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.
Maker Education scholarship is accumulating increasingly complex understandings of the kinds of learning associated with maker practices along with principles and pedagogies that support such learning. However, even as large investments are being made to spread maker education, there is little understanding of how organizations that are intended targets of such investments learn to develop new maker related educational programs. Using the framework of Expansive Learning, focusing on organizational learning processes resulting in new and unfolding forms of activity, this paper begins to fill
We found that the learners seeking out resources to teach themselves to code were generally college educated women who were motived either by the desire to be able to read and understand the code written by hired developers or the desire to become developers themselves. The importance of a female-focused learning setting was mixed; while most women acknowledged a more comfortable atmosphere created by such a setting, very few cited that as a primary reason for joining the group.
All learner participants in this study persisted through the ten weeks of the Women’s Coaching and Learning
In 2016, ETR received a National Science Foundation grant to study, under Principal Investigator Louise Ann (“Lou Ann”) Lyon, PhD, a newly formed, real-world organization dedicated to helping women in the workforce learn to write computer code. This project formed a partnership between a research team with experience in computer science (CS) education and learning sciences research and a newly fashioned practitioner team focused on building a grassroots, informal, volunteer group created to help women help themselves and others learn to write computer code. This research-practitioner
Participants in this study reported a variety of resources used in the past to learn to code in Apex, including online tutorials, one-day classes sponsored by Salesforce, and meet-up groups focused on learning. They reported various difficulties in learning through these resources, including what they viewed as the gendered nature of classes where the men already seemed to know how to code—which set a fast pace for the class, difficulty in knowing “where to start” in their learning, and a lack of time to practice learning due to work and family responsibilities. The Coaching and Learning Group
Participants in this study reported a variety of resources used in the past to learn to code in Apex, including online tutorials, one-day classes sponsored by Salesforce, and meet-up groups focused on learning. They reported various difficulties in learning through these resources, including what they viewed as the gendered nature of classes where the men already seemed to know how to code—which set a fast pace for the class, difficulty in knowing “where to start” in their learning, and a lack of time to practice learning due to work and family responsibilities. The Coaching and Learning Group
Participants in this study reported a variety of resources used in the past to learn to code in Apex, including online tutorials, one-day classes sponsored by Salesforce, and meet-up groups focused on learning. They reported various difficulties in learning through these resources, including what they viewed as the gendered nature of classes where the men already seemed to know how to code—which set a fast pace for the class, difficulty in knowing “where to start” in their learning, and a lack of time to practice learning due to work and family responsibilities. The Coaching and Learning Group
Grassroots women's learn-to-code groups are springing up in many places. This infographic a study of one such group, in which more-knowledgeable "coaches" lead novice "learners" in learning software programming on the Salesforce platform. This study found that women create such groups to have supportive, non-threatening environments that nuture their learning to build confidence before entering male-dominated software development communities.
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 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. This project is a two-day conference, along with pre- and post-conference activities, with the goal of furthering the informal science learning field's review of the research and development that has been conducted on data visualizations that have been used to help the public better understand and become more engaged in science. The project will address an urgent need in informal science education, providing a critical first step towards a synthesis of research and technology development in visualization and, thus, to inform and accelerate work in the field in this significant and rapidly changing domain.
The project will start with a Delphi study by the project evaluator prior to the conference to provide an Emerging Field Assessment on data visualization work to date. Then, a two-day conference at the Exploratorium in San Francisco and related activities will bring together AISL-funded PIs, computer scientists, cognitive scientists, designers, and technology developers to (a) synthesize work to date, (b) bring in relevant research from fields outside of informal learning, and (c) identify remaining knowledge gaps for further research and development. The project team will also develop a website with videos of all presentations, conference documentation, resources, and links to social media communities; and a post-conference publication mapping the state of the field, key findings, and promising technologies.
The initiative also has a goal to broaden participation, as the attendees will include a diverse cadre of professionals in the field who contribute to data visualization work.
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.
The goal of FLIP (Diversifying Future Leadership in the Professoriate), an NSF INCLUDES Design and Development Launch Pilot, is to address the broadening participation challenge of increasing the diversity of the future leadership in the professoriate in computing at research universities as a way to achieve diversity across the field. According to the 2016 CRA Taulbee Survey, only 4.3% of the tenure-track faculty at PhD-granting universities are from underrepresented minorities. This challenge is important to address because diverse faculty contributes to academia in the following critical ways: serve as excellent role models for a diverse study body, bring diverse backgrounds to the student programs and policies developed by the department, and bring diverse perspectives to the research projects and programs. Further, the focus is on research universities, because in practice, key national leadership roles, such as serving on national committees that impact thefield of computing, often come from research universities.
The shared purpose and broad vision of the FLIP launch pilot is to increase faculty diversity in computing at research universities by increasing the diversity of PhD graduates from the top producers of computing faculty. The focus is on four underrepresented groups in computing: African Americans; Hispanics; Native Americans and indigenous peoples; and Persons with Disabilities. The long-term goal is to pursue this vision through strategic partnerships with those institutions that are the top producers of computing faculty and organizations that focus on diverse students in STEM, as well as partnerships that collectively adopt proven strategies for recruiting, graduating, and preparing a diverse set of doctoral students for academic careers. The purpose of the pilot is to establish a unified approach across the different partners that will build upon proven strategies to develop novel practices for increasing the diversity of the PhD graduates from key institutions, thereby increasing the faculty diversity in computing at research universities. For the pilot, FLIP will focus on recruitment and admissions and professional development for current PhD students.
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TEAM MEMBERS:
Valerie TaylorCharles IsbellJeffrey ForbesUniversity of Chicago
resourceprojectProfessional Development, Conferences, and Networks
Aligning for Impact: Computer Science Pathways Across Contexts [CS-PAC] is an NSF INCLUDES Design and Development Launch Pilot. It broadens participation of students who are underrepresented in computer science by using the convening and policy-making power of the Georgia State Department of Education to coalesce school district leaders to implement K-12 computer science education. The project provides a national model for how to work toward systemic change. With the State Department of Education's coordination, several school districts will collaboratively seek improvements in their own student participation rates. The coordination of data reporting and analysis, resources, communications, and policy promote more equitable participation in computer science education. Research emerging from this project informs other states about how to collaboratively shape computer science education policy and policy implementation.
Using a Collective Impact approach to systemic change, the project creates sustainable institutional change at the community, state, and national levels. Qualitative and quantitative data provide descriptions about how to utilize alignment strategies within Collective Impact in three different contexts: rural, suburban, and urban. Outcomes utilize a regression discontinuity analysis to justify successful implementation as well as qualitative analysis of implementation efforts that were deemed most effective by all stakeholders. The project outputs directly affect over 88,000 students across five districts and indirectly affect over 1.7 million in Georgia alone. The culminating project goal is the development of a coherent framework for aligning K-12 computer science education pathways.