The purpose of this paper is to explore results from a qualitative study of how high school aged BLV youth used spatial language during a virtual engineering experience administered by the National Federation of the Blind (NFB). Findings from this study can provide recommendations to enhance language in curricula that better reflects BLV students' content and may ultimately encourage more BLV students to pursue careers in STEM fields.
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TEAM MEMBERS:
Gary TimkoNatalie ShaheenWade GoodridgeTheresa GreenDaniel Kane
This paper describes the development and preliminary validation of a new spatial ability instrument that is designed to be accessible non-visually. Although additional work is needed to finalize the test, preliminary analysis indicates that the test has high reliability and validity.
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TEAM MEMBERS:
Sarah LopezWade GoodridgeIsaac GouglerDaniel KaneNatalie Shaheen
This paper seeks to illustrate the first steps in a process of adapting an existing, valid, and reliable spatial ability instrument – the Mental Cutting Test (MCT) – to assess spatial ability among blind and low vision (BLV) populations. To adapt the instrument, the team is developing three-dimensional (3-D) models of existing MCT questions such that a BLV population may perceive the test tactilely with their hands.
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TEAM MEMBERS:
Tyler AshbyWade GoodridgeBJ CallSarah LopezNatalie Shaheen
resourceresearchProfessional Development, Conferences, and Networks
"Conectando Saberes" united experts and learners from diverse backgrounds to explore the current landscape, amplify voices, and identify priorities for equity and transformation in STEM learning among Latiné youth and families.
The conference will convene library leaders, climate researchers and educators, public health experts, and informal educators to examine the current prevalence of climate related programming in libraries, and how the concept of environmental health can be used by libraries to create locally and culturally relevant, change oriented, and equitable STEM (science, technology, engineering, and math) learning experiences.
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TEAM MEMBERS:
Anne HollandNoah LenstraSteph HarmonPaul Dusenbery
resourceprojectProfessional Development, Conferences, and Networks
The conference will provide a critical opportunity for enhancing knowledge around innovation in these areas and sharing lessons learned with and advancing collaboration. The focus will be on collective impact, rural empowerment, and successful rural STEM programs.
An adapted three-dimensional model of place attachment is proposed as a theoretical framework from which place-based citizen science experiences and outcomes might be empirically examined in depth.
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TEAM MEMBERS:
Julia ParrishYurong HeBenjamin Haywood
The Green Bank Observatory organized a community workshop on research experiences for high school students in disciplines supported by NSF’s Directorate for Mathematical and Physical Sciences (MPS). The workshop was intended as a forum for sharing, gathering community input, and illuminating best practices in providing research experiences to high school students and organizing such research activities across universities, labs, and observatories. The input gathered from the workshop may be useful to others wanting to support K-12 research activities.
It is often stated that solving the global challenges presented by the 21st century requires a United States workforce with training in STEM fields, and that the STEM workforce may be insufficient to fill that need. Education research literature in STEM suggests that engaging students early and often in authentic research experiences enhances STEM identity, STEM self-efficacy, and STEM career interest: three personal attributes that are linked to entry into and persistence on a STEM career pathway. Much of this literature is focused on college students, however. This workshop convened people and organizations who have designed and implemented research experiences for high school students, and who will examine the role such experiences can play in the development of a student’s interest and STEM identity.
Data science is ever-present in modern life. The need to learn with and about data science is becoming increasingly important in a world where the quantity of data is constantly growing, where one’s own data are often being harvested and marketed, where data science career opportunities are rapidly increasing, and where understanding statistics, data sources, and data representation is integral to understanding STEM and the world around us. Museums have the opportunity to play a critical role in introducing the public to data science concepts in ways that center personal relevance, social connections and collaborative learning. However, data science and statistics are difficult concepts to distill and provide meaningful engagement with during the brief learning experiences typical to science museums. This Pilot and Feasibility study brings together data scientists, data science educators, and museum exhibit designers to consider these questions:
What are the important data science concepts for the public to explore and understand in museum exhibits?
How can museum exhibits be designed to support visitors with diverse backgrounds and experiences to engage with these data science concepts?
What principles can shape these designs to promote broadening participation in data science specifically and STEM more broadly?
This Pilot and Feasibility project combines multidisciplinary expert convening, feasibility testing, and early exploratory prototyping around the focal topic of data science exhibits. Project partners, TERC, the Museum of Science, Boston, and The Tech Interactive in San Jose will engage in an iterative process to develop a theoretical grounding and practical guidance for museum practitioners. The project will include two convenings, bringing together teams of experts from the fields of data science, data science education and museum exhibit design. Prior to the first convening, an initial literature summary and a survey of convening participants will be conducted, culminating in a preliminary list of big ideas about data science. Periodically, participants will have the opportunity to rank, annotate and expand this list, as a form of ongoing data collection. During the convenings, participants will explore the preliminary list, share related work from the three disciplines, engage with related data science activities in small groups, and work together to build consensus around promising data science topics and approaches for exhibits. Participant evaluation will allow for iterative improvement of the convenings and the capture of missed points or overlooked topics. After each convening, museum partners will create prototypes that respond to the convening conversations. Prototypes will be pilot tested (evaluated) with an intentionally recruited group of families that includes both frequent visitors and those who are less likely to visit the museum; diversity in terms of race, languages and dis/ability will be reflected in selection. Pilot data collection will consist of structured observations and interviews. Results from the first round of prototyping will be shared with convening participants as a way to modify the list of big ideas and to further interrogate the feasibility of communicating these ideas in an exhibit format. Results from the convenings and from both rounds of prototyping will be combined in a guiding document that will be shared on all three partner websites, and more broadly with the informal STEM learning field. The team will also host a workshop for practitioners interested in designing data science exhibits, and present at a conference focused on museum exhibits and their design.
The New York Hall of Science (NYSCI) will convene a two-day participatory design conference of to identify research and education opportunities in informal settings for supporting literacy concerning Artificial Intelligence (AI), especially for diverse and underserved youth whose communities are impacted by the bias in some AI processes. AI uses computer systems that simulate human intelligence. AI systems impact nearly every aspect of daily living, performing tasks underlying navigation apps, facial recognition, e-payments, and social media. AI can perpetuate inequities and biased outcomes in the culture at large. The conference will explore how to promote engagement and conceptual learning among youth about how AI works and what skills are needed to critically use and apply AI. The conference will also explore ways to support the interests of diverse and underserved children and youth in shaping AI and joining the growing STEM workforce that will use AI in their professions.
The conference will identify key features and needs with respect to AI literacy and explore the specific roles that informal learning can play in advancing AI literacy for youth in diverse and underserved communities. Participants in the conference will include designers, learning scientists, researchers, informal and formal educators, and science center professionals. Attendees will work in separate teams and as a group to explore and critique existing AI tools and learning frameworks, discuss lessons learned from promising AI literacy programs, and identify design principles and future directions for research. Specific attention will be paid to informal mechanisms of engagement, promising networks, and research-practice partnerships that take advantage of the unique affordances of informal learning and community services to accelerate AI literacy for historically excluded youth. The insights gained from this work will result in a set of research and programmatic priorities for informal institutions to promote AI literacy in culturally responsive ways. The resulting published guide and community events will broadly disseminate priorities and design principles generated by this convening to help informal learning institutions and community learning organizations identify both assets and priorities for addressing diversity, equity, access, and inclusion issues related to AI literacy.
This project's goal is to advance the field by providing resources that empower STEM educators to design and deliver high-quality connected learning experiences based on relevant research and incorporating evidence-based practices.
This poster was presented at the 2021 NSF AISL Awardee Meeting.
This project will host a workshop in order to identify and synthesize research findings from NSF awards that addressed the unanticipated effects of the COVID-19 pandemic on STEM teaching and learning. The interruptions from the pandemic had dramatic, widespread effects in education. Across the nation, teachers, students, parents, staff, and school administrators experienced extended school closures and a rapid and unexpected shift to virtual instruction. Although long-term consequences are unknown, early observations revealed deeper disparities in access and opportunity for many students of color. These inequities extend beyond STEM education and include challenges to student’s mental health and wellbeing. In spring 2020, NSF invited researchers to submit educational research proposals in response to this national crisis. Each award has its own dissemination and plans for broader impacts, yet the public is underserved by separate reports published in many different venues. To enable stakeholders to find and discern the most important insights, our research team will aggregate and organize major findings across these projects via a workshop, synthesize key findings, identify unresolved issues, and communicate overall insights to broader audiences.
To synthesize findings, Digital Promise will organize and convene a workshop with NSF awardees who conducted research on the educational impacts of the pandemic. Workshop attendees will participate in answering four questions: (1) What are the major themes and topics across the different NSF awards? (2) How were imperatives to address emerging inequities related to STEM education addressed in research plans and findings? (3) Within each topic or theme, what are the major findings, insights and recommendations for teaching and learning in STEM? (4) Across awardees, what was learned about doing RAPID research during a pandemic, and what are recommendations for improvement when subsequent needs for RAPID research in education arise? Data sources for the synthesis will be collected from project artifacts (e.g., reports, journal articles, practitioner resources, etc.), pre/post-workshop surveys, and workshop outputs from workshop presentations, panel discussions, and small group discussions. Interviews with a subset of workshop attendees will provide insight into what was learned about conducting research during a global pandemic. Data will be codified, categorized, and coded using established qualitative methods. Digital Promise’s broad network of partners and collaborators will achieve broad dissemination and outreach to education stakeholders at both the K-12 and postsecondary levels. This project is jointly funded by the Advancing Informal STEM Learning (AISL) program, the Discovery Research PreK-12 program (DRK-12) program, the EHR Core Research (ECR:Core) program, and the Innovative Technology Experiences for Students and Teachers (ITEST) program.