Opportunities @ LearnLab
LearnLab's program provides support for talented undergraduates to spend two months during the summer working in a research laboratory at Carnegie Mellon University or the University of Pittsburgh. The program aims to encourage the participation of underrepresented students in our graduate programs and to make LearnLab's programs more visible to students not traditionally exposed to our fields.
Partnering with Minority Institutions - LearnLab is interested in increasing diversity in the learning sciences. As such we are actively seeking partnerships with researchers and universities at minority institutions such as those listed on the Department of Education website. At http://www.ed.gov/about/inits/list/whhbcu/edlite-list.html and http://www.ed.gov/about/inits/list/whtc/edlite-tclist.html If you are interested in pursuing a relationship with LearnLab, please contact us.
This internship program in technology-supported education will draw on broad areas such as mobile learning, educational games, technology-assisted language learning, computer-assisted collaborative learning, intelligent tutors, machine learning, educational data mining, human-computer interaction, as well as speech and language technologies. The goal is to create an international bridge between institutions of higher learning in India and Carnegie Mellon University, which is at the forefront of research both in technology and in the learning sciences in the U.S., and even worldwide.
This internship program will provide valuable research training opportunities for Indian undergraduates through a partnership between one of India's premier technical universities and one of the top ranking schools of computer science in the world, with the goal of expanding the pool of talented young researchers in India. A secondary goal is to provide a mechanism through which ongoing research partnerships can form and flourish between researchers at institutes for higher learning in India and researchers at Carnegie Mellon University, such as taking the form of co-advised B-Tech projects. And finally, the internship program directly benefits the infrastructure for education in India as a biproduct of the research projects the students will engage in. As part of the internship program, participants will focus on topics relevant to education in India, and in the developing world more generally.
The internship program will be composed of two stages. In the first stage, students will apply to participate in a two-week winter school from December 10-22, 2009 in Hyderabad. During these two weeks, students will attend lectures that will cover research and research methodologies, tools and techniques, insights about theory and practice, and a broad overview of the field of technology-supported education. Students will participate in team projects, which will be presented in demo sessions at the end of the winter school. Students who successfully complete the winter school will be invited to apply for research internships at Carnegie Mellon University. Successful applicants for stage two will be matched with internship advisors for a summer internship at Carnegie Mellon University's main campus in Pittsburgh, USA, for summer 2010. Some financial support for the summer internship may be available.
The LearnLab Summer School is an intensive 1-week course on technology-enhanced learning experiments and building intelligent tutoring systems. The summer school will provide a conceptual background and considerable hands-on experience in developing, running and analyzing technology-enhanced learning experiments. This past year's summer school was held July 13-17, 2009.
Research Assistance for Graduate
This is an internal source of funds aimed at providing existing LearnLab grad students with small supplements to more established grants, or to an existing, but as yet unfunded, proposal to LearnLab or outside agency, etc. All graduate students supervised by LearnLab-funded faculty are eligible to apply. RAGS proposals may be submitted at any time. The LearnLab Education Director, in conjunction with one of the LearnLab Directors, will make funding decisions within two weeks. Proposal inclusions:
- Project Title
- Name of LearnLab faculty advisor.
- Identification of the overarching funded project and thrust within LearnLab.
- Project Description including the core research question
- Expected Results
- Budget and Justification (i.e., why do you need the $$?)
The following ground rules apply:
1. No more than one grant per graduate student per year.
2. No "banking", i.e., if you don't get one in one year, doesn't mean you are entitled to two the next year.
3. Max $1000.
4. Students must submit a 500-word proposal, as well as a description of the larger LearnLab project (and the Thrust) of which the proposed work is, or could become, a part.
5. A clear and reasonable justification for the budget.
6. Students should allow a two week lead time before an answer is required.
7. Recipients of RAGS grants are expected to file a brief report at the end of the grant period describing how the funds were actually used, what was accomplished, etc etc (2 - 3 pages). In addition, they will be asked to provide brief progress reports, as needed, in order to meet various LearnLab reporting deadlines (Advisory Board meetings, site visits, annual reports, etc.)
Send RAGS requests to David Klahr:
Attending Graduate School in Areas Related to LearnLab
Students who are interested in applying to graduate school to work on subjects in the Learning Sciences are encouraged to see the websites of the Departments and Institutes at Carnegie Mellon and the University of Pittsburgh that are affiliated with LearnLab. They should contact those Departments for more information since applications go to them, not to LearnLab directly
Postdoctoral Positions at LearnLab
Postdoctoral candidates have can identify a faculty of interest from one our participating Departments and Institutes at Carnegie Mellon and the University of Pittsburgh (see the member list on the website) and contact that faculty member directly to inquire about the possibility of joining their research team.
Faculty and Graduate Students Can Run a LearnLab In Vivo Experiment
Learning researchers worldwide are invited to run in vivo learning experiments in a LearnLab course.
Participants can run studies in an affiliated course or one of our seven supported LearnLab courses. Two of which are in mathematics and taught at the high school level (Algebra and Geometry); two are in the sciences and taught at the college level (Physics and Chemistry). The remaining three are in the language arts and are also taught at the college level (Chinese, French, and English as a second language).
For qualified individuals and organizations interested in conducting an external study, we can provide you with a detailed course curriculum as well as a description of our logging capabilities. Email email@example.com for more information. Please indicate which course or courses for which you are interested in running a study. Also please briefly state your qualifications.
Faculty and Graduate Students Can Analyze Learner Data
Learning researchers worldwide are invited to submit projects to analyze data from the LearnLab DataShop. Data from student interactions are being stored in LearnLab's DataShop and being made available to learning researchers. The data comes primarily, but not exclusively, from online student interactions with intelligent tutoring systems and other interactive software in use one of our seven LearnLab courses (see above). Find out more by following links to the DataShop on www.learnlab.org.
Faculty members interested in an extended visit should contact one of the directors or a faculty member of interest.
Summer Research Experience for Undergraduates
No longer offered. LearnLab at Carnegie Mellon and the University of Pittsburgh has an exciting summer research opportunity available to undergraduate students. This program encourages applications from students who would like to do research in the fields of psychology, education, computer science, human-computer interfaces and language technologies.