Announcements
- DataShop 6.2 released!
- DataShop 6.1 released!
- The Cross-Linguistic Study of Reading Acquisition Workshop co-hosted by Charles Perfetti
- NIPS Tutorial on Machine Learning for Student Learning
- Strong LearnLab presence at NIPS Workshop: Personalizing education with machine learning
- Blog Post About MS LSE!
- OLI and LearnLab presentation at House of Representatives
- Ilya Goldin Co-Edits Journal of Writing Research
- Ken Koedinger on Big Data in Education Panel
- Vincent to become co-editor of Int'l Journal of AI in Education.
Apr 05 2013DataShop 6.2 released!
DataShop 6.2 released - upload datasets, project access enhancements, and moreWith today's update to DataShop, we've made another big step toward allowing you to import datasets directly. You can now upload a file to be imported into DataShop, as well as create and manage projects and files-only datasets. All progress on the import of your datasets will be shown in the Import Queue at the top of My Datasets. Upload datasetsTwo new items in the main navigation under My Data—Upload a dataset and Create a project—allow you to get started adding new data to DataShop. You can create a dataset with or without transaction data. Transaction data is data that is in either of the two formats DataShop accepts (XML and tab-delimited). More info about these formats can be found in our help. After you upload a dataset with transaction data, you'll see it in the new Import Queue on the My Datasets page. Information about the file format verification and import status (such as estimated import date) will be show in the queue and emailed to you. Manage project access directlyOn each project page in DataShop you'll see an updated Permissions tab. If you are a project admin for that project, you can now see the list of people who have access to your project, modify that access, and grant access to new users directly by entering their username (in addition to responding to requests for access). An access report for that project is also available. New "condition" column in the student-problem exportThe "condition" column is now also included in the student-problem export, in addition to the transaction and student-step exports. Access Report optimizationsThe Access Report, which shows who has accessed your projects and what their permissions are, has been optimized to be much faster. You can view the main Access Report on the Access Requests page. Jan 24 2013DataShop 6.1 released!DataShop 6.1 released - new navigation, error bars, improved project pages, and moreRevised home page and navigationThe latest version of DataShop has a new navigation section along the left-hand side of the application. We've grouped together things that are specific to your account—your datasets, access requests, and profile—under the heading My Data. My Datasets now appears under this heading, while Public Datasets and Private Datasets (renamed from Other Datasets) appear under the heading Explore. We have also removed the login box in favor of the login page. (To log in, just click the "Log in" button.) Error Bars in Learning CurvesTurn on error bars on a learning curve by clicking the "Error Bars" checkbox in the navigation. You can choose between error bars that represent one standard deviation or one standard error. New project pages and subtabsA project in DataShop is a way to group together datasets and specify who has permissions to those datasets. In this release, the project page has new fields for a project description (what are these datasets about?), tags (words describing the project or its data), and external links (links to a research page, wiki, or anything else). You can view your current permission level for a project from the new "Permissions" subtab. "Terms of Use" has been moved to its own subtab. With this new project page, more information will be capable of being captured and indexed, making pages more intelligible to both researchers and Google search. Revised permissionsIn addition the the existing project access levels of "edit" and "view", we've added a third—"admin". A project admin has full control over a project and its datasets. This role will be even more useful when we've added the ability to upload datasets. We've created a table to show the difference between the three roles. As of this release, if you were a PI for a project, you are now also its admin. IRB managementAnother addition to the project page is a subtab called "IRB" (visible if you are the project admin for a project). When you add a dataset to DataShop, you must complete a few steps on the IRB subtab of your project page. These requirements, specified in the latest IRB for DataShop and on our help page, apply to all datasets added to DataShop after April 2012. Included in these are requirements for what you must do before being allowed to use DataShop to share data outside of your immediate research team. More information about this process is available on our help page. Change to Performance Profiler controlsWe've added controls for changing the X and Y axes to the navigation area. The existing controls, which can be accessed by positioning your cursor over the X and Y axis labels, are still available. Tweaks to access requests and the access reportWe made the following changes related to access requests and the access report:
Jan 21 2013The Cross-Linguistic Study of Reading Acquisition Workshop co-hosted by Charles PerfettiCharles Perfetti co-hosted a workshop on the The Cross-Linguistic Study of Reading Acquisition held at the Netherlands Institute for Advanced Study. Co-hosted by Ludo Verhoeven of the Radbout University of Nijmegen, the workshop brought together researchers who represented 17 different languages and their writing systems to examine how learning to read is similar and different across these languages and writing systems. Jan 17 2013NIPS Tutorial on Machine Learning for Student LearningNIPS Tutorial on Machine Learning for Student Learning was held December 03, 2012 and was conducted by Emma Brunskill and Geoffrey J Gordon. Intelligent tutoring systems and online classes have the potential to revolutionize education. Realizing this potential requires tackling a large number of challenges that can be framed as machine learning problems. We will first provide a survey of several machine learning problems in education, such as modeling a student's thought process as she solves a problem, constructing the atoms of knowledge, and automated problem design. We will then discuss cognitive modeling and instructional policy construction in more depth, and describe state-of-the-art methods as well as ongoing challenges. Throughout the tutorial we will highlight where student learning results in opportunities for new algorithmic and theoretical advances in machine learning. Jan 17 2013Strong LearnLab presence at NIPS Workshop: Personalizing education with machine learningStrong LearnLab presence at the NIPS Workshop: Personalizing education with machine learning. Emma Brunskill gave an invited talk Pedagogical Activity Selection: Drawing Insight From Sequential Decision Making Under Uncertainty José González-Brenes presented his poster Topical HMMs for Factorization of Input-Output Sequential Data Nan Li presented here poster Automated Creation Of Intelligent Tutoring To Support Personalized Online Learning Richard Scheines gave a talk on Machine Learning, Causal Model Search, and Educational Data LearnLab Alums April Galyardt, Andrew Ng, Min Chi, and Norma Ming, Richard Scheines also presented talks. Dec 14 2012Blog Post About MS LSE!Another blogger posted about the new Learning Science and Engineering Masters Program. Click the link below to see more: Dec 10 2012OLI and LearnLab presentation at House of RepresentativesNice video at the house of representatives given on the emerging field of science of learning. Speakers included Jared Cohen, Martha Kanter, Ken Koedinger, and Candace Thille. Nov 07 2012Ilya Goldin Co-Edits Journal of Writing ResearchIlya Goldin Co-Edits a special issue of the Journal of Writing Research. He also published a new paper in the same journal. The reference and link to the paper are below. Ilya M. Goldin & Kevin D. Ashley, Eliciting formative assessment in peer review, Journal of Writing Research 4(2), 203-237. http://www.jowr.org/Ccount/click.php?id=56 The special issues focused on Redesigning educational peer review interactions using computer tools with guest editors Christian D. Schunn, Kevin D. Ashley, & Ilya M. Goldin Click the link below to see the issue. Nov 05 2012Ken Koedinger on Big Data in Education PanelKen Koedinger was on panel at Strata conference on Big Data in Education entitled:
Click the link to find the full list of speakers at the conference. Oct 26 2012Vincent to become co-editor of Int'l Journal of AI in Education.Congratulations to Vincent Aleven who was named co-editor of International Journal of AI in Education along with Judy Kay. |