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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Shuchi GroverMarie BienkowskiJohn Stamper
Increasingly, the prosperity, innovation and security of individuals and communities depend on a big data literate society. Yet conspicuously absent from the big data revolution is the field of teaching and learning. The revolution in big data must match a complementary revolution in a new kind of literacy, through a significant infusion of STEM education with the kinds of skills that the revolution in 21st century data-driven science demands. This project represents a concerted effort to determine what it means to be a big data literate citizen, information worker, researcher, or policymaker; to identify the quality of learning resources and programs to improve big data literacy; and to chart a path forward that will bridge big data practice with big data learning, education and career readiness.
Through a process of inquiry research and capacity-building, New York Hall of Science will bring together experts from member institutions of the Northeast Big Data Innovation Hub to galvanize big data communities of practice around education, identify and articulate the nature and quality of extant big data education resources and draft a set of big data literacy principles. The results of this planning process will be a planning document for a Big Data Literacy Spoke that will form an initiative to develop frameworks, strategies and scope and sequence to advance lifelong big data literacy for grades P-20 and across learning settings; and devise, implement, and evaluate programs, curricula and interventions to improve big data literacy for all. The planning document will articulate the findings of the inquiry research and evaluation to provide a practical tool to inform and cultivate other initiatives in data literacy both within the Northeast Big Data Innovation Hub and beyond.
This poster was presented at the 2010 Association of Science-Technology Centers Annual Conference. The Saint Louis Science Center is a partner in Washington University's Cognitive, Computational, and Systems Neuroscience interdisciplinary graduate program funded by the NSF-IGERT (Integrative Graduate Education and Research Traineeship) flagship training program for PhD scientists and engineers.
This Integrative Graduate Education and Research Training (IGERT) award supports the establishment of an interdisciplinary graduate training program in Cognitive, Computational, and Systems Neuroscience at Washington University in Saint Louis. Understanding how the brain works under normal circumstances and how it fails are among the most important problems in science. The purpose of this program is to train a new generation of systems-level neuroscientists who will combine experimental and computational approaches from the fields of psychology, neurobiology, and engineering to study brain function in unique ways. Students will participate in a five-course core curriculum that provides a broad base of knowledge in each of the core disciplines, and culminates in a pair of highly integrative and interactive courses that emphasize critical thinking and analysis skills, as well as practical skills for developing interdisciplinary research projects. This program also includes workshops aimed at developing the personal and professional skills that students need to become successful independent investigators and educators, as well as outreach programs aimed at communicating the goals and promise of integrative neuroscience to the general public. This training program will be tightly coupled to a new research focus involving neuro-imaging in nonhuman primates. By building upon existing strengths at Washington University, this research and training initiative will provide critical new insights into how the non-invasive measurements of brain function that are available in humans (e.g. from functional MRI) are related to the underlying activity patterns in neuronal circuits of the brain. IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing innovative new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries.
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TEAM MEMBERS:
Kurt ThoroughmanGregory DeAngelisRandy BucknerSteven PetersenDora Angelaki
The Environmental Scientist-in-Residence Program will leverage NOAA s scientific assets and personnel by combining them with the creativity and educational knowledge of the pioneer hands-on science center. To do this, the program will embed NOAA scientists in a public education laboratory at the Exploratorium. Working closely with youth Explainers, exhibit developers, and Web and interactive media producers at the Exploratorium, NOAA scientists will share instruments, data, and their professional expertise with a variety of public audiences inside the museum and on the Web. At the same time the scientists will gain valuable skills in informal science communication and education. Through cutting-edge iPad displays, screen-based visualizations, data-enriched maps and sensor displays, and innovative interactions with visitors on the museum floor, this learning laboratory will enable NOAA scientists and Exploratorium staff to investigate new hands-on techniques for engaging the public in NOAA s environmental research and monitoring efforts.
Focusing on climate change and its impact on coastal zones and marine life, Visualizing Change will build educator capacity in the aquarium community and informal science education field. Building on NOAA datasets and visualizations, we will provide interpreters with strategic framing communication tools and training using the best available social and cognitive research so that they can become effective climate change educators. Objectives are to (1) Develop and test four exemplary interpretive "visual narratives" that integrate research-based strategic communication with NOAA data visualization resources; (2) Test the application of the visual narratives in a variety of geographic regions, institution types (aquarium, science center, etc.), and using multiple technology platforms (Science on a Sphere, Magic Planet portable globe display, iPad/tablets, and video walls); (3) Build a professional development program for climate change interpretation with data visualization; and (4) Leverage existing networks for dissemination and peer support.
C-RISE will create a replicable, customizable model for supporting citizen engagement with scientific data and reasoning to increase community resiliency under conditions of sea level rise and storm surge. Working with NOAA partners, we will design, pilot, and deliver interactive digital learning experiences that use the best available NOAA data and tools to engage participants in the interdependence of humans and the environment, the cycles of observation and experiment that advance science knowledge, and predicted changes for sea level and storm frequency. These scientific concepts and principles will be brought to human scale through real-world planning challenges developed with our city and government partners in Portland and South Portland, Maine. Over the course of the project, thousands of citizens from nearby neighborhoods and middle school students from across Maine’s sixteen counties, will engage with scientific data and forecasts specific to Portland Harbor—Maine’s largest seaport and the second largest oil port on the east coast. Interactive learning experiences for both audiences will be delivered through GMRI’s Cohen Center for Interactive Learning—a state-of-the-art exhibit space—in the context of facilitated conversations designed to emphasize how scientific reasoning is an essential tool for addressing real and pressing community and environmental issues. The learning experiences will also be available through a public web portal, giving all area residents access to the data and forecasts. The C-RISE web portal will be available to other coastal communities with guidance for loading locally relevant NOAA data into the learning experience. An accompanying guide will support community leaders and educators to embed the interactive learning experiences effectively into community conversations around resiliency. This project is aligned with NOAA’s Education Strategic Plan 2015-2035 by forwarding environmental literacy and using emerging technologies.
The project team is developing and testing a prototype of a computer science game-based intervention intended for Grade 1 students. The prototype will include physical robots that will be designed and controlled on a game board by students through a blue-tooth enabled smartphone app. The product will include teacher resources and suggestions to facilitate classroom integration. In the Phase I pilot research with 5 classrooms and 150 students, the researchers will examine whether the prototype functions as planned, if teachers are able to implement it with small groups of students, and whether
This article examines certain guiding tenets of science journalism in the era of big data by focusing on its engagement with citizen science. Having placed citizen science in historical context, it highlights early interventions intended to help establish the basis for an alternative epistemological ethos recognising the scientist as citizen and the citizen as scientist. Next, the article assesses further implications for science journalism by examining the challenges posed by big data in the realm of citizen science. Pertinent issues include potential risks associated with data quality
Thanks, on the one hand, to the extraordinary availability of colossal textual archives and, on the other hand, to advances in computational possibilities, today the social scientist has at their disposal an extraordinary laboratory, made of millions of interacting subjects and billions of texts. An unprecedented, yet challenging, opportunity for science. How to test, corroborate models? How to control, interpret and validate Big Data? What is the role of theory in the universe of patterns and statistical correlations? In this article, we will show some general characteristics of the use of
The Science Museum of Minnesota (SMM) leverages a professional educator team (“instructors”) comprised of about two dozen individuals who facilitate both formal and informal educational programming in the museum, in K–12 classrooms, and at community-based sites. The experienced instructors of SMM’s Lifelong Learning Group bring innovative programs to both students and their teachers. Recognizing that long-term experiences can have a profound impact on students and teachers, SMM works to develop multiyear relationships based on collaboration. This article focuses primarily on SMM’s well
SciGirls Strategies is a National Science Foundation–funded project led by Twin Cities PBS (TPT) in partnership with St. Catherine University, the National Girls Collaborative, and XSci (The Experiential Science Education Research Collaborative) at the University of Colorado Boulder’s Center for STEM Learning. This three-year initiative aims to increase the number of high school girls recruited to and retained in fields where females are traditionally underrepresented: technical science, engineering, technology, and math (STEM) pathways. We seek to accomplish this goal by providing career and
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Rita KarlBradley McLainAlicia Santiago