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Call for Participation

3rd Annual Learning Science Workshop

Research and Innovation for Enhancing Achievement and Equity

June 14-15

Carnegie Mellon University

Pittsburgh PA

Applications Due May 15, 2014

No Cost To Attend

Overview

LearnLab, an NSF Science of Learning Center (SLC) at Carnegie Mellon and the University of Pittsburgh, has an exciting summer research opportunity available to early career researchers in the fields of psychology, education, computer science, human-computer interfaces and language technologies.

The workshop is targeted to senior graduate students, post-docs and early career faculty. The workshop seeks broad participation, especially members of underrepresented groups as defined by NSF (African American, Hispanic, Native American) who may be considering a research or faculty position in the learning sciences.

This two-day workshop immediately precedes the LearnLab Summer School (www.learnlab.org/opportunities/summer/).  Our workshop theme is the research and innovation for enhancing achievement and equity, including these five areas:

·      Enhancing Achievement through Educational Technology and Data Mining.  Using domain modeling, and large datasets to discover when learning occurs and to provide scaffolding for struggling students. See www.learnlab.org/research/wiki/index.php/Computational_Modeling_and_Data_Mining.

·      21st Century Skills, Dispositions, and Opportunities. Re-examining the goals of education and assessment and considering transformative changes in how and where learning occurs. 

·      Opening Classroom Discourse.  Studying how classroom talk contributes to domain learning and supports equity of learning opportunity.  See LearnLab's Social-Communicative Factors thrust www.learnlab.org/research/wiki/index.php/Social_and_Communicative_Factors_in_Learning.

·      Course-Situated Research.  Running principle-testing experiments while navigating the complex waters of real-world classrooms.  See www.learnlab.org/research/wiki/index.php/In_vivo_experiment.

·      Motivation Interventions for Learning. Implementing theory based motivational interventions to target at risk populations to improve robust student learning. See http://www.learnlab.org/research/wiki/index.php/Metacognition_and_Motivation

The substantive focus of the workshop is the use of current research and innovations to enhance achievement and equity at all levels of learning. Activities will include demonstrations of the diverse set of ongoing learning sciences research projects at LearnLab, and poster presentations or talks by participants. Participants will also meet with LearnLab faculty in research groups and various informal settings. We will provide information about becoming a part of the Carnegie Mellon or University of Pittsburgh learning science community.

In addition to these substantive themes, the workshop will provide participants with opportunities for professional development and the chance to gain a better understanding of the academic career ladder. These include mentoring that focuses on skills, strategies and "insider information" for career paths. Sessions will include keynote speakers and LearnLab senior faculty discussing professional development topics of interest to the attendees. These may include the tenure and promotion process, launching a research program, professionalism, proposal writing, among other topics.  There is no cost to attend this workshop

We are very pleased to announce that the workshop will have two distinguished keynote speakers:

Dr. Tawanna Dillahunt is a Presidential Postdoctoral Fellow at the University of Michigan’s School of Information. Her research interests are in the areas of human-computer interaction, ubiquitous computing, and social computing. She is primarily interested in identifying needs and opportunities to further explore how theories from the social sciences can be used to design technologies that have a positive impact on group and individual behavior. With the narrowing of the digital divide, the ubiquity of smart devices and mobile hotspots in common places in the U.S. (e.g., libraries, community centers, and even McDonald’s) she sees an urgent need to explore the use of these technologies for those that stand the most to gain from these resources. Therefore, her research targets the use of these technologies among people in disadvantaged communities. Results from her past studies in the environmental sustainability domain suggest that improved communication provides individual community members with access to new information and helps to resolve common problems. Dr. Dillahunt plans to continue to apply her past research techniques to clarify and potentially meet the needs of disadvantaged, and often understudied communities in environmental and economic sustainability, and in other domains such as education and health. Her goal is to design and enhance innovative technologies to solve real-world problems.

She holds a M.S. and Ph.D. in Human-Computer Interaction from Carnegie Mellon University, a M.S. in Computer Science from the Oregon Graduate Institute School of Science and Engineering (now a part of the Oregon Health and Science University in Portland, OR), and a B.S. in Computer Engineering from North Carolina State University. She was also a software engineer at Intel Corporation for several years.

Dr. Charles Isbell is a Senior Associate Dean and Professor in the School of Interactive Computing in the College of Computing at Georgia Institute of Technology. Dr. Isbell's research passion is artificial intelligence. In particular, he focuses on applying statistical machine learning to building autonomous agents that must live and interact with large numbers of other intelligent agents, some of whom may be human.

Lately, Dr. Isbell has turned his energies toward adaptive modeling, especially activity discovery (as distinct from activity recognition); scalable coordination; and development environments that support the rapid prototyping of adaptive agents. As a result he has begun developing adaptive programming languages, worrying about issues of software engineering, and trying to understand what it means to bring machine learning tools to non-expert authors, designers, and developers.

Dr. Isbell earned his M.S. and Ph.D. from MIT and his B.S. in Computer Science from Georgia Tech in 1990.

About LearnLab

LearnLab is funded by the National Science Foundation (award number SBE-0836012).  Our center leverages cognitive theory and computational modeling to identify the instructional conditions that cause robust student learning.  Our researchers study robust learning by conducting in vivo experiments in math, science and language courses. We also support collaborative primary and secondary analysis of learning data through our open data repository LearnLab DataShop, which provides data import and export features as well as advanced visualization, statistical, and data mining tools. 

To learn more about our cognitive science theoretical framework, read our Knowledge-Learning-Instruction Framework.

The results of our research are collected in our theoretical wiki which currently has over 400 pages. It also includes a list of principles of learning which are supported by learning science research. The wiki is open and freely editable, and we invite you to learn more and contribute.

Application Process

Applicants should email their CV, this demographic form, a proposed presentation title and abstract, and a brief statement describing their research interests to Jo Bodnar (jobodnar@cs.cmu.edu) by May 15, 2014. Please use the subject Application for LearnLab Summer Workshop 2014. Upon acceptance, we will let you know if you have been selected for a talk or poster presentation.

Costs

There is no registration fee for this workshop.  However, attendance is limited so early applications are encouraged.  Scholarships for travel are available.  Scholarships will be awarded based on your application, including your research interests, future plans, and optional recommendation letter.

Important Dates

·      May 15 Application Deadline

·      May 29 Notification of Acceptance

·      June 14-15 Workshop held at Carnegie Mellon University in Pittsburgh