Educational Robotics and Computational Thinking in Elementary School Students

This study examined the role of educational robotics in fostering computational thinking in elementary settings, both in classrooms and extracurricular programs. Among growing concerns over K–12 students’ computational thinking deficits, the research evaluated the impact of Lego EV3 and VEX IQ platforms. Data was sourced from lesson plans, student work surveys, and teacher interviews and then subjected to thematic analysis using a qualitative approach. The participants were Texas educators engaged in robotics instruction, even though specific robotics statistics are absent in the Texas Education Agency. Instructional strategies varied from hands-on experiences to translating mathematical concepts into robotic actions. A key finding was robotics’ role in advancing computational and critical thinking skills. Teachers believed that robotics went beyond a mere science, technology, engineering, and mathematics introduction, promoting advanced computational thinking and linking creativity to real-world application. Robotics challenges were seen to enhance students’ computational and critical thinking capabilities. The study drew from constructionism theory, which promotes learning through action and knowledge creation. In conclusion, educational robotics, reinforced by constructionism, is essential for equipping students for a technologically advanced future. Early exposure to robotics equips elementary students with vital 21st-century skills, enhancing their science, technology, engineering, and mathematics preparedness

Design of Curriculum Matrix for Robotics Education Derived from Bloom's Taxonomy and Educational Curriculum of 2013

Even though robotics have gaining an attention from students of every educational level since elementary school up to higher education, their impact in student’s education itself is still relatively small. Most of the robotics competitions in Indonesia are still focus on the result but not in the process. This paper presents an educational matrix of curriculum based on robotics which focused on the process and learning outcomes of the education. The proposed Curriculum Matrix is derived from Bloom's Taxonomy which synchronized with the Educational Curriculum of 2013 from the Indonesian Ministry of Education and Culture. Hereafter, the activities of education are designed based the available robotics module together with the designed Curriculum Matrix. By using the Curriculum Matrix, the proportion of education activities can be evaluated to achieve the learning outcomes for the specified educational level more easil

EDUCATIONAL ROBOTICS AND COMPUTATIONAL THINKING IN EARLY CHILDHOOD - LINKING THEORY TO PRACTICE WITH ST(R)EAM LEARNING SCENARIOS

STEAM enhances critical and computational thinking, problem-solving, algorithmic thinking, decision-making, through Science, Technology, Engineering and Arts, as well as Mathematics. With the contribution of Reading (Reading) and Writing (wRiting) which include recognition and visualisation, pattern formation as well as skills acquired through the use of tools such as pencil and brush, which are proven to be valuable for children's development, STREAM is now also linked to Thinking and Art in its broadest sense. Therefore, in this paper, STREAM Learning Scenarios are proposed that can be implemented within the kindergarten and primary school classroom using the BeeBot robot, highlighting its added pedagogical value and linking the theoretical framework with the playful practical implementation.  Article visualizations

A Contextual Approach To Learning Collaborative Behavior Via Observation

This dissertation describes a novel technique to creating a simulated team of agents through observation. Simulated human teamwork can be used for a number of purposes, such as expert examples, automated teammates for training purposes and realistic opponents in games and training simulation. Current teamwork simulations require the team member behaviors be programmed into the simulation, often requiring a great deal of time and effort. None are able to observe a team at work and replicate the teamwork behaviors. Machine learning techniques for learning by observation and learning by demonstration have proven successful at observing behavior of humans or other software agents and creating a behavior function for a single agent. The research described here combines current research in teamwork simulations and learning by observation to effectively train a multi-agent system in effective team behavior. The dissertation describes the background and work by others as well as a detailed description of the learning method. A prototype built to evaluate the developed approach as well as the extensive experimentation conducted is also described

Enhancement of Real-Time Object Detection and Tracking in Collaborative Environment using AI and Mixed Reality

The area of mixed reality has had rapid growth in recent years, with a notable rise in funding. This may be attributed to the rising recognition of the potential advantages associated with the integration of virtual information into the physical environment. The majority of contemporary mixed reality apps that rely on markers use algorithms for local feature identification and tracking. This study aims to enhance the accuracy of object recognition in complicated environment and enable real-time classification operations via the introduction of a unique detection approach known as the lightweight and efficient YOLOv4 model. In the present setting, Computational vision emerges as a very valuable and engaging manifestation of artificial intelligence (AI) that finds widespread application in many aspects of daily existence. The field of computer vision is dedicated to the development of advanced artificial intelligence and computer systems that aim to replace complex elements of the human environment. In recent times, deep neural networks have emerged as a crucial component in several sectors owing to their well-established capacity to process visual input. This study presents a methodology for classifying and identifying objects using the YOLOv4 object detection algorithm. Convolutional neural networks (CNNs) have shown exceptional efficacy in the tasks of object tracking and feature extraction from pictures. Therefore, the enhanced network architecture optimizes both the precision of identification and the speed at which it operates. This research will contribute to developing mixed-reality simulations system for object detection and tracking in collaborative environment that are accessible to everyone, including users in the architectural filed. The model was evaluated in comparison to other object detection approaches. Based on the empirical results, it was observed that the YOLOv4 model exhibited a mean average precision (mAP) of 0.988, surpassing the performance of both YOLOv3 and other object identification models

Examining Trajectories of Elementary Students’ Computational Thinking Development Through Collaborative Problem-Solving Process in a STEM-Integrated Robotics Program

Developing K-12 students’ computational thinking (CT) skills is essential. Building on the existing literature that has emphasized programming skill development, this study expands the focus to examine students’ use of underlying CT cognitive skills during collaborative problem-solving processes. A case study approach was employed to examine video data of 5th graders engaging in an integrated-STEM robotics curriculum. The findings reveal that students applied algorithmic thinking most frequently and prediction the least. They recorded most debugging behaviors initially in the problem-solving process, but after accumulating more experiences their uses of other CT skills, including algorithmic thinking, pattern recognition, and prediction, increased. Implications for developing young learners’ CT skills to solve real-world problems are discussed

An evaluation of the total quality management implementation strategy for the advanced solid rocket motor project at NASA's Marshall Space Flight Center

An evaluation of the NASA's Marshall Space Flight Center (MSFC) strategy to implement Total Quality Management (TQM) in the Advanced Solid Rocket Motor (ASRM) Project is presented. The evaluation of the implementation strategy reflected the Civil Service personnel perspective at the project level. The external and internal environments at MSFC were analyzed for their effects on the ASRM TQM strategy. Organizational forms, cultures, management systems, problem solving techniques, and training were assessed for their influence on the implementation strategy. The influence of ASRM's effort was assessed relative to its impact on mature projects as well as future projects at MSFC

Development of Workforce Skills: Student Perceptions of Mentoring in FIRST Robotics

In today’s global economy, new workforce competencies are needed for success at both individual and societal levels. The new workforce skills extend beyond basic reading, writing, and arithmetic to include higher order processes such as critical thinking and problem solving. Technical job opportunities have grown by approximately 17%, yet the United States continues to decline in science, technology, engineering and mathematics (STEM) disciplines. Further, U.S. students earn average or below average test scores when compared to other developed countries. Researchers cite the need to incorporate the learning of workplace skills into secondary education curriculum, and advocates call for new teaching methodology and contextual experiences to enhance learning. A popular and expanding method for teaching students is the use of technical mentors to develop workforce skills. Education studies demonstrate learning is a social activity, and mentors can play a vital role in understanding and learning skills. The FIRST Robotics program relies heavily on mentor expertise for student instruction. This study uses FIRST Robotics teams as a population to investigate student perception of the effectiveness of mentors on the development of workforce skills. Findings show students perceive mentors have a positive effect on the development of workforce skills, and, furthermore, students’ perceptions of mentors impact student learning

On the Relationship between People, Objects, & Interactive Technologies: Transforming Digital & Physical experiences through the process of Realizing Empathy

La manera com les persones es relacionen amb el seu entorn, ja sigui físic o digital, és cada cop més complexa i fugaç, fent que la relació de l'usuari amb els seus objectes i eines digitals, de vegades, sigui extrema i de curta durada. Tanmateix, la propietat d'objectes i objectes tecnològics interactius no és buida de significat, són mostres de reflexió i representació per als altres i del seu paper a la societat. La clau per mantenir una relació i el significat amb aquests objectes rau en el disseny i la intenció de l'experiència interactiva creada. Inspirats en les disciplines de la psicologia, el procés de disseny, la interacció humà-ordinador i els models de negoci, aquesta tesi explora, analitza, crea i prova els fonaments teòrics sobre l'empatia i el concepte d'entaular una relació de llarga durada entre les persones i les tecnologies interactives.  Amb aquesta finalitat, aquesta tesi es divideix en 4 fases: (1) l’estudi en profunditat de les referències bibliogràfiques dins del sector HCI, amb especial atenció al rol del disseny i la psicologia amb la intenció de respondre preguntes com: “Com podem construir relacions de llarga durada entre persones i objectes intel·ligents?” (2) Recopilar i adoptar definicions, eines i terminologia de treballs relacionats que aportin a la construcció de la contribució principal d'aquesta tesi, (3) Crear i presentar un model d'interacció entre persones i tecnologia que aporti a una interacció de llarga durada, i (4) presentar un cas d’estudi on s’implementi el model proposat.  Després del treball bibliogràfic, al sector de l'HCI, s'ha identificat un buit, fruit de les principals preocupacions expressades: la manca de connexió entre la teoria i la pràctica del disseny, així com una mancança en l’àmbit de l'Empatia. El resultat fa que molts dels models d’interacció amb intenció empàtica i afectiva no se sustentin entre si. Això ens ha portat a la segona fase de la tesi on aprofitem les referències de múltiples disciplines per estudiar què és l'empatia, com s'implementa, com es percep i com evoluciona cap a l'objectiu d'una relació a llarg termini, com a punt focal cap a les principals contribucions de la tesi. .  Després de reunir i analitzar exhaustivament les referències al voltant de l'empatia, entrem a la tercera fase on presentem el model teòric d'interacció amb el potencial d'establir una interacció a llarg termini i l’anomenat Procés de realització de l'empatia (RE). Més que intentar definir què és l'empatia, aquesta proposta intenta oferir una perspectiva diferent de l'empatia i visualitza el seu abast com un procés influenciat per models de diàleg i col·laboració amb el propòsit de crear comprensió mútua i donar significat a aquest intercanvi.  Amb un model clar i una sòlida base teòrica, la fase final de la tesi cerca provar el model proposat amb l'objectiu d'observar si es poden detectar indicadors d'afecció afectiva i confiança entre una persona i el seu objecte tecnològic. En aquest cas, vam tenir l'oportunitat de treballar amb robots socials com el nostre “altre actor” per dissenyar les proves del model. Aquestes proves pretenien capturar els indicadors d'empatia entre un humà i un robot que abraça: l'aferrament afectiu, la confiança, la regulació de les expectatives i la reflexió sobre la perspectiva de l'altre dins un conjunt d'estratègies de col·laboració. Plantegem la hipòtesi que una estratègia de col·laboració activa condueix a un compromís més significatiu de generar empatia entre un humà i un robot en comparació amb una estratègia passiva. Els resultats són encoratjadors i clarament estableixen un camí per a futures investigacions sobre el disseny d'aquest model. La forma en que las personas se relacionan con su entorno, ya sea físico o digital, se vuelve cada vez más compleja y fugaz, haciendo que la relación del usuario con sus objetos y herramientas digitales, en ocasiones, sea extrema y de corta duración. Sin embargo, la propiedad de objetos y objetos tecnológicos interactivos no es vacía de significado, son muestras de reflexión y representación para los demás y de su papel en la sociedad. La clave para mantener una relación y significado con estos objetos radica en el diseño y la intención de la experiencia interactiva creada. Inspirados en las disciplinas de la psicología, el proceso de diseño, la interacción humano-ordenador y los modelos de negocio, esta tesis explora, analiza, crea y prueba los fundamentos teóricos sobre la empatía y el concepto de entablar una relación de larga duración entre las personas y las tecnologías interactivas.  Con este fin, esta tesis se divide en 4 fases: (1) estudio en profundidad de las referencias bibliográficas dentro del sector HCI, con especial atención al rol del diseño y la psicología con la intención de responder a preguntas como: “¿Cómo podemos construir relaciones de larga duración entre personas y objetos inteligentes?”(2) Recopilar y adoptar definiciones, herramientas y terminología de trabajos relacionados que aporten a la construcción de la contribución principal de esta tesis, (3) Crear y presentar un modelo de interacción entre personas y tecnología que aporte a una interacción de larga duración, y (4) presentar un caso de estudio donde se implemente el modelo propuesto.  Tras el trabajo bibliográfico en el sector del HCI se ha identificado un vacío, fruto de las principales preocupaciones expresadas: la falta de conexión entre la teoría y la práctica del diseño, así como una falta en el tema de la Empatía. El resultado hace que muchos de los modelos de interacción con intención empática y afectiva no se sustenten entre sí. Esto nos ha llevado a la segunda fase de la tesis en la que aprovechamos las referencias de múltiples disciplinas para estudiar qué es la empatía, cómo se implementa, cómo se percibe y cómo evoluciona hacia el objetivo de una relación a largo plazo, como punto focal hacia las principales contribuciones de la tesis. .  Después de una reunir y analizar exhaustivamente las referencias en torno a la empatía, entramos en la tercera fase donde presentamos el modelo teórico de interacción con el potencial de entablar una interacción a largo plazo y denominado Proceso de realización de la empatía (RE). Más que intentar definir qué es la empatía, esta propuesta trata de ofrecer una perspectiva diferente a la empatía y visualiza su alcance como un proceso influenciado por modelos de diálogo y colaboración con el propósito de crear comprensión mutua y dar significado a ese intercambio.  Con un modelo claro y una sólida base teórica, la fase final de la tesis busca probar el modelo propuesto con el objetivo de observar si el modelo puede detectar indicadores de Apego Afectivo y Confianza entre una persona y su objeto tecnológico. En el caso de este trabajo, tuvimos la oportunidad de trabajar con robots sociales como nuestro “otro actor” para diseñar las pruebas del modelo. Estas pruebas pretendían capturar los indicadores de de empatía entre un humano y un robot que abarca: el apego afectivo, la confianza, la regulación de las expectativas y la reflexión sobre la perspectiva del otro dentro de un conjunto de estrategias de colaboración. Planteamos la hipótesis de que una estrategia de colaboración activa conduce a un compromiso más significativo de generar empatía entre un humano y un robot en comparación con una estrategia pasiva. Los resultados son alentadores y claramente establecen un camino para futuras investigaciones sobre el diseño de este modelo. How people engage with their surroundings, whether physical or digital, becomes increasingly complex and rapid, making the user’s relationship with their objects and digital tools, at times, extreme and short-lived. Yet, there is still meaning in ownership of objects and interactive technological objects, they are tokens of reflection and representation to others and their role in society. The key to sustaining a relationship and sense of meaning with these objects lies in the design and intention of the interactive experience created. Inspired by disciplines of psychology, design, Human-computer interaction, and business modeling, this thesis explored, analyzed, created, and tested theoretical foundations on Empathy and the concept of initiating a long-term relationship between people and their interactive technologies.  To that end, the thesis book was managed in 4 main stages: (1) presenting a deeper dive into bibliographic references within HCI and the role of both design and psychology in the attempt to tackle questions like: “How can we build long-term relationships between people and their smart objects?” (2) Collect and adopt from related works that helped build the main contributions of the thesis book, (3) Create an interaction model between humans and their technology that lent itself for potential long-term engagement, and (4) a case study that implemented and instantiated the model designed.     After mapping the HCI bibliographical works in the first phase, a gap was revealed indicative of the main concerns expressed: a lack of connection between theory and design practice as well as a lack in the topic of Empathy. The result makes many of the models of interaction with empathetic and affective intention unsupported between each other. This has led us to the second phase of the thesis where we leveraged references across multiple disciplines to survey what empathy is, how it is implemented, perceived and evolved toward the goal of long-term relationship, as a focal point toward the main thesis contributions.   After an exhaustive gathering and analysis of the work around Empathy, we entered the third phase where we present the proposed theoretical model of interaction with the potential for long-term engagement named the Process of Realizing Empathy (RE). Rather than attempting to further define empathy, this proposal is about offering a different perspective to empathy that visualizes its scope as a process influenced by dialogue and collaborative models with the goal to reach meaning between the actors involved.  With a clear model in place and a strong theoretical foundation, the final phase of the thesis looked to test the proposed model with the goal of observing if the model can provoke its indicators of Affective Attachment and Trust between a person and their technological object. In the case of this thesis work, we had the opportunity to work with social robots as our “other actor” to design the tests for the model. This testbed meant to capture the indicators of early empathy realization between a human and a robot encompassing affective attachment, trust, expectation regulation, and reflecting on the other’s perspective within a set of collaborative strategies. We hypothesized that an active collaboration strategy is conducive to a more meaningful and purposeful engagement of realizing empathy between a human and a robot compared to a passive one. The results are encouraging and clearly establish a path for further research on this model’s design.