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The article describes the implementation of IoT technology in the teaching of microprocessor technology. The method presented in the article combines the reality and virtualization of the microprocessor technology laboratory. A created IoT monitoring device monitors the students’ microcontroller pins and sends the data to the server to which the teacher is connected via the control application. The teacher has the opportunity to monitor the development of tasks and student code of the program, where the functionality of these tasks can be verified. Thanks to the IoT remote laboratory implementation, students’ tasks during the lesson were improved. As many as 53% (n = 8) of those students who could improve their results achieved an improvement of one or up to two tasks during class. Before the IoT remote laboratory application, up to 30% (n = 6) of students could not solve any task and only 25% (n = 5) solved two tasks (full number of tasks) during the class. Before implementation, 45% (n = 9) solved one problem. After applying the IoT remote laboratory, these numbers increased significantly and up to 50% (n = 10) of students solved the full number of tasks. In contrast, only 10% (n = 2) of students did not solve any task.

Facing calls for greater emphasis on STEM education in primary school classrooms, teachers may be anxious because of limited exposure to STEM in their own education. The Australian Curriculum: Technologies is new and many teachers are not familiar with its content. Hence both in-service and pre-service teachers (PSTs) require preparation. This research used a case study method to investigate factors influencing PSTs' use of Remote Access Laboratories (RAL) with activities intended to develop their capacity to teach STEM in primary schools. Results highlighted the importance of PSTs' experience of STEM in their own education and showed the benefits of hands-on learning and scaffolding to support preparation of PSTs for teaching STEM subjects.

Remote learning has advanced from the theoretical to the practical sciences with the advent of virtual labs. Although virtual labs allow students to conduct their experiments remotely, it is a challenge to evaluate student progress and collaboration using learning analytics. So far, a study that systematically synthesizes the status of research on virtual laboratories and learning analytics does not exist, which is a gap our study aimed to fill. This study aimed to synthesize the empirical research on learning analytics in virtual labs by conducting a systematic review. We reviewed 21 articles that were published between 2015 and 2021. The results of the study showed that 48% of studies were conducted in higher education, with the main focus on the medical field. There is a wide range of virtual lab platforms, and most of the learning analytics used in the reviewed articles were derived from student log files for students’ actions. Learning analytics was utilized to measure the performance, activities, perception, and behavior of students in virtual labs. The studies cover a wide variety of research domains, platforms, and analytical approaches. Therefore, the landscape of platforms and applications is fragmented, small-scale, and exploratory, and has thus far not tapped into the potential of learning analytics to support learning and teaching. Therefore, educators may need to find common standards, protocols, or platforms to build on each others’ findings and advance our knowledge.

The presented article aims to design an educational test bench setup for smart grids and renewable energies with multiple features and techniques used in a microgrid. The test bench is designed for students, laboratory engineers, and researchers, which enables electrical microgrid system studies and testing of new, advanced control algorithms to optimize the energy efficiency. The idea behind this work is to design hybrid energy sources, such as wind power, solar photovoltaic power, hydroelectric power, hydrogen energy, and different types of energy storage systems such as batteries, pumped storage, and flywheel, integrating different electrical loads. The user can visualize the state of the components of each emulated scenario through an open-source software that interacts and communicates using OPC Unified Architecture protocol. The researchers can test and validate new solutions to manage the energy behavior in the grid using machine learning and optimization algorithms integrated in the software in form of blocks that can be modified and improved, and then simulate the results. A model-based system of engineering is provided, which describes the different requirements and case studies of the designed test bench, respecting the open-source software and the frugal innovation features in which there is use of low-cost hardware and open-source software. The users obtain the opportunity to add new sources and new loads, change software platforms, and communicate with other simulators and equipment. The students can understand the different features of smart grids, such as defect classification, energy forecasting, energy optimization, and basics of production, transmission, and consumption.

Integrating remote Internet of Things (IoT) laboratories into project-based learning (PBL) in higher education institutions (HEIs) while exploiting the approach of technology-enhanced learning (TEL) is a challenging yet pivotal endeavor. Our proposed approach enables students to interact with an IoT-equipped lab locally and remotely, thereby bridging theoretical knowledge with practical application, creating a more immersive, adaptable, and effective learning experience. This study underscores the significance of combining hardware, software, and coding skills in PBL, emphasizing how IoTRemoteLab (the remote lab we developed) supports a customized educational experience that promotes innovation and safety. Moreover, we explore the potential of IoTRemoteLab as a TEL, facilitating and supporting the understanding and definition of the requirements of remote learning. Furthermore, we demonstrate how we incorporate generative artificial intelligence into IoTRemoteLab’s settings, enabling personalized recommendations for students leveraging the lab locally or remotely. Our approach serves as a model for educators and researchers aiming to equip students with essential skills for the digital age while addressing broader issues related to access, engagement, and sustainability in HEIs. The practical findings following an in-class experiment reinforce the value of IoTRemoteLab and its features in preparing students for future technological demands and fostering a more inclusive, safe, and effective educational environment.

Sustainability education, a multidisciplinary field demanding a profound understanding of intricate scientific, engineering, social and economic systems, necessitates innovative approaches. Laboratory experimentation plays a pivotal role in engineering and scientific education. The emergence of the COVID-19 pandemic heightened the importance of remote learning and home-based study in pedagogical practices. However, engineering education has faced challenges in adapting to novel teaching methodologies. A significant challenge during lockdowns was the effective delivery of laboratory experiences in virtual spaces. Virtual and remote laboratories, while not substituting the hands-on experience of physical labs, offered promising avenues to enhance learning during the disruption of in-person education. While most teaching activities transitioned seamlessly to online formats, laboratory sessions presented unique logistical challenges, including cancellations of fieldwork. Additionally, concerns arose regarding disparities in student achievement based on income levels. This study seeks to provide an overview of the implementation status of virtual and remote laboratories during the lockdown period in education. Its goal is to offer practical insights to improve the quality of learning experiences at home and in online settings.

The interconnection between sensors, controllers and instruments through a communication network plays a vital role in the performance and effectiveness of a control system. Since its inception in the 90s, the Object Linking and Embedding for Process Control (OPC) protocol has provided open connectivity for monitoring and automation systems. It has been widely used in several environments such as industrial facilities, building and energy automation, engineering education and many others. This paper presents a novel OPC-based architecture to implement automation systems devoted to R&D and educational activities. The proposal is a novel conceptual framework, structured into four functional layers where the diverse components are categorized aiming to foster the systematic design and implementation of automation systems involving OPC communication. Due to the benefits of OPC, the proposed architecture provides features like open connectivity, reliability, scalability, and flexibility. Furthermore, four successful experimental applications of such an architecture, developed at the University of Extremadura (UEX), are reported. These cases are a proof of concept of the ability of this architecture to support interoperability for different domains. Namely, the automation of energy systems like a smart microgrid and photobioreactor facilities, the implementation of a network-accessible industrial laboratory and the development of an educational hardware-in-the-loop platform are described. All cases include a Programmable Logic Controller (PLC) to automate and control the plant behavior, which exchanges operative data (measurements and signals) with a multiplicity of sensors, instruments and supervisory systems under the structure of the novel OPC architecture. Finally, the main conclusions and open research directions are highlighted.

The COVID-19 pandemic has compelled innovations in science teaching and learning, such as blending online sessions with conventional face-to-face classes. We developed and validated the Blended Laboratory and E-learning iNstructional Design (BLEND) model for university-level remote laboratory sessions (RLS) to respond to the fluctuating instructional environment necessitated by the pandemic. We used the design and development research method to construct and apply an ID model in an analytical chemistry experiment (ACE) course for pre-service chemistry teachers, iteratively revising the model with participant feedback. We based the initial BLEND model on a literature review and lessons from our preliminary study in 2020. For internal validation, six stakeholders participated in the usability test, and 10 science subject-matter educators and three educational technology experts provided expert reviews. For external validation, we developed and implemented an ACE-RLS course module, and surveyed and interviewed seven university students who took the course. After two rounds of validation, the BLEND model was confirmed to be internally efficient and externally effective, with interactions between the instructor and students particularly appreciated. The final BLEND model for university-level RLS emphasizes constant formative evaluation, feedback, and structures and visualizes the RLS instructional system at both weekly and overall course levels.

The increasing demand for digital education drives the need to develop effective and engaging tools for students and teachers, notably in technical disciplines. This study aimed to validate the applicability and usability of the Remote Microcontroller Laboratory (RML) as a practical teaching tool in the field of engineering and mechatronics education. To this end, experimental applied research was conducted using three analysis techniques: the System Usability Scale (SUS) questionnaire, the User Experience Questionnaire (UMUX), and a qualitative analysis of responses. The aim was to gain a comprehensive view of the characteristics and difficulties associated with the use of the MRL. The results obtained showed a high average usability score, with 84.81 on the SUS and 85.90 on the UMUX, indicating that the vast majority of participating students found the MRL easy to use as a study tool. Additionally, qualitative responses demonstrated student satisfaction and the feasibility of implementing the MRL in a real teaching environment. In conclusion, the study emphasizes the importance and relevance of remote laboratories in the current educational context, showing their viability and potential as a teaching tool. The validated solution and methodology developed in this study contribute to the advancement of knowledge in the field and pave the way for future research and improvements in remote laboratories and educational technologies. A crescente demanda por ensino digital impulsiona a necessidade de desenvolver ferramentas eficazes e envolventes para estudantes e professores, notadamente em disciplinas técnicas. O presente estudo buscou validar a aplicabilidade e usabilidade da solução Laboratório Remoto de Microcontroladores (LRM) como uma ferramenta de ensino prático na área da educação em engenharia e mecatrônica. Para tanto, foi realizada pesquisa aplicada experimental com a aplicação de três técnicas de análise: questionário System Usability Scale(SUS), User Experience Questionnaire(UMUX) e análise qualitativa das respostas, buscando-se assim obter uma visão abrangente das características e dificuldades associadas à utilização do LRM. Os resultados obtidos mostraram uma pontuação média de usabilidade elevada, com 84,81 no SUS e 85,90 no UMUX, indicando que a ampla maioria dos alunos participantes teve facilidade ao utilizar o LRM como ferramenta de estudo. Em complemento, as respostas qualitativas demonstraram a satisfação dos alunos e a viabilidade do LRM em um ambiente real de ensino. Em conclusão, o estudo ressalta a importância e relevância de laboratórios remotos no contexto educacional atual, mostrando a viabilidade e o potencial como ferramenta de ensino. A solução ora validada, bem como a metodologia desenvolvida neste estudo, contribui para o avanço do conhecimento na área e abrem caminho para futuras pesquisas e aprimoramentos no campo dos laboratórios remotos e das tecnologias educacionais em geral. La creciente demanda de educación digital impulsa la necesidad de desarrollar herramientas efectivas y atractivas para estudiantes y profesores, especialmente en disciplinas técnicas. Este estudio buscó validar la aplicabilidad y usabilidad de la solución Laboratorio Remoto de Microcontroladores (LRM) como una herramienta de enseñanza práctica en el campo de la educación en Ingeniería y Mecatrónica. Para ello, se llevó a cabo una investigación experimental aplicada utilizando tres técnicas de análisis: el cuestionario System Usability Scale (SUS), el cuestionario User Experience(UMUX), y un análisis cualitativo de las respuestas, con el objetivo de obtener una visión integral de las características y dificultades asociadas al uso del LRM. Los resultados obtenidos mostraron una alta puntuación media de usabilidad, con 84,81 en el SUS y 85,90 en el UMUX, indicando que la gran mayoría de los estudiantes participantes encontraron fácil utilizar el LRM como herramienta de estudio. Además, las respuestas cualitativas demostraron la satisfacción de los estudiantes y la viabilidad del LRM en un entorno real de enseñanza. En conclusión, el estudio resalta la importancia y relevancia de los laboratorios remotos en el contexto educativo actual, mostrando su viabilidad y potencial como herramienta de enseñanza. La solución validada aquí, así como la metodología desarrollada en este estudio, contribuyen al avance del conocimiento en el área y abren el camino para futuras investigaciones y mejoras en el campo de los laboratorios remotos y las tecnologías educativas en general.

Remote laboratories are essential in addressing access and quality challenges in technical education. They enable students from various locations to engage with real equipment, overcome geographic and economic constraints, and provide solutions during crises, such as pandemics, when in-person learning is limited. As a key element of Education 4.0, remote labs promote technical skill development, enhance engineering education, and support diverse learning approaches. This study presents a remote laboratory based on Field Programmable Gate Arrays (FPGAs), developed using a waterfall methodology integrating IoT and Cloud Computing technologies to facilitate close interaction between hardware and software. The lab focuses on controlling DC, servo, and stepper motors, allowing students to apply theoretical concepts such as digital signals, pulse-width modulation (PWM), and data representation in bits in a practical setting. The testing phase involved 50 robotics and mechatronics engineering students who participated in hands-on sessions for one month, followed by a structured survey evaluating their experience, interaction, and the educational relevance of the platform. The survey shows high student satisfaction, highlighting the platform’s strengths and identifying areas for improvement. The results also underscore the system’s potential to significantly enhance the educational experience in remote environments, aligning with the United Nations Sustainable Development Goals (SDGs).