In this paper we describe the development and evaluation of AITK, the Artificial Intelligence Toolkit. This open-source project contains both Python libraries and computational essays (Jupyter notebooks) that together are designed to allow a diverse audience with little or no background in AI to interact with a variety AI tools, exploring in more depth how they function, visualizing their outcomes, and gaining a better understanding of their ethical implications. These notebooks have been piloted at multiple institutions in a variety of humanities courses centered on the theme of responsible AI. In addition, we conducted usability testing of AITK. Our pilot studies and usability testing results indicate that AITK is easy to navigate and effective at helping diverse users gain a better understanding of AI and its ethical implications. Our goal, in this time of rapid innovations in AI, is for AITK to provide an accessible resource for faculty from any discipline looking to incorporate AI topics into their courses and for anyone eager to learn more about AI on their own.

This workshop is a hands-on exploration of Deep Learning techniques and topics for use in the classrooms of Computer Science and related fields. Deep Learning denotes the latest in a series of advances in neural network training algorithms and hardware that allow Artificial Neural Networks (ANNs) to learn quickly and effectively, even with many, stacked layers. These types of networks can be applied to almost any learning problem, such as driving a car, describing images, controlling a robot, or understanding language. This workshop will start with the mathematical and algorithmic foundations of Deep Learning, and introduce an accessible Python-based library, called "conx," which is based on the Keras library and was developed by the workshop instructors. The workshop will demonstrate ideas through animation and visualizations, examine the path to advanced topics, and explore ideas for incorporating Deep Learning topics into the classroom. The workshop is designed to allow participants to gain a foothold with these complex topics, and to help them develop their own materials for teaching. Workshop materials will be made freely available before the workshop as Jupyter notebooks.

The Calico project is a multi-language, multi-context programming framework and learning environment for computing education. This environment is designed to support several interoperable programming languages (including Python, Scheme, and a visual programming language), a variety of pedagogical contexts (including scientific visualization, robotics, and art), and an assortment of physical devices (including different educational robotics platforms and a variety of physical sensors). In addition, the environment is designed to support collaboration and modern, interactive learning. In this paper we describe the Calico project, its design and goals, our prototype system, and its current use.

The SIGCSE community has been exploring the role of multimedia to enhance computing education since the earliest algorithm visualization systems and studies [1]. Media Computation is a shift in focus [2]. Where algorithm visualization presents information to the student to facilitate their understanding, media computation is about having students manipulate media as the data for their programming, i.e., as the focus of the course activities. Students in media computation produce new images, sounds, and video. We aim to show that computer science is about more than numbers and strings. Computer science is also about creative expression. The original media computation work focused on using media to motivate non-computing majors [2]. The role of media in motivating student learning for computing education has broadened. Inventive teachers are using media computation for lots of different kinds of students, at different kinds of institutions, with a range of languages and toolkits. This special session is a mixture of "Five Minute Madness," science fair, and art gallery. Each participant will present how he or she is using media to motivate student learning, and some student work will be available for audience inspection

We describe myro.chuck, a Python module for controlling music synthesis, and its applications to teaching introductory computer science. The module was built within the Myro framework using the ChucK programming language, and was used in an introductory computer science course combining robots, graphics and music. The results supported the value of music in engaging students and broadening their view of computer science.

We have developed a CS1 curriculum that uses a robotics context to teach introductory programming [1]. Core to our approach is that each student has their own personal robot. Our robot and software have been specifically developed to support the needs of a CS1 curriculum. We frame traditional problems (robot control) in terms that are personal, relevant, and fun. Initial trial classes have shown that our approach is successful and adaptable.

Developmental robotics is a broad, new discipline that lies at the intersections of psychology, biology, artificial intelligence (AI) and robotics. This new field was inspired by the fact that most...

We propose an intrinsic developmental algorithm that is designed to allow a mobile robot to incrementally progress through levels of increasingly sophisticated behavior. We believe that the core ingredients for such a developmental algorithm are abstractions, anticipations, and self-motivations. We describe a multilevel, cascaded discovery and control architecture that includes these core ingredients. As a first step toward implementing the proposed architecture, we explore two novel mechanisms: a governor for automatically regulating the training of a neural network and a path-planning neural network driven by patterns of “mental states” that represent protogoals.

In this article we describe a programming framework called Pyro, which provides a set of abstractions that allows students to write platform-independent robot programs. This project is unique because of its focus on the pedagogical implications of teaching mobile robotics via a top-down approach. We describe the background of the project, its novel abstractions, its library of objects, and the many learning modules that have been created from which curricula for different types of courses can be drawn. Finally, we explore Pyro from the students' perspective in a case study.

Male and female students often hold different views of the culture within the same computer science department. These differences may, in part, account for why women are underrepresented in computer science. We found that surveying students about their views of our departments' environments was an important first step in evaluating the cultures of our own departments, in determining what issues needed to be addressed, and in determining how to address them. Our survey results revealed some problems in our classroom and lab environments, and showed that there are gender differences in students' perceptions of our departments. We describe a set of changes that were implemented in response to our findings. These solutions are specifically designed to address problems that we discovered through our student survey, but they are not all original to us. The contribution of our work is in demonstrating how surveying is critical to identifying and understanding problems in our departments. We argue that a process of continually surveying students is vital to the maintenance and evolution of a healthy computer science program.

This paper describes Pyro, a robotics programming environment designed to allow inexperienced undergraduates to explore topics in advanced robotics. Pyro, which stands for Python Robotics, runs on a number of advanced robotics platforms. In addition, programs in Pyro can abstract away low-level details such that individual programs can work unchanged across very different robotics hardware. Results of using Pyro in an undergraduate course are discussed.

In this article we describe a programming framework called Pyro, which provides a set of abstractions that allows students to write platform-independent robot programs. This project is unique because of its focus on the pedagogical implications of teaching mobile robotics via a top-down approach. We describe the background of the project, its novel abstractions, its library of objects, and the many learning modules that have been created from which curricula for different types of courses can be drawn. Finally, we explore Pyro from the students' perspective in a case study.