Disabled People deal with a series of barriers that limit their inclusion, empowerment, well-being, and role in society with a special emphasis in low and medium-income countries. One of these barriers is concerning the accessibility and affordability of assistive technologies (ATs) that help to enhance the quality of life of these persons. In this context, this systematic literature review (SLR) analyzes and describes how free and open-source hardware (OSHW) and open software (OSS) are employed in the design, development, and deployment of low-cost ATs. In the SLR process, different ATs were analyzed for disabilities such as visual, mobility, upper body, prostheses, hearing & speaking, daily living, and participation in society. The ATs were designed with diverse OSHW and OSS technologies such as Arduino, Raspberry Pi, NVidia Jeston, OpenCV, YOLO, MobileNet, EEG and EMG signal conditioning devices, actuators, and sensors such as ultrasonic, LiDar, or flex. 809 studies were collected and analyzed from the database Web of Science, GitHub, and the specialized journals in OSHW HardwareX and the Journal of Open Hardware during the years 2013-2022. In the first part of the SLR, the bibliometric trends and topic clusters regarding the selected studies are described. Secondly, the ATs identified with open source technologies, e.g., sensor-based or computer vision-based, are described along with a complete state-of-art about these based on each disability recognized. Finally, the issues and challenges to this approach are explored including technical factors, documentation, government policies, and the inclusion of disabled people in open source co-creation. The purpose of this study is to inform practitioners, designers, or stakeholders about low-cost (frugal) ATs with OSHW and OSS, and thus promote their development, accessibility, and affordability, contributing to benefit the community of disabled people.

Since the release of diverse generative AI (GenAI) tools such as ChatGPT, Google Gemini, DALL $\cdot $ E, and GitHub Copilot, there has been much debate around the impacts and implications of these tools on education. Currently, extant literature remarks on the affordances, challenges, and opportunities of GenAI, but few studies report and analyze empirical studies and educational practices coming up by GenAI usage in learning settings. Then, in this Scoping Review (ScR) based on 146 studies retrieved from the databases SCOPUS, Web of Science (WoS), and ERIC, we analyzed the implications of integrating GenAI in engineering and computing education from K-12 to tertiary levels. We adopted an approach starting from the bibliometric features of the studies in terms of authors, cites, years, or cluster topics, and navigating to the identification of methodologies, strategies, AI literacy instruments and guidelines, learning outcomes, and students’ and teachers’ perceptions, among other features. We advocate that current educational practices in engineering and computing with GenAI can indicate to us a roadmap of its potentialities, uses, and risks from the standpoint of both teachers and students, and this could help us to create more reflexive methodologies that enhance the teaching-learning process based on the evidence. Our purpose with the outcomes and conclusions of this scoping review is to support educators, faculty members, and other stakeholders in engineering and computing education to co-create educational methodologies that articulate GenAI with curricula, AI literacy, and prompt engineering encompassing students’ learning domains such as cognitive, affective, or behavioral.

In recent years, there has been a growing interest in education for sustainable development (ESD). Although several national and international agencies, e.g., the UN or UNESCO, have promoted its deployment in higher education institutions, educators are still facing problems with how to articulate this type of education within the curriculum, allowing students to develop their technical and labor competencies, and soft skills as well. In this way, this study describes a methodology with Project-Based Learning in renewable and sustainable energies through the development of an electrical vehicle (EV) known as EOLO. This initiative arose from an industry-academia collaboration to develop the first Colombian EV with the support of solar and wind energy sources. Twelve engineering students participated in the development of the vehicle through a set of capstone projects over a year and a half with the support of two tutors (professors) and two engineers (technical staff) of the project. Additionally, two versions of EOLO with vertical and horizontal axis wind turbines were made with the cooperation of the students. The results evidence that the methodology helped to engage students, promoted meaningfully and situated learning through real-world problems in renewable energies, and fostered motivation and peer collaboration. Nonetheless, aspects such as the improvement of the communications channels, the revision of the complexity of the projects, the sense of community to achieve a common goal, or the tutoring and monitoring processes should be strengthened for further initiatives and/or active learning methodologies. In this sense, some challenges and recommendations that can help to develop methodologies that combine ESD and engineering are provided based on the experience in this study.

This article describes the development and assessment of RaspyLab which is a low-cost Remote Laboratory (RL) to learn and teach programming with Raspberry Pi and Python language. The RL is composed of 16 stations or nodes that contain hardware components such as display LCD, robotic arm, temperature sensor, among others, and two modes of programming (graphical and text-based) for the students to experiment with their designed algorithms. The concept of the RL was conceived as a pedagogical tool to support the students of Engineering and Computer Science (CS) in an online learning format, given the context of the COVID-19 pandemic. The laboratory has been used by ( ${n} =30$ ) CS students during the second semester of 2020 in the subject of mathematical logic through the methodology of Problem-Based Learning (PBL). To evaluate preliminary the laboratory, it was used a survey with 3 open-ended questions and 12 closed-ended questions on a Likert scale according to the Technology Acceptance Model (TAM). The outcomes show a good reception of the laboratory, an enhancement of the students’ learning regarding the concepts addressed in the course, and an interest of the students for the laboratory to be included in other subjects of the curricula.