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Sample Selector

Sample Selector is a tool for creating and editing samples, or groups of data you compare across—they're not "samples" in the statistical sense, but more like filters.

By default, a single sample exists: "All Data". With the Sample Selector, you can create new samples to organize your data.

You can use samples to:

A sample is composed of one or more filters, specific conditions that narrow down your sample.

Creating a sample

The general process for creating a sample is to:

The effect of multiple filters

DataShop interprets each filter after the first as an additional restriction on the data that is included in the sample. This is also known as a logical "AND". You can see the results of multiple filters in the sample preview as soon as all filters are "saved".

Help

Teachersourcing and crowdsourcing ITS hints improvements (private) (terms of use)

Datasets Terms of Use

Project Terms of Use

Effective March 30, 2020

The following terms apply for this dataset and the other datasets in the project Teachersourcing and Crowdsourcing Hints Improvement.

Dataset Terms of Use

This dataset was made public under the Creative Commons license. It is under the license of Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). The was licensed to the researchers at Carnegie Mellon University working on this research project (under an approved IRB protocol), primarily including Vincent Aleven (PI), Kexin Yang (graduate student researcher).

Access to the Teachersourcing and Crowdsourcing Hints Improvement datasets is conditional upon agreement to terms of Creative Commons. You are free to share, copy and redistribute the material in any medium or format under the following terms:

  • You may not use the material for commercial purposes.
  • You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. That is, you will acknowledge Carnegie Mellon University in any publication resulting from this research and notify Vincent Aleven (vincent.aleven@cs.cmu.edu) and Kexin Yang (kexinyang.bella@gmail.com) of any publications resulting from this research.
  • No Derivatives: You agree that if you remix, transform, or build upon the material, you may not distribute the modified material.

Creative Commons Terms of Use

As these datasets were made public under Creative Commons license, using this datasets means you have acknowledged and agreed to the terms of use of Creative Commons (CC BY-NC-ND 4.0).

DataShop Terms of Use

The DataShop terms of use also apply.
Version 10.12.6 June 22, 2023