Mar 30 2010Summer School Application Deadline Extended to April 16, 2010
Find out more:
http://www.learnlab.org/opportunities/summer/
Apply by clicking below or by visiting http://www.learnlab.org/opportunities/summer/application.php
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Feb 18 2010DataShop 4.0 Released!
New DataShop Web Services features, plus more
There seemed to be a lot of interest in DataShop Web Services at the
DataShop User Meeting in November. At the time of the meeting, we could only
demo what was in development. We're now happy to release the services we
previewed. We hope these two new features—Get Transactions and Get
Student-Step Records—will make Web Services a useful
approach for researchers who want to automate data retrieval and
analysis.
Get Transactions
https://pslcdatashop.web.cmu.edu/services/datasets/[id]/[?samples/id]/transactions
- Get a tab-delimited response (can be zipped as well) of transactions
for a given dataset or sample and your request parameters
- If a sample ID is not provided, transactions for the "All Data"
sample will be returned.
Get Student-Step Records
https://pslcdatashop.web.cmu.edu/services/datasets/[id]/samples/[?id]/steps
- Get a tab-delimited response (can be zipped as well) of student-step
records for a given dataset or sample and your request parameters.
- If a sample ID is not provided, student-step records for the "All
Data" sample will be returned.
Learn more about these new services on the Web Services
page.
We've also released the following tweaks and improvements:
- Project announcements. On the home page that lists
the datasets in DataShop, you'll see a small box with the title
"Announcements" that shows recent news about the project, with links to
the full news posts.
- Learning curve point info "Obs" column. When
clicking on points in a learning curve, you can now see the frequency of
items going into the breakdown by KCs/Problems/Steps/Students. For
example, before you could only tell that data for 13 steps contributed
to an aggregate point in the learning curve, and you could see error
rate values (for example) for each, but you didn't know how much each
step contributed to the aggregate. Now, an "Obs" (Observation) column
displays the frequency of each item in the aggregate, so you can tell
which step is contributing most to that error rate.
- "#" column header renamed to "Row, "Total # Hints" renamed
to "Total Num Hints". In all of the export formats,
the "#" symbol, which appeared in the column header of the first column to
represent the number of the row, is now the text "Row". In the
transaction export format, the column header "Total # Hints" is now
"Total Num Hints". We made these changes because
the "#" character is a comment character in analysis programs such as R, so
directly opening a DataShop export file was problematic.
- The DataShop import file verification tool was also changed to
expect a column with the title "Row" instead of "#" and "Total Num
Hints" instead of "Total # Hints". If you plan on importing data
into DataShop, you will need to make these changes to your
file(s).
- Study "Condition" in student-step export. You'll
now see a "Condition" column in the student-step rollup. This new column
appears as the last column in the table. In the case of a student
assigned to multiple conditions (factors in a factorial design),
condition names are separated by a comma and space. This differs from
the transaction format, which optionally has "Condition Name" and
"Condition Type" columns.
- Cached export file status. With the DataShop
release in April 2009, we started caching transaction export files,
resulting in less wait time and faster downloading of these files.
Caching, however, is done on a sample-by-sample basis, and it wasn't
clear from the DataShop interface which samples were cached or when they
were created. We're now displaying a small table on the transaction
export page that shows the cache status of each sample and when that
cached file was created. This will tell you which samples can be
downloaded most quickly and those that will take longer (but will be
cached when you request them). The date and time of the cached file
tells you the cutoff for data included in the file, useful if you're
running a study that's logging to DataShop. To learn more about the
various states of a cached export file, visit our
help
topic on exporting.
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Oct 12 2009Internship Program in Technology Supported Education (IPTSE)
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.
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Jul 14 2009AIED 2009 PSLC Best Paper Awards
Congratulations to all:
At AIED2009:
Best student paper
Martina Rau, Aleven Vincent and Nikol Rummel. Intelligent Tutoring Systems with Multiple Representations and Self-Explanation Prompts Support Learning of Fractions
Honorable mention for best paper:
Ryan Baker, Adriana de Carvalho, Jay Raspat, Vincent Aleven, Albert Corbett and Ken Koedinger. Educational Software Features that Encourage and Discourage “Gaming the System”
Jul 14 2009Carnegie Learning and WPI Take Top Honors at EDM '09
Congratulations to Carnegie Learning and to Zachary and Neil as well on their winning papers at EDM '09.
Best Paper
Steven Ritter, Thomas Harris, Tristan Nixon, Daniel Dickison, R. Charles Murray and Brendon Towle. Reducing the Knowledge Tracing Space.
[pdf]
Student's Best Paper
Zachary Pardos and Neil Heffernan. Determining the Significance of Item Order In Randomized Problem Sets.
[pdf]
Jun 25 2009DataShop v3.4 Released!
Hi Everyone,
Ah, another summer another release. The one you've been waiting for.
- Exporting new samples is faster than ever
- Learning Curve Point Info Details
You can now drill down on the point of a learning curve to find out
what problems, steps, students or knowledge components make up that
point. Take a look at our 30-second
video that demonstrates this new feature.
Exporting by transaction for a brand new, very large sample is no
longer slow like we told you before. For example, a sample with 344,530
transactions took 2 hours to export before but now it takes only 7
minutes! That's 17 times faster.
On our new Case
Studies page, you'll find stories of DataShop use—what were some
research goals and how was DataShop used to approach them? The first,
presented as a 7-minute
video, illustrates the use of DataShop to perform exploratory
analysis of DataShop data, generate a theory for optimizing a cognitive
model, and test that theory both visually and statistically within
DataShop. We hope these are helpful to others who have used DataShop,
are considering using DataShop, or want to learn more about the project.
We also created a publications
page and posted our Educational Data Mining 2008 paper there. We
think it serves as a good introduction to the project and web
application.
It turned out we had an out-of-date FAQ on learnlab.org and a few other
sources of similar information, so we've revised and combined them into
this new FAQ.
Going forward, we'll keep this one updated with answers to real
frequently asked questions.
As always, keep up-to-date on the latest DataShop news on our about page.
Apr 02 2009DataShop v3.3 Released!
We have good news for you! There is a new version of DataShop that does two things faster:
- Creating new samples
- Exporting by transaction
You can now create samples faster than before, and the bugs associated with creating big samples on large datasets have been fixed as well.
Also, we are caching the transaction export files before you ask for them to make the download of these files "infinitely" faster than before. For example, the 'Algebra I 2006-2007 (6 schools)' dataset, which has 5.4 million transactions, has been cached.
But we still have work to do: exporting by transaction for a brand new, very large sample is still slow—for example, a sample with 344,530 transactions takes 16 minutes to create and 2 hours to export by transaction. For samples larger than this, you should opt to wait a day to retrieve it so that DataShop has time to cache it, or contact us if it's urgent. The fix for this problem is coming in our next release in June.
Oct 28 2008PSLC Server Downtime
PSLC-OLI course and study delivery software, DataShop, and logging services will be unavailable Tuesday, November 11, 2008 due to system upgrades and maintenance. Downtime will start around 6:00 am EST and could last until 2:00 pm EST.
Jul 29 2008Salden et al Win CogSci IES CaSL Prize
Ron Salden, Vincent Aleven, Alexander Renkl, and Rolf Schwonke won for Worked examples and tutored problem solving: redundant or synergistic forms of support?
This Pittsburgh/Freiburg collaboration would not have happened without the PSLC.
The Cognition and Student Learning (CaSL) Prize, is sponsored by the Institute of Education Sciences, and given to the best full paper submission to the 2008 Annual Conference of the Cognitive Science Society on a topic directly related to cognitive science, educational practice and subject-matter learning.
Click below to read the paper...
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Jul 08 2008Min Chi Wins ITS Best Student Paper
Congratulations to Min Chi!
At the Intelligent Tutoring Systems conference, she won the Best Student Paper award for her paper "Eliminating the Gap between the High and Low Students through Meta-Cognitive Strategy Instruction"
