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
Purpose: This project will develop and test Happy Atoms, a physical modeling set and an interactive iPad app for use in high school chemistry classrooms. Happy Atoms is designed to facilitate student learning of atomic modeling, a difficult topic for chemistry high school students to master. Standard instructional practice in this area typically includes teachers using slides, static ball and stick models, or computer-simulation software to present diagrams on a whiteboard. However, these methods do not adequately depict atomic interactions effectively, thus obscuring complex knowledge and understanding of their formulas and characteristics.
Project Activities: During Phase I (completed in 2014), the team developed a prototype of a physical modeling set including a computerized ball and stick molecular models representing the first 17 elements on the periodic table and an iPad app that identifies and generates information about atoms. A pilot study at the end of Phase I tested the prototype with 187 high school students in 12 chemistry classes. Researchers found that the prototype functioned as intended. Results showed that 88% of students enjoyed using the prototype, and that 79% indicated that it helped learning. In Phase II, the team will develop additional models and will strengthen functionality for effective integration into instructional practice. After development is complete, a larger pilot study will assess the usability and feasibility, fidelity of implementation, and promise of Happy Atoms to improve learning. The study will include 30 grade 11 chemistry classrooms, with half randomly assigned to use Happy Atoms and half who will continue with business as usual procedures. Analyses will compare pre-and-post scores of student's chemistry learning, including atomic modeling.
Product: Happy Atoms will include a set of physical models paired with an iPad app to cover high school chemistry topics in atomic modeling. The modeling set will include individual plastic balls representing the elements of the periodic table. Students will use an iPad app to take a picture of models they create. Using computer-generated algorithms, the app will then identify the model and generate information about its physical and chemical properties and uses. The app will also inform students if a model that is created does not exist. Happy Atoms will replace or supplement lesson plans to enhance chemistry teaching. The app will include teacher resources suggesting how to incorporate games and activities to reinforce lesson plans and learning.
This project team will develop and test a prototype of SuperChem VR, a game to support high school students' basic chemistry learning. The prototype will include a set of web-based laboratory modules which will be integrated within a virtual reality headset to allow for a 360-degree visual exploration of the environment. The prototype will also include teacher resources for classroom implementation. In the Phase I pilot research with 3 teachers and 54 students, the project team will examine whether the hardware and software prototype functions as planned, whether teachers are able to integrate it within the classroom environment, and whether students are engaged while using the prototype.
As part of an overall strategy to enhance learning within informal environments, the Innovations at the Nexus of Food, Energy, and Water Systems (INFEWS) and Advancing Informal STEM Learning (AISL) programs partnered to support innovative models poised to catalyze well-integrated interdisciplinary research and development efforts within informal contexts that transform scientific understanding of the food, energy, and water systems (FEWS) nexus in order to improve system function and management, address system stress, increase resilience, and ensure sustainability. This project addresses this aim by using systems thinking and interdisciplinary integration approaches to develop a novel immersive educational simulation game and associated materials designed to highlight the role and importance of corn-water-ethanol-beef (CWEB) systems in supporting the ever increasing demands for food, energy, and water in the United States. The focus on FEWS and sustainable energy aligns well with both the INFEWS program and the sizable sustainability-related projects in the AISL program portfolio. The development and broad dissemination of a multiuser game specific to CWEB systems are particularly innovative contributions and advance for both program portfolios and their requisite fields of study. An additional unique feature of the game is the embedding of varying degrees of economic principles and decision-making along with the nuisances of cultural context as salient variables that influence systems thinking. Of note, a team of computer science, management and engineering undergraduate students at the University of Nebraska - Lincoln will be responsible for the engineering, development, and deployment of the game as their university capstone projects. If successful, this game will have a significant reach and impact on youth in informal programs (i.e., 4-H clubs), high school teachers and students in agriculture vocational education courses, college students, and the public. The impact could extend well beyond Nebraska and the targeted Midwestern region. In conjunction with the game development, mixed-methods formative and summative evaluations will be conducted by an external evaluator. The formative evaluation of the game will focus on usability testing, interest and engagement with a select sample of youth at local 4-H clubs and youth day camps. Data will be collected from embedded in-game survey questionnaires, rating scales, observations and focus groups conducted with evaluation sample. These data and feedback will be used to inform the design and refinement of the game. The summative evaluation will focus on the overall impacts of the game. Changes in agricultural systems knowledge, attitudes toward agricultural systems, interest in pursuing careers in agricultural systems, and decision making will be aligned with the Nebraska State Science Standards and tracked using the National Agricultural Literacy Outcomes (NALOs) assessment, game analytics and pre/post-test measures administered to the evaluation study sample pre/post exposure to the game.
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TEAM MEMBERS:
Jeyamkondan SubbiahEric ThompsonDeepak KeshwaniRichard KoelschDavid Rosenbaum
Well-designed educational games represent a promising technology for increasing students interest in and learning of STEM topics such as physics. This project will research how to optimally combine and embed dynamic assessment and adaptive learning supports within an engaging game design to build effective educational games. The project will add enhancements to a physics game called Physics Playground. The general goal of this research is to test a valid methodology that can be used in the design of next-generation learning games. The enhancement of Physics Playground will leverage the popularity of video games to capture and sustain student attention and teach physics to a much broader audience than is currently the case in traditional physics classrooms. To be most effective, this new genre of learning games needs to not only be highly engaging as a game but also to provide real-time assessment and feedback to students; support understanding of science content (i.e.,Newtonian physics); be accessible to beginners; accommodate a range of proficiencies and interests; and support equity. The research will have particular relevance to designers developing other science games and simulation by providing information about the kinds of learning supports and feedback to students are most effective in promoting engagement and learning. The project is supported by the Cyberlearning and Future Learning Technologies Program, which 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.
The project will systematically develop, test, and evaluate ways to integrate engaging, dynamic learning supports in Physics Playground to teach formal conceptual physics competencies. More generally, the project aims to advance the learning sciences, particularly in the fields of adaptivity and assessment in educational technology. Using a design-based research approach spanning three years, the research team will: (1) develop and test the effectiveness of various learning support features included in the game in Year 1; (2) develop and test an adaptive algorithm to manage the progression of difficulty in game levels in Year 2; and (3) test learning supports and adaptive sequencing in a controlled evaluation study. This research will provide evidence of the instructional effectiveness of an educational game designed using principles of instructional, game, and assessment design. It will advance understanding of the contributions of different kinds of learning supports (e.g., visualizations and explanations) and adaptivity to game-based learning and contribute to the design of next-generation learning games that successfully blur the distinction between assessment and learning. The project will generate research findings that can be incorporated into other types of STEM learning games.
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TEAM MEMBERS:
Valerie ShuteRussell AlmondFengfeng Ke
This project, a collaboration of teams at Georgia Institute of Technology, Northwestern University, and the Museum of Design Atlanta and the Museum of Science and Industry in Chicago, will investigate how to foster engagement and broadening participation in computing by audiences in museums and other informal learning environments that can transfer to at-home and in-school engagement (and vice versa). The project seeks to address the national need to make major strides in developing computing literacy as a core 21st century STEM skill. The project will adapt and expand to new venues their current work on their EarSketch system which connects computer programming concepts to music remixing, i.e. the manipulation of musical samples, beats and effects. The initiative involves a four-year process of iteratively designing and developing a tangible programming environment based on the EarSketch learning environment. The team will develop three new applications: TuneTable, a multi-user tabletop exhibit for museums; TunePad, a smaller version for use at home and in schools; and an online connection between the earlier EarSketch program and the two new devices.
The goal is to: a) engage museum learners in collaborative, playful programming experiences that create music; b) direct museum learners to further learning and computational music experiences online with the EarSketch learning environment; c) attract EarSketch learners from local area schools to visit the museum and interact with novice TuneTable users, either as mentors in museum workshops or museum guests; and d) inform the development of a smaller scale, affordable tangible-based experience that could be used at homes or in smaller educational settings, such as classrooms and community centers. In addition to the development of new learning experiences, the project will test the hypothesis that creative, playful, and social engagement in the arts with computer programming across multiple settings (e.g. museums, homes, and classrooms) can encourage: a) deeper learner involvement in computer programming, b) social connections to other learners, c) positive attitudes towards computing, and d) the use and recognition of computational concepts for personal expression in music. The project's knowledge-building efforts include research on four major questions related to the goals and evaluation processes conducted by SageFox on the fidelity of implementation, impact, success of the exhibits, and success of bridging contexts. Methods will draw on the Active Prolonged Engagement approach (unobtrusive observation, interviews, tracking-and-timing, data summaries and team debriefs) as well as Participatory Action Research methods.
This work 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.
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TEAM MEMBERS:
Michael HornBrian MagerkoJason Freeman
Hexacago Health Academy (HHA) is a game-based science and health curriculum intervention. HHA engages high school students in learning about and addressing major sexual and reproductive health issues and risk behaviors. A board game, Hexacago, depicting the city of Chicago with an overlay of hexagons is the cornerstone of HHA. Students use the board design games and think critically about public health problems in the city of Chicago. HHA uses game-play, interaction with STEM science and health professionals, and mentoring to create a rich, game-based learning experience for high school students. The object of HHA is to improve academic performance, increase science and health career interest, and improve health behaviors among youth living in Chicago.
Great Lakes Science Center (GLSC), home of the NASA Glenn Visitor Center, is dedicated to sharing NASA content to inform, engage, and inspire students, educators, and the public. To further this goal, GLSC will develop a digital experience focused on collaboration and teamwork, emphasizing the benefits of a systems approach to STEM challenges. At the recently, fully renovated NASA Glenn Visitor Center, GLSC visitors will embark on an exciting mission of discovery, working in teams to collect real data from NASA objects and experiences. Mobile devices will become scientific tools as students, teachers, and families take measurements, access interviews with NASA scientists, analyze results from Glenn Research Center (GRC) test facilities, and link to NASA resources to assemble mission-critical information. This initiative will provide experiences that demonstrate how knowledge and practice can be intertwined, a concept at the core of the Next Generation Science Standards. GLSC’s digital missions will engage students and families in STEM topics through the excitement of space exploration. In addition, this project has the potential to inform the design of future networked visitor experiences in science centers, museums and other visitor attractions.
The Mars Exploration Exhibit is a new public exhibition designed to provide experiential learning opportunities for students, educators and the public while inspiring greater excitement about space science. The exhibit emphasizes the importance of STEM education and careers through practical application and inquiry-based learning. Space Center Houston, the official visitor center of Johnson Space Center, is creating the new Mars landscape simulation in partnership with the Houston Independent School District and University of Houston Clear Lake. The exhibit will offer interactive science education activities that will be delivered through distance learning and onsite instruction at Space Center Houston. Utilizing research-based practices in both formal and informal learning environments, the project will help to attract and retain students in science, technology, engineering and mathematics. It will also foster life-long learning and enthusiasm toward the promise of space science and innovation. This unique exhibit will enable students and Space Center Houston’s more than 800,000 annual visitors to increase their knowledge of Earth science and apply their learning to the Mars environment. The exhibit will also highlight the role NASA missions serve in scientific innovation. The project will build the capacity of the Greater Houston community and school-based organizations to engage girls, minorities and other underrepresented students in STEM learning. It will offer in-depth science education for low-performing and gifted/talented students, ultimately bridging achievement gaps, increasing student performance and cultivating greater interest in science. Project outcomes will include: a 1,500-square-foot Mars landscape exhibition; interactive video presentations highlighting water recovery and other environmental processes; a standards-based learning curriculum aligned with Texas Essential Knowledge and Skills (TEKS ) and National Science Standards; and a menu of K-12 experiential learning activities focused on water, air, renewable energy and other critical science topics.
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TEAM MEMBERS:
Janet BrownMelanie JohnsonPaul SpanaMeg Naumann
Brigham Young University and the University of Maryland, in partnership with the Smithsonian Institution, the Computer History Museum, and NASA, plus leading game designers, educators, scientists, and researchers, will conduct research on the design and development of two large-scale Alternate Reality Games (ARGs) based on deep-time science in astrobiology, astrophysics, and interplanetary space travel. The project will iteratively design and test two distinct types of ARGs (closed- and open-ended) to study the effects of these ARGs on STEM learning. The ARGs will be based upon the Next Generation Science Standards (NGSS), affording learners with intensive, self-driven, and scaffolded scientific learning and will be aimed at attracting girls and other groups historically underrepresented in science and technology. Each ARG will be designed by NASA scientists, educators and education researchers, and game-based learning experts and will be highly interactive: engaging learners in collaborative investigations in real and virtual worlds to collect scientific data, conduct data analysis, and contribute scientific evidence that will help solve scientific questions within a science-based narrative derived from real world problems that will develop learners' computational thinking skills in a collaborative, participatory virtual learning environment. Combining data from web and social media analytics, player interviews, surveys, and user-generated content, researchers, and evaluation experts at UXR who will provide an outcomes-based evaluation, including front-end, formative, remedial, and summative evaluations, will establish the properties of ARGs that most effectively advance informal STEM learning outcomes. By comparing open-ended and closed-ended ARGs, the PIs will be able to assess the relative strengths and weaknesses of two distinct approaches to Alternate Reality Game design. The project team will test the hypothesis that open-ended, user-generated content will support inquiry-based learning, peer-to-peer learning, and life-wide and life-deep learning, while close-ended, narrative-rich ARGs will support specific transfer of STEM knowledge, collaboration, and problem solving. To help ensure that the games appeal to their target audiences, the project team will adopt co-design methods, enlisting the creative input of participating teens at each stage of the design process. Supplementary materials and lesson plans developed in close consultation with teachers, librarians, teens, and external stakeholders will enable the ARGs to be widely and effectively used as a model in museums, classrooms, libraries, and after-school programs. The proposed ARGs represent a unique environment to test learning principles that enable players to bridge their learning through transmedia across multiple contexts and test the effects of collaboration with massive numbers of concurrent players. As a result, the project should yield insights on how learning principles can be adopted and re-appropriated for emerging learning environments, including those that that might be crowd-sourced. The research is well grounded in the literature and the PIs do an excellent job of mapping ARG design principles to the pertinent learning science research, providing a clear sense of the particular affordances of the genre that should lead to new understandings. The approach has profound implications for the way we might teach the next generation of students. The ability to mix problem solving and learning in virtual spaces with experiences and data derived from the physical world could dramatically change how we understand the role of technology in education.
In this full-scale research and development project, Oregon State University (OSU), Oregon Sea Grant (OSG) and the Hatfield Marine Science Center Visitors Center (HMSCVC) is designing, developing, implementing, researching and evaluating a cyberlaboratory in a museum setting. The cyberlaboratory will provide three earth and marine science learning experiences with research and evaluation interwoven with visitor experiences. The research platform will focus on: 1) a climate change exhibit that will enable research on identity, values and opinion; 2) a wave tank exhibit that will enable research on group dynamics and problem solving in interactive engineering challenges; and 3) remote sensing exhibits that will enable research on visitor interactions through the use of real data and simulations. This project will provide the informal science educaton community with a suite of tools to evaluate learning experiences with emerging technologies using an iterative process. The team will also make available to the informal science community their answers to the following research questions: For the climate change exhibit, "To what extent does customizing content delivery based on real-time visitor input promote learning?" For the wave tank exhibit, "To what extent do opportunities to reflect on and share experiences promote STEM reasoning processes at a build-and-test exhibit?" For the data-sensing exhibit, "Can visitors' abilities to explain or use visualizations be improved by shaping their visual searches of images?" Mixed-methods using interviews, surveys, behavioral instruments, and participant observations will be used to evaluate the overall program. Approximately 60-100 informal science education professionals will discuss and test the viability of the exhibit's evaluation tools. More than 150,000 visitors, along with community members and local middle and high school students, will have the opportunity to participate in the learning experiences at the HMSCVC. This work contributes to the fields of cyberlearning and informal science education. This project provides the informal science education field with important knowledge about learning, customized content delivery and evaluation tools that are used in informal science settings.
This REAL project arises from the 2013 solicitation on Data-intensive Research to Improve Teaching and Learning. The intention of that effort is to bring together researchers from across disciplines to foster novel, transformative, multidisciplinary approaches to using the data in large education-related data sets to create actionable knowledge for improving STEM teaching and learning environments in the medium term and to revolutionize learning in the longer term. This project addresses the issue of how to represent and communicate data to young people so that they can track their learning and weaknesses and take advantage of what they learn through that tracking. The project team aims to address this challenge by giving young people (middle schoolers) the tools and support to create, manipulate, analyze, and share representations of their own understanding, capabilities, and participation within the Scratch environment. Scratch is a programming language and online community in which youngsters (mostly middle schoolers) engage in programming together, sometimes to make scientific models and sometimes to express themselves artistically using sophisticated computer algorithms. Scratch community participants are often interested in keeping track of what they are learning, so this population is a good one for exploring ways of helping young people make sense of data that records their participation and learning. The team will extend the Scratch programming language with facilities for manipulating, analyzing, and representing such data, and Scratch participants will be challenged to make sense of their learning and participation data and helped to use the new facilities to do write programs to carry out such interpretation. Scratch participants will become visualizers of their participation patterns and learning trajectories; research will address how such data explorations influence their learning trajectories. Scratch and its community are the place for the proposed investigations, but what is learned will apply far more broadly to construction of tools for allowing learners to understand their participation and learning across a broad range of environments. This project addresses the sixth challenge in the program solicitation: how can information extracted from large datasets be represented and communicated to maximize its usefulness in real-time educational stings, and what delivery mechanisms are right for that? The PIs go right to the learners; rather than looking for delivery mechanisms for communicating the data representations, they give young people tools and support to create manipulate, analyze, and share those representations, bringing together approaches to quantitative evidence-based learning analytics with the constructionist tradition of learning through design experiences. In addition to helping us learn about how to help youngsters analyze data about their perforance and self-assess, the PIs expect that their endeavor will help us better learn how to help young people become data analyzers, an important part of computational thinking. Learners will, in the process of engaging with data representing their development and participation, interact with visualizations, model and troubleshoot data sets, and search for patterns in large data sets. In addition, the tools being developed as part of this project will be applicable for analysis of other types of data sets. The results that will transfer beyond Scratch and the Scratch community, are (1) the kinds of tools that make such analysis possible for youngsters, (2) the kinds of challenges that will get youngsters interested in doing such analyses, (3) the kinds of data youngsters can handle, and (4) the kinds of scaffolding and coaching youngsters need to make sense of that data.
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TEAM MEMBERS:
Benjamin Mako HillMitchel ResnickNatalie Rusk