The Center for Integrated Quantum Materials pursues research and education in quantum science and technology. With our research and industry partners, the Museum of Science, Boston collaborates to produce public engagement resources, museum programs, special events and media. We also provide professional development in professional science communication for the Center's students, post-docs, and interns; and coaching in public engagement. The Museum also sponsors The Quantum Matters(TM) Science Communication Competition (www.mos.org/quantum-matters-competition) and NanoDays with a Quantum Leap. In association with CIQM and IBM Q, the Museum hosted the first U.S. museum exhibit on quantum computing.
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TEAM MEMBERS:
Robert WesterveltCarol Lynn AlpertRay AshooriTina Brower-Thomas
This Research Advanced by Interdisciplinary Science and Engineering (RAISE) project is supported by the Division of Research on Learning in the Education and Human Resources Directorate and by the Division of Computing and Communication Foundations in the Computer and Information Science and Engineering Directorate. This interdisciplinary project integrates historical insights from geometric design principles used to craft classical stringed instruments during the Renaissance era with modern insights drawn from computer science principles. The project applies abstract mathematical concepts toward the making and designing of furniture, buildings, paintings, and instruments through a specific example: the making and designing of classical stringed instruments. The research can help instrument makers employ customized software to facilitate a comparison of historical designs that draws on both geometrical proofs and evidence from art history. The project's impacts include the potential to shift in fundamental ways not only how makers think about design and the process of making but also how computer scientists use foundational concepts from programming languages to inform the representation of physical objects. Furthermore, this project develops an alternate teaching method to help students understand mathematics in creative ways and offers specific guidance to current luthiers in areas such as designing the physical structure of a stringed instrument to improve acoustical effect.
The project develops a domain-specific functional programming language based on straight-edge and compass constructions and applies it in three complementary directions. The first direction develops software tools (compilers) to inform the construction of classical stringed instruments based on geometric design principles applied during the Renaissance era. The second direction develops an analytical and computational understanding of the art history of these instruments and explores extensions to other maker domains. The third direction uses this domain-specific language to design an educational software tool. The tool uses a calculative and constructive method to teach Euclidean geometry at the pre-college level and complements the traditional algebraic, proof-based teaching method. The representation of instrument forms by high-level programming abstractions also facilitates their manufacture, with particular focus on the arching of the front and back carved plates --- of considerable acoustic significance --- through the use of computer numerically controlled (CNC) methods. The project's novelties include the domain-specific language itself, which is a programmable form of synthetic geometry, largely without numbers; its application within the contemporary process of violin making and in other maker domains; its use as a foundation for a computational art history, providing analytical insights into the evolution of classical stringed instrument design and its related material culture; and as a constructional, computational approach to teaching geometry.
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.
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
This pilot study will examine the effectiveness of an innovative applied social change, community and technology based program on marginalized youths' access, interest, efficacy and motivation to learn and engage in digital technology applications. Using stratified near-peer and peer-to-peer mentoring approaches, the pilot builds on extant literature that indicates that peer-supported hands-on mentoring and experiences can alleviate some barriers to youth engagement in digital technologies, particularly among underrepresented groups. In this project, undergraduate students will mentor and work collaboratively with high school youth primarily of Hispanic descent and community-based organizations to develop creative technology-based solutions to address social issues and challenges within their local communities, culminating in events called Impactathons. These community-hosted local and state-wide events set this pilot project apart from similar work in the field. The Impactathons not only provide a space for intellectual discourse and problem-solving among the undergraduate-youth-community partners but the Impactathons will also codify expertise from scientists, social scientists, technologists, community leaders, and other stakeholders to develop technology-based solutions with real world application. If successful, a distal outcome will be increased youth interest in digital technologies and related fields. In the short term, favorable findings will provide preliminary evidence of success and lay the foundation for a more extensive study in the future.
This pilot project is a collaboration between the Everett Program, a student-led program for Technology and Social Change at the University of California Santa Cruz - a Hispanic Serving Institution - and the Digital NEST, a non-profit, high-tech youth career development and collaboration space for young people ages 14-24. Through this partnership and other recruitment efforts, an estimated 70-90 individuals will participate in the Impactathon pilot program over two years. Nearly two-thirds of the participants are expected to be undergraduate students. They will receive extensive training in near-peer and peer-to-peer mentoring and serve as mentors for and co-innovation developers with the high school youth participants. The undergraduates and youth will partner with local community organizations to identify a local social challenge that can be addressed through a technology-based solution. The emergent challenges will vary and could span the spectrum of STEM and applied social science topics of interest. Working in informal contexts (i.e., afterschool. weekend), the undergraduate-youth-community partner teams will work collaboratively to develop practical technology-based solutions to real world challenges. The teams will convene three times per year, locally and statewide, at student and community led Impactathons to share their work and glean insights from other teams to refine their innovations. In parallel, the research team will examine the effectiveness of the Impactathon model in increasing the undergraduate and youths' interest, motivation, excitement, engagement and learning of digital technologies. In addition to the research, the formative and summative evaluations should provide valuable insights on the effectiveness of the model and its potential for expansion and replication.
The project is co-funded by the Advancing Informal STEM Learning (AISL) Program and STEM +C. The AISL program seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. STEM + C focuses on research and development of interdisciplinary and transdisciplinary approaches to the integration of computing within STEM teaching and learning for preK-12 students in both formal and informal settings.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative research, approaches and resources for use in a variety of settings. This AISL project investigates how informal programs can broaden participation by building social capital in STEM for youth from underrepresented groups. The project integrates social network analysis with research on informal learning, and draws on a framework to connect learning across a variety of sectors. It builds on evidence that sponsorship of youth interest, affinity-based mentorship, and brokering connections to other settings and opportunities can build social capital and support interest and persistence in STEM. It represents a strategic and timely investment into research that solidifies these emerging insights from research and practice, conducting focused investigation into relational supports for STEM interests that are particularly well suited to informal programs.
The project is guided by two research questions: (1) What forms of social capital are tied to persistence in and connecting across informal STEM programs for youth from underrepresented groups? (2) What program features--specifically sponsorship, mentorship, and brokering--grow these social supports for persistence in and connecting across informal STEM programs for underserved youth? These questions are addressed through a mixed methods 18-month cross-sectional study of 200 students in three informal programs in Orange County, California that offer project-based engineering and coding programs, support mentorship, and focus on groups underrepresented in STEM. The sample will include three age categories, capturing the transition to high school, persistence during high school, and transition to college and career. Teens will be interviewed three times at 6-month intervals, spanning these transitions. The goal of this research and effort is to determine if social capital plays an extra ordinary role in learning by this group.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
This project tackles the urgent needs of the nation to engage people of all ages in computational thinking and help them learn basic computer science concepts with a unique and innovative approach of structured in-game computer program coding. Researchers will explore the design and development of a 3D puzzle-based game, called May's Journey, in which players solve an environmental maze by using the game's pseudo code to manipulate game objects. The game is designed to teach introductory but foundational concepts of computer programming including abstraction, modularity, reusability, and debugging by focusing players on logic and concepts while asking them to type simple instructions in a simplified programming language designed for novices. The game design in this project differs from today's block-based programming learning approaches that are often too far from actual computer code, and also differs from professional programming languages which are too complex for novices. The game and its embedded programming language learning are designed to be responsive to the progress of the learner throughout the game, transitioning from pseudo code to the embedded programming language itself. Error messages for debugging are also designed to be adaptive to players' behavior in the game. Using extensive log data collected from people playing the game, researchers can study how people learn computer programming. Such knowledge can advance understanding of the learning processes in computer programming education. Additionally, this work emphasizes the use of games as informal learning environments as they are accessible and fun, drawing attention and retention of many learners of different age groups with the potential to change attitudes towards computer programming across different populations. This project is co-funded by the STEM + Computing (STEM+C) program that supports research and development to understand the integration of computing and computational thinking in STEM learning, and the Advancing Informal STEM Learning (AISL) program that funds innovative research, approaches and resources for use in a variety of settings with its overall strategy to enhance learning in informal environments.
The project's formative and summative evaluation methods, including surveys, expert reviews of learners' computer code developed in the game, and interviews, are used to gauge learners' engagement as well as learning. In exploring learning, researchers aim to understand how players build implicit computer science knowledge through gameplay and how that gameplay relates to their performance on external transfer tasks. The project will answer the following three research questions: (1) Can observers reliably detect and label patterns of gameplay that provide evidence of learning or misconceptions regarding the four computer science constructs - abstraction, modularity, debugging and semantics - that learners exhibit playing May's Journey? (2) How does learner's implicit knowledge of these computer science constructs change over time and do those patterns vary by gender and prior programming experiences? (3) Is there a strong correlation between implicit learning measures and transfer of CS concepts: modularity, debugging, semantics, and abstraction? How do these correlations vary across elements of the game? This work will result in several outcomes: game design metaphors tested for their learning and engagement value that can be abstracted and embedded in different games. This project will also contribute patterns and an understanding of how people learn and engage in problem solving using concepts of abstraction, modularity, debugging and semantics. These outcomes will lead to advancement in knowledge in the learning sciences as well as the design of educational games that enrich STEM learning, particularly in programming and computational thinking. In addition, this project will engage female participants and underserved populations through partnering organizations including National Girls Collaborative project.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative research, approaches, and resources for use in a variety of settings. This Pilots and Feasibility Studies project will design and study computer science education programs in three New York State prisons and cutting-edge computer science learning spaces in New York City and Bennington, VT for recently released men and women. These two sites of investment will be designed and operated with the goals of bridging informal STEM education inside the prison and post-release. The project aims to help incarcerated and formerly incarcerated men and women gain hands-on experience and technical fluency in computer science. The project will also help people build effective pathways that link training and informal learning communities in prison to professional and educational success after prison.
The research will examine how informal STEM learning can 1) provide incarcerated and post-incarceration populations more effective pathways into computer science and technology professions, and 2) help revitalize neighborhoods struggling with high rates of incarceration and high rates of adults under correctional supervision. Results will be shared among the STEM learning community and prison educators through existing networks, scholarly and journalistic publications, and conferences. As a pilot program, this project aims to develop a comprehensive, rigorous, and transferable model that may be used as a resource in other prison education programs as well as in rural and urban communities across the United States seeking to address economic and educational inequalities of post-incarceration life.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative research, approaches, and resources for use in a variety of settings. The pilot and feasibility study will develop instructional workshops for an adult population of quilters to introduce them to computational thinking. By leveraging pre-existing social structures, skill sets, and engagement in quilting, the researchers hope to help participants develop computer science and computational thinking knowledge and skills. The long-term goal is to broaden public awareness of computational thinking and build links between computer science and other areas of interest. By leveraging the social structure and existing skills held by practicing quilters, the workshops have the potential to reach an audience of millions of quilters around the nation and worldwide, the majority of whom are adult women. The research will be developed and tested with two groups: the Orlando Modern Quilt Guild in Orlando, FL, and an informally gathered quilting class in the Worcester, MA area. Outcomes for the project include workshop materials that can be used in a variety of quilting group contexts nationwide, a deeper understanding of the processes and mechanisms for adult computer science education through crafts, and evaluation of the pilot workshop focused on the impact on participants' engagement, self-identity, and learning for computational thinking. The research especially focuses on leveraging pre-existing knowledge, interests, and social structures to draw connections to computational thinking, and studying how this impacts participants' self-described identity, attitude, and engagement with computer science. The project also assesses a novel method for teaching computational thinking that has potential for broad applicability in a variety of social and creative hobbies. Participants will use and modify generative design software that creates quilt designs and, in doing so, learn how creative interests can be expanded through computer science. By focusing on the hobby of quilting, which is not typically associated with computer science, the knowledge built through designing and evaluating the research offers strategies for altering public perception of computer science. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
This Research in Service to Practice 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 project will research the educational impact of social robots in informal learning environments, with applications to how social robots can improve participation and engagement of middle-school girls in out-of-school computer science programs in under-resourced rural and urban areas. The use of robots to improve STEM outcomes has focused on having learners program robots as tools to accomplish tasks (e.g., play soccer). An alternate approach views robots as social actors that can respond intelligently to users. By designing a programmable robot with social characteristics, the project aims to create a culturally-responsive curriculum for Latina, African American, and Native American girls who have been excluded by approaches that separate technical skill and social interaction. The knowledge produced by this project related to the use and benefits of social programmable robots has the potential to impact the many after-school and weekend programs that attempt to engage learners in STEM ideas using programmable robot curricula.
The project robot, named Cozmo, will be programmed using a visual programming language and will convey emotion with facial expressions, sounds, and movements. Middle school girls will engage in programming activities, collaborative reflection, and interact with college women mentors trained to facilitate the course. The project will investigate whether the socially expressive Cozmo improves computer science outcomes such as attitudes, self-efficacy, and knowledge among the middle school female participants differently than the non-social version. The project will also investigate whether adding rapport-building dialogue to Cozmo enhances these outcomes (e.g., when a learner succeeds in getting Cozmo to move, Cozmo can celebrate, saying "I can move! You're amazing!"). These questions will be examined research conducted with participants in multi-session after-school courses facilitated by Girl Scout troops in Arizona. The project will disseminate project research and resources widely by sharing research findings in educational and learning science journals; creating a website with open source code for programming social robots; and making project curriculum and related guidelines available to Girl Scouts and other educational programs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Cities and communities in the U.S. and around the world are entering a new era of transformational change, in which their inhabitants and the surrounding built and natural environments are increasingly connected by smart technologies, leading to new opportunities for innovation, improved services, and enhanced quality of life. The Smart and Connected Communities (SCC) program supports strongly interdisciplinary, integrative research and research capacity-building activities that will improve understanding of smart and connected communities and lead to discoveries that enable sustainable change to enhance community functioning. This project is a Research Coordination Network (RCN) that focuses on achieving SCC for medium/small size, remote, and rural communities through a polycentric (multiple centers) integrated policy, design, and technology approach. The communities served by the RCN have higher barriers to information, resources, and services than larger urban communities. To reduce this gap, the PIs propose to develop need-based R&D pipelines to select solutions with the highest potential impacts to the communities. Instead of trying to connect under-connected communities to nearby large cities, this proposal aims to develop economic opportunities within the communities themselves. This topic aligns well with the vision of the SCC program, and the proposed RCN consists of a diverse group of researchers, communities, industry, government, and non-profit partners.
This award will support the development of an RCN within the Commonwealth of Virginia which will coordinate multiple partners in developing innovations utilizing smart and connected technologies. The goal of the research coordination network is to enable researchers and citizens to collaborate on research supporting enhanced quality of life for medium, small, and rural communities which frequently lack the communication and other infrastructure available in cities. The research coordination network will be led by the University of Virginia. There are 14 partner organizations including six research center partners in transportation, environment, architecture and urban planning, and engineering and technology; two State and Industry partners (Virginia Municipal League and Virginia Center for Innovative Technology); four community partners representing health services (UVA Center for Telemedicine), small and remote communities (Weldon Cooper Center), neighborhood communities (Charlottesville Neighborhood Development), and urban communities (Thriving Cities); and two national partners which support high speed networking (US-Ignite) and city-university hubs (MetroLab). Examples of research coordination include telemedicine services, transportation services, and user-centric and community-centric utilization and deployment of sensor technologies.
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TEAM MEMBERS:
Ila BermanT. Donna ChenKaren RheubanQian Cai
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.
Becoming computationally literate is increasingly crucial to everyday life and to expanding workforce capacity. Research suggests that computational literacy--knowing what, when, how, and why to use the ideas of computer science, in combination with the capacity to view problems and potential solutions through the lens of computational structures and procedures--can be supported through digital game play. This project aims to develop a social and creative exhibit game that foregrounds aspects of computer science, specifically artificial intelligence (AI) and computer programming, in ways that enable youth to explore, construct, and share computational complex systems content with one another and other museum visitors. To play the game, pairs of youth visitors will use code cards to program the behavior of AI animals in a virtual forest. As they do so, youth will engage with computational literacy practices, such as basic computer programming, describing their computational ideas, and doing computational problem solving with their friends. Their activity will be projected on a large screen as a strategy for enabling youth to test, rehearse, and communicate their computational ideas and to also interest other visitors into computational problem solving.
Using multi-perspective and iterative design-based research, university learning scientists, museum practitioners, and game developers will pursue research questions around how science museums can better engage youth who are traditionally underrepresented in computer science in complex computational practices. Data sources will include interactive-log data, observations of visitor interactions with the game, visitor interviews, and visitor surveys. A multimodal and mixed methods approach that searches for convergences between qualitative analysis, quantitative analysis, and learning analytics will be used to generate research findings. Changes in computational literacy will be assessed by evaluating what problems visitors choose to solve with programming, how they frame those problems, and their selections from among possible solutions, what they program, how they program, and how they describe programming ideas. The results of this project will include: 1) a social, interactive gameplay experience that supports the development of computational literacy; 2) design principles for game-based exhibits that facilitate development of computational literacy; and 3) new knowledge of variations in design and gameplay across diverse gameplay users, including those from underrepresented groups in computer science. It is anticipated that 1,000 museum youth visitors will directly participate in the study.
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.
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TEAM MEMBERS:
Matthew BerlandLeilah LyonsMatthew Cannady