This paper presents a study using a robotics platform for teaching computing and cybersecurity concepts to high school students. 38 students attended a week-long camp, starting with projects such as a simulation-only game and a simple autonomous driving program for the robots in order to learn and apply computational thinking (CT) and networking skills. They were then assigned a series of challenges that required developing progressively more advanced cybersecurity measures to protect their robots. This culminated in a final challenge that required implementing defensive measures such as encryption, secure key exchange and sequence numbers. We used an evidence-centered design framework to construct rubrics for grading student work. The pre- and post-test results show that the interventions helped students learn cybersecurity and CT concepts, but they had difficulties with networking concepts. These results correlate with scores from the game and the final challenge. Overall, surveys show that the competition-based robotics learning framework engaged students and supported their overall learning, but our intervention needs to be modified to help students learn networking concepts

Robots are a popular and engaging educational tool for teaching computational thinking, but they often have significant costs and limitations for classroom use. Switching to a simulated environment can eliminate many of these difficulties. By also providing students with a block-based programming environment, the barrier to entry can be further reduced. This paper presents a networked virtual robotics platform designed to create an environment which is highly accessible for novice students and their teachers alike, along with components of a curriculum designed to teach computational thinking skills through robotics programming challenges, including autonomous challenges and in-class competitions. Students access this platform through an extension of the same web interface used for programming their robots, which allows students to collaborate on code and view a shared simulated virtual space. Previously, this virtual robotics platform was used only to facilitate distance education. This paper demonstrates its use in an in-person class during the Spring 2022 semester, illustrating the affordances of a virtual robotics environment for face-to-face learning contexts as well. Students' computational thinking skills were evaluated with assessments both before and after the class, along with surveys and interviews given to determine their opinions and outlooks regarding computer science. The results show that students had a significant improvement in both attitudes and aptitudes.

Despite its potential for STEM education, educational robotics remains out of reach for many classrooms due to upfront purchase costs, maintenance requirements, storage space, and numerous other barriers to entry. As demonstrated previously, these physical robot limitations can be reduced or eliminated through simulation. This work presents a new version of RoboScape Online, a browser-based networked educational robotics simulation platform that aims to make robotics education more accessible while expanding both the breadth and depth of topics taught. Through cloud-hosted simulations, this platform enables distant students to collaborate and compete in real-time. Integration with NetsBlox, a block-based programming environment, allows students at any level to participate in computer science activities. By incorporating a virtual machine for running NetsBlox code into the server, RoboScape Online enables scenarios to be built using the same syntax and abstractions used to program the robots. This approach enables more creative curriculum activities while proving that block-based programming is a valuable development tool, not just a “toy language”. Classroom case studies demonstrate RoboScape Online’s potential to improve students’ computational thinking skills and foster positive attitudes toward STEM subjects, with especially significant improvements in attitudes toward self-expression and creativity within the realm of computer science.

This work presents an overview of a new system to provide motion tracking and mixed reality integration of robots for use in K12 STEM education. The robots, commanded by students through a block-based programming environment, are placed in a virtual environment visible as an overlay on the physical space. The system’s control loop allows the robots to interact with virtual objects as if they are physically present within easily reconfigurable environments. This virtual space allows for lower cost robots to be used by incorporating virtual sensors and actuators, and creates the potential for a wider range of scenarios for students to work with.

In this paper, the problem of clustering intelligent web using K-means algorithm has been analyzed and the need for a new data clustering algorithm such as Genetic Algorithm (GA) is justified. We propose an Intelligent Extended Clustering Genetic Algorithm (IECGA) using Business Process Execution Language (BPEL) to be an optimal solution for data clustering. It improves the efficiency and performance for retrieving a proper information results that satisfy user's needs. The proposed IECGA uses several mutation operators simultaneously to produce next generation. This series of random mutation process depend on chromosome best fitness in the population and rely on high relevancy as well. The mutation operation will guarantee the success of IECGA for data clustering since it expands the search. So the highly effective mutation operators the greater effects on the genetic process. Finally, IECGA for data clustering gives the user needed documents based on similarity between query matching and relevant document mechanism. The results obtained from the web intelligent search engine are optimal.