This award takes an innovative approach to an ongoing, pervasive, and persistent societal issue: women are still drastically underrepresented in computing careers. This project targets middle school-aged girls because it is a time when many of them lose interest and confidence in pursuing technical education and computing careers. This project will design, develop, and deploy a one-week experience focused on middle school girls that targets this issue with a novel combination of teaching techniques and technology. The project will use wearable computing devices to support girls' social interactions as they learn computing and solve technical challenges together. The goals of the project are to raise interest, perceived competence, and involvement in the computational ability of girls. Additionally, the project aims to increase a sense of computational community for girls that makes pursuing computational skills more relevant to their identities and lives, and that helps continued participation in computing. The project will deploy a one-week experience four times per year with a socioeconomically diverse range of campers. The project will also develop a 'program in a box' kit that can be broadly used by others wishing to deliver a similar experience for girls.
The planned research will determine if a one-week experience that uses social wearable construction in the context of live-action role play can use the mediating process of computational community formation to positively impact middle school girls' engagement with and interest in computation. Computational community is defined as girls engaging together in the process of learning computation, trading resources and knowledge, and supporting growth. Research participants will include 100 6th to 9th-grade girls. At least 75% of the participants will be either low income, first-generation college-bound, or underrepresented in higher education. Students will be recruited through the longstanding partnerships with title one schools in the Salinas Valley, the Educational Partnership Center, and in the Pajaro Valley Unified School district, where 82% of the students are Hispanic/Latinx, 42% are English Learners, and 73% are eligible for free or reduced lunch. The research questions are: 1) Does the proposed experience increase girls' self-reported competence, self-efficacy, and interest in computational skills and careers? and 2) Will the proposed experience lead to activity-based evidence of learning and integration of computational skills at the group social level? The project will use a mixed-methods, design-based research approach which is an iterative design process to rapidly collect and analyze data, and regularly discuss the implications for practice with the design team. Data will be collected using observations, interviews, focus groups, surveys, and staff logs. Quantitative data will be analyzed using frequencies, means, and measures of dispersion will be applied to survey data from both time points. Pearson correlation coefficients will be used to describe the bivariate relationship between continuous factors. ANOVAs will assess whether there are significant differences in continuous measures across groups. Qualitative data will be analyzed using a constant comparison method.
This Innovations in Development award 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.
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 Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Exploration (EXP) Projects explore the viability of new kinds of learning technologies by designing and building new kinds of learning technologies and studying their possibilities for fostering learning and challenges to using them effectively. This project brings together two approaches to help K-12 students learn programming and computer science: open-ended learning environments, and computer-based learning analytics, to help create a setting where youth can get help and scaffolding tailored to what they know about programming without having to take tests or participate in rigid textbook exercises for the system to know what they know.
The project proposes to use techniques from educational data mining and learning analytics to process student data in the Alice programming environment. Building on the assessment design model of Evidence-Centered Design, student log data will be used to construct a model of individual students' computational thinking practices, aligned with emerging standards including NGSS and research on assessment of computational thinking. Initially, the system will be developed based on an existing corpus of pair-programming log data from approximately 600 students, triangulating with manually-coded performance assessments of programming through game design exercises. In the second phase of the work, curricula and professional development will be created to allow the system to be tested with underrepresented girls at Stanford's CS summer workshops and with students from diverse high schools implementing the Exploring Computer Science curriculum. Direct observation and interviews will be used to improve the model. Research will address how learners enact computational thinking practices in building computational artifacts, what patters of behavior serve as evidence of learning CT practices, and how to better design constructionist programming environments so that personalized learner scaffolding can be provided. By aligning with a popular programming environment (Alice) and a widely-used computer science curriculum (Exploring Computer Science), the project can have broad impact on computer science education; software developed will be released under a BSD-style license so others can build on it.
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TEAM MEMBERS:
Shuchi GroverMarie BienkowskiJohn Stamper
The University of Massachusetts Lowell and Machine Science Inc. propose to develop and to design an on-line learning system that enables schools and community centers to support IT-intensive engineering design programs for students in grades 7 to 12. The Internet Community of Design Engineers (iCODE) incorporates step-by-step design plans for IT-intensive, computer-controlled projects, on-line tools for programming microcontrollers, resources to facilitate on-line mentoring by university students and IT professionals, forums for sharing project ideas and engaging in collaborative troubleshooting, and tools for creating web-based project portfolios. The iCODE system will serve more than 175 students from Boston and Lowell over a three-year period. Each participating student attends 25 weekly after-school sessions, two career events, two design exhibitions/competitions, and a week-long summer camp on a University of Massachusetts campus in Boston or Lowell. Throughout the year, students have opportunities to engage in IT-intensive, hands-on activities, using microcontroller kits that have been developed and classroom-tested by University of Massachusetts-Lowell and Machine Science, Inc. About one-third of the participants stay involved for two years, with a small group returning for all three years. One main component for this project is the Handy Cricket which is a microcontroller kit that can be used for sensing, control, data collection, and automation. Programmed in Logo, the Handy Cricket provides an introduction to microcontroller-based projects, suitable for students in grades 7 to 9. Machine Science offers more advanced kits, where students build electronic circuits from their basic components and then write microcontroller code in the C programming language. Machine Science offers more advanced kits, which challenge students to build electronic circuits from their basic components and then write microcontroller code in the C programming language. Machine Science's kits are intended for students in grades 9 to 12. Microcontroller technology is an unseen but pervasive part of everyday life, integrated into virtually all automobiles, home appliances, and electronic devices. Since microcontroller projects result in physical creations, they provide an engaging context for students to develop design and programming skills. Moreover, these projects foster abilities that are critical for success in IT careers, requiring creativity, analytical thinking, and teamwork-not just basic IT skills.
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TEAM MEMBERS:
Fred MartinDouglas PrimeMichelle Scribner-MacLeanSamuel Christy
Internet Community of Design Engineers (iCODE) program, which took an innovative approach to structuring self-directed learning – using a collaborative on-line environment to facilitate hands-on activities, was a three year program led by the University of Massachusetts Lowell and Machine Science Inc., Cambridge. The overall objective of this program, which involved after-school and summer sessions and was funded by NSF’s Innovative Technology Experiences for Students and Teachers (ITEST) Program, was to increase the likelihood that participating middle school and high school students will
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TEAM MEMBERS:
Rucha LondheColleen ManningRachel SchechterLaura HousemanIrene Goodman
Parents and children are rapidly adopting mobile technologies, yet designs for mobile devices that serve a communication function to connect parents to children's out-of-school time activities are limited. As a result, our team designed the Digital Postcard Maker so that children attending summer camps can create digital photographs to send home to their parents. These digital postcards help to connect children's home life with out-of-school learning experiences and also support 21st Century Skills' media literacy practices. The research design included two iterations of a design-based
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TEAM MEMBERS:
Heather ZimmermanChristopher GamratSimon Hooper