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Animal-borne acoustic sensors provide valuable insights into wildlife behavior and environments but face significant power and storage constraints that limit deployment duration. We present a novel adaptive acoustic monitoring system designed for long-term, real-time observation of wildlife. Our approach combines low-power hardware, configurable firmware, and an unsupervised machine learning algorithm that intelligently filters acoustic data to prioritize novel or rare sounds while reducing redundant storage. The system employs a variational autoencoder to project audio features into a low-dimensional space, followed by adaptive clustering to identify events of interest. Simulation results demonstrate the system’s ability to normalize the collection of acoustic events across varying abundance levels, with rare events retained at rates of 80–85% while frequent sounds are reduced to 3–10% retention. Initial field deployments on caribou, African elephants, and bighorn sheep show promising application across diverse species and ecological contexts. Power consumption analysis indicates the need for additional optimization to achieve multi-month deployments. This technology enables the creation of novel wilderness datasets while addressing the limitations of traditional static acoustic monitoring approaches, offering new possibilities for wildlife research, ecosystem monitoring, and conservation efforts. 

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. 

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. 

Distributed computing, computer networking, and the Internet of Things (IoT) are all around us, yet only computer science and engineering majors learn the technologies that enable our modern lives. This paper introduces PhoneIoT, a mobile app that makes it possible to teach some of the basic concepts of distributed computation and networked sensing to novices. PhoneIoT turns mobile phones and tablets into IoT devices and makes it possible to create highly engaging projects through NetsBlox, an open-source block-based programming environment focused on teaching distributed computing at the high school level. PhoneIoT lets NetsBlox programs—running in the browser on the student’s computer—access available sensors. Since phones have touchscreens, PhoneIoT also allows building a Graphical User Interface (GUI) remotely from NetsBlox, which can be set to trigger custom code written by the student via NetsBlox’s message system. This approach enables students to create quite advanced distributed projects, such as turning their phone into a game controller or tracking their exercise on top of an interactive Google Maps background with just a few blocks of code. 

Historically, female students have shown low interest in the field of computer science. Previous computer science curricula have failed to address the lack of female-centered computer science activities, such as socially relevant and real-life applications. Our new summer camp curriculum introduces the topics of artificial intelligence (AI), machine learning (ML) and other real-world subjects to engage high school girls in computing by connecting lessons to relevant and cutting edge technologies. Topics range from social media bots, sentiment of natural language in different media, and the role of AI in criminal justice, and focus on programming activities in the NetsBlox and Python programming languages. Summer camp teachers were prepared in a week-long pedagogy and peer-teaching centered professional development program where they concurrently learned and practiced teaching the curriculum to one another. Then, pairs of teachers led students in learning through hands-on AI and ML activities in a half-day, two-week summer camp. In this paper, we discuss the curriculum development and implementation, as well as survey feedback from both teachers and students. 

The Computer Science Frontiers (CSF) project introduces teachers to the topics of artificial intelligence and distributed computing to engage their female students in computing by connecting lessons to relevant cutting edge technologies. Application topics include social media and news articles, as well as climate change, the arts (movies, music, and museum collections), and public health/medicine. CSF educators are prepared in a pedagogy and peer-teaching centered professional development program where they simultaneously learn and teach distributed computing, artificial intelligence, and internet of things lessons to each other. These professional developments allow educators to hone in on their teaching skills of these new topics and gain confidence in their ability to teach new computer science materials before running several activities with their students in the academic year classroom. In this workshop, teachers participating in the CS Frontiers professional development will give testimonials discussing their experiences teaching these topics in a two week summer camp. Attendees will then try out three computing activities, one from each Computer Science Frontiers module. Finally, there will be a question and answer session. 

The AP Computer Science Principles (CSP) high school course introduces students to computer science and programming. What should motivated students study after successful completion of AP CSP? The AP CSA class teaches Java programming and it has traditionally not attracted students from underrepresented groups. We are working on an alternative, projects-based course that will teach cutting edge CS concepts, such as distributed computing, computer networking, cybersecurity, the internet of things and machine learning, in a hands-on, accessible manner. Such an approach enables students to work on problems that interest them making computing more relevant and the curriculum more engaging. We utilize NetsBlox, a collaborative, block-based programming environment that extends Snap! with a few carefully selected abstractions that open up the vast array of resources freely available on the internet for student programs. Moreover, the tool enables students to work together on the same project remotely similarly to how Google Docs operate. This demonstration will introduce the environment and highlight its utility in creating distributed applications such as a shared whiteboard app and projects that access public domain scientific data sources and visualize them in various ways using online services such as Google Maps or charting. More information is available at https://netsblox.org. 

The paper introduces DeepForge, a gateway to deep learning for scientific computing. DeepForge provides an easy to use, yet powerful visual/textual interface to facilitate the rapid development of deep learning models by novices as well as experts. Utilizing a cloud-based infrastructure, built-in version control, and multiuser collaboration support, DeepForge promotes reproducibility and ease of access and enables remote execution of machine learning pipelines. The tool currently supports TensorFlow/Keras, but its extensible architecture enables easy integration of additional platforms. 

C2STEM is a web-based learning environment founded on a novel paradigm that combines block-structured, visual programming with the concept of domain specific modeling languages (DSMLs) to promote the synergistic learning of discipline-specific and computational thinking (CT) concepts and practices. Our design-based, collaborative learning environment aims to provide students in K-12 classrooms with immersive experiences in CT through computational modeling in realistic scenarios (e.g., building models of scientific phenomena). The goal is to increase student engagement and include inclusive opportunities for developing key computational skills needed for the 21st century workforce. Research implementations that include a semester-long high school physics classroom study have demonstrated the effectiveness of our approach in supporting synergistic learning of STEM and CS/CT concepts and practices, especially when compared to a traditional classroom approach. This technology demonstration will showcase our CS+X (X = physics, marine biology, or earth science) learning environment and associated curricula. Participants can engage in our design process and learn how to develop curricular modules that cover STEM and CS/CT concepts and practices. Our work is supported by an NSF STEM+C grant and involves a multi-institutional team comprising Vanderbilt University, SRI International, Looking Glass Ventures, Stanford University, Salem State University, and ETR. More information, including example computational modeling tasks, can be found at C2STEM.org.