DataShop provides two main services to the learning science community:

Researchers can rapidly access standard reports such as learning curves, as well as browse data using the interactive web application. To support other analyses, DataShop can export data to a tab-delimited format compatible with statistical software and other analysis packages.

Case Studies

Watch a video on how DataShop was used to discover a better knowledge component model of student learning. Read more ...

Systems with data in DataShop

Browse a list of applications and projects that have stored data in DataShop, and try out some of the tutors and games.
Read more ...

DataShop News

Tuesday, 7 November 2017

DataShop 10.0 released!

With this release of DataShop we continue to extend the functionality of Tigris, the LearnSphere workflow tool, as well as enhance it's usability. There is now a 'Recommended Workflows' section at the top of the main Tigris page. This list of workflows contains those we feel best highlight the most useful features of the tool. Using the 'Save As' button, these workflows can be used as templates for users to create their own workflows. In addition, on the main page, there is a search feature that allows users to filter the workflows by name, owner or component.

A focus of this release has been adding support that facilitated the creation of many new components. For example, dynamic options are now supported. This provides component developers with option constraints that can trigger changes to the UI based on the user's selections. Dependencies can be combined in logical combinations to accomodate complex parameter sets.

The new Linear Modeling Analysis component uses this feature, allowing users to call the R functions lm, lmer, glm and glmer on a data file of their choice.

Similarly, the component definition language was extended to allow for optional inputs on components. These are common in components which generate data and also take an optional set of inputs or parameters. An example of this is the new Tetrad Graph Editor. Tetrad is a causal modeling tool that allows users to build models, simulate data from those models (or use them on real data), apply algorithms to the models and graphically display the causal relationships found.

Many features of Tetrad are now supported as Tigris workflow components, making it easier for researchers to do multiple analyses on datasets that may include data from both DataShop and external sources. For example, the following Tetrad support is now available in Tigris:

  • Data Conversion
  • Classifier
  • Estimator
  • Search
  • Knowledge
  • Graph Editor

Following is an example workflow with several of these components. A tab-delimited data file is transformed both to filter missing values and then discretize those values before passing the data to the Search component which searches for causal explanations represented by directed graphs.

Also, two new Analysis components have been added by colleagues at LearnSphere@Memphis. They facilitate analyses of a wider variety of learning sciences data. The new modeling components are TKT (Temporal Knowledge Tracing) and LSA (Latent Semantic Analysis).

Source code for all of the LearnSphere components can be found in our GitHub repository. If you would like to add your analysis, import, transform or visualization component(s) to Tigris, please contact us for information on how to get started.

The last release added 'Request Access' support to workflows, allowing users to request access to data and results in public workflows with shareable data, but it required that all of the data used in the workflow be shareable. Workflows often use multiple data sources, though, so authorization is now enforced per-component. This means that workflows which include both private and shared data can be partially accessed by users. Results and data that are inaccessible show up as 'Locked' components.

In addition to the above Tigris improvements, the following features were added to DataShop:

  • The Learning Curve Model Values page now includes the 'Number of Unique Steps' and 'Number of Observations' for each skill (KC) in the selected Knowledge Component model.
  • The Web Services API was extended to allow users to query and modify project authorization values.
  • Tigris and DataShop both now support a GitHub login option.

Posted by Cindy at 2:00 PM

Wednesday, 1 November 2017

Attention! DataShop downtime for release of v10.0

DataShop is going to be down for 2-4 hours beginning at 8:00am EST on Tuesday, November 7, 2017 while our servers are being updated with the new release.

Posted by Cindy at 3:00 PM

Tuesday, 27 June 2017

DataShop 9.4 released - several Tigris enhancements and bug fixes

The latest release of DataShop includes several enhancements and bug fixes for Tigris, the LearnSphere workflow tool.

Returning users will notice a new user interface for Tigris. We have changed the look-and-feel of the tool while making numerous styling improvements and fixing several bugs.

The biggest change is the addition of Request Access support to Tigris. DataShop users are familiar with the feature that allows users to request access to projects with private, shareable datasets. This feature has been extended to Tigris; users can request access to data directly from the Workflows page.

Workflows that use private, shareable data will have a REQUEST button with which users can ask for access to the workflow data. Without access to the data, users are able to view the Public workflows as a template only. Regardless of data access, users can make a copy of any Public workflow for use with their own data.

Most of the Tigris components now have tooltips which contain information on what the component does, the required input(s) and the output(s) generated as well as the component options.

The implementation code for each of the Tigris workflow components is publicly available in GitHub. If you would like to add your analysis, import, transform or visualization component to Tigris, please contact us for information on how to get started.

In addition to these Tigris improvements, the maximum allowed size for Custom Field values has been increased -- the new limit will now allow for values up to 16M in size -- and a bug in the renaming of Knowledge Component (KC) models has been fixed.

Posted by Cindy at 5:00 PM

Sunday, 25 June 2017

Attention! DataShop downtime for release of v9.4

DataShop is going to be down for 2-4 hours beginning at 9:00am EST on Monday, June 26, 2017 while our server\ s are being updated with the new release.

Posted by Cindy at 5:00 PM

Thursday, 16 February 2017

DataShop 9.3 released - Beta version of Tigris

The latest release of DataShop includes a Beta version of the workflow tool, now referred to as Tigris.

In order to facilitate the sharing of analyses, Tigris users can view global workflows created by other users. If the data included in a workflow is public or is attached to a dataset that the user has access to, then the workflow imports, component options and results are all accessible. If the user does not have access to the dataset they can view the workflow as a template. In both cases, users can create a copy of the workflow for use with their own data.

As part of the LearnSphere project, contributors from CMU, the University of Memphis, MIT and Stanford have been building workflow components, many of which are already available in Tigris. The latest code, with descriptions of each component, can be found in GitHub. If you would like to add your analysis, import, or visualization component to Tigris, please contact us for information on how to get started.

In addition to Tigris improvements, we have added a few enhancements and fixed several bugs:

  • Users can now make a web service call to retrieve the list of data points that make up any given Learning Curve graph. The list of points can be generated for a particular skill in a specific skill model (KC Model). More about this feature can be found in the updated DataShop Public API doc.
  • For OLI datasets, the Learning Curve graphs were extended to include a "high stakes error rate" data point. If you have an OLI dataset for which you'd like to see this analysis, please contact us as we will need to reaggregate your dataset to generate the necessary information.

  • Long Input values were being truncated in the Error Report. This issue has been addressed.
  • The Problem List page was failing to load for datasets with a very large number of problems per hierarchy, or dataset level. This has been fixed.
Posted by Cindy at 10:00 AM

Friday, 10 February 2017

Attention! DataShop downtime for release of v9.3

DataShop is going to be down for 2-4 hours beginning at 8:00am EST on Thursday, February 16, 2017 while our server\ s are being updated with the new release.

Posted by Cindy at 03:00 PM

Friday, 14 October 2016

DataShop 9.2 released - Alpha version of Workflow tool

The latest release of DataShop introduces an analytic workflow authoring tool. The alpha version of this tool allows users to build and run component-based process models to analyze, manipulate and visualize data.

The workflow authoring tool is part of the community software infrastructure being built under the umbrella of the LearnSphere project, with partners at Stanford, MIT and the University of Memphis. The primary data flow in a workflow is a table so users are not restricted to DataShop data. The platform will provide a way to create custom analyses and interact with proprietary data formats and repositories, such as MOOCdb, DiscourseDB and DataStage.

Users can request early access to the Workflow tool using the "Workflows" link in the left-hand navigation. Once granted access, this becomes a link to the "Manage Workflows" page, which is also available as a main tab on each dataset page.

Workflows are created by dragging and dropping components into the tool and making connections between components. Options can be configured for each component by clicking on the gear icon . For example, in the import component, users can upload a file or choose from a list of dataset files for which they have access.

Once a workflow has been run, clicking on any component's magnifying glass icon or the primary "Results" button will display the output of each component. A preview of the results is also available as a mouse-over on the component output nodes.

In the near future, we will invite users to contribute their own components to the Workflow tool. This feature will allow researchers to share analysis tools, for application to other datasets.

In addition to the Workflow tool, we have added a few enhancements and fixed several bugs:

  • The Metrics Report now includes an "Unspecified" category for datasets without a Domain or LearnLab configured. In previous releases these datasets were not reflected in the report, causing the amount of data shown to be less than the actual data.
  • KC Model exports are now being cached, allowing for faster exports of models in the same dataset.
  • Users running their own DataShop instances will find that Research Goals now include links to recommended datasets and papers on the master server, DataShop@CMU.
  • For Dataset Uploads, two restrictions on the upload format have been relaxed. See the Tab-delimited Format Help for details.
    • If a Step Name is specified, the Selection-Action-Input is no longer required.
    • Previously, if both the Problem View (PV) and Problem Start Time (PST) were specified, then the PV was recomputed based on the PST. With this release, if the two values do not agree, the PV in the upload is used.
  • Users are now required to select a Domain/LearnLab designation during dataset upload.
Posted by Cindy at 10:00 AM

Tuesday, 26 April 2016

DataShop 9.1 released

In the spirit of collaboration, this release focuses on integration with our LearnSphere partners, with the long-term goal of creating a community software infrastructure that supports sharing, analysis and collaboration across a wide variety of educational data. Building on DataShop and efforts by partners Stanford, MIT and the University of Memphis, LearnSphere will not only maintain a central store of metadata about what datasets exist, but also have distributed features allowing contributors to control access to their own data. The primary features in support of this collaboration are:

  • DataShop now supports both Google and InCommon Federation single sign-on (SSO) options. SSO allows users to access DataShop with the same account they're already using elsewhere, e.g., your university or institution in the case of the InCommon login.

    If you currently use the local login option, please contact us about migrating your account to one of the SSO options.

  • Users can now upload a DiscourseDB discourse to DataShop. With support for DiscourseDB, users can view meta-data for discourses and, with appropriate access, download the database import file (MySQL dump).

  • We have developed a DataShop virtual machine instance (VMI) which allows users to configure their own slave DataShop instance. The remote (slave) instance is a fully-functioning DataShop instance that runs on your server, allowing you to maintain full control over your data, while having your dataset meta-data synced with the production, or master, DataShop instance. If you are interested in having your site host a remote DataShop instance, please contact us.

In addition to the headlining features, this release also adds the following support:

  • Users can now create a sample of their dataset by filtering on Custom Fields. Sampling by the name and/or the value of the custom field is supported. This allows users to create subsets of datasets based on particular values assigned to each transaction by the tutor. For example, a step can be categorized as being high- or low-stakes for the student and the tutor can mark the relevant transactions with this information allowing those analyzing the data to filter on this information.

  • The Additive Factors Model (AFM) is no longer limited explicitly by the number of skills in a skill model. Previously, AFM would not be run if there more than 300 skills in a model. Now, the number of students and the size of the step roll-up, as well as the number of skills, factor into the decision.
  • The file size limit for dataset and file uploads was increased from 200MB to 400MB.
  • The number of KC Models in a dataset is now part of the dataset summary on the project page.

Bug fixes

  • Alignment errors were fixed in the KC Model Export for the case of multiple models with multiple skills.
  • Clearing the Project on the Dataset Info page no longer results in a error.
  • The Error Report now correctly displays HTML/XML inputs in the Answer and Feedback/Classification columns. Similarly, display errors resulting from inputs that contain mark-up, were fixed in the Exports.
Posted by Cindy at 10:00 AM

Friday, 4 September 2015

DataShop 9.0 released

With the latest release of DataShop, our focus was on fixing bugs and enhancing a few existing features.

  • Users can now quickly navigate from problem-specific information in a Learning Curve or Performance Profiler report directly to that problem in the Error Report; an "Error Report" button has been added to the tooltips. The Error Report includes information on the actual values students entered and the feedback received when working on the problem.

  • In the Performance Profiler, if a secondary KC model is selected, the skills from the secondary model that are present in the problem are included in the problem info tooltip.

  • If the Additive Factors Model (AFM) or Cross Validation (CV) algorithms fail or cannot be run, the reason is now available to the user as a tooltip. The tooltip is present when hovering over the status in the KC Models table. If you have a follow-up questions, remember that you can always send email to datashop-help.

  • Users can now sort the skills in a particular KC model to indicate learning difficulty. By sorting the KC model skills by intercept and then tagging those for which the slope is below some threshold, users can easily identify skills that may be misspecified and should be split into multiple skills. See the DataShop Tutorial videos on how to change the skills and test the result of that change. This sorting feature is available on the "Model Values" tab of the Learning Curve page.

  • The Cross Validation calculation was modified to provide more statistically valid results. The new calculation computes an average over 20 runs in determining the root mean squared error (RMSE).

Bug fixes

  • The Student-Step Export was updated to print only a single predicted-error-rate value for steps with multiple skills, as the values are always the same.
  • The Help pages for the Additive Factors Modeling (AFM) have been updated to indicate that DataShop implements a compensatory sum across all Knowledge Components when there are multiple KCs assigned to a single step.
  • The KC Model Import was fixed to ensure that invalid characters cannot be used in the model name not only during initial model import, but also in the dialog box that comes up when a duplicate name is detected.
Posted by Cindy at 10:00 AM