Educational Robotics

This scoping review examines the utilization of inclusive technologies for students with neurodevelopmental disorders after the COVID-19 pandemic. It classifies technologies into six categories: taskspecific software, virtual and augmented reality, video modeling, hardware equipment, learning environments, and computer-mediated communication systems for interactions with peers and tutors occurring online. Findings indicate that most interventions focus on academic skills, with limited emphasis on fostering social inclusion or peer interaction. Intellectual and developmental disabilities were the most represented conditions, followed by learning disabilities and Attention-deficit/hyperactivity disorder. Gaps include the need for more holistic pedagogical frameworks and insufficient research on emotional well-being and long-term impact, highlighting the need for future exploration.

The present study is aimed at analyzing the process of building and programming robots as a metacognitive tool of mathematics. Quantitative data from a study performed on a sample of students attending an Italian secondary school are described. Results showed that robotics activities may be used as a new metacognitive environment allowing students to improve their attitude towards mathematics, and to increase their attitude to reflect on themselves and on their own learning, and their higher-level control components, such as forecasting, planning, monitoring and evaluation exercises and problems related to implementation.

Neste estudo procuramos verificar como a exploração de Recursos educativos digitaiscontribuiparaoenvolvimentonaaprendizagemdealunoscomnecessidades educativas especiais. A utilização destes recuros com estas crianças é um campo promossor, mas ainda pouco explorado. Os recursos foram desenvolvidos especificamente para três alunos com essas necessidades. Envolveram-se os alunos na recolha e criação de alguns elementos multimédia e foram desenvolvidos no programa de autor Jclic que permite a criação de atividades interativas multimédia. Na investigação optamos pelo estudo de casos múltiplos (três casos). Foi possível verificar o potencial destes recursos na aprendizagem dos alunos envolvidos.info:eu-repo/semantics/publishedVersio

Here is a comprehensive abstract of the provided text, structured to capture the core themes, pedagogical insights, and technological discussions running through the chapters.

Abstract
Title: The Silent Architecture: Navigating the Landscape of Computing and Digital Tools

Author: Zarafshan Manzoor Banday (ZMB)

This text offers a multi-dimensional exploration of the evolving relationship between human pedagogy, cognitive development, and the pervasive digital architecture of the twenty-first century. Blending personal reflective narrative with historical context and empirical research, the compilation functions as both a guide and a critical commentary on navigating modern educational technologies and digital habits.

The volume begins by challenging traditional instructional hierarchies, advocating for "the teacher as a student" framework. Utilizing the CLEAR pedagogical model and Professional Development Qualification (PDQ) training, it highlights the transition of educators from rigid authority figures to active classroom facilitators who bridge the opportunity gap through lived, student-centered transactions. This philosophical shift is grounded in physical computing through an analysis of the BBC micro:bit—tracing its evolution from the 1980 UK Computer Literacy Project to the global STEM movement, illustrating how interactive hardware fosters logical reasoning, teamwork, and creative problem-solving in young learners.

Furthermore, the text analyzes the cognitive and historical dimensions of coding and algorithmic thought. It traces programming from Ada Lovelace’s foundational 19th-century algorithms to Al-Khwarizmi’s 9th-century mathematical systems, emphasizing how computational thinking improves working memory, resilience, and mathematical synthesis. Turning toward contemporary challenges, the work balances the immense utility of mobile devices, visual learning aids (such as the VARK model), and generative AI platforms (e.g., Google Workspace, Microsoft Copilot) against their psychological and developmental risks. It critically examines the "distraction tax" of smart devices in classrooms, citing UNESCO data regarding the severe cognitive recovery time required after notification-induced disruptions, alongside pressing cyber-safety hazards like digital footprint vulnerability and sophisticated academic malpractice.

Finally, the text addresses the ecological and personal dimensions of our digital existence. It introduces the hidden burden of "dark data" and digital hoarding, noting that the exponential growth of the global datasphere demands urgent structural mitigation strategies, such as Digital Cleanup Day initiatives, to minimize individual digital carbon footprints and reclaim lost professional productivity. The volume concludes with a reflective transition from handwritten journals to secure, encrypted digital diaries, framing modern technology not as a creative crutch, but as a loyal, eco-friendly depository for human memory and a vehicle for leaving an intentional digital legacy. Ultimately, the text presents a unified call to action for educators and learners alike: to become highly tech-savvy without becoming tech-dependent, ensuring that digital tools serve to enhance, rather than stifle, human intellect and empathy.

Digital technology is increasingly used in STEM education for young children aged 0-8 years. An extensive literature search was conducted using seven databases to systematically investigate the effect of digital technology on young children's STEM education. Twenty-two eligible articles published from 2010 to 2021 were identified. Results showed that robotics, programming, and multimedia were used to support young children's STEM education. Digital technology plays different roles in the process of STEM education. Outcomes also showed that digital technology positively affected young children's STEM education in terms of STEM knowledge or skill acquisition and learning engagement. This was regardless of gender but relevant to age and the learning condition. Participating children and teachers reported high acceptance and satisfaction with the included programs. However, many difficulties, challenges and criticisms were revealed by the extracted data, including how digital technology is used in young children's STEM education, the nature of young children, the requirements placed upon educators, and different types of adult-child interactions. We also look at the limitations of the study design within included studies and provide recommendations accordingly.

Edge AI is reshaping industrial robotics by moving perception, inference, and coordination closer to sensors, actuators, and motion controllers operating under strict timing constraints. This chapter examines latency optimization in real-time robotic control as an architectural and benchmarking problem rather than a hardwareselection issue alone. It develops a layered reference architecture linking sensing, middleware, inference runtimes, control execution, safety envelopes, and edge-cloud orchestration. It also proposes a benchmarking framework centered on end-to-end latency, jitter, deadline misses, control-age, energy efficiency, and thermal stability. Drawing on literature in edge computing, ROS 2, embedded AI, deterministic networking, and industrial robotics, the chapter synthesizes design trade-offs and presents literature-grounded industrial case studies in machine tending, visionguided handling, and mobile robotics, concluding with implementation guidance and a research agenda.

AbstractRobotics competitions for K-12 students are popular, but are students really learning and improving their Science, Technology, Engineering, and Mathematics (STEM) scores through robotics competitions? If they are, how much more effective is learning through competitions than traditional classes? What is the best robotics competition model to maximize students' STEM learning? One robotics competition designed to promote the use of math and science is Robofest. Robofest is an autonomous robotics competition with some unique features for STEM education. An example is that students need to solve unknown problems on the day of the competition. The Robofest competition requires the use of mathematics and sensors which discourages dead reckoning. Results from 5th-12th graders who completed a STEM assessment before and after the Robofest competitions found students in the Robofest group showed improvement and achieved higher scores in math and science after the competition. Thes...

Artificial Intelligence (AI) is increasingly recognized as a critical educational tool for K-12 students worldwide. This systematic literature review focuses on research from the past five years, examining how AI is integrated with robotics to enhance programming learning in K-12 settings. From an initial pool of 1,696 studies, 11 papers were selected for in-depth analysis. While using AI to promote programming skills holds great potential, it also raises important ethical considerations. The review highlights current trends, pedagogical strategies, and practical applications that enhance learning in the fields of AI and programming. It also provides detailed insights into the hardware platforms, software tools, and instructional methods employed across studies. The findings reveal that various hardware platforms have been employed in diverse educational settings, with a particular focus on secondary education, specifically in the use of AI for more complex cognitive activities. Nonetheless, a growing trend is emerging in studies at the primary education level. Future research should focus on developing pedagogical frameworks that enable educators to effectively introduce AI concepts to younger learners of programming.

Artificial Intelligence (AI) has become an influential force transformative technological development influencing worldwide educational system. The integration of intelligent technologies in teaching environments has opened new possibilities for custom-made instruction, evidence-based decisionmaking, and improved academic outcomes. A steadily expanding body of research in Artificial Intelligence in Education highlights growing scholarly interest in exploring how intelligent systems are transforming pedagogical practices. In this context, the present study undertakes a bibliometric analysis to investigate research trends, patterns of publication growth, collaborative networks, and the evolution of key themes within the field of AI in Education. The analysis focuses on scholarly publications from the past decade to explore the evolution of this emerging field. The findings indicate a consistent rise in research output, particularly in areas such as adaptive learning, intelligent tutoring systems, automated assessment, and learning analytics. The study also identifies emerging concerns related to ethical use of AI, teacher readiness, and equitable access to technological resources. The findings suggest that Artificial Intelligence has strong potential to support learner-centered pedagogy and improve educational quality. However, successful integration requires systematic policy planning, teacher training, and responsible technological implementation. The study provides meaningful insights for researchers, educators, and policymakers who aim to better understand how Artificial Intelligence is shaping changes in teaching and learning practices.

В процесі багаторічної експлуатації матеріал трубопроводу істотно змінює свої фізико-механічні властивості. Розроблено методику моделювання роботи матеріалу трубопроводу у експлуатаційних середовищах. Створено програмне забезпечення, яке дозволяє, крім стандартних можливостей запису вимірюваних величин у файл та одночасної побудови графічних залежностей в режимі реального часу, регулювати частоту вимірів в залежності від швидкості зміни вимірюваного параметра.Created method of modeling material pipeline in operational environments and software, which allows, in addition to standard features recording measured values in a file of graphic and simultaneous dependencies in real time, adjust the frequency of measurements depending on the rate of change of the measured parameter

Il materiale prodotto e qui pubblicato è stato sviluppato da INDIRE USR Umbria ed Equipe formativa
umbra, utilizzato dai docenti e revisionato, ma la consideriamo ancora una buona versione beta. Per
la stesura di questo volume le diverse parti, prodotte in momenti diversi della sperimentazione, sono
state razionalizzate, ma il lettore attento noterà che alcune parti hanno ancora la forma di commento
o di testo in progress. Abbiamo deciso di lasciare in questo modo pur decidendo di pubblicare per
mettere un punto fermo nell’evoluzione, ma allo stesso tempo per far comprendere al lettore che ci
sono parti che anche a nostro avviso non sono ancora “ferme”.
Contiamo di avere una prima versione stabile di questo materiale alla fine dell’anno scolastico 2025
- 2026, quando i materiali di questo volume, in questa forma, verranno validati attraverso la
sperimentazione in classe delle scuole del progetto “Curricoli Verticali di Coding e Robotica
Educativa”.
Saremo altresì interessati a commenti e revisioni da parte della comunità scientifica e educante.
Inoltre, il volume tratterà la parte relativa agli strumenti forniti durante il progetto di cui sopra,
risultando consapevolmente come un racconto parziale di tutta la complessità organizzativa e
pedagogica emersa, che, pur essendo fondamentali per un resoconto del progetto, non rientrano
negli obiettivi di questa pubblicazione.

The integration of robotics into basic and tertiary education remains limited in resource-constrained institutions due to the high cost of commercial educational robotic kits. This study aimed to design, develop, and evaluate a low-cost Line-Follower Robot with functional performance comparable to higher-priced systems while establishing a structured framework for curriculum integration. A developmental-experimental research design was employed following a Design–Build–Test–Implement framework. The prototype utilized affordable components including an Arduino Uno microcontroller, infrared sensors, an L298N motor driver, and TT gear motors. Performance metrics such as tracking accuracy, speed stability, response time, and error rate were measured and compared against commercially available units. Additionally, pre-test and post-test assessments were conducted to evaluate student learning outcomes during pilot classroom implementation. Results indicate that the developed prototype achieved comparable line-tracking efficiency while reducing total cost by approximately 40–60%. Findings suggest that structured exposure to low-cost robotics not only enhances STEM competencies but also equips students with foundational skills applicable to industrial automation systems, such as warehouse transport robots and factory-guided vehicles. The study contributes a replicable and scalable model for integrating robotics into school curricula in developing educational contexts.

The integration of artificial intelligence (AI) in education is transforming traditional teaching paradigms, opening up new possibilities for personalised, effective, and accessible learning; meanwhile, the discussion about ethical usage and bias is still growing. This study uses a knowledge mapping approach to explore the research landscape of AI in education by systematically analysing key research topics, trends, and knowledge gaps. It also discusses and explores the emerging debates on the use of AI as a "humanizer" and its impact on academic integrity. A bibliometric analysis was conducted on Scopus-indexed publications from 1976 to 2026. Network visualisation methods implemented in VOSviewer were used to examine publication growth, patterns of international collaboration, most influential studies, keyword co-occurrence patterns, and bibliographic relationships at the journal level. The results demonstrate the evolutionary nature of artificial intelligence applications all over the world from the perspectives of most cited works, collaborations among countries etc., the interdisciplinary collaborations that drive innovations, and the ethical issues associated with its implementation. This study provides a comprehensive overview of the current state of research highlighting the main trends, like countries with the most contribution in AI research in education are the USA and China, the biggest rise of AI research was seen from 2020 and 2024. However, despite the fact that AI is strongly influencing education processes, the study also discusses ethical aspects, like what should be done (and what can be at all), if a text is humanised?

The use of ChatGPT and other generative AI tools in education has increased the need to assess how these tools affect students academic performance, particularly in areas such as problem-solving and ethical awareness. However, there is a lack of a comprehensive instrument to assess these areas among Malaysian Technical and Vocational Education and Training (TVET) students. This study addresses the gap by developing and validating a questionnaire to evaluate the responsible use of ChatGPT among TVET students. The questionnaire was constructed in three phases: (i) questionnaire development, (ii) content validation by four experts using Aikens V (threshold ≥ 0.83) and (iii) pilot testing with 43 purposively sampled TVET students to assess internal consistency. Expert evaluations of item relevance, clarity, and simplicity (RCS) led to minor items refinement. The pilot results showed high reliability (Cronbachs α > 0.80) across all sections. Due to the limited sample size (n = 43), exploratory or confirmatory factor analysis was not conducted. Instead, item-level performance was evaluated using descriptive statistics, corrected item–total correlations, and Cronbachs alpha, which provided sufficient evidence for validation. The validated instrument serves as a foundation that offers a reliable tool for full-scale studies and lays a strong foundation for future research on AI-assisted problem-solving and ethical awareness in Malaysian TVET programs.

Artificial Intelligence (AI) is revolutionizing inclusive education by providing personalized, accessible learning tools that address diverse student needs, particularly in science classrooms. This thought paper examines AI's transformative potential through adaptive platforms, virtual labs, and real-time feedback systems, while addressing critical challenges like algorithmic bias, digital divides, and teacher preparedness. Drawing from STEM education studies and global AI implementations, it argues for ethical frameworks, professional development, and equitable access to ensure AI amplifies inclusion rather than exclusion. Science educators must lead interventions to harness AI effectively in 21st-century classrooms, fostering scientific reasoning for all learners. Introduction Imagine a science classroom where a visually impaired student independently conducts a chemistry experiment using voice-activated AI tools, while a peer with dyslexia receives realtime text-to-speech explanations of complex molecular structures. This scenario exemplifies how artificial intelligence (AI) is reshaping inclusive education, particularly in science disciplines, by dismantling traditional barriers to learning. This thought paper argues that AI holds transformative potential for inclusive science education but demands ethical safeguards, teacher training, and equitable access to prevent exacerbating inequalities. Inclusive education ensures all learners, regardless of ability, engage meaningfully in curricula like science, where hands-on labs and abstract concepts often exclude marginalized students. As AI integrates into classrooms, it offers personalized tools aligning with 21st-century demands, yet challenges like bias and digital divides persist. Drawing from studies on problembased learning in STEM and AI applications, this paper explores AI's role, benefits, challenges, and interventions for science teachers. Background and Context Inclusive education traces its roots to the 1994 Salamanca Statement, which advocated for schooling all children in mainstream settings regardless of abilities, yet science education has historically lagged due to inaccessible labs and abstract concepts like molecular structures or relativity. The rise of AI coincides with global shifts: UNESCO reports 258 million children out of school, many with disabilities, while the Philippines' K-12 science curriculum emphasizes performance-based assessments that AI can now support through adaptive tech. In the STEM context, studies like Blancia's problem-based learning research reveal persistent gaps in scientific reasoning among diverse learners, exacerbated by traditional methods. The COVID-19 pandemic accelerated AI adoption, with tools like Google Classroom and AI tutors exposing both potential (e.g., 30% engagement gains) and pitfalls (e.g., 40% digital divide in rural areas). Current trends show AI integration in 65% of U.S. schools but only 20% in Southeast Asia, highlighting equity needs for contexts like Romblon State University classrooms.

This study explores students’ perceptions and learning experiences using NaviOS, a digital learning platform developed to support the teaching and learning of Operating Systems courses in polytechnic education. The increasing demand for technology-integrated learning environments highlights the need for innovative tools that address challenges such as limited structured materials, low engagement, and difficulties in understanding complex technical concepts. NaviOS was designed as an interactive, centralized, and accessible platform incorporating multimedia elements, real-life analogies, and an AI-powered chatbot to enhance student learning. A quantitative descriptive survey design was employed, using a Likert-scale questionnaire distributed via Google Forms. The study involved 200 Diploma in Information Technology students from Polytechnic Ungku Omar. Data were analyzed to evaluate usability, learning experience, engagement, and students’ intention to use the platform. Findings are expected to provide insights into the effectiveness of NaviOS in improving students’ conceptual understanding, motivation, and engagement. The study contributes to the growing body of knowledge on digital learning innovations in Technical and Vocational Education and Training (TVET). Additionally, it offers practical implications for educators and policymakers in enhancing curriculum delivery through structured and technology-driven learning approaches aligned with modern educational needs.

Educational Technologies can be used both as mediators for didactic activities in different specific contexts, and as self-sustaining tools in various settings, acquiring a relevant role in competence building and in developing an attitude to a scientific approach. In this contribution we propose a systematic overview of theorical assumptions in order to activate some Robotic experiences and didactic paths in which students act as researchers, continuously discovering and verifying if their intuitions are valid. Robotics shows a fantasy dimension which motivate the students and engage them in skill acquisition processes.

This chapter develops raakbaarheid, translated as affectability, as a pedagogical concept for
understanding maker education beyond technical skill acquisition. The concept is introduced to
describe how learning processes do not only lead to the development of competencies, but also
transform learners in emotional, embodied, relational, and existential ways. Raakbaarheid
refers to the depth at which learning becomes formative, a process in which learners are not
only acting, producing, or solving problems, but are also being shaped by what they encounter.

El presente artículo presenta una experiencia de aplicación de Aprendizaje Basado en Proyectos (ABP) a nivel de educación superior, con el objetivo de incrementar la motivación de los alumnos y mejorar su autoaprendizaje en una asignatura generalista de primer curso del Grado en Ingeniería Eléctrica de la Universidade da Coruña. En concreto, se planteó la incorporación de una nueva herramienta tecnológica: robots. La idea general es que los alumnos tengan que programar un dispositivo que actúa en el mundo real, es decir, fuera del entorno digital del ordenador, y que sea cercano a la especialidad de su titulación. Además de mostrar los resultados concretos obtenidos en esta experiencia durante dos cursos académicos, se analizan las repercusiones didácticas de una forma más global, y se plantean conclusiones y recomendaciones para otras asignaturas similares de otras titulaciones que pudiesen aplicar metodología ABP.

In the era of the Fourth Industrial Revolution, technologies such as Artificial Intelligence (AI), Educational Robotics (ER), big data analytics, and other innovations have a significant impact on many areas of daily life, including education. This study attempts to examine how robotic assistants-i.e., Educational Robotics devices that combine mechanical parts, sensors, actuators, and equipment that incorporates Artificial Intelligence (such as AI cameras, voice recognition sensors, etc.)-can contribute effectively to the experimental approach of concepts and phenomena of the Natural Sciences.

This project and paper would not be possible without the help of many hands of whom I'd like to take a moment and thank. First, I'd like to thank the students in my physics and physical science classes and the students in the FIRST Lego League and Tech Challenge clubs at my school along with their parents; the students for their hard work and participation in this project and the parents for giving me the consent to use the data that I was able to collect from their children to put this project together. Secondly, I'd like to thank my administrator, Travis Schueller, for guiding me along the way and kindly reminding me of things that I needed to take care of in order for this project to be a go. Next, my colleague Alecia Schoonover who was the "go--to" for discussing the project with my students and for collecting all the permission forms, which at times was an arduous task. Next, I'd like to thank the Science Education faculty at the University of Northern Iowa (UNI), specifically Dr. Larry Escalada for being my outside reader; Dr. Dawn Del Carlo for guiding me along the way in the process of developing this research project and reading through early copies of my paper in the "Research Methods" class at UNI; Dr. Jeff Morgan for all of his efforts in reading through numerous revisions of my paper, making corrections and suggestions, and taking care of all the legwork to help me get this paper and project finished. Lastly, I'd like to thank my wife, Kristen Nall, for helping me on the home--front by reading through many of my revisions, giving me ideas, helping watch the kids while I spent numerous hours working on this project, and for being my rock and support whenever I needed it for the past seven years as I worked through my graduate degree at UNI. There were many hurdles along the way, but we made it!! iii iv

The paper describes an ongoing research on teacher education for the implementation of making and digital fabrication in educational settings taking part at LABoral Art Centre, Spain. It aims to define key points and indications for the design of learning environments for teachers through making and prototyping in the context of an art centre as an open education lab. We present a qualitative instrumental case study articulated around two dimensions: the analysis of the context of the art centre, and the design of two teaching education programs. The analysis of LABoral context aims to explore the potentiality of an open lab and its related community as a learning environment for teacher education. The study of the teaching education programs is set to define the principles in order to put forward a proposal for the design of a learning environment for teacher education in making.

This paper presents the design of a Brazilian robot, named Zequinha, for cultural and educational purposes in light of Human-Centered Artificial Intelligence challenges. Zequinha’s development is a blend of art, robotics, and AI, evolving from MIDI-programmed animatronics to an autonomous entity integrating multiple local AIs. This shift to local processing inherently enhances privacy and governance, minimizing reliance on external APIs and enabling offline operability. The project’s human-centered design approach is evident in its iterative methodology and its collaborative development with children. Zequinha promotes human wellbeing by enriching cultural mediation, engaging diverse audiences, and demonstrating potential in health and education. Moreover, the focus on local AI fosters responsible design and meaningful human-AI interaction, aiming to create a charismatic, safe, and useful robotic mediator.

With increasing attention on the potential overlap between computational thinking (CT) and mathematical reasoning, STEM education researchers seek to understand how integrating CT and mathematics can deepen student learning across disciplines. Although there are various professional development programs that introduce teachers to CT concepts and strategies for curriculum integration, limited research exists on how teachers might apply this knowledge to create math + CT activities for use with their students. Additionally, the majority of research on CT integration through programming has focused on upper elementary grades, leaving the early grades (K-2) relatively unexplored. This qualitative exploratory study aims to examine how teachers in a graduate STEM education program collaborated with university STEM faculty to explore and critique a set of integrated math + CT block-based programming activities designed to build place value conceptual understanding. In-service elementary teachers enrolled in an online graduate CT course for educators (n = 13) explored these activities as learners and drew on their experiences as classroom teachers to offer feedback for program redesign. A sequence of deductive pattern coding and inductive holistic coding of course transcripts, collaborative problem-solving slides, and individual teacher reflections provided insights into how teachers were able to establish connections between their mathematical knowledge related to teaching place value and their emerging understanding of CT concepts, such as abstraction, algorithms, decomposition, and debugging. Implications for the design of professional development for elementary teachers on integrating CT and mathematics are offered.

Reflective writing is a core component of teacher education, especially during practical internships. However, providing high-quality feedback on reflections is resourceintensive. This study examines descriptively observable associations between an early dual-feedback approach combining basic (automated) and elaborate (human-generated) feedback and structural features of preservice physics teachers' reflective writing, prior to the widespread adoption of generative AI in education. Using an exploratory, nonequivalent, non-concurrent cohort design, we analyzed participant-level aggregates of written reflections from a non-intervention cohort (N = 22) and an intervention cohort (N = 32), applying a validated reflection-supporting model to assess structural composition and discursive elements of reflective writing. In the intervention, basic feedback was generated by a previously validated BERT-based machine learning model focusing on structural reflection elements, while elaborate feedback addressed content-related and pedagogical depth. In this study, the automated model was employed as an analytic measurement instrument drawing on validation work demonstrating its transferability across comparable reflection contexts. Quantitative analyses did not reveal systematic longitudinal growth in indicators of reflective writing quality in either cohort. Across comparable measurement points, descriptively different structural reflection profiles were observed between cohorts, without permitting causal or developmental interpretations. Feedback acceptance was high overall, although structural AI feedback was perceived as less personalized and less useful. These findings highlight the descriptive value of early, non-generative AI-based approaches for scalable structural diagnostics of reflective writing, while underscoring the continued importance of human-generated, content-focused feedback. The study establishes an empirical baseline for evaluating contemporary generative AI-based feedback systems in teacher education.

Sustainability actions have the potential to exert a lasting impact on higher education didactics. Universities are often regarded as key actors in educating the next generation of decision-makers who are capable of making more informed choices from a sustainability perspective. However, significant challenges remain regarding the understanding about how sustainability can be integrated into higher education, and disciplines differ considerably in how they engage with the topic. To address these issues, we employ collaborative auto-ethnographic approach to examine how eight lecturers from different disciplinary backgrounds approached sustainability education, and what affordances and tensions they encountered during and after a joint international course on Higher Education Didactics for Sustainability organized by Karlstad University in Sweden. The findings indicate that substantial challenges persist, despite participants' high levels of motivation and transdisciplinary mindsets. These challenges appear to be linked to disciplinary differences in approaches and emphasis regarding which aspects of sustainability education are considered applicable to the participants' teaching practices.

Sustainability actions have the potential to exert a lasting impact on higher education didactics. Universities are often regarded as key actors in educating the next generation of decision-makers who are capable of making more informed choices from a sustainability perspective. However, significant challenges remain regarding the understanding about how sustainability can be integrated into higher education, and disciplines differ considerably in how they engage with the topic. To address these issues, we employ collaborative auto-ethnographic approach to examine how eight lecturers from different disciplinary backgrounds approached sustainability education, and what affordances and tensions they encountered during and after a joint international course on Higher Education Didactics for Sustainability organized by Karlstad University in Sweden. The findings indicate that substantial challenges persist, despite participants' high levels of motivation and transdisciplinary mindsets. These challenges appear to be linked to disciplinary differences in approaches and emphasis regarding which aspects of sustainability education are considered applicable to the participants' teaching practices.

This study aims to analyze how pre-service informatics teachers design learning scenarios with robotics to teach programming fundamentals and to promote computational thinking skills. A descriptive and exploratory case study design was implemented with 26 pre-service informatics teachers. Data were collected from the participants using qualitative and quantitative instruments. The main results pointed out the affordances and possibilities of the use of learning scenarios with robotics to teach programming fundamentals and to promote computational thinking skills as well as a strong path to promote the application of contents of the other Science, Technology, Engineering, Arts and Mathematics (STEAM) areas. Another significant finding was the impact of the didactic experience on the level of interest and self-confidence of the pre-service teachers in using robotics for teaching purposes. The results showed the importance of these didactics experiences to the pre-service teachers prep...

In this paper we propose a discussion about the development of autonomy in the educational process by considering its importance and the difficulty to observe and measure this phenomenon in the learning process. Although, in theory, the educational process, especially in the formal education, aims to promote the development of students' ability to understand and act autonomously in daily life, educational practices do not always lead to that end. The research is based on a survey conducted with 313 basic education teachers that attended and concluded a specialization course in pedagogical coordination. Based in the survey's results, we analyze some aspects concerning the development of autonomy in the process of learning regulation in virtual environments. Findings show it is possible to affirm that teachers consider that the learner's autonomy is an important factor in learning regulation and that a course in a virtual environment can also facilitate continuing education regarding the pedagogical use of Digital Information and Communication Technologies (DICT) in education.

In this study, a different geometric model that is thought to be used in teaching derivatives and integrals will be introduced. This geometric model is based on the meanings of the words derivative and integral. The geometric models used for teaching consist of plane geometric regular shapes. With this study, whether this geometric model should be used in teaching derivatives and integrals, its deficiencies or incorrects will be opened to discussion by mathematics and mathematics educators.

prompted by the fact that STEM education is usually promoted in specific types of schools and not in the majority of the students' population. To this end, four STEM dissemination Hubs were created, one of which is a pre-existing laboratory in the Department of Primary Education in the National and Kapodistrian University of Athens, while the remaining three are located in three different schools: a primary school in a rural area of Greece, a second chance school and an evening high school, the latter two located in Athens. Following brief research on teachers' and students' needs, teaching seminars were designed for teachers and original educational STEM activities were developed for both students and teachers. All activities are based on environmental issues, namely solar energy, weather and climate, air pollution, energy saving through precise control of household appliances, and promotion of sustainability including physical computing. Through the proposed actions, teachers and students conceptualized the relationship between science, society and the environment on a local and global scale and practice on real problems with the aim of improving their everyday lives while encouraging the taking of initiatives for actions and making decisions.

Students of mechatronic during education will get to know programming different robots and robotarms. The robot such a apparatus which use mechanics, electronics and informatics knowledge, can solve different exercises alone or programmed examples. The LEGO ® kits take less place, need less protect because of plastic parts and more cheaper than other use for special example robot. It's teach the studets in form of play for building, using and programming. They can learn easily the controlling, feedback controlling, programming knowledge with the multimedia, and they will be able to use later in individual complicate exercises. The kit contain different sensors, servomotors and can controll with the central control unit. The LEGO ® Mindstorms ® kits can integrate and expand with Technic family. The competition consists of more rounds. All rounds last at most three minutes. An attack may not be longer than one minute. The robots have to fit into a 305 x 305 mm square and 0,91 kg! [13] LEGO® MINDSTORMS® application appears justified in the education of the mechatronic. Recognising this in all more advanced countries deal with the programming of LEGO® robots between frameworks a some kind of level. In our country increasingly in more middle and higher education institution is available in the training of the informatics and the mechatronic because of his price. Countless areas may be conquered in the future and the artificial intelligence, algorithm theory, image processing, formation recognition, communication, game theory may turn into the important devices of researches. Abroad and in our country increasingly more programming-, building competition are organized motivating the students for achieve a right result. In the competitions and the project tasks the students can be motivated, they learn to collaborate, to communicate with each other on vocational language. The acquired knowledge is applicable excellently in the later employment.

Artificial intelligence (AI), including rapidly expanding generative AI tools, is increasingly shaping how school-age students search for information and complete learning tasks. Yet comparative evidence on AI awareness, use, and attitudes across school levels-especially among under-18 learners-remains limited in Central and Eastern Europe. Guided by the Technology Acceptance Model (TAM), this cross-sectional survey study examined Hungarian elementary and high school students' AI use and school-related applications, focusing on perceived usefulness and willingness to use AI in learning contexts. Data were collected from 183 elementary and 127 high school students using a structured questionnaire. AI use was widespread in both groups, but marked school-level differences emerged. High school students reported more frequent and academically oriented AI use, greater reliance on AI tools when seeking help, and a stronger willingness to use AI during classroom activities. In contrast, elementary students more often relied on familiar platforms such as social media and YouTube and reported comparatively more recreational or conversational uses of AI. Across school levels, students generally viewed AI as useful and potentially engaging for learning, while many also expressed uncertainty about the reliability of AI-generated responses. These findings underscore the need for age-appropriate AI literacy education aligned with students' developmental characteristics and digital habits, and they highlight the importance of teacher support and training to integrate AI meaningfully and responsibly into classroom practice.

Paper presents a concept that is new to robotics education and social robotics. It is based on theatrical games, in which students create "biological", "characteristic" and natural motions for social robots and animatronic robots. Presented here motion model is based on Drift Differential Model from biology and Fokker-Planck equations. This model is used in various areas of science to describe many types of motion. The model was successfully verified on various simulated mobile robots and a motion game of three robots called "Mouse and Cheese".

Scalable cloud-based intelligent decision systems are investigated for industry-specific problems in different sectors that can be optimized by AI-assisted big-data analytics. Despite the growing popularity of cloud-based AI and bigdata-driven decision systems, evolution in the required cloud infrastructure and the actual data pipelines have not yet been undertaken in detail. In addition, the current research has not gone into sufficient detail on cloud-based systems for specific high-scaling industry problems such as for the healthcare and life sciences sector or those supported by the manufacturing or supply chain domain. Cloud decision systems also have specific requirements for management and governance due to the nature of data belonging to different parties, and these aspects require further consideration. Consequently, the focus is on cloud systems for scalable manufacturing or supply chain operation decision management, with practical industry examples clearly described for evaluation and cross-validation of accuracies. The study serves teleological domain-focused decision-systems deployment in generic governance-integrity-demandsupporting environments. For exemplary industry-use domain-focused problems, demand forecasting, inventory/supply, production scheduling, logistics, or resiliency-enhancement of supply chains, patient-flow management, clinical-decision-support allocation of resources in healthcare, and integration of multiple-organization datasets for results comparison and research in life-sciences decision support are highlighted. The encoding and timing aspects of teleological risks are also emphasized at the decision-system level, while general privacy and security requirements specify the data-handling and incident-reaction measures needed for protection against unauthorized disclosure or service unavailability.

In the current work, the researchers examine 20 years (2004-2024) of literature on Industry 4.0 and IoT, visualizing intellectual organisations, knowledge sharing, and changes in themes. Based on data collected from 6,000+ articles scraped from Scopus and processed with VOSviewer, Biblioshiny, and Python, it answers three research questions: the creation of Industry 4.0 and IoT scholarship, market forces and market uptake, and convergences in technologies. Results indicate soaring growth in publications starting in 2016, with significant contributions from China, the US, Germany, India, and the UK. The study identifies a gap in the scholarly literature and in the uptake of IoT, with high implementation evident in the manufacturing and logistics sectors, whereas in the healthcare, agriculture, and building sectors, implementation challenges persist. It includes suggestions for what researchers should consider in the future, including socio-technical integration, cybersecurity, and sustainable digital ecosystems.

Este trabajo presenta una propuesta didáctica basada en proyectos diseñada para que docentes de primaria y secundaria sin experiencia previa en robótica educativa, puedan aprender sobre componentes básicos de hardware y su relación con el software en un curso de dos meses de duración con 4 clases virtuales y 3 presenciales. El curso es parte de una Especialización en Programación de dos años de duración. Analizamos los principales aspectos de la propuesta y los resultados en términos de las producciones que lograron los docentes y sus valoraciones del curso'.

This study reports the results of a single-case intervention involving a child with spinal muscular atrophy. The aim of the study was to promote fine motor skills, visual-motor integration, attentional behaviors, and learning. The treatment was based on the RE4BES protocol, which consists of a set of guidelines for conducting tailored educational robotics activities designed for children with special needs. We employed an experimental single-case ABA design, including Baseline 1 (A1), Treatment (B), and Baseline 2 (A2), with eight sessions per phase. The treatment phase involved activities with Blue-Bot and LEGO® WeDo 2.0. Results showed significant improvements in gross and fine motor skills from baseline to the treatment phase, with these gains maintained after the intervention. Moreover, in alignment with the main goals of school inclusion for people with special needs, results demonstrated that the intervention also improved awareness, flexibility, cooperation, and initiative within the classroom. Despite the study's limitations, the findings support the effectiveness of the RE4BES protocol and suggest that educational robotics can be a valuable tool in special education settings.

Artificial intelligence (AI) is changing the terrain of higher education institutions in a time of unparalleled technological development, thereby requiring a basic change in curriculum design. This chapter explores innovative strategies for integrating AI into higher education institutional frameworks to prepare learners for an AI driven future. Instead of perceiving AI as a disruptive technology, it is envisioned to be an innovation driver in pedagogy, learning processes, and organizational systems. This section discusses several dimensions of how AI restructures learning. It focuses on understanding AI, learning that is personalized for oneself, blending several subjects, and ongoing skill development. It focuses on developing a growth mindset for students and educators, in which flexibility, ethical thinking, and critical thinking are as crucial as technical skills. Some of the key strategies include curriculum alignment with industry needs, training teachers to use AI tools, and using real-world AI examples in several subjects.

Programming and robotics-based training programs have been shown to
enhance computational thinking and self-efficacy, yet limited attention has been paid to preparing future teachers to effectively implement these methodologies in educational practice. This study analyses the impact of an educational intervention based on visual block programming, educational robotics, and machine learning on the initial training of pre-service teachers and in-service primary school teachers. A quasi-experimental design was employed. The sample consisted of 170 participants: 83 students enrolled in a Primary Education degree program and 87 in-service primary school teachers. The instructional procedure was implemented through hands-on activities with micro:bit, Maqueen robots, and introductory machine learning concepts. Data were collected using a coding, robotics, and machine learning knowledge test, along with several validated Likert-type scales to assess attitudes toward the curricular integration of these technologies. For the first dimension, Student’s t-tests and linear regression
analyses were conducted, while correlation analyses and nonparametric
tests were applied to the second dimension. The findings revealed significant
improvements in the acquisition of basic computational concepts (sequences,
loops, and conditionals) and in the understanding of machine learning, with university
students outperforming practicing teachers. Comparative tests indicated a
greater self-perception of technological competence among university students,
particularly in block-based programming and the use of game engines for educational
purposes. The results suggest that the structured integration of robotics
and machine learning appears to constitute a viable and effective strategy for
enhancing teacher training, promoting active methodologies, and fostering an
interdisciplinary approach in primary education.

This study investigates the effectiveness of problem-solving methodologies in computational science. A quantitative research approach with descriptive and exploratory design was employed. A total of 400 questionnaires were distributed, of which 385 were correctly completed and returned. Data were analyzed using SPSS version 26.0 through descriptive and inferential statistical techniques. The results revealed a strong positive correlation between Innovative Problem-Solving Methodologies (IPSM) and problem-solving effectiveness, and a moderate positive correlation for Visualization Tools (VT). Conversely, Interdisciplinary Collaboration Strategies (ICS), Advanced Computational Tools (ACT), and Education and Training Programs (ETP) showed weak or non-significant correlations with effectiveness. The study concludes that structured methodologies and targeted training programs are critical for enhancing outcomes in computational science. Recommendations include promoting innovative problem-solving methodologies, investing in visualization tools, reviewing collaboration strategies, and strengthening education and training programs. Future research should examine the interactions between these factors to provide deeper insights into their contributions to problem-solving effectiveness.

Abstract
This research work focused on the Design and Development of Customized Computer Assisted Instruction (CCAI) Model for Teaching Science Subjects in Nigerian Senior Secondary Schools. As science education is yet to achieve its target objective of achieving sustainable science education for industrialization, there is need to find out the causes of the problem and proffer solution to it. Survey method was used to find out the current scenario in the teaching and learning of science subjects in Nigeria secondary schools. Three hundred copies of questionnaire were used to collect data from a sample of 20 secondary schools across the six
geo-political zones of the country. Three research questions and two hypotheses were formulated that guided the study. Data collected were analyzed using mean and standard deviation. Chi-square was used to test the hypothesis. The major finding, among others showed that all the schools in the six geo-political zones still lacked science teachers, particularly in physics subject. This finding therefore justified the need to find an alternative solution to the teaching of science subjects in our schools. The researchers therefore, designed and developed a customized CAI for teaching science subjects at the senior secondary school level using physics as case study. The methodology adopted for the design of the CAI software was top down, and the structured systems analysis and design methodology. Visual Studio 2015 and Microsoft SQL. server 2013 were also used to develop the model CAI. Experimentation of the software by students offering physics recorded huge success, thus raising the hope that full utilization of the software will go a long way in addressing the lack of science teachers, and as well aid students' understanding of the subject for improved academic performance.
Keywords: Sustainable, CAI, Chi-Square, ICT, Science Education.

The integration of robotics into secondary education is often hindered by the high cost of proprietary systems and the pedagogical limitations of "Black Box" abstraction. This study presents a comparative analysis between proprietary robotic ecosystems (e.g., LEGO Education) and open-architecture "White Box" alternatives to evaluate their respective financial efficiency and educational efficacy. Utilizing a replicated quasi-experimental design, high school students were tasked with constructing a functionally analogous 3-DOF robotic arm using either a snap-fit commercial kit or a bare-metal open-source kit. The study measures technical competence through the lens of "Hardware Transparency"-the extent to which users interact with fundamental engineering components-and assesses economic viability via Life Cycle Cost Analysis (LCCA). The results indicate that the open-architecture approach demonstrates superior educational outcomes, with students exhibiting a significantly deeper understanding of critical mechanical and electronic principles compared to their peers in the proprietary group. Furthermore, the financial analysis confirms that open-source systems provide a substantial reduction in acquisition and maintenance costs, facilitating easier and more sustainable integration into school curricula. These findings suggest that a paradigm shift toward open-architecture systems is not only an economic necessity but a pedagogical upgrade, offering a more effective pathway for cultivating the next generation of engineers.

The adoption of robotics in education has increasingly gained attention. Robotics activities can be applied in any level of education since the early childhood up to, starting in primary schools until graduate schools. Besides, the concept of STEM learning is still a trending issue in the world of education. STEM-based learning with robotics can develop knowledge and the awareness of robotics for students. Notwithstanding the vast literature on adoption of robotics into the educational context activities, there is a possibility of a limited lack of explanation on how robotics contribute in the STEM learning environment at primary school. A systematic literature review was carried out to evaluate the latest developments of robotics topics in the literature. It is prominent in the literature that robotics contribute to teaching and learning in primary schools. Teachers indicated positive responses to robotics due to the ability to attract students’ attention and motivation. However, n...

The integration of generative AI tools, such as ChatGPT, Gemini, and DeepSeek, into higher education offers transformative opportunities for personalised learning and academic productivity. However, their unregulated use raises concerns about academic integrity, critical thinking, and educational equity. This systematic review synthesises insights from 96 peer-reviewed articles, identifying six key intervention themes, namely, curriculum integration, policy and governance, faculty development, student-centred strategies, assessment adaptation, and technological infrastructure. Together, these themes form a comprehensive intervention framework designed to guide students' ethical and effective engagement with AI. This review highlights the need for institutions to move beyond fragmented policies, fostering systemic cultural and pedagogical change to align AI use with authentic learning outcomes. By bridging theoretical gaps and providing actionable strategies, this framework equips educators and policymakers to scaffold responsible AI integration across diverse higher education contexts.