Maqasid Al-Shariah.
Bridging Accreditation and SDGs through Outcome-Based Education: Pathways for Transforming Engineering Curricula
The convergence of global sustainability challenges and the Fourth Industrial Revolution (IR 4.0) has amplified the need for transformative approaches in engineering education and accreditation. This paper explores how the newly launched Engineering Accreditation Standard 2024 (EAC2024) by the Board of Engineers Malaysia (BEM) serves as a strategic platform to embed both the Sustainable Development Goals (SDGs) and Environmental, Social, and Governance (ESG) values into engineering curricula through Outcome-Based Education (OBE). ESG, a framework widely adopted in the corporate and policy world, emphasises responsible environmental stewardship, social inclusivity, and strong governance—values that are increasingly vital in engineering practice. Through constructive alignment and gap analysis, this paper illustrates how EAC2024’s 11 Graduate Attributes map directly to SDG and ESG-aligned competencies, such as sustainable design (PO3), global and societal impact (PO6), ethical practice (PO7), and lifelong learning (PO11). Besides, the paper discussed the implementation pathways including curriculum reform, authentic and inclusive assessments, stakeholder engagement, and integration of Generative AI. Case studies from Malaysia such as Service Learning Malaysia-University for Society (SULAM) and capstone projects, demonstrate real-world alignment. Ultimately, accreditation is positioned as a catalyst for producing engineers ready to lead in building a sustainable, inclusive, and ethically grounded future.