1,720,984 research outputs found
Control Systems Engineering and Robotics Education Since Primary School
No full textControl engineering and robotics hold significant potential to support the development of valuable skills that allow the comprehension and analysis of the current real-world problems. Unfortunately, usually, education on control engineering does not start before undergraduate courses. This paper reviews some of the current experiences whose aim is to introduce control engineering education in K12 education. Subsequently, it presents a whole curriculum based on Educational Robotics that could be integrated into primary school curricula to face control engineering education. One of the key aspects in the creation of such curriculum is the co-creation of the educational curriculum with teachers and education experts. Notably, empowering teachers is essential to effectively convey the fundamental concepts of control theory, enhancing students' problem-solving and critical thinking skills in the domain of control engineering
Correction to: Inert gas narcosis in scuba diving, different gases different reactions (European Journal of Applied Physiology, (2019), 119, 1, (247-255), 10.1007/s00421-018-4020-y)
No full textThe original version of this article unfortunately contained a mistake. Collaborator (Scaradozzi D) name was incorrect in the Acknowledgements section. The correct information is given below. Acknowledgements ROAD Project Investigators include: Scaradozzi D, Gala F, Screpanti L, Argentario Diving, Nicolini S, Mesa S
Correction to: Implementation and Assessment Methodologies of Teachers’ Training Courses for STEM Activities (Technology, Knowledge and Learning, (2019), 24, 2, (247-268), 10.1007/s10758-018-9356-1)
No full textThe article listed above was initially published with incorrect copyright information. Upon publication of this Correction, the copyright of this article has been changed to “The Author(s)”. The original article has been corrected
Designing Courses in Modeling and Identification of Dynamic Systems for Real-Time Assessment
No full textIn undergraduate engineering education, particularly in the area of control systems, it is vital for students to gain knowledge on the identification of linear systems. Undergraduate students need to be equipped with both theoretical understanding and practical skills in this field. The key to achieving this goal is creating an effective course design that maximizes student learning outcomes by promoting active learning and integrating diverse instructional strategies and resources. In response to this educational requirement, the present work aims at describing the design of an undergraduate course on the modeling and identification of dynamic systems based on a blended learning approach. Thanks to the course design, the traditional educational experience allows for additional practice exercises and laboratory experiments exploiting the virtual learning environment. Moreover, the integration of the online environment also enables the personalization of learning by means of automated formative and summative assessments of student learning. Initial findings from the course implementation underscore the efficacy of the blended learning approach in eliciting student engagement, offering promising implications for educational practices and pedagogical strategies
Machine learning for modelling and identification of educational robotics activities
No full textEducational Robotics (ER) is a powerful tool to help students learn school subjects, robotics, and developing cognitive skills and soft skills. Assessing the learning outcomes of ER activities requires the identification of the model that underly the process. Machine learning can be useful to identify such models and to interpret data. This paper aims to present a system that could help integrating Educational Data Mining and Learning Analytics techniques into the open-ended learning environment that characterizes the constructionist approach of ER. Both supervised and unsupervised learning methods could be applied to extract meaningful information. Students' approaches to learning as well as a prediction of their final performance could inform teachers' decision and facilitate the implementation of effective ER activities in formal and non-formal education. First results show good premises for a future broader implementation, but more research is needed to face all the open issues
A digital twin infrastructure for designing an underwater survey with a professional DPV
No full textThis paper presents a digital twin infrastructure developed to study and test the buoyancy set-up of a diver propulsion vehicle (DPV) with and without payloads prior to the underwater survey. In order to obtain the final software simulator, MATLAB/Simulink (for physical and mathematical models) was connected with Unity (for robot and environment visualization and navigation). A user interface is also presented to simulate the model directly and guide the user in adding objects to the DPV and in running the code to recalculate the fundamental parameters of the model. The system was verified and validated through case studies designed to test the behavior of the virtual DPV
Robotics in the Context of Primary and Preschool Education: A Scoping Review
Full text linkThis article presents an overview of educational robotics (ER) in primary and preschool education. As ER seems to be gaining popularity for its effectiveness as a learning tool, more research needs to be done in this area. Recent results from ER pilot projects advocate for the integration of ER in K-12 education curricula. On the other hand, teachers may face various difficulties in carrying out such activities due to lack of experience or knowledge in this field. Previous research has shown that ER is still an open field for exploration. Even though an increasing number of experiences are available for the use of robotic tools in early education, there is not enough empirical evidence on the features they need to present for young learners to perceive them as attractive and easy to use. In addition, the high cost of some tools may prevent educational institutions from using them systematically. To detect possible gaps in the current research, in the context of this work, 21 articles representing ER applications and frameworks were collected and reviewed between 2011 and 2021. The results of this study demonstrate that ER can be a valuable tool for supporting primary and preschool students. However, the review supports that more research is needed on the technical features that a robotic tool must have to be successfully introduced to students of this age. Moreover, future work is needed to develop low-cost ER tools so they can become more accessible to educational institutions
Identification and Assessment of Educational Experiences: Utilizing Data Mining with Robotics
No full textThis article describes an example of data mining techniques applied to an open educational environment. These novel assessment methods in the educational robotics (ER) field provide empirical evidence of problem-solving styles behind the key tasks of proposed activities within real operative scenarios. A supervised, mixed machine learning (ML) approach was applied to data from seven Italian secondary schools (197 students), and four ML techniques [logistic regression (LR), support vector machine (SVM), k-nearest neighbors (KNN), and random forest (RF)] were explored to predict students' success
Analysis of Educational Robotics Activities Using a Machine Learning Approach
No full textThis paper presents the preliminary results of using machine learning techniques to analyze educational robotics activities. An experiment was conducted with 197 secondary school students in Italy: the authors updated Lego Mindstorms EV3 programming blocks to record log files with coding sequences students had designed in teams. The activities were part of a preliminary robotics exercise. We used four machine learning techniques—logistic regression, support-vector machine (SVM), K-nearest neighbors and random forests—to predict the students’ performance, comparing a supervised approach (using twelve indicators extracted from the log files as input for the algorithms) and a mixed approach (applying a k-means algorithm to calculate the machine learning features). The results showed that the mixed approach with SVM outperformed the other techniques, and that three predominant learning styles emerged from the data mining analysis
Identification of the Students Learning Process During Education Robotics Activities
Full text linkThis paper presents the design of an assessment process and its outcomes to investigate the impact of Educational Robotics activities on students' learning. Through data analytics techniques, the authors will explore the activities' output from a pedagogical and quantitative point of view. Sensors are utilized in the context of an Educational Robotics activity to obtain a more effective robot–environment interaction. Pupils work on specific exercises to make their robot smarter and to carry out more complex and inspirational projects: the integration of sensors on a robotic prototype is crucial, and learners have to comprehend how to use them. In the presented study, the potential of Educational Data Mining is used to investigate how a group of primary and secondary school students, using visual programming (Lego Mindstorms EV3 Education software), design programming sequences while they are solving an exercise related to an ultrasonic sensor mounted on their robotic artifact. For this purpose, a tracking system has been designed so that every programming attempt performed by students' teams is registered on a log file and stored in an SD card installed in the Lego Mindstorms EV3 brick. These log files are then analyzed using machine learning techniques (k-means clustering) in order to extract different patterns in the creation of the sequences and extract various problem-solving pathways performed by students. The difference between problem-solving pathways with respect to an indicator of early achievement is studied
- …
