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I-Corps: Virtual Reality Biofeedback Education Technologies

Award Number: 1938166
Sponsor : Cornell University
Michael Timmons [email protected] (Principal Investigator)

ABSTRACT
The broader impact/commercial potential of this I-Corps project is to provide a new means for how educational content is delivered in virtual reality (VR) with consistent impact, independent of demographics and environment. This technology offers a higher level of personalized learning that can be administered without requiring accompanying professional development for teachers due to the delivery of lessons in a highly controlled virtual environment. Removing this dependence on additional training facilitates the adoption across schools with limited resources. The increased efficacy in learning and retention of material through VR has made it a technology of interest for teachers and school administrators. This technology can be used across a range of educational subjects, and with the immersive personalized learning experience, offers a high-quality learning solution for educators.

This I-Corps project uses biofeedback to personalize learning in virtual reality (VR). The technology manipulates a user’s environment based on their physiological reactions. This can include the surrounding physical objects, light source, or landscape. The auditory manipulation is a more indirect change where the audio path of a lesson is based on the emotional reaction of a user, such as when someone is distracted or agitated. This emotional reaction is based on tracking numerous physiological inputs over time. The identification process is based on existing research using the same physiological measures to classify users’ emotional states and improved through this project This level of adaptation enables a higher degree of VR program customization and more a meaningful learning experience while using the technology.

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.

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AwardsInventXRNSFThe Research University

NeuroTech – Bringing Technology to Neuroscience

Sponsor: Stanford University

Eduardo Chichilnisky [email protected] (Principal Investigator)
James McClelland (Co-Principal Investigator)
Jin Hyung Lee (Co-Principal Investigator)
Surya Ganguli (Co-Principal Investigator)

ABSTRACT

Deciphering how the brain works could have untold impacts on medicine, technology, commerce, and our understanding of ourselves. For example, advances in neurotechnology could lead to brain-machine interfaces to overcome sensory impairments and loss of movement due to neurodegenerative disease. Many of the most important advances in neuroscience have required interaction with technical fields such as physics, electrical and chemical engineering, bioengineering, statistics, and computer science, and this will increasingly be the case as the field advances. However, the path for top students from these disciplines to enter the field of neuroscience has always been challenging because they lack the appropriate background and awareness of key questions and technological limitations in the field. This National Science Foundation Research Traineeship (NRT) award to Stanford University will accelerate fundamental developments in neuroscience by attracting promising young talent from these technical disciplines to neuroscience and training them to be leaders in the field. The program will allow students to apply technological developments in diverse fields to the most important problems in neuroscience today and train a new generation of neuroscientists who will bring these technologies to fruition in academia, medicine, and the private sector. The project anticipates training thirty (30) PhD students, including twelve (12) funded trainees, from physics, electrical and chemical engineering, bioengineering, materials science, computer science, and other technical fields.

This traineeship program consists of a novel integrated curriculum of coursework, internship and training experiences, and outreach to achieve its goals. The program will emphasize training for acquiring and analyzing vast data sets, enabling an understanding of nervous system circuitry at a scale that was unimaginable just a few years ago, and connecting the novel data to Stanford’s strength in theory, inference from large data sets, and computational modeling. The program will introduce a rigorous multi-year curriculum for trainees, building on their home-discipline training and allowing them to collaborate with each other and with the members of the Neurosciences PhD program. Training will leverage the highly successful Stanford ADVANCE program that supports new PhD students with a special summer program prior to the start of graduate training, and build on it with several approaches customized to this program. The program will be specifically designed to optimize trainee preparation for a career in academia or in a technology industry setting, utilizing internship placements with both startups and established corporations.

The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.

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.

 

Please report errors in award information by writing to: [email protected].

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Technology-Human Integrated Knowledge Education and Research (THINKER)

Sponsor: Clemson University

Laine Mears [email protected] (Principal Investigator)
Amy Apon (Co-Principal Investigator)
Deborah Switzer (Co-Principal Investigator)
Mary Kurz (Co-Principal Investigator)
Joshua Summers (Co-Principal Investigator)
Laura Stanley (Former Co-Principal Investigator)

ABSTRACT

The pervasiveness of new digital technologies in manufacturing is changing the way that data are generated, interpreted and shared over networks of machines, robotics and software systems. This “industrial internet of things” holds great promise for improving the quality and productivity of manufacturing in the United States. However, the ability of human workers to effectively interface with such digital systems is limited, potentially leading to disruptions in cognition that may negatively affect output and job satisfaction. This National Science Foundation Research Traineeship (NRT) award prepares master’s and doctoral degree students at Clemson University to advance discoveries at the nexus of humans, technology, work, and health, through the convergence of human factors, robotics, cognitive sciences, artificial intelligence, systems engineering, education, manufacturing and social behavioral sciences. This will be achieved through the design and integration of human digital technologies that enhance humans’ physical and cognitive interaction and abilities in manufacturing environments. The project anticipates training fifty (50) M.S. and Ph.D. students, including twenty-two (22) funded trainees, from electrical engineering, industrial engineering, computer science, manufacturing, systems integration, psychology, and sociology. These students will interface with a parallel program of undergraduate and technical college students in a controlled manufacturing environment to test deployment and integration across multiple academic levels.

This project responds to the critical need to help shape and better prepare the STEM graduate student of tomorrow through an innovated curriculum that focuses on the new digital and smart manufacturing, automation, and associated data systems. The training and research takes a human-centered design approach in the emerging digital manufacturing enterprise (i.e., Industrial Internet of Things), by quantifying physical and human cognition and developing augmented technologies (e.g. augmented reality aids for worker empowerment) to improve worker behaviors and attitudes in the manufacturing enterprise. This project will focus on an automotive industry exemplar (i.e., vehicle assembly operation), employing a factory setting which includes parts manufacture, structural and subassembly operations, robotics, kitting, logistics, and a full-scale vehicle assembly line, together with parallel programs in undergraduate and technical college curricula. The multi-level educational approach is expected to drive improved team communication, generate knowledge on worker behaviors and attitudes, and prepare students for leading implementation of the technologies under study in manufacturing and other industries.

The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.

"Research
AwardsInventXRMovement ThinkingNSFThe Research University

Innovations in Development: Community-Driven Projects That Adapt Technology for Environmental Learning in Nature Preserves

Sponsor: University of Maryland College Park

Jennifer Preece [email protected] (Principal Investigator)
Tamara Clegg (Co-Principal Investigator)

ABSTRACT

While low-income and minority communities suffer disproportionately from poor environmental conditions, members of these communities tend to be under-represented in participatory scientific projects and informal science learning opportunities. There are many benefits to community-driven STEM projects, both for individuals’ experiential learning and for the betterment of communities. Expanding participation also contributes to a more complete understanding of complex environmental problems, including STEM content and skills. This project engages members of racially and economically diverse communities in identifying and carrying out environmental projects that are meaningful to their lives, and adapts technology known as NatureNet to assist them. NatureNet, which encompasses a cell phone app, a multi-user, touch-based tabletop display and a web-based community, was developed with prior NSF support. Core participants involved in programs of the Anacostia Watershed Society in Washington, D.C., and Maryland, and the Reedy Creek Nature Preserve in Charlotte, NC, will work with naturalists, educators, and technology specialists to ask scientific questions and form hypotheses related to urban waterway restoration and preservation of native species. They will then collect and analyze data using NatureNet, requesting changes to the technology to customize it as needed for their projects. Casual visitors to the nature centers will be able to interact with the environmental projects via the tabletop, and those who live farther away will be able to participate more peripherally via the online community. This study 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 research project, led by researchers from the University of Maryland, College Park, with collaborators from the University of North Carolina, Charlotte, and the University of Colorado, Boulder, will provide answers to two questions: 1) How do community-driven informal environmental learning projects impact participants, including their motivation to actively participate in science issues via technology and their disposition toward nature preserves and scientific inquiry, and 2) What are the key factors (e.g., demographic composition of participants, geographical location) that influence the development of community-driven environmental projects? Researchers will gather extensive qualitative and quantitative data to understand how community projects are selected and carried out, how participants approach technology use and adaptation, and how informal learning and engagement on STEM-related issues can be fostered over a period of several months and through iterative project cycles. Data will be collected through motivation questionnaires; focus groups; interviews; tabletop, mobile, and website interaction logs; field notes from participatory design and reflection sessions; and project journals kept by nature preserve staff. Through extensive research, iterative design, and evaluation efforts, researchers will develop an innovative model for community-driven environmental projects that will deepen informal science education by demonstrating how members of diverse communities connect environmental knowledge and scientific inquiry skills to the practices, values, and goals of their communities, and how technology can be used to facilitate such connections.

 

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A Youth-Led Citizen Science Network for Community Environmental Assessment

Sponsor: Southern Illinois University at Edwardsville

Georgia Bracey [email protected] (Principal Investigator)
Sharon Locke (Co-Principal Investigator)
Ben Greenfield (Co-Principal Investigator)
Adriana Martinez (Co-Principal Investigator)

ABSTRACT

This project will advance efforts of the Innovative Technology Experiences for Students and Teachers (ITEST) program to better understand and promote practices that increase student motivations and capacities to pursue careers in fields of science, technology, engineering, or mathematics (STEM) by developing a technology-rich, out-of-school time STEM program for underserved middle and high school youth. The new program features citizen science activities involving mobile sensors, drones, mapping software, and other technologies associated with environmental science data collection and careers. Four learning modules will be developed that focus on air, noise, and soil pollution, and how factors associated with land use contribute to different types of pollution. Field data will be compared to land cover classifications to examine how pollutants are related to and influenced by natural and built environments. Participants will also use their developing technology skills to communicate their findings to larger audiences using a website, digital stories, videos, and citizen science cafes. In the science cafes, youth will gain leadership skills by guiding their parents or caregivers, siblings, and the community at large in citizen science activities. This project extends the typical pattern of citizen science projects by having participants go beyond joining established citizen science projects to initiating their own projects grounded in issues and affordances of their local communities. If successful, the model from this project has the potential to be broadly adapted to other communities and linked to research of local or regional interest or importance.

This design and development project will directly engage 45 students in grades 8 and 9, with potential for reaching over 300 individuals as participants’ families and community members become involved in citizen science cafes. Most project activities will take place at government subsidized housing sites. The program progresses through five elements: curriculum development, instructor preparation, immersive summer sessions, school-year sessions for participating youth, and citizen science cafes. The project will develop four teaching modules: Air Pollution, Noise Pollution, Soil Pollution, and Natural and Built Environments. Students will gain experience with field research methods while learning to collect high-quality data using various sensors and related technologies. They will use the data to answer scientific questions. A mixed methods approach will be employed to examine outcomes related to the research questions: (1) How does participation in community-focuses environmental citizen science impact the development of three aspects of science: performance, competence, and recognition as a scientist?(2) To what extent and how does participation in community-focused environmental citizen science activities move youth towards full participation in the science community? and (3) How do levels of performance, competence, and recognition influence progress towards full participation in the science community? Data sources will include a student science identity survey, a test of relevant knowledge, a student interview protocol, a student observation protocol, student artifact rubrics, and a parent/caregiver interview protocol. Interviews will be conducted with student participants at regular intervals, and with parents/caregivers at the end of program sessions.

This project will expand the existing ITEST portfolio by addressing important questions relating to community-relevant curricula, linkages of formal and informal education, and examining potential new elements of STEM learning ecosystems, including the use of student-initiated citizen science endeavors and youth-led citizen science cafes. Through the embedded research, this project will also advance understanding of science identity development and its relationship to STEM occupational choices.

 

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AwardsInventXRMovement ThinkingNSFThe Research University

Trans-disciplinary Education in Biology and Engineering Technology

Sponsor: University of Cincinnati Main Campus

Stephanie Rollmann [email protected] (Principal Investigator)
John Layne (Co-Principal Investigator)
Kathie Maynard (Co-Principal Investigator)
Anna DeJarnette (Co-Principal Investigator)
Dieter Vanderelst (Co-Principal Investigator)
Bridgette Peteet (Former Co-Principal Investigator)

ABSTRACT

This project focuses on increasing diversity in STEM and increasing student and teacher experiences and competency in the fields of biology and engineering. An integrated education program at the intersection of biology and engineering – the sensory guidance of behavior in biological organisms and autonomous robots – will be developed and studied. The project will consist of: (a) an integrated three-week summer program for rising 12th-grade students and in-service secondary education teachers; (b) a college credit course and workshops for students during their 12th grade school year, and; (c) paid summer internships upon graduation. In these programs, students will engage in hands-on biological investigations to learn how animals sense and respond to their environments. They will then integrate scientific principles with authentic engineering technology to build and program robots based on animals. The robots will be equipped with sensors and behaviors and execute tasks designed by the students. Subsequent internships will serve to further connect student knowledge of integrated biology and engineering with real-world experiences. Creating this program under the framework of animal/robot sensorimotor systems is particularly timely since biology and robotics are producing exciting, emerging technologies and are major growth industries. This project will advance efforts of the Innovative Technology Experiences for Students and Teachers (ITEST) program to better understand and promote practices that increase student motivations and capacities to pursue careers in fields of science, technology, engineering, or mathematics (STEM).

The research seeks to (1) increase awareness and participation of underrepresented groups in STEM fields; (2) increase interest, attitudes, knowledge, and self-efficacy in biology, engineering, and technology fields and occupations, and; (3) develop a model to educate students and to train teachers in concepts that examine the interrelatedness between science and engineering. The project’s formative and summative evaluation methods, including surveys, focus groups, and open-ended evaluations of workshop and internship experiences, will be used to study these issues. The research will contribute new insights into integrated STEM curricula and how they support students in developing and sustaining interests in learning and working in scientific fields. The project also engages underrepresented youth in critical thinking, problem-solving, and real-world investigations in biology and engineering that may lead them to pursue STEM careers.

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AwardsInventXRMovement ThinkingNSFSuperintendentsThe Research University

The Research University: Center for Renewable Energy Advanced Technological Education Resource Center

Sponsor: Madison Area Technical College

Kenneth Walz [email protected] (Principal Investigator)
Kathleen Alfano (Co-Principal Investigator)
Joel Shoemaker (Co-Principal Investigator)
Andrew McMahan (Co-Principal Investigator)

ABSTRACT

Over the past decade, renewable energy has grown at a much faster pace than many other industry sectors. This growth results from recent technological advances, government policy and regulatory reforms, and tremendous reductions in the cost of solar and wind equipment. As a result, the electricity sector is now engaged in a dramatic shift from energy obtained from fossil fuels to energy obtained from renewable resources. STEM careers in renewable energy provide technicians with well-paying jobs that can support families, that cannot be easily exported, and that benefit the local community. The Resource Center for Renewable Energy Advanced Technological Education (CREATE) aims to support preparation of a new generation of renewable energy educators and skilled technical professionals. The expected outcomes include greater use of renewable energy, an improved power infrastructure, greater resilience of US energy systems, and a larger role for the United States as a global industry leader in renewable energy technology.

CREATE will support two-year institutions to develop, promote, grow, and advance robust academic programs to provide the renewable energy industry with a skilled technical workforce. This goal will be accomplished through six key objectives: 1) provide support, mentoring, and professional development for faculty and prospective NSF principal investigators in renewable energy technology; 2) coordinate and support additional renewable energy industry, business, and academic partnerships; 3) educate the public about renewable energy and renewable energy technician careers; 4) develop, screen, validate, update, and distribute renewable energy teaching materials, curricula, and pedagogical practices; 5) connect and support existing and new ATE project Principal Investigators in renewable energy and related fields; and 6) develop a plan for achieving sustainability and institutionalization of key center functions. Additional plans include serving high school educators to create bridges to higher education. The Center will also reach out to faculty at Hispanic Serving Institutions, Tribal Colleges and Historically Black Colleges to encourage them to apply to the ATE program. Increasing the number of women in the renewable energy fields will continue to be a focus of CREATE. This project is funded by the Advanced Technological Education program that focuses on the education of technicians for the advanced-technology fields that drive the nation’s economy.

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AwardsInventXRMovement ThinkingSuperintendentsThe Research University

The Research University: The Agave Platform: An Open Science-As-A-Service Cloud Platform for Reproducible Science

Sponsor: Chapman University

Rion Dooley [email protected] (Principal Investigator)

ABSTRACT

In today’s data-driven research environment, the ability to easily and reliably access compute, storage, and derived data sources is as much a necessity as the algorithms used to make the actual discoveries. The earth is not shrinking, it is digitizing, and the ability for US researchers to stay competitive in the global research community will increasingly be determined by their ability to reduce the time from theory to discovery. Over the last 5 years, the open source commercial sector has greatly outpaced the academic research world in its growth and adoption of programming languages, infrastructure design, and interface development. Problems that were primarily academic in nature several years ago are now common in the commercial world. Terms like big data, business intelligence, remote visualization, and streaming event processing, have moved from the classroom to the board room. However, academic projects are largely unable to take advantage of many today’s most popular and widely used open source technologies within the context of their campus and shared research infrastructure. The recently completed, NSF funded, Science Gateway Institute planning project revealed just how far behind many communities are. In a survey of over 26,000 NSF-funded PIs, science gateway developers, and leaders in higher education (i.e., CIOs, CTOs, and others), over 85% of respondents said they needed help adapting existing technologies to realize the needs of their gateway. Another 80% said they needed help simply understanding what technologies were available to them. The research community doesn’t just see the gap, they live it. This project seeks to quickly close the capability gap between academic and commercial infrastructure by extending and making robust the Agave Platform, an open, Science-as-a-Service cloud platform for reproducible science. Essentially, this project will allow scientists to focus their energies on their science rather than so much on the computing technologies they use.

This Agave Platform will build upon the success of the existing Agave Developer APIs which currently serve over 20,000 users in the plant biology community. This project includes three well-defined efforts which will synergistically evolve the current technology into a sustainable Science-as-a-Service platform for the national research community. First,it will extend the Agave Developer APIs with additional services and management interfaces to create a cohesive, self-provisioning Agave Platform which will enable Science-as-a-Service to the developer community. Second, the project team will partner with commercial and academic institutions to create a community driven Application Exchange (AX) based on Docker container technology to facilitate application transparency, portability, attribution, and reproducibility. Third, the project will consolidate existing open source contributions from projects already with the Agave ecosystem into Agave ToGo, a collection of reference science gateways in multiple languages and web frameworks. The Agave Platform will democratize access to software and infrastructure across all areas of science and engineering by modernizing the mechanisms with which the research community can utilize and access academic research infrastructure. This will bridge the gap between industrial and academic research infrastructure and allow researchers to use a new generation of open source software and technologies. The AX will enable greater interoperability and accountability in the way computational science results are published and reviewed. Through the matching investment of industrial partners, reproducibility, best practices, and rigorous scientific review will be brought to the mainstream and promoted as a fundamental aspect of the scientific process in an open, sustainable way. Agave ToGo will make custom gateways readily available to end users and developers alike. For end users, it will empower them to focus on domain science rather than computer science. For developers, it will stimulate innovation and increase the opportunity for discovery. When combined with the Agave Platform and Application Exchange, Agave ToGo will enable novice users to create scalable, reproducible, digital labs that span their office, commercial cloud, and national data centers in a matter of minutes.

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AwardsInventXRMovement ThinkingThe Research University

Data Visualization Literacy: Research and Tools that Advance Public Understanding of Scientific Data

Sponsor: Indiana University

Katy Borner [email protected] (Principal Investigator)
Kylie Peppler (Co-Principal Investigator)
Bryan Kennedy (Co-Principal Investigator)
Stephen Uzzo (Co-Principal Investigator)
Joe Heimlich (Co-Principal Investigator)

ABSTRACT

As the world is increasingly dependent upon computing and computational processes associated with data analysis, it is essential to gain a better understanding of the visualization technologies that are used to make meaning of massive scientific data. It is also essential that the infrastructure, the very means by which technologies are developed for improving the public’s engagement in science itself, be better understood. Thus, this AISL Innovations in Development project will address the critical need for the public to learn how to interpret and understand highly complex and visualized scientific data. The project will design, develop and study a new technology platform, xMacroscope, as a learning tool that will allow visitors at the Science Museum of Minnesota and the Center of Science and Industry, to create, view, understand, and interact with different data sets using diverse visualization types. The xMacroscope will support rapid research prototyping of public experiences at selected exhibits, such as collecting data on a runner’s speed and height and the visualized representation of such data. The xMacroscope will provide research opportunities for exhibit designers, education researchers, and learning scientists to study diverse audiences at science centers in order to understand how learning about data through the xMacroscope tool may inform definitions of data literacy. The research will advance the state of the art in visualization technology, which will have broad implications for teaching and learning of scientific data in both informal and formal learning environments. The project will lead to better understanding by science centers on how to present data to the public more effectively through visualizations that are based upon massive amounts of data. Technology results and research findings will be disseminated broadly through professional publications and presentations at science, education, and technology conferences. The 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 is driven by the assumption that in the digital information age, being able to create and interpret data visualizations is an important literacy for the public. The research will seek to define, measure, and advance data visualization literacy. The project will engage the public in using the xMacrocope at the Science Museum of Minnesota and at the Center of Science and Industry’s (COSI) science museum and research center in Columbus, Ohio. In both museum settings the public will interact with different datasets and diverse types of visualizations. Using the xMacroscope platform, personal attributes and capabilities will be measured and personalized data visualizations will be constructed. Existing theories of learning (constructivist and constructionist) will be extended to capture the learning and use of data visualization literacy. In addition, the project team will conduct a meta-review related to different types of literacy and will produce a definition with performance measures to assess data visualization literacy – currently broadly defined in the project as the ability to read, understand, and create data visualizations. The research has potential for significant impact in the field of science and technology education and education research on visual learning. It will further our understanding of the nature of data visualization literacy learning and define opportunities for visualizing data in ways that are both personally and culturally meaningful. The project expects to advance the understanding of the role of personalization in the learning process using iterative design-based research methodologies to advance both theory and practice in informal learning settings. An iterative design process will be applied for addressing the research questions by correlating visualizations to individual actions and contributions, exploring meaning-making studies of visualization construction, and testing the xMacroscope under various conditions of crowdedness and busyness in a museum context. The evaluation plan is based upon a logic model and the evaluation will iteratively inform the direction, process, and productivity of the project.

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AwardsInventXRMovement ThinkingThe Research University

Improving Collaborative Learning in Engineering Classes Through Integrated Tools

Sponsor: University of Illinois at Urbana-Champaig

Emma Mercier [email protected] (Principal Investigator)
Luc Paquette (Co-Principal Investigator)

ABSTRACT

The Cyberlearning and Future Learning Technologies Program funds efforts that support envisioning the future of learning technologies and advance what we know about how people learn in technology-rich environments. Development and Implementation (DIP) Projects build on proof-of-concept work that shows the possibilities of the proposed new type of learning technology to build and refine a minimally-viable example of their proposed innovation that allows them to understand how such technology should be designed and used in the future and that allows them to answer questions about how people learn, how to foster or assess learning, and/or how to design for learning. This project is focused on the teaching of collaborative problem solving activities in introductory engineering courses and builds on a prior project to design tools for collaborative sketching in these courses. The project is based on a recognition of the importance of collaborating in engineering, the need for student to learn this skill, the value of collaborative learning tasks for engaging students in authentic problem solving activities, and the difficulty that graduate student teaching assistants (TAs) encounter when trying to teach in this way. There are two parts to the technology innovation. The first part is a set of tools for the teaching assistants, to help them manage the classroom technologies, and to help them understand how to intervene in groups who are struggling with the content or collaborative processes. The second part is a set of tools for the students. Building on the collaborative sketch software previously developed, prompts to support their collaborative processes will be embedded in the software students will use, based on analysis of the logfiles that help determine who needs what prompts when. Research goals include understanding how receiving prompts changes the nature of students’ collaborative activity, and how receiving insight into the difficulties students are having helps TAs learn about to foster collaborative learning in their classes.

The PIs are addressing the difficulties encountered implementing collaborative learning activities in engineering courses by designing and studying tools for TAs and students in these classes. Through an iterative design approach, the PIs will design and study tools for TAs to orchestrate the classroom and collaboration activities and to tools for students which support their collaborative problem solving processes. The PIs will investigate the use of learning analytics in evaluating the collaborative practices of students using these tools; in particular, logfiles will be examined for collaborative indicators based on prior research on collaborative processes, then clustered to look for patterns of engagement, and finally used to create regression models of successful collaboration processes using machine learning techniques. Cross-validation of the models will be done with both logfile and video data to avoid overfitting. These insights will be provided to TAs to examine whether such information is helpful in determining how and when to intervene in groups. Findings from the research will provide insight into: 1) The knowledge that TAs need in order to successfully implement collaborative problem solving in undergraduate courses; 2) Whether TAs can learn more about collaborative problem solving with the support of tools aimed at helping them implement this form of pedagogy; 3) Whether students can learn collaborative problem solving skills through embedded prompts during multi-week collaborative activities and 4) The potential of analytics in determining when and how to reduce the collaboration supports from groups.

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