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

Tab-delimited format

You can import a tab-delimited text file of transaction data similar to that generated by the DataShop transaction export. Use the Upload Dataset page to upload and verify your file(s). You may want to import data as tab-delimited text to:

  • create a smaller dataset from an existing one
  • rename problems or steps
  • clean up an existing dataset
  • add data to DataShop without creating XML

Read more about the import process.

Note: If you want to create a new domain KC model for an existing dataset in DataShop, use the KC Model export/import feature.

Format Documentation

Import file column requirements are described below.

For a handy list of columns, check out our printable DataShop Cheat Sheet.

Column Required? Additional Description Size Limit (characters)
Anon Student Id * An anonymized student identifier. ≤ 55
Session Id * A dataset-unique string that identifies the user's session with the tutor. ≤ 255
Time * Local time when the transaction occurred. For instance, if a student types "25" and presses return, the transaction time is at the point in which they press return. Must be given in one of the following standard time formats [1]
Time Zone Local time zone ID as provided by the zoneinfo (or tz) database. Select a time zone name from the "TZ" column in this List of zoneinfo time zones. ≤ 50
Student Response Type A semantic description of the event. DataShop-expected values are ATTEMPT or HINT_REQUEST. See the corresponding "Tutor Response Type" below. ≤ 30
Student Response Subtype A further classification of student response type. ≤ 30
Tutor Response Type A semantic description of the tutor's response. DataShop-expected values are RESULT or HINT_MSG. See the corresponding "Student Response Type" above. ≤ 30
Tutor Response Subtype A further classification of tutor response type. ≤ 30
Level () * A Dataset Level. An example of the correct use of this column heading is Level (Unit), where "Unit" is the dataset level title and the value in the column is the level name (e.g., "Understanding Fractions"). The Level column should always be of the format Level (level_title). The level title must be ≤ 100 characters and consist of letters, numbers, dashes, underscores, and spaces. If a dataset level title is not included, it will become "Default". Multiple Level columns are OK. For additional description, see the level element in the Guide. In tutor-message format XML, level "title" is referred to as "type". ≤ 100
Problem Name * The name of the problem or activity. ≤ 255
Problem View The number of times the student encountered the problem so far. This counter increases with each instance of the same problem. If this column is not provided you must provide the Problem Start Time; it will be used to determine the Problem View. If both are provided, but it is determined that they do not agree, the Problem View will not be recomputed. A longer description of problem view, including how it is determined if it's not present in the imported data, is available here.
Problem Start Time The time the problem is shown to the student. Must be given in one of the standard time formats [1]. This column is used to determine the Problem View if it is not given. If both are provided, but it is determined that they do not agree, the Problem View will not be recomputed. A longer description of problem start time, including how it is determined if it's not present in the imported data, is available here.
Step Name The name of a discrete problem-solving step. Include a step name for a transaction if the transaction also has a Tutor Response Type and an Outcome. Otherwise, Attempt At Step will not be calculated. ≤ 255
Attempt At Step DataShop ignores the values in this column when processing the import file. "Attempt at Step" is computed from the rest of the transaction data, but only if Step Name is provided.
Outcome The tutor's evaluation of the action, if applicable. DataShop prefers the values CORRECT, INCORRECT, or HINT. ≤ 30
Selection A description of the interface element that the student selected or interacted with. Multiple Selection columns are OK. Also see Selection in the Guide. ≤ 255
Action A description of the manipulation applied to the selection. Multiple Action columns are OK. ≤ 255
Input The input the student submitted. Multiple Input columns are OK. Also see Input in the Guide. ≤ 255
Feedback Text The body of a hint, success, or error message shown to the student. ≤ 65,535
Feedback Classification A further classification of the outcome. See action_evaluation / classification in the Guide. Note that if Feedback Classification has a value, Feedback Text must have a value as well. ≤ 255
Help Level Applicable only to hints, this is the current hint level/depth. If given, value must be a number.
Total Num Hints Total number of hints available to the student for this step. If given, value must be a number.
Condition Name A study/experimental condition. Must always be paired with Condition Type, even if a condition does not have a condition type. Multiple Condition Name columns are OK. See condition in the Guide. ≤ 80
Condition Type A condition classification. Must always be paired with Condition Name, even if a condition does not have a condition type. Multiple Condition Type columns are OK. If Condition Type is specified, Condition Name must have a value as well. ≤ 255
KC () A knowledge component. An example of the correct use of this column heading could be KC (Area), where 'Area' is the KC model name for that knowledge component. The KC column should always be of the format KC (kc_model_name). The model name must be ≤ 50 characters and consist of letters, numbers, dashes, underscores, and spaces. If a KC model name is not included, the name will default to "Default". Multiple KC columns are OK. ≤ 65,535
KC Category () A knowledge component category. An example of the correct use of this column heading could be KC Category (Area), where 'Area' is the KC model name for that knowledge component. The KC Category column should always be of the format KC Category (kc_model_name). The model name must be ≤ 30 characters and consist of letters, numbers, dashes, underscores, and spaces. If a KC model name is not included, the name will default to "Default". If including KC Category, be sure to pair it with a corresponding KC column by using the same KC model name. (Condition Name and Type must be paired together in the same way.) If you specify a a KC Category value, a KC value must be given as well. Multiple KC Category columns are OK. ≤ 50
School The school in which the data were collected, if applicable. ≤ 100
Class The class in which the data were collected, if applicable. ≤ 75
CF () A custom Field. Use this element to describe other contextual information or a new variable not adequately captured by the other columns. An example of the correct use of this column heading could be CF (Factor or add-m), where 'Factor or add-m' is the name for that custom field. The CF column should always be of the format CF (custom_field_name). The custom field name must be ≤ 65,000 characters and consist of letters, numbers, dashes, underscores, and spaces. If a custom field name is not included, the name will default to "Default". Multiple CF columns are OK. ≤ 65,000
Event Type Optional. Allowed values are: assess, instruct and assess_instruct; an empty value is interpreted as assess_instruct. The value in the Event Type column affects how the opportunity count is computed for the Student Step Rollup export. Values of instruct and assess_instruct cause the opportunity count to be incremented by 1. Value of instruct causes the Outcome column to be blank. ≤ 30

At least one of Step Name, Selection, or Action must have a value for each row.

[1] Time must be given in one of the following formats:

Format Example and Notes
yyyy-MM-dd HH:mm:ss.SSS2001-07-04 12:08:56.0 ** OLI and DataShop export format
yyyy-MM-dd HH:mm:ss:SSS2001-07-04 12:08:39:110 ** Carnegie Learning format
yyyy-MM-dd HH:mm:ss2001-07-04 12:08:56 ** CTAT Flash format
yyyy-MM-dd HH:mm2001-07-04 12:08
MMMMM dd, yyyy hh:mm:ss aJuly 04, 2001 12:08:56 AM ** WPI-Assistments format
MM/dd/yyyy HH:mm:ss2/24/2007 17:18:02
MM/dd/yyyy HH:mm2/24/2007 17:18
MM/dd/yy HH:mm:ss:SSS07/04/01 12:08:56:322
MM/dd/yy HH:mm:ss07/04/01 12:08:56
MM/dd/yy HH:mm07/04/01 12:08
yyyy/MM/dd HH:mm:ss.SSS2010/05/11 16:06:28.65 ** CTAT Java format
long1239939193 ** Unix time in milliseconds
double01239939193.31 ** Unix time in milliseconds
Bad formats
mm:ss.008:56.0
This date-less format is the result of Excel applying its own formatting. You may see this format if you opened and saved a DataShop transaction export file in Excel, but didn't apply TEXT formatting to the columns while opening it. See our advice on how to avoid this issue. To correct it, you will need to find a copy of your file that has date information.

[2] For columns that are required as pairs— Condition Name and Condition Type, or KC and KC Category—these columns must be listed in the order that they are paired. For example, if a dataset file has two condition columns, the column format would be Condition Name, Condition Type, Condition Name, Condition Type.