This paper contributes a theoretical framework informed by historical, philosophical and ethnographic studies of science practice to argue that data should be considered to be actively produced, rather than passively collected. We further argue that traditional school science laboratory investigations misconstrue the nature of data and overly constrain student agency in their production. We use our “Data Production” framework to analyze activity of and interviews with high school students who created data using sensors and software in a ninth-grade integrated science class. To understand the
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.
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.