This poster was presented at the 2021 NSF AISL Awardee Meeting.
Collaborative robots – cobots – are designed to work with humans, not replace them. What learning affordances are created in educational games when learners program robots to assist them in a game instead of being the game? What game designs work best?
Research that seeks to understand classroom interactions often relies on video recordings of classrooms so that researchers can document and analyze what teachers and students are doing in the learning environment. When studies are large scale, this analysis is challenging in part because it is time-consuming to review and code large quantities of video. For example, hundreds of hours of videotaped interaction between students working in an after-school program for advancing computational thinking and engineering learning for Latino/a students. This project is exploring the use of computer-assisted methods for video analysis to support manual coding by researchers. The project is adapting procedures used for computer-aided diagnosis systems for medical systems. The computer-assisted process creates summaries that can then be used by researchers to identify critical events and to describe patterns of activities in the classroom such as students talking to each other or writing during a small group project. Creating the summaries requires analyzing video for facial recognition, motion, color and object identification. The project will investigate what parts of student participation and teaching can be analyzed using computer-assisted video analysis. This project is supported by NSF's EHR Core Research (ECR) program, the STEM+C program and the AISL program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. The project is funded by the STEM+Computing program, which seeks to address emerging challenges in computational STEM areas through the applied integration of computational thinking and computing activities within disciplinary STEM teaching and learning in early childhood education through high school (preK-12). As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants.
The video analysis systems will provide video summarizations for specific activities which will allow researchers to use these results to quantify student participation and document teaching practices that support student learning. This will support the analysis of large volumes of video data that are often time-consuming to analyze. The video analysis system will identify objects in the scene and then use measures of distances between objects and other tracking methods to code different activities (e.g., typing, talking, interaction between the student and a facilitator). The two groups of research questions are as follows. (1) How can human review of digital videos benefit from computer-assisted video analysis methods? Which aspects of video summarization (e.g., detected activities) can help reduce the time it takes to review the videos? Beyond audio analytics, what types of future research in video summarization can help reduce the time that it takes to review videos? (2) How can we quantify student participation using computer-assisted video analysis methods? What aspects of student participation can be accurately measures by computer-assisted video analysis methods? The video to be used for this study is drawn from a project focused on engineering and computational thinking learning for Latino/a students in an after-school setting. Hundreds of hours of video are available to be reviewed and analyzed to design and refine the system. The resulting coding will also help document patterns of engagement in the learning environment.
This project is funded by the National Science Foundation's (NSF's) Advancing Informal STEM Learning (AISL) program, which supports innovative research, approaches, and resources for use in a variety of learning settings.
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TEAM MEMBERS:
Marios PattichisSylvia Celedon-PattichisCarlos LopezLeiva
Robots and robotics excite and challenge youths and adults. Unfortunately, the cost of purchasing robots or building useful robots is prohibitive for many low resource individuals and groups. This project will relieve this expense and provide an opportunity for resource limited individuals to experience the thrilling aspects of robotics by building a computer game that simulates robotic action. This project uses co-robotics wherein the participating player programs an avatar to assist in a symbiotic manner to achieve the goals of the game and participant. The game will provide access to the ideas and concepts such as programing, computational thinking and role assumption. The overarching goals are (1) to engage low-resource learners in STEM education through robotics in out-of-school spaces, and (2) to update the field of robotics-base STEM education to integrate the co-robotics paradigm.
This project is designed to gain knowledge on how co-robotics can be used in the informal education sector to facilitate the integration of computational science with STEM topics and to expand the educational use of co-robotics. Because the concept of co-robotics is new, a designed-based research approach will be used to build theoretical knowledge and knowledge of effective interventions for helping participants learn programing and computational thinking. Data will be collected from several sources including surveys, self-reports, in game surveys, pre and post-tests. These data collection efforts will address the following areas: Technology reliability, Resolution of cognitive tension around co-play, Accelerate discovery and initial engagement, Foster role-taking and interdependence with co-robots, Investigate social learning, and Validate measures using item response theory analysis. The DBR study questions are:
1.What design principles support the development of P3Gs that can effectively attract initial engagement in a free-choice OST space that offers large numbers of competing options? 2.What design principles support a P3G gameplay loop that enables learning of complex skills, computational thinking and co-robotics norms, and building of individual and career interest over the course of repeated engagement?
3.What design principles support P3Gs in attaining a high rate of re-engagement within low-resource OST settings? 4.What kinds of positive impact can P3Gs have on their proximal and distal environment? In addition, the project will research these questions about design: 1.What technical and game design features are needed to accommodate technological interruption? 2.What design elements or principles mitigate competition for cognitive resources between real-time play and understanding the co-robotic's behavior in relation to the code the player wrote for it? 3.What design elements are effective at getting learners in OST settings to notice and start playing the game? 4.What designs are effective at encouraging learners to engage with challenging content, particularly the transition from manual play to co-play? 5.What design elements help players develop a stake in the role the game offers? 6.What social behaviors emerge organically around a P3G prototype that is not designed to evoke specific social interactions?
This project is funded by the National Science Foundation's (NSF's) Advancing Informal STEM Learning (AISL) program, which supports innovative research, approaches, and resources for use in a variety of learning settings.
The goal of this three-year project is to leverage NSF’s investment in both SciGirls and computer science education by engaging 8-13 year-old girls in computational thinking and coding through innovative transmedia programming which inspires and prepares them for future computer science studies and careers.
As the maker movement is increasingly adopted into K-12 schools, students are developing new competences in exploration and fabrication technologies. This study assesses learning with these technologies in K-12 makerspaces and FabLabs.
Our study describes the iterative process of developing an assessment instrument for this new technological literacy, the Exploration and Fabrication Technologies Instrument, and presents findings from implementations at five schools in three countries. Our index is generalizable and psychometrically sound, and permits comparison between student confidence
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TEAM MEMBERS:
Paulo BliksteinZaza KabayadondoAndrew P. MartinDeborah A. Fields
This project, an NSF INCLUDES Design and Development Launch Pilot, managed by the University of Nevada, Reno, addresses the grand challenge of increasing underrepresentation regionally in the advanced manufacturing sector. Using the state's Learn and Earn Program Advanced Career Pathway (LEAP) as the foundation, science, technology, engineering and mathematics (STEM) activities will support and prepare Hispanic students for the region's workforce in advanced manufacturing which includes partnerships with Truckee Meadows Community College (TMCC), the state's Governor's Office of Economic Development, Charles River Laboratories, Nevada Established Program to Stimulate Competitive Research (Nevada EPSCoR) and the K-12 community.
The expected outcomes from the project will inform the feasibility, expandability and transferability of the LEAP framework in diversifying the state's workforce locally and the STEM workforce nationally. Formative and summative evaluation will be conducted with a well-matched comparison group. Dissemination of project results will be disseminated through the Association for Public Land-Grant Universities (APLU), STEM conferences and scholarly journals.
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TEAM MEMBERS:
David ShintaniJulie EllsworthKarsten HeiseRobert StachlewitzRegina Tempel
Women continue to be underrepresented in computer science professions. In 2015, while 57% of professional occupations in the U.S. were held by women, only 25% of computing occupations were held by women. Furthermore, the share of computer science degrees going to women is smaller than any STEM field, even though technology careers are the most promising in terms of salaries and future growth. Research suggests that issues contributing to this lack of computer science participation begin early and involve complex social and environmental factors, including girls' perception that they do not belong in computer science classes or careers. Computer science instruction often alienates girls with irrelevant curriculum; non-collaborative pedagogies; a lack of opportunities to take risks or make mistakes; and a heavy reliance on lecture instead of hands-on, project-based learning. Computer science experiences that employ research-based gender equitable best practices, particularly role modeling, can help diminish the gender gap in participation. In response to this challenge, Twin Cities PBS (TPT), the National Girls Collaborative (NGC) and Code.org will lead Code: SciGirls! Media for Engaging Girls in Computing Pathways, a three-year project designed to engage 8-13 year-old girls in coding through transmedia programming which inspires and prepares them for future computer science studies and career paths. The project includes five new PBS SciGirls episodes featuring girls and female coding professionals using coding to solve real problems; a new interactive PBSKids.org game that allows children to develop coding skills; nationwide outreach programming, including professional development for informal educators and female coding professionals to facilitate activities for girls and families in diverse STEM learning environments; a research study that will advance understanding of how the transmedia components build girls' motivation to pursue additional coding experiences; and a third-party summative evaluation.
Code: SciGirls! will foster greater awareness of and engagement in computer science studies and career paths for girls. The PBS SciGirls episodes will feature girls and female computer science professionals using coding to solve real-world challenges. The project's transmedia component will leverage the television content into the online space in which much of 21st century learning takes place. The new interactive PBSKids.org game will use a narrative framework to help children develop coding skills. Drawing on narrative transportation theory and character identification theory, TPT will commission two exploratory knowledge-building studies to investigate: To what extent and how do the narrative formats of the Code: SciGirls! online media affect girls' interest, beliefs, and behavioral intent towards coding and code-related careers? The studies aim to advance understanding of how media builds girls' motivation to pursue computer science experiences, a skill set critical to building tomorrow's workforce. The project team will also raise educators' awareness about the importance of gender equitable computer science instruction, and empower them with best practices to welcome, prepare and retain girls in coding. The Code: SciGirls! Activity Guide will provide educators with a relevant resource for engaging aspiring computer scientists. The new media and guide will also reside on PBSLearningMedia.org, reaching 1.2 million teachers, and will be shared with thousands of educators across the SciGirls CONNECT and National Girls Collaborative networks. The new episodes are anticipated to reach 92% of U.S. TV households via PBS, and the game at PBSKids.org will introduce millions of children to coding. The summative evaluation will examine the reach and impact of the episodes, game and new activities. PIs will share research findings and project resources at national conferences and will submit to relevant publications. This project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants.
The FIRST Longitudinal Study is a multi-year longitudinal study assessing the impacts of FIRST’s afterschool robotics programs on the STEM related interests and educational and career trajectories of program participants. FIRST is one of the nation’s largest after-school robotics programs, serving more than 460,000 youth aged 6-18 annually through the FIRST LEGO League (Ages 7-14), the FIRST Tech Challenge (grades 7-12) and the FIRST Robotics Competition (grades 9-12). The study is tracking over 1200 program participants and comparison students, using a quasi-experimental design, over a
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TEAM MEMBERS:
Alan MelchiorCathy BurackMatthew HooverJill Marcus
Increasingly, the prosperity, innovation and security of individuals and communities depend on a big data literate society. Yet conspicuously absent from the big data revolution is the field of teaching and learning. The revolution in big data must match a complementary revolution in a new kind of literacy, through a significant infusion of STEM education with the kinds of skills that the revolution in 21st century data-driven science demands. This project represents a concerted effort to determine what it means to be a big data literate citizen, information worker, researcher, or policymaker; to identify the quality of learning resources and programs to improve big data literacy; and to chart a path forward that will bridge big data practice with big data learning, education and career readiness.
Through a process of inquiry research and capacity-building, New York Hall of Science will bring together experts from member institutions of the Northeast Big Data Innovation Hub to galvanize big data communities of practice around education, identify and articulate the nature and quality of extant big data education resources and draft a set of big data literacy principles. The results of this planning process will be a planning document for a Big Data Literacy Spoke that will form an initiative to develop frameworks, strategies and scope and sequence to advance lifelong big data literacy for grades P-20 and across learning settings; and devise, implement, and evaluate programs, curricula and interventions to improve big data literacy for all. The planning document will articulate the findings of the inquiry research and evaluation to provide a practical tool to inform and cultivate other initiatives in data literacy both within the Northeast Big Data Innovation Hub and beyond.
This project, a collaboration of teams at Georgia Institute of Technology, Northwestern University, and the Museum of Design Atlanta and the Museum of Science and Industry in Chicago, will investigate how to foster engagement and broadening participation in computing by audiences in museums and other informal learning environments that can transfer to at-home and in-school engagement (and vice versa). The project seeks to address the national need to make major strides in developing computing literacy as a core 21st century STEM skill. The project will adapt and expand to new venues their current work on their EarSketch system which connects computer programming concepts to music remixing, i.e. the manipulation of musical samples, beats and effects. The initiative involves a four-year process of iteratively designing and developing a tangible programming environment based on the EarSketch learning environment. The team will develop three new applications: TuneTable, a multi-user tabletop exhibit for museums; TunePad, a smaller version for use at home and in schools; and an online connection between the earlier EarSketch program and the two new devices.
The goal is to: a) engage museum learners in collaborative, playful programming experiences that create music; b) direct museum learners to further learning and computational music experiences online with the EarSketch learning environment; c) attract EarSketch learners from local area schools to visit the museum and interact with novice TuneTable users, either as mentors in museum workshops or museum guests; and d) inform the development of a smaller scale, affordable tangible-based experience that could be used at homes or in smaller educational settings, such as classrooms and community centers. In addition to the development of new learning experiences, the project will test the hypothesis that creative, playful, and social engagement in the arts with computer programming across multiple settings (e.g. museums, homes, and classrooms) can encourage: a) deeper learner involvement in computer programming, b) social connections to other learners, c) positive attitudes towards computing, and d) the use and recognition of computational concepts for personal expression in music. The project's knowledge-building efforts include research on four major questions related to the goals and evaluation processes conducted by SageFox on the fidelity of implementation, impact, success of the exhibits, and success of bridging contexts. Methods will draw on the Active Prolonged Engagement approach (unobtrusive observation, interviews, tracking-and-timing, data summaries and team debriefs) as well as Participatory Action Research methods.
This work is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments.
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TEAM MEMBERS:
Michael HornBrian MagerkoJason Freeman
This document contains the appendices and literature review from the report "Art+Science: Broadening Youth Participation in STEM Learning." It includes assessment tools used during the project.
The purposes of the STUDIO 3D evaluation were to collect information about the impact upon student learning as a result of participating in the STUDIO 3D Project, as well as to elicit information for program improvement. Areas of inquiry include recruiting and retention, impact on project participants, tracking student impacts, and the project as a whole.