Grants
National Science Foundation Big Data Grant
BIGDATA Program of the National Science Foundation: Collaborative Research: F: Study of a Cyber-Enabled Social Computing Framework for Improving Practice in Online Computing Communities
Carolyn P. Rose, Carnegie Mellon University, is the principal investigator, along with Co-principal Investigators: James Herbsleb, Carnegie Mellon University; and George Siemens, UT Arlington.
The Principal Investigators (PIs) will examine environments that many people engage in independently to learn computing, online communities, and massive open online courses (MOOCs). This activity could be very compelling as people come to these environments because they have personal goals to learn the material. However, a challenge in these environments is that there is little support for learning. In addition, these environments are not adaptive to learners’ needs. This project will tackle both of these challenges. The PIs will first characterize groups of learners to understand their needs and then design approaches to personalizing the environments based on those needs.
The PIs address a need for both learning and independent online work communities by providing a combined learning work community. Many authentic production communities, such as GitHub, do not provide support for novices who want to learn to contribute. Similarly many learning communities, such as MOOCs and other online learning environments, do not provide outlets for learners’ products to become authentic. The PIs will combine data from MOOCs and online communities to discover groups of participants who behave in similar ways and investigate how to support the needs of these groups. This will lead to the proposed novel combined learning and work community that both provides support and offers authentic outlets for work products that are valued beyond a particular course.
The Digital Learning Research Network (dLRN)
The Digital Learning Research Network (dLRN), made possible by a $1.6m grant from the Bill & Melinda Gates Foundation, will form connections among researchers and educators to close the gap between research and practice. UT Arlington serves as the principal investigator for the grant and has partnered with Stanford, Carnegie Mellon University, University of Michigan, Smithsonian, SRI International, University System of Georgia, California Community Colleges, and University of Arkansas System. The participating researchers are leaders in innovative pedagogical approaches which will have important implications for the future of higher education. The primary beneficiaries of the project’s outcomes will be underrepresented learners and institutions that are making the transition to digital learning. The work for the two-year grant will include: 1) identifying commonalities between research capacities and institutional needs focused on research questions, 2) partnering Tier-One researchers with participating state systems, and 3) collaborating to develop appropriate, high-impact solutions. The goals of the grant are to help remove barriers to digital learning and articulate the conditions needed for successful learning for all students so that they may more fully participate in the global economy.
Additional details available on the dLRN website.
Christopher Brooks, University of Michigan, is the principal investigator, along with Co-principal Investigators: Stephanie Teasley, UMSI; and George Siemens, UT Arlington.
Online learning environments are rapidly expanding the nature of the data that can be collected about student opportunity to learn and the details of the learning process. Borrowing from multiple traditions, analysis of educational discourse data addresses multiple persistent problems in education, including the development of ways to better predict student success during a course and to design interventions to provide support. The researchers in this proposal will build a community to address three important areas: ethics in data sharing; technical issues in data sharing; and, plans for an infrastructure to support and develop capabilities in both of these. The community built in this effort will collaboratively create the necessary metadata and standards for data sets and tools, templates for appropriate approval to use online discourse data, and de-identification algorithms that can be shared across data platforms.
At the conclusion of the work, a white paper will be constructed and disseminated that addresses ethical and technical issues and solutions, as well as infrastructure needs to facilitate collaborative educational discourse research.
Smart Science Network for Postsecondary Success in Entry Level Science for Disadvantaged Students
The Smart Science Network project, funded by a $5.2 million grant by the Bill and Melinda Gates Foundation, is a collaboration between world-leading universities, community colleges, ed-tech companies, and learning experts to develop and deliver next-generation undergraduate science courseware. The network’s partners will combine their expertise, resources, and technologies to deliver on a shared mission: to materially improve the success rate of disadvantaged students in entry-level science courses, while inspiring them to address challenging problems and motivating them to persist through difficulty. This will be done through the development of Smart Courses – innovative, next-generation courseware that ties traditional science disciplinary material to transdisciplinary big questions of wide appeal, using project-based, interactive, adaptive, simulation-based, constructivist pedagogy that works at scale. Partnering with Smart Sparrow, e.mersion, and Arizona State University Online, George Siemens (UTA LINK Lab) will serve as both the learning analytics and research lead for project. He will work in collaboration with Shane Dawson (University of South Australia), Dragan Gasevic (University of Edinburgh), and Carolyn Rose (Carnegie Mellon University), utilizing machine learning, process mining, and learning analytics to investigate the effectiveness of social and immersive learning through the courseware.
MOOCs
Massive Open Online Courses (MOOCs) have created a surge of interest in the future of higher education in recent years. The “massive” nature of these courses indicates that they are attracting unprecedented numbers of students. For example, in an 18 month period, leading MOOC providers edX and Coursera enrolled nearly 10 million learners in close to 1000 courses. In Fall 2014, the LINK Lab spearheaded a MOOC focused on Data, Analytics, and Learning (DALMOC). DALMOOC attracted over 19,000 participants while serving as a test bed for several innovative designs and technology tools. The LINK lab and its research associates are currently examining the data from DALMOOC to see how they can glean insight into open online learning. Some of the issues that this analysis will examine include: How sustainable is the MOOC model (a question that has plagued MOOCs since the first MOOC was offered in 2008)? How well do learners adjust to new technology and course designs? What aspects of open learning are most effective in online environments? Additionally, large amounts of data were recorded about participant activities (clicks, activities, video views, etc.) in the course, the analysis of which can help researchers understand how these participants engage with free content.
Projected for Summer 2016 is a MOOC for the professional development of K-12 teachers entitled Emerging Technologies and their Practical Applications in K12 Teaching and Learning. Under the leadership of Andrew Berning, and in cooperation with the LINK Lab and the College of Education this course will be offered through the edX platform in four modules, each two weeks in length featuring insight from thought leaders and practitioners in the field. Major topics include connecting learners through technology, promoting literacies, and expanding assistive technology. Registrations will begin in November 2015.
Data Analytics
LINK Lab participates in LAK 16, the 6th International Learning Analytics and Knowledge Conference at the University of Edinburgh in Edinburgh, United Kingdom, April 25-29, 2016.