With the rise of Artificial Intelligence (AI) systems in society, our children have routine interactions with these technologies. It has become increasingly important for them to understand how these technologies are trained, what their limitations are and how they work. To introduce children to AI and Machine Learning (ML) concepts, recent efforts introduce tools that integrate ML concepts with physical computing and robotics. However, some of these tools cannot be easily integrated into building projects and the high price of robotics kits can be a limiting factor to many schools. We address these limitations by offering a low-cost hardware and software toolkit that we call the Smart Motor to introduce supervised machine learning to elementary school students. Our Smart Motor uses the nearest neighbor algorithm and utilizes visualizations to highlight the underlying decision-making of the model. We conducted a one week long study using Smart Motors with 9- to 12- year old students and measured their learning through observation, questioning and examining what they built. We found that students were able to integrate the Smart Motors into their building projects but some students struggled with understanding how the underlying model functioned. In this paper we discuss these findings and insights for future directions for the Smart Motor.

Urban air pollution has been linked to various human health concerns, including cardiopulmonary diseases. Communities who suffer from poor air quality often rely on experts to identify pollution sources due to the lack of accessible tools. Taking this into account, we developedSmell Pittsburgh, a system that enables community members to report odors and track where these odors are frequently concentrated. All smell report data are publicly accessible online. These reports are also sent to the local health department and visualized on a map along with air quality data from monitoring stations. This visualization provides a comprehensive overview of the local pollution landscape. Additionally, with these reports and air quality data, we developed a model to predict upcoming smell events and send push notifications to inform communities. We also applied regression analysis to identify statistically significant effects of push notifications on user engagement. Our evaluation of this system demonstrates that engaging residents in documenting their experiences with pollution odors can help identify local air pollution patterns and can empower communities to advocate for better air quality. All citizen-contributed smell data are publicly accessible and can be downloaded fromhttps://smellpgh.org.

Urban air pollution has been linked to various human health considerations, including cardiopulmonary diseases. Communities who suffer from poor air quality often rely on experts to identify pollution sources due to the lack of accessible tools. Taking this into account, we developed Smell Pittsburgh, a system that enables community members to report odors and track where these odors are frequently concentrated. All smell report data are publicly accessible online. These reports are also sent to the local health department and visualized on a map along with air quality data from monitoring stations. This visualization provides a comprehensive overview of the local pollution landscape. Additionally, with these reports and air quality data, we developed a model to predict upcoming smell events and send push notifications to inform communities. Our evaluation of this system demonstrates that engaging residents in documenting their experiences with pollution odors can help identify local air pollution patterns, and can empower communities to advocate for better air quality.

Developing information technology to democratize scientific knowledge and support citizen empowerment is a challenging task. In our case, a local community suffered from air pollution caused by industrial activity. The residents lacked the technological fluency to gather and curate diverse scientific data to advocate for regulatory change. We collaborated with the community in developing an air quality monitoring system which integrated heterogeneous data over a large spatial and temporal scale. The system afforded strong scientific evidence by using animated smoke images, air quality data, crowdsourced smell reports, and wind data. In our evaluation, we report patterns of sharing smoke images among stakeholders. Our survey study shows that the scientific knowledge provided by the system encourages agonistic discussions with regulators, empowers the community to support policy making, and rebalances the power relationship between stakeholders.

Robotics activities allow students to gain confidence in their abilities to use technology creatively, express themselves, and solve problems of interest. However, many traditional robotics elective programs suffer from self-selection and reach only a subset of students. Arts & Bots is a middle school robotics program which integrates robotics into non-technology classes to engage a more diverse population of students. In this paper, we present the collected student outcomes from our program evaluation study which ran from 2013 until 2017. During this time, Arts & Bots was implemented by 24 teachers in 66 classes, reaching 727 middle school students. Program evaluation data included pre- and post-surveys, daily reflection sheets, project presentation videos, and classroom observations. Between pre- and post-tests, we recorded better student understanding of what engineering careers entail, and found that female students caught up to their male peers in their understanding. Our analysis also shows pre/post improvement in student technical knowledge. Quantitative survey results are complemented by our coding and analysis of qualitative student short answers. We found that female students were significantly more likely than male peers to mention increases in confidence on the post-survey. This paper concludes with a discussion of trends in the evaluation results.

This paper describes the development of Flutter, a new sensor-driven, robotics technology kit for in-school use with elementary-age students. Our development began by conducting focus groups with teachers (N=6) in which we guided a participatory design process. Through affinity diagramming, we identified science and math as areas of focus for the program; we also brainstormed project-topics with the teachers. The Flutter Kit is controlled by an app that allows for touch based interactions and enables the kits to be programmable by tablets. The app interface, developed with teachers through the use of paper and digital prototypes, builds on the concept of data flow from an input to an output and emphasizes the use of sensor data for creating interactive devices. The central element of the Flutter hardware is a custom microcontroller board that connects to the tablet app via bluetooth; permits students to log sensor data; and controls a buzzer, three sensor ports, three tricolor LEDs, and three servo ports. From observations of four pilot classes (N=84) and student interviews, we generated ideas for future improvements to the system, such as: hardware changes for ease of use and changes to the curriculum to support students' data analysis skills.

In this paper we describe our process for synthesizing frameworks for recognizing student talents in the areas of Computational Thinking (CT) and Engineering Design (ED) from prior research. Computer science education research has resulted in multiple, overlapping definitions of CT as an approach towards solving problems using methods and tools that are derived from computer science. Our development of operationalized definitions of CT talent for middle school educators is focused on uniting models for CT in a simplified structure. Our ED definition framework builds on multiple distinct models of the engineering design process along with concepts from systems engineering models and the design thinking process. We operationalize these frameworks to provide teachers with metrics and examples for recognizing and assessing the CT and ED skills of their students in non-technical classes. By training teachers to evaluate students' processes from the perspective of an engineer and computer scientist, teachers are more able to help their STEM-inclined students recognize the alignments between their own talents and possible careers. Through the analysis of teacher surveys and interviews from 19 classroom implementations, we evaluated the changes that the Arts & Bots program has had on teacher perceptions of student CT and ED skills and talents.

The next generation of world citizens must be technologically fluent members of society. By technological fluency we mean the ability to manipulate technology creatively and for one's own use. This fluency is composed of knowledge and skills utilizing materials and tools, as well as attitudes, (e.g. confidence), with respect to technology. Numerous interventions exist to support middle school students' technological fluency, and robotics activities are popular. It is critical that instruments assessing student attitudes towards robotics are available for the development and evaluation of these interventions. We present an instrument for assessing middle school students' technological fluency attitudes specifically tailored for robotics activities. Survey subscales were developed from existing science motivation research, and individual measurement items were generated and adapted within those subscales. The robotics activity attitudes scale (RAAS) was revised through three rounds of pilot testing in 2010, 2012 and 2015. The final RAAS in 2015 consisted of 50 items with an overall Cronbach's alpha of .972 (N=236) organized in four dimensions of Curiosity, Interest, Expectancy Value, and Confidence and Identity.

The Arts & Bots Math and Science Partnership program integrates creative technological fluency projects as transdisciplinary activities into non-technical courses, creating a pathway for students of all abilities and areas of interests to engage with engineering and computing. The Professional Development provided by the program prepares teachers from traditional disciplines, such as English, History or Science, to integrate robotics projects into disciplinary classrooms, and aims to promote teacher skill, confidence, and self-efficacy in the design and classroom implementation of robotics design projects. The Arts & Bots project has developed and piloted a new program for in-service secondary school teachers. To date, we have trained 38 teachers from a variety of disciplines to implement Arts & Bots robotics design projects in their classrooms. Teacher training integrates experience with robotics kit components, a programming interface, the engineering design process, and recognition of student affinities towards engineering and computer science. We present the development model for our teacher training program as well as preliminary positive results regarding teacher practice and self-efficacy. Data includes teacher surveys, interviews, and class observations. Teacher training has developed over the course of several years, and we discuss how teacher experiences have shaped the development of the program to its current form.

When engineering and computing activities are solely electives, extra curriculars, or informal learning activities, student participation is limited by self-selection. By integrating technological projects into required coursework, all students gain exposure. The Arts & Bots Math and Science Partnership integrates creative robotics into middle school classes such as English and history as transdisciplinary, creative robotics projects. We discuss two case studies of such projects, describing how teachers developed projects through sequential implementations; and how project instruction focuses on developing student technological fluency, collaboration, and understanding of class content. One case study describes the integration of Arts & Bots into 7th and 8th grade English Language Arts in which students build robotic sculptures that represent a poem or scene in a play. The second case study describes a 7th grade Health and Physical Education project in which students build models of human joints and limbs in order to understand muscle pairs. We discuss differences, themes, and best practices for integration of creative robotics into non-technical classes through a comparison of projects implemented to date. The case studies are supplemented by data from student (N=195) and teacher (N=6) evaluations.

Arts & Bots combines intrinsically creative craft materials, common robotics components, a custom programming environment and teacher professional development to create a flexible robotics intervention for secondary school classrooms. In order to engage students underserved by other robotics programs, Arts & Bots is oriented to support the creation of collaborative expression-focused robots, as opposed to more commonly implemented competitive task-focused robot activities. Specifically, Arts & Bots targets integration into traditional nontechnical classes, such as literature and history, to reach a broader base of students than would be enrolled in elective technology programs. This paper describes three classroom implementations, including a secondary school poetry project. By including Arts & Bots in these core courses, we expose diverse students to engineering education activities such as hands-on experiences with computer programming, prototyping, and the engineering design process. We present our outcomes grouped within two primary themes: first, in Technological Fluency, we present students' self-reporting of concepts learned, confidence with technology, and breaking of technology stereotypes; second, in Complementary Non-Technical Skills, we present other skills students learned by participating in the Arts & Bots program.

Arts & Bots is an educational program that aims to broaden diversity and participation in technology by integrating arts and crafts with robotics. Arts & Bots is a flexible program that can be integrated into in-school and out-of-school programs in many subject areas. This paper describes the visual programming environment developed for Arts & Bots and its goals of low barriers to entry, classroom compatibility, supporting student acquisition of computational thinking skills, and enabling complex robot behaviors. The authors also compare and contrast the programming environment with other popular visual programming environments, namely Scratch, Alice and LEGO NXT-G.