Hello, and welcome!
This document will explain how to use the Claned Data Export tool. We will cover each setting, data type and filtering methods so you can easily build your own data report using the tool. To access this tool, you need to have Admin privileges in your organization. You can find the tool when you open the admin panel and go to the advanced tab. Example export reports can be found at the end of this article.
1. What is the purpose of this tool?
The Claned platform collects comprehensive learning activity and results data. While some selected analysis examples are available in the board analytics tab, the Data Export Tool (hereafter abbreviated as DET) allows you plenty of freedom to export the data that you require to the analysis tools that you prefer to use. In short, the DET is the middleware that enables custom analytics at your end.
The exported data is tabular and saved to your computer as a CSV file i.e., a plain text file with comma-separated values per row. Most spreadsheet software, such as Microsoft Excel, can easily import CSV files. In the typical Python environment, e.g., JupyterLab, you can easily use the Pandas data analysis library to load these CSV files.
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2. How it works
By default, a data report contains rows for all users in your organization that have data for whatever datatype you select. Rows reflect users (by default), groups or labels depending on how you group the data. Columns reflect individual content pieces (by default), boards, or content types (e.g. documents, videos). Depending on the datatype(s) you choose for your report, data can refer to any event (e.g. login, signup, content view), text (comment, note), or a calculation produced by Claned (board score, media resource progress). If a user does not have data for a given datatype, they will not appear in the report. For example, if you select the “Content view” and “Comment” datatypes, then a user that has not viewed content nor left any comments on your boards will not appear in the report at all. If that user has viewed at least one content, then they will have a row for the Content view event but no row for comments. Again, this is with the default settings (no filters or grouping applied).
There are many possible combinations of filters, groupings, and datatypes to choose from so that you can generate the perfect data report for your needs. We always recommend selecting only the essential datatypes for your reports, and filtering or grouping the data so that the report is well-organized and easy to parse (readable), not just for yourself and colleagues or stakeholders, but also for any computer systems that may process the file. At the end of this document, we will cover different calculation and grouping types. These settings will help you to quickly get a summary of the data without having to modify it afterwards or perform calculations on your own.
Please note that this is a Beta version of the tool, so there is a small chance that you may encounter issues. Please send any feedback you may have to our Support team at support@claned.com.
Menu to select the data you want to download. We recommend fetching only one data type per report, otherwise the outcome might be confusing as the data is not in the same format.
3. Data types:
Interest rating
Rating menu that collects the different rating metrics from learners after each content.
The difficulty, interest and skill rating are an academic metric for engagement. Difficulty and skill rating form the classical “Flow” state: https://en.wikipedia.org/wiki/Flow_(psychology) These metrics will allow you to explore how your course and students are performing.
Description: A rating that learners can use to provide feedback on your course content, specifically how interesting it was. It is collected after each content (video, assessment, article, link or embedded content).
Format: Cell value is the given rating for interest (1-5) for each rated content piece. No value is provided if content is not rated. “Timestamp“ column shows the time the rating was made.
Use cases: Count the average interest for items, courses or see interest rating per user to understand your course performance.
Skill rating
Description: A rating that learners can use to provide a rating to describe their skill level for the topic of a content piece. It is collected after each content (video, assessment, article, link or embedded content).
Format: Cell value is the given rating for skill (1-5) for each rated item. No value is provided if content is not rated. “Timestamp“ column shows the time the rating was made.
Use cases: Count the average perceived skill for items, courses or skill rating per user to understand your learners’ perceived skill in each topic.
Challenge rating
Description: A rating that learners can use to provide a rating to describe how challenging the topic is. It is collected after each content (video, assessment, article, link or embedded content).
Format: Cell value is the given rating for skill (1-5) for each rated item. No value is provided if content is not rated. “Timestamp“ column shows the time the rating was made.
Use cases: Count the average perceived challenge for items, courses or skill rating per user to understand your learners’ perceived skill in each topic.
Signup
Description: Signup is tracking the events of users signing up for the platform. Each registration event will create an event that will be counted as signup.
Format: Each event is logged as a count of signups. By default, each event is its own row (as users can only have one signup), so you will see only one row for this datatype per user. “Timestamp“ column shows the time the user signed up.
Use cases: Count the number of signups within different time periods to for example track course enrollment status etc. Also can be used together with other data points to see for example signup activity between different groups, e.g. location or title.
Comment
Description: Comments track the commenting events. It will create one row for each comment event per user.
Format: Each comment is logged as a commenting event with a timestamp. Content of the comment is not included in the event. “Timestamp“ column shows the time the comment was left on the content.
Use cases: Can be used to track anything related to commenting: active commenters, popular content to comment, active times for commenting. Can help to identify socially active boards for closer inspection.
Board score
Description: Overall score for a given board, calculated from the board’s grading settings you’ve defined.
Format: A numerical value (0-100) representing the accrued “points” according to the board grading settings (Assessments, Progress, Comments, Manually rated items, or a combination of these). “Timestamp“ column shows the time of the last relevant event based on whatever grading settings you have chosen for a board. For instance, your last grading event for a given user’s assessment, the most recent comment left by a user, or an opening of a content piece.
Use cases: Generating a periodic report of user grades across boards for import into your LMS for tracking how learners develop over time. This allows you to identify e.g. poorly-performing learners for intervention.
Assessment completion
Description: Assessment completion will give a value based on if assessment is passed or not. It will return information of an assessment attempt to a given filtered assessment.
Format: Each attempt is logged with either 0 (not passed) or 1 (passed). The "Timestamp” column show when an assessment attempt was made.
Use cases: Can be used for tracking amount of attempts per assessments, tracking amount of failed attempts. Also as an activity metric if looking for amount of assessment attempts in whole organization for example.
Content view
Description: Each time an activity is opened on a board, a content view event is created. This is represented in the report by the account details of a user, the time the event occurred, and which content was viewed.
Format: One row per content view event; the cell value “1” marks this event. If a user did not view any of the content pieces included in the report, they will either not have a row for that datatype, or not appear in the report entirely (if they do not have rows for the other datatypes in your report). The “Timestamp“ column shows the time the content was opened.
Use cases: Can be used to track popularity of different contents, content viewing activity between boards or activity between different users or groups of users.
Login
Description: Each time a user logs in to the platform, a login event is created with user details and timestamp.
Format: How the rows appear is dependent on your grouping and calculation selections. No grouping means that each login event for a given user has its own row and an additional timestamp column (when the login occurred).
Use cases: Can be used to track logins for users. For example compare activity between different groups or general activity over time in the platform. Note: if users has Claned always open, a new login event is not tracked, so login should not used as the only source of comparison, but as one of many.
Assessment score
Description: A user’s final score for a given assessment.
Format: A numerical value representing a user’s total number of points scored for a given assessment. The “Timestamp” column reflects the time an assessment was completed or graded.
Use cases: Viewing the average score for a given assessment across users in a group (use “Filter by group” filter), or across groups (use “Each group as a row” grouping).
Note
Description: A value representing how many private notes have been left for a given piece of content.
Format: Each note is logged as a commenting event with a timestamp. Content of the note is not included in the event. The “Timestamp“ column shows the time the note was left on the content.
Use cases: Check to see how many notes users are leaving on any given content. This can be useful to gain insight into learners’ study habits as well as which content pieces engage learners.
Media resource progress
Description: Progress is defined for each user for each content depending on their progression through the content itself.
Format: A value between 0 and 1. If user has not opened up the content, it will get value of 0. It translates to percentages directly, so a value of 0.67% would mean that 67% of the content has been completed. That would mean 1 minute of 3 minute video or 2 pages of 6 pages document. When the value is 1, it means that the content has been fully completed. Must always be used together with user-grouping : all user as one row, each user as one row, each group as one row, each label as one row. The “Timestamp” column is not generated when a grouping option is applied.
For assessment, it will use values 0, 0.5 and 1. 0 if assessment is not opened, 0.5 if there is an attempt that is failed (according to assessment settings) or it’s waiting for grading and 1 if the assessment has been completed successfully.
Use cases: Can used to get an idea of overall progress % for users for each content, overall progress % per user for the board itself or for example compare average progress between groups for specific boards.
Complete path
This data type has been deprecated and will be removed from the selection menu in an upcoming release.
4. Data Filters
Time period
Selecting the time period will allow you to filter data only to be fetched from a specific time period. We recommend using recent data, as it will make requesting the data much faster.
Filter users
The "Filter users" section allows you to include only specific groups into the data export. To be able to fetch data from specific groups of users we recommend using filters. You can choose any existing group(s) in your organization. Doing so will only include events from users who are members of selected groups.
Filter content
In the "Filter content" section, you can choose to fine-tune your data by filtering by a board, content type, or content labels
Filter by board:
You can choose any boards you want to fetch the data from. You can choose any, none or just one. The default is none, meaning all boards will be included in the report dependent on any other filters you may have chosen. The board name will be displayed in the report so you can easily see the differences between the groups.
Filter by content type:
You can choose which content types you want to include. By default, it will show data from all content types but you can choose combinations of any items.
Filter by labels:
You can choose which specific content items you want to include based on their labels. If no labels exist, then no data will appear in the selection list
5. Data grouping and export calculation methods
In the "Group the data" section, you can choose to group the data in the export spreadsheet to whatever row/column format you desire.
Groupings are an easy way to help with organization of the data file. The grouping section of the data export tool has two primary elements, 1. grouping (column and row, both can be selected), and 2. a calculation type. When a grouping option is selected from either the column or row menus, the calculation menu will appear (“Select how data will be calculated”). Data will be condensed into just one row (e.g. each user has only one row) or column (e.g. each board shared to your organization has its own column). The data value in each cell will be aggregated based on what calculation you select in the “Select how data will be calculated” menu. You can choose to calculate data by Sum, Average, Count, Minimum value, or maximum value.
Average will calculate the data to average. For example, average media resource progress or average skill rating for an item, if user had 0.5, 1, 0.75 and 0.1 as the reported media resource progress it would display value of 0.5875 as the average.
Sum will group the data to a sum of the values it has received. If user has scored 56, 21,17 and 80 for assessment if using sum as the calculation type it would be reported as 174.
Count will provide the total count of event disregarding the value of the item. For example each login event is reported as “1”, so count would provide each row with a login event and provide the value or rating events of 5,3,2,4 would be 4.
Max will report only the largest value.
Min will report only the smallest value.
Use cases: For most cases, we recommend using grouping for the sake of easier parsing of the data report file. However, if you want, for instance, track all login events from all users of a group, then select the login datatype, filter by the relevant group, and do not apply any grouping. This will return each login event as a row. Alternatively, if you want to see the total number of logins for each user in a group, then follow the first two steps mentioned above, but this time select “Each user as a row” grouping, and the “Count” calculation. The value shown in the data file is a number reflecting the total number of logins. Of course, we recommend experimenting with the different groupings to find the one that best suits your needs.
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Please see this article for an example a commonly used data export for seeing user progress in their courses.
More examples coming soon!