LASI13 Wednesday (2): Funding

Second liveblogging post from Wednesday 3 July 2013 at  LASI13 #lasi13, the Learning Analytics Summer Institute, at Stanford University, CA.

Panel: Funding and Institutional Support

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Chair: Taylor Martin

Learning Analytics Funding Opportunities

Edith Gummer (DRL), Janet Kolodner (CISE & DRL), Barry Sloane (DRL) – NSF. 

Via videoconference from DC. Directorate for Education and Human Resources.

Edith starts.

EHR Core research program (ECR). New this year. Mechanism for education and human resources to provide funding in foundational research areas that are broad, essential and enduring. Seeking proposals to synthesise, build and expand research foundations in all disciplines in STEM learning, environments, workforce development, broadening participation. The research you folks are interested in will find an appropriate home here.

NSF welcomes LA proposals for CORE. Broadening participation – how learners are engaging in learning about STEM, large and diverse pool of learners. Broadening participation should be central part of LA. STEM learning can be addressed too. Development of theories of learning and teaching in a more comprehensive, rigorous and compelling way with LA. Empirical evidence of learning. And methodologies for what counts as evidence about learning, and program evaluation.

Reconceptualise concepts of college and career readiness. Workforce development, 21st century skills and STEM learning, how skills might be enhanced across stages of learning. 

Proposals due 12 July 2013! NSF 13-355. Two types of proposals – ECR – a program, target dates not due dates. Core research proposals,< $1.5m budget max, 5y. Capacity building proposals, <$300k, 3y. Workshops, ideas labs, requests to bring researchers together in a new way. Address grand challenges of great importance that are enduring.

Other opportunities across CISE – cyberlearning transforming education; EHR – core research program, DRK-12, REAL, Ideas Lab for Data Intensive Research, SBE-EHR Building collaborative communities. 

Ideas Lab – Data-Intensive Research to Improve Teaching and Learning. Sandpit. Researchers come together to help identify research area in a field. Solicitation is out. Scheduled for autumn. Range of experts, incl educational researchers. Scope on determining research agenda. End of research lab is self-organisation and proposals submission. Not infrastructure development. Solicitation NSF 13-565, 2pp proposals due August 19 – why you should be invited, full proposals December 9. Proposing PIs do not have to attend the Ideas Lab. $5m total funding, up to 10 proposals.

Building Community and Capacity for Data Intensive Research – BCC-SBE/EHR. Infrastructure development. Researchers in large scale data in education, social science, planning/prototype grant for new ways to use data resources and analytics techniques to advance research. Integration of datasets, especially ones they’ve funded. Didn’t get many educational proposals last year, likely 6 or 7 this time.  Think broadly across multiple disciplines. Solicitation not yet released, previous was 12-538. About 25 awards with $5m. Probably another $3m because of lots of well-reviewed proposals.

Cyberlearning – Janet. 

Program shared across SBE, EHR, and CISE, idea to take multidisciplinary approach, transforming opps for learning and learning outcomes.Projects need three parts – informed by what is known about learning; make tech work – good enough – and draw out lessons from process; answer fundamental questions: when people can have experiences they couldn’t have without tech, and when software can collect data that wouldn’t otherwise get.

CTE continued, similar to previous solicitations. Four kinds of projects – exploration to try out new ideas; development and implementation; integration; capacity building. Require interdisciplinary teams – learning, domain learning experts, technology, scalability. Teams not very integrated, so capacity-building projects to help a team coalesce, or community coalescence like ideas lab or conferences. Have to be potentially transformative, not incremental. Add to the lit on how people learn, and contribute to model technology products. Must be in real-world contexts. 

Funding and Institutional Support

Ed Dieterlie (Gates Foundation)

The NSF is very transparent organisation. Shortcoming of ours, so want to answer questions.

Personalised learning at scale is their central goal in K-12 strategy – 80% of class to graduate high school college ready. Don’t need remediation. Currently 55m students in K12 pipeline. If they state on current trajectory, likely to not graduate college ready. Opportunity to accelerate learning and get those students back on track.

4.2m enter kindergarten each year. Goal to use 1 million in-school minutes wisely. Personalised learning key.

Confluence of breakthroughs moving towards that in the US. inBloom, Common Core Standards, Advanced Learning Analytics. Multi-state, open source cyber infrastructure, what should we study? Very divergent views. Best research play was to find common threads – building up human capacity for learning analytics. Have made 3 investments, plan many more.

First in learning analytics workgroup, Roy Pea PI. Gates and MacArthur. Help foundations understand major activities to take on, timeline, resources needed. 5y strategy. Second to Nat Acad Sci, Trish talked about it, it’s IRB reform. Not glamorous but important, influences 4000 IRBs throughout the US. Last investment, support of LASI13! Bringing together researchers to build the field. Once report issued in the fall, likely to make more.

Do invest in other spaces.

Three frameworks for puzzling through a potential investment. Four drivers – optimism, collaboration, rigor, innovation. Big tough messy challenges. Partnering key. Not just activities of those in the study, want strong research and evaluation to improve investments, report back to field. Think about where the Gates came from. 

Second – need, approach, benefit, alternatives. Think of the need first. 3.5m teachers in US, what do they need, how do you know? Then the marketplace – Stephen’s 2×2 matrix from yesterday. Diagrams, pictures even better than words. The benefit – how to measure. Also puzzle through alternatives – what to compare it to? Business as usal isn’t very creative. What’s similar to look at?

Last framework – learning questions is what separates a good from a great investment. Methods classes – be clear about purposes, conceptual context, methods, validity. (Don’t begin with methods.) 

Theory of action – draft! Working document. We change the map. Want to let you know we have notion of building blocks, feed in to whole school models, to intermediate outcomes, lead to long-term outcomes.

Funding and institutional support

Suzi Hewlett (Australian Office of Learning & Teaching)

Fun Prezi.

Australian Office for Learning and Teaching – promote excellence in T&L in Australian HE. Sixth body in the country to do this. Small budget – $14.5m/y for suite of awards and fellowships. Strongly encourage collaboration, including international partners to share and promote good practice. Networking and professional development within the sector, supported SoLAR Flare in Australia. Also advise ministers. Some love getting in to the data. Some just want high-level messages.

Three questions.

Vision for big data/LA. Policy issues and how you can help solve them. Demand-driven funding system created significant growth in student numbers, more non-trad backgrounds. Increased importance of support for retention and attainment. Focus on TEL used to enhance student outcomes, and LA to ID and support at-risk students.

Changing role of tertiary educator. New approaches to teaching, diverse students, quality. Not just individual student performance.

Investments funding? SNA and data vis to evaluate student behaviour. ICT to understand impact of L&T practices. Pilot enhancing learning experiences in LMS.

Want to know: What works and doesn’t? What do university staff know about the tools? How does university use LMS/analytics to identify groups and support them? ID good practice in analytics reporting? Is data matching done? Ethics, security and integrity issues. How many students use it to engage help.

You have to be in receipt of funding from Australian Government to get their funding. But can have international partners. 

No funding for capital projects, don’t like single institution projects. Keen not to reinvent the wheel, worldwide perspective.


Shirley: (inaudible)

Suzi: Deadline for proposals closed recently. Commissioned some work on LA from the sector. Proposals in, but also identify major themes of interest, scoping papers, ask what’s happening. Time to get a stock take about what’s happening, what people are doing, where they’re using it more broadly. One on elearning, graduate employability. 41 proposals from consortia around those issues. Will be commissioning that in a few weeks, and about what’ll be funded.

John Stamper: Opportunities for international collaborations at Gates, Australia?

Ed: Fund 3 things. Global health, vaccines. Global devt. In US, focus on education. Around education, 99% of effort is in US. We can imagine collaboration involving students and others in both countries.

Suzi: We love collaborations, as long as there’s an Australian university leading it. We don’t have big bucks. But we like international collaborations.

Ken: College success, or others. Do we understand the problems enough to focus on solutions. Do you think we know well enough why students are failing on the path to college such that efforts would focus on those. Or analytics to ID which problems are the real ones. Problem finding?

Ed: College readiness 3 dimensions – academic content knowledge, have stable measures; college knowledge, understanding what it takes to apply to, to go, right exams, references, etc, there are nascent measures; academic tenacity, long-term goals, getting back on the horse – red light there. Lot of theories, interventions to target range of things, but constructs not mature. We can imagine problem seeking – Ryan Baker measures of engagement, measures of persistence, measures of academic tenacity. All three can be improved. LA has promise to improve over e.g. student self-report.

Suzi: In government, we’ve been good at designing parameters of a program, getting proposals in. But bad at looking at impact of our investment on those whose lives it was intended to improve. We’re becoming more focused on impact evaluation. This is a key area, great field, great opportunity to come in and help us identify if we’ve achieved the objectives

Ed: Depending on the measure, college ready students, 30-40%. Goal is 80%. LA as well as personalisation as significant accelerator to get closer to the goal. Greatly shifting percentage. 

 Piotr: Rationale for area of focus. Increasing college readiness. Most of my time was wasted in high school. Emphasis to target students like that, don’t have advanced questions.

Ed: Right now, time is held constant, learning varies. One of our ideas is notion of mastery measures of learning. More like driver’s licence, when you’re ready, you sit for the assessment, regardless of how long you learned about it. A lot of effort going after that challenge. Don’t have scalable solutions.

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Author: dougclow

Data scientist, tutxor, project leader, researcher, analyst, teacher, developer, educational technologist, online learning expert, and manager. I particularly enjoy rapidly appraising new-to-me contexts, and mediating between highly technical specialisms and others, from ordinary users to senior management. After 20 years at the OU as an academic, I am now a self-employed consultant, building on my skills and experience in working with people, technology, data science, and artificial intelligence, in a wide range of contexts and industries.

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