The evaluation of many STEM (Science, Technology, Engineering and Mathematics) interventions focuses on planned outcomes. However, the impact of unintended consequences from interventions remains largely unexplored in the literature. This case study presents the design and evaluation of a school-based workshop about an engineering-adjacent career: environmental planning. The authors used a community of inquiry action research approach focusing on knowledge and aspirational outcomes from outreach, particularly around broadening children's knowledge and understanding of careers. The developed evaluation tools allowed identification of intended and unintended consequences from the intervention. Participants were children aged 10-11 years (n = 83) from two schools in North East England. Results showed an increase in knowledge of environmental planning. The qualitative data indicate unanticipated consequences due to children's temporal misunderstanding of timescales involved in coastal changes. Findings are discussed in the context of 'lessons learned' and highlight the importance for engineering and technology outreach interventions of incorporating a well-designed evaluation strategy and feedback mechanism to identify and mitigate unintended and unanticipated consequences.
Since the advent of COVID-19, educational institutions worldwide have increasingly adopted online learning where challenges in maintaining student engagement have been observed. Consequently, innovative solutions for monitoring and improving engagement in virtual environments have been explored. This paper presents the design and implementation of an affordable, efficient device equipped with a camera that infers student engagement in real time using Deep Learning techniques. The system utilizes a convolutional neural network to analyze visual data and classify student behavior into three categories; focusing on paper, focusing on the screen, and being distracted. To ensure compatibility with resource-constrained edge platforms, the trained model was quantized using TensorFlow Lite (TFLite), enabling efficient deployment across a variety of devices, ranging from low-power microcontrollers like the Sony Spresence and OpenMV cam to more powerful GPU and TPU-based edge platforms such as NVIDIA Jetson Orin and Google Coral. We also established a baseline on the Raspberry Pi 5, optimizing for performance and resource constraints. A key focus of the work presented here was safeguarding student privacy. All data processing occurs locally on the device, ensuring that no sensitive information is transmitted externally. The quantized model enables real-time performance without compromising privacy, as all engagement data is securely analyzed on the edge device; only the student's engagement state is transmitted across potentially insecure networks, while the sensitive video feed remains confined to the student's device. A comprehensive comparison between the quantized, non-quantized, and quantization-aware models was conducted to assess the impact of quantization on accuracy and inference speed. In addition, trade-offs between power consumption and performance across different devices were evaluated. These findings demonstrate a balanced approach to achieving computational efficiency while ensuring real-time student engagement monitoring. By leveraging these cost-effective technologies, our approach offers an accessible and scalable realtime student engagement monitoring tool and addresses privacy challenges posed by remote education, even beyond the pandemic.
Artificial Intelligence (AI) is transforming education by offering innovative tools that enhance teaching, learning, and administrative processes. However, its integration introduces significant ethical challenges that demand critical attention. This systematic literature review (SLR) explores key ethical concerns associated with AI-driven educational technologies, including data privacy, algorithmic bias, student autonomy, and inclusivity. It systematically analyzing existing literature to provide actionable guidelines for promoting ethical AI use, emphasizing transparency, fairness, and accountability. The review also examines the impact of AI on the dynamics of instructor-student relationships, highlighting both opportunities for personalized learning and risks of reduced human interaction. By addressing these challenges and proposing strategies for responsible AI implementation, this study aims to guide educational institutions in navigating the complexities of AI adoption while fostering equitable and meaningful learning experiences.
The standards system of Geometrical Product Specifications (GPS) is fundamental to the creation of technical drawings and/or 3D CAD models. It provides a non-verbal symbolic language to geometrically describe and verify components. In addition to the benefits of having a global means of communication between companies, it also brings challenges. Teaching GPS is particularly difficult because the GPS system can be considered complex and there are few teaching approaches [1]. This paper presents an interdisciplinary teaching concept that combines selected GPS content from different areas of mechanical engineering such as design, manufacturing and quality control. This is done on the basis of the GPS competences that teachers and students considered necessary in a previous study at universities in Germany [2]. The developed teaching examples take into account the advancing digitalization in teaching as well as the use of haptic models. To evaluate the results, the content will be used and assessed in a course of the mechanical engineering bachelor's degree with focus on GPS. The aim of this study is also to find out whether the cross-module concept can promote students' interdisciplinary understanding of GPS. Or does the importance of the correlation between functionality, manufacturing and metrology in design work remain intangible? What needs to be optimized for futureoriented teaching in mechanical engineering?
The metaverse is a concept that has recently emerged as a key topic of discussion across various industries, including education. Although there is no universally accepted definition of the metaverse, it is generally understood as a collective technology-supported virtual space that facilitates interactive communication, collaborative learning, and innovative content creation. This paper seeks to investigate multiple perspectives on the definition of the metaverse, placing special emphasis on its applications within the educational sector, and employing keyword analysis from relevant academic literature to highlight current trends and key insights. The need for this study stems from the potential of the metaverse to transform educational experiences by offering personalized, immersive, and engaging learning opportunities. Nonetheless, successful implementation of the metaverse in education requires overcoming a range of technical, security, and social challenges. Educational institutions must invest in the necessary infrastructure, training, and resources to effectively integrate these technologies into their curricula. This paper contributes to the body of research with a coherent overview of how the metaverse can be defined and applied in educational processes, and by analyzing key terms and trends, aims to highlight the essential technologies and approaches that shape this emerging field. The research findings indicate that the metaverse in education is increasingly linked to the development and application of cutting-edge technologies that foster richer interactive experiences. Key technologies such as virtual reality (VR) and augmented reality (AR), as well as artificial intelligence (AI), Internet-of-Things (IoT), blockchain technologies and others, are revolutionizing traditional educational paradigms by providing immersive environments where students can engage with content in new and innovative ways. Critical issues like ethical concerns, data privacy, AI bias, and the psychological effects of immersive environments, are pivotal to the ongoing discussion and essential for the integration of the metaverse into education in a sustainable, scalable and holistic manner.
This paper presents the development and implementation of a remote laboratory for thermal radiation, realized as part of the Online Laboratories for Science Education and Training (OnLabEdu) project in Austrian schools. The OnLabEdu initiative meets the demand for remote learning with innovative, accessible online labs for practical science education via internetoperated systems. The Leslie Cube, invented and introduced by John Leslie in 1804, serves as the central experiment in this project to deepen the understanding of thermal radiation processes. The project overcame various technical challenges to establish a low-maintenance, remote-capable foundation, detailed within this work. Furthermore, it defines specific learning goals and introduces new subject-oriented didactic concepts, contributing to the advancement of science education in both practical and pedagogical dimensions.
Recently the education system has progressively emphasized computational thinking (CT) and coding skills. The curriculum progresses from foundational tools like Scratch in elementary education to more complex languages such as Python and C++ in senior high school. However, traditional teaching methods often fail to engage students effectively, hindering their development of critical coding skills. This research evaluates the effectiveness of myChatCT, an artificial intelligence (AI)-enabled learning assistant designed to enhance CT and coding skills among high school students. A distinctive feature of myChatCT is its integration of activity diagrams, bridging the gap between students' cognitive processes and their visual representations, along with the corresponding programming code. This not only clarifies complex concepts but also promotes deeper understanding and engagement. The study involved four distinct cohorts of high school students who completed coding tasks both with and without the assistance of myChatCT. A mixed-methods approach was employed, combining quantitative assessments of coding performance with qualitative feedback on learning experiences. The results revealed a significant improvement in performance metrics among students using myChatCT, as evidenced by higher accuracy rates and faster completion times. Qualitative feedback revealed that students felt more confident in their coding abilities and were more motivated to engage with programming concepts when supported by myChatCT. These findings underscore myChatCT's potential as a valuable educational tool that can facilitate deeper understanding and engagement in coding education, preparing high school students for a technology-driven future. By leveraging AI capabilities and visual aids, myChatCT not only enhances students' coding skills but also fosters a more interactive and supportive learning environment. This research contributes to the growing body of literature on AI application in education, emphasizing the significance of innovative pedagogical approaches in improving student learning experiences and outcomes within an evolving educational landscape. Ultimately, the integration of tools like myChatCT represents a significant step forward in addressing the challenges of traditional education, paving the way for a more effective and engaging learning experience in the digital age.
The adoption of virtual laboratories has seen significant growth, particularly within tertiary education, driven by the increasing need for flexible, accessible, and scalable learning environments. A significant development in this area is the integration of Virtual Reality (VR) technologies, leading to the emergence of VR Labs, which offer immersive, interactive simulations that enhance experiential learning. Recognizing the potential of these VR Labs to transform education, several Massive Open Online Courses (MOOCs) have begun incorporating them as part of the course content, providing students with hands-on experience that transcends geographical and physical limitations. Some of these VR Labs use avatar recordings to demonstrate lab procedures, but research on their design for effective learning and live learner monitoring remains limited. In this work, we examined how experiment complexity, equipment placement, and instructor avatar positioning affect learning in a VR Lab. By analyzing an existing avatar recording-based VR Lab, we designed an improved VR Lab by using the Polymerase Chain Reaction (PCR) test for COVID-19 in biomedical engineering as an example experiment. We conducted a user study with 10 users to evaluate the learning experience and gathered feedback on live monitoring and educational use of VR Labs from a learner's perspective. The findings are summarized as novel design guidelines for creating enhanced avatar recording-based VR Labs, focusing on the experiment steps, the equipment placement, the instructor avatar placement, a monitoring interface, and recommendations on utilizing VR Labs as a pedagogical tool in standalone experiences and a course component scenario.
Investments in quantum technologies, which are based on the effects of quantum mechanics, have escalated in recent years, with big players such as IBM, Google, and Microsoft engaging in the race for quantum supremacy. Some potential benefits of this cutting-edge technology include developing new drugs and materials through accurate molecule simulation, establishing more secure and reliable communication channels, and finding faster solutions for complex optimization problems. As quantum technologies evolve, however, the demand for new software, interfaces, and end-to-end systems to properly program and explore the advantages of quantum mechanics becomes paramount. This requires engineers, especially software engineers, and computer scientists, to have multidisciplinary knowledge and skills. Unfortunately, introductory quantum computing and technologies courses are mostly available in physics, and most engineering and computer science courses do not have modules on quantum physics, leading to a talent gap in the current job market. Therefore, this paper proposes a short teaching plan for introducing quantum computing to students with a more technology-based background, such as computer science and engineering students. This plan uses active learning methodologies, such as Challege-Based Teaching, to better engage these students and contextualize the many applications of this new technology. The initial teaching plan consists of a 3-hour seminar introducing the main quantum mechanics concepts and the technology applications, a 3-hour introduction to the math fundamentals and quantum logic gates, and a 3-hour handson workshop using the IBM Qiskit platform. Two versions of this plan were executed in two different moments: (1) a one-day event open to undergraduate students from different institutions and backgrounds, and (2) a 3-day internal training course for computer science and information technology management undergraduate students from our higher education institution. Data was collected during both events through online forms and interviews to measure the learning outcomes of the produced material and better understand the public interest in the field. The results identified key elements for better teaching quantum computing for computer scientists and engineers, providing guidelines for developing a more extensive and term-long teaching plan for undergraduate technology courses.
In today's technological age, algorithmic thinking and problem-solving skills are essential. To foster these skills, educators need accessible teaching methods for effective lesson planning. This study presents a teaching approach that employs the theory of the semantic wave to connect abstract concepts with practical applications, with the aim of improving students' algorithmic thinking and digital skills while promoting deeper learning. Tested in a CS teaching-learning lab, pre-service teachers practiced teaching K-12 students and refined their methods for teaching computer science. While previous studies have shown promise, this research advances the approach by integrating Necessity Learning Design (NLD), a method that builds on students' prior knowledge through structured tasks, improving problemsolving skills and significantly increasing algorithmic thinking. This “solve first, teach later” approach aligns with the principles of productive failure, where students initially attempt to solve problems on their own, encountering challenges that prepare them for deeper learning when guidance is later provided. The novelty of this work lies in the application of semantic wave theory with the Necessity Learning Design, which was not explored in CS education so far. Results provide valuable insights for pre-service computer science teachers and demonstrate the potential of this pedagogical approach to enrich both conceptual understanding and practical skills for the challenges of digital transformation.
The profile of undergraduate students that partici-pate in a face-to-face entrepreneurship multidisciplinary course is presented. The course is part of the engineering curricula in an university of Mexico. Entrepreneurial experiences, background, interests, attitudes, intention and perception of entrepreneurial skills of the participant students are addressed through this paper. The experimental protocol consisted of a pre-test, intensive entrepreneurship activities, with experiential and sustainable perspective, and a post-test. Data were collected by applying a validated questionnaire to fifty two students. The questionnaire consists of eighty questions on a four-point Likert scale. After a rigorous statistical analysis, results show that this course positively impacted the perceived organizational entrepreneurial culture and skills, attitudes, and interests in the participant students, and offers valuable data for decision making to impact the entrepreneurial intention to start a business in the short-term.
Generative Artificial Intelligence (GenAI) is rapidly transforming higher education by automating complex processes, augmenting human capabilities, and fostering essential competencies for a global workforce. This study investigates GenAI's impact on educational practices within the Transnational Education (TNE) sector, focusing on its role in enhancing content creation, supporting personalised learning, and fostering critical thinking skills. Through qualitative focus group discussions with university educators and industry professionals, this research explores the dual challenges and opportunities GenAI presents, including ethical considerations, evolving student behaviours, and the need for innovative assessment methods. Educators emphasise GenAI's potential to improve student engagement and learning outcomes, while industry professionals highlight the critical importance of interdisciplinary skills and AI literacy. Drawing on both current literature and practical insights, the study calls for a balanced integration of GenAI, where it complements traditional teaching methods and prepares students for an AI-driven global workforce. Findings underscore the need for curriculum innovations and training programmes that equip TNE graduates with technical proficiency and the collaborative skills essential for effective human-AI interaction, ultimately shaping a workforce ready for the demands of AI-integrated industries.
The technological boom of recent decades has significantly impacted global education. To maintain educational standards at the highest level, new teaching tools utilizing online resources are emerging. Particularly in application-based education, various modern solutions for laboratory experiments are developing, including virtual and remote options. However, such digital elements should be effectively integrated into the existing curriculum and combined with hands-on tasks to enhance overall learning outcomes. A standardized pedagogical model for the didactic realization of digital laboratories has yet to be established. This paper presents a hybrid concept for the fundamentals of electrical engineering labs. The aim is to develop a flexible learning environment that progressively introduces students to the complexity of the course content. A blended learning approach is implemented, combining online preparatory and follow-up phases with traditional in-person execution. It thus provides learners with comprehensive theoretical knowledge along with critical practical and future skills necessary in modern academic and work settings. To achieve this, the physical lab context was expanded via a learning platform, based on the findings of a preliminary evaluation of modern students' needs. Laboratory experiments were digitized, with consideration to both didactic and technical aspects. The developed content was structured into a learning pathway, consisting of gamified video tutorials, single-choice quizzes, and online experiments. The network and server structure were designed with the objective of providing flexibility, expandability, and open access learning. To facilitate the maintenance and organization of other services, an information management dashboard has been developed. The initial results confirm strong student engagement, enhanced lab preparation, and overall comprehension, as well as the potential for time- and location-independent learning. The developed concept is a student-centered, user-friendly, cost-effective, adaptable, and scalable solution. It can serve as a framework for the hybridization of other laboratory courses, setting a new standard for engineering education.
Gamification has emerged as a powerful educational tool, offering innovative ways to engage students and enhance learning outcomes. This study investigates the impact of gamification on seventh-grade students learning mathematics in Arabic, addressing a gap in research on its effectiveness in Arabic K-12 mathematics education. Using a between-subjects design with two groups, this study examined academic performance and motivation via a digital learning system. The system included three activities: a video tutorial, a messaging app simulation, and a treasure hunt game, each incorporating different gamification elements. Academic performance was measured through pre- and post-tests and an end-of-unit quiz, while motivation was assessed using the Instructional Materials Motivation Survey (IMMS). Results showed significant improvement in academic performance in the digital learning group compared to traditional methods, as measured by post-pre test scores (M-diff = 17.4%, p <.001). However, the end-of-unit quiz showed no significant difference between the two groups. Additionally, students reported higher motivation scores for the messaging app simulation and treasure hunt game versus the video tutorial across all components of the IMMS. The study also observed increased peer learning and engagement, although initial unfamiliarity with the digital approach led to challenges that were overcome in subsequent classes during the study. These findings contribute to understanding the potential of gamification in Arabic mathematics education, highlighting promising outcomes in academic performance, motivation, and engagement.
In this paper, we discuss the implementation and evaluation of a project-based self-direct learning competency-based module on AI literacy. This module was developed for various Bachelor's degree programs from the school of Engineering at the University of Applied Sciences and Arts Northwestern Switzerland. The aim of this course is not only to show how AI can help with writing and programming (learning), but also to get students firstly to reflect on working with AI and introduce them to important current debates, and secondly to teach the basics of large language models and central methods of data science. Students should be made aware to academic work (including finding and evaluating sources) with and about AI. During the course, they have to combine analytical and technical skills like programming and web scraping when developing a selfchosen project. An important finding of our work is that, despite their daily engagement with computer science and digital tools, without such specific formats, students are unlikely to acquire the necessary knowledge and critical thinking to navigate the rapidly changing landscape of AI autonomously and confidently.
Flipped Learning has been widely recognised for its potential to enhance student engagement and academic performance. However, its success depends on students completing asynchronous activities, which can be challenging due to motivational issues. This study investigates the introduction of gamification as a strategy to address this challenge by integrating Kahoot-based competitive quizzes into face-to-face sessions within the flipped learning model. This intervention is aimed at increasing student participation, attendance, online engagement, and overall academic achievement. Building on a similar pilot study conducted at the School of Engineering and Materials Science (SEMS), this research extends the implementation to a transnational educational context at Queen Mary Engineering School (QMES), Xi'an, China [1]. The study examines the impact of gamified flipped learning across diverse cultural groups and seeks to identify best practices for optimising student engagement through active learning strategies. The methodology involved the use of Kahoot! quizzes and interactive challenges aligned with learning outcomes to promote knowledge retention and gather data on student performance and engagement. Learning analytics were used to evaluate the effectiveness of the intervention. The results showed an increase in student engagement, higher passing rates, and no failures in the examined module. The latest cohort shows a significant improvement, with a sharp increase in high scores (80+ mark range) and a marked reduction in students scoring below 50 compared to the previous cohort, resulting in a passing rate increase from 87 % to 100 %. The success of this intervention has led to its application in other modules, where similarly positive outcomes are anticipated.
University education develops professional identities by instilling knowledge, skills, and attitudes. In engineering, this process often prioritizes technical expertise over societal considerations, fostering a narrow view of the “good engineer.” However, the growing need for ethics literacy - understanding and integrating technology's societal impacts into their professional practice - requires a broader perspective, particularly in Information and Communication Technologies (ICT), where ethical compliance is also increasingly mandated by regulatory frameworks. This study explores whether the medical profession's wellestablished social contract, which balances specialized knowledge with societal responsibility, can serve as an effective model for integrating ethics into engineering identities. Using qualitative analysis, it investigates how exposing ICT engineering students to this analogy reshapes their perceptions of their professional roles. Results suggest that the medical analogy encourages students to expand their understanding of engineering as a socially impactful profession, emphasizing societal welfare alongside technical competence. This approach demonstrates the potential of analogies to foster ethical literacy and reshape professional identities, contributing to discussions on ethical literacy and professional identity formation in engineering education.
Over the last two decades, ‘Living Labs’ have sprung around the globe as innovative and efficient research infrastructures, involving several stakeholders in a user-centered, iterative, open innovation ecosystem, where co-creation takes place in a real-life environment. Universities present a great opportunity for Living Labs, given that they have the infrastructure, technologies, and experienced academic staff for their implementation. Therefore, this paper presents the case of a Living Lab focused on Educational Technologies (EdTechs), the 'IFE Living Lab' (IFE-LL), as part of the Institute for the Future of Education at Tecnologico de Monterrey. The IFE-LL focuses on the evaluation, experimentation, and improvement of EdTechs through co-creation in a Living Lab environment. Throughout the paper, a description of the IFE-LL users, innovation process, cocreation and evaluation frameworks, and examples of successful projects is presented. The IFE-LL offers an innovation space for evidence-based educational technologies that links EdTech companies and startups, researchers, faculty members, and students, for the continuous improvement of EdTechs, development of academic and professional competences, creation and transfer of educational innovation knowledge, and collaboration in enriched and effective experiential teaching/learning environment.
The governance of digital public organizations hinges on two fundamental elements: clear decision-making rights supported by a robust accountability framework, and the integration of emerging technologies facilitated by collaborative methods and tools. In Greece's public administration, collaboration shortcomings stem from fragmented responsibilities, inconsistent policy implementation across different levels of government, weak horizontal coordination, limited utilization of digital collaborative tools, and insufficient stakeholder engagement. The Hellenic National School of Public Administration and Local Government (ESDDA) has proactively addressed these issues by promoting educational programs, that foster the development of new administrative executives through collaborative methods by implementing Project-Based Learning (PBL), while simultaneously utilizing a variety of collaborative tools. This approach aims to cultivate advanced digital and collaborative competencies among public administration executives, catalyzing a transformation in traditional practices. The study evaluates the impact of ESDDA's methodology through the lens of learning outcomes, the impact assessment of these courses, and the factors that contribute to the digital governance. A mixed method of qualitative and quantitative field research is designed and the analysis includes 630 Greek public administration officials. An exploratory data analysis (EDA) was conducted, along with inferential methods such as the Chi-Square Test (X2) for independence and the t-test for mean differences. Additionally, logistic regression was used to predict the factors that affect the use of collaborative methods and tools, contributing to digital transformation in public administration. The analysis uncovers significant improvements in digital competencies, demonstrating that the synergy between these competencies reinforces digital transformation initiatives. Training in digital collaborative methods and tools can foster the creation of new collaborative groups, human networks, and learning communities. This, in turn, can redefine the principles of knowledge management, transforming public administration bodies into learning organizations. Such transformation is crucial for enhancing competitiveness in the digital age, promoting digital transformation, and improving administrative effectiveness for the greater good. Most importantly, the findings emphasize that sustainable governance is rooted in collaboration, and the development of adaptive, learning-focused public institutions.
Computer science is an important subject not only for those who want to become computer scientists but also for everyone because it develops necessary skills for different fields. Upper secondary school is a critical time for making the choice regarding further studies. However, students' choices can be influenced by the organization of computer science (CS) education in upper-secondary schools or the availability of opportunities to study CS. As schools in Estonia have a high degree of autonomy, the aim of this research is to give an overview of the organization of CS education at the upper secondary level in Estonian schools and find out how it influences further studies in the information technology (IT) field. Three research questions were set for the research: (1) How is the teaching of computer science organized in different upper secondary schools, and what kind of additional activities are conducted to support it? (2) What support elements and obstacles are identified by school leaders in computer science education? (3) Are the supporting and hindering factors in school related to further study in the field of IT? The sample of the research consists of 30 different upper secondary schools (18.5 % of all schools of this type) in Estonia. Data was collected from the schools' curricula and school principals' questionnaires. The SPSS program was used for data processing and chi-square test and correlation analyses were performed. The study revealed that the organization of computer science education can be very variable across schools in Estonia. There are schools with compulsory courses, schools with elective courses, and those with both options. There are schools where computer science is not taught at all and schools where 7 different CS courses are offered. More than half of the schools cooperate with universities, and half of the schools get support to teach CS from the local government. A lack of qualified teachers and quality learning content was identified as hindering factors by both, the schools that teach computer science and those that do not. Principals of the schools where CS is not taught are significantly more concerned about the curriculum being overloaded, as opposed to those of the schools where CS is taught. On average, 13 % of all students choose IT as their further field of study. It was found that the more computer science courses a school offers, the more students proceed to study IT. In addition, students from the schools that cooperate with universities and other partners are more likely to continue their studies in the IT field. On the other hand, significantly fewer students proceed with their studies in IT if they come from schools where principals identified obstacles such as insufficient technical bases, missing technological support, overloaded curriculum, and limited interest of students. The results can be useful in understanding how different approaches to teaching computer science can affect the choice of further studies and what can be done, based on this, to improve computer science education in upper secondary schools.
