Reporting and Insights - General - Leadership Academy

Once you have navigated to the Current Courses dashboard, you can run a report to track enrollments, participation, and collaboration across all courses that are currently running, as well as unpaced courses. 

1. Click on Filters at the top of the page.

2. Next, select whether or not to include cohorts with no end date, i.e. unpaced courses.

3. From the dropdown, choose the initiative(s), course(s), and cohort(s) you would like to report on. You can include as many initiatives, courses, and cohorts as you’d like. Tip: If you have many to include, you can change any of the dropdowns to “excludes” and then select only the initiative(s), course(s), and/or cohort(s) you would like to exclude from the report.

4. Finally, select the dimension you would like the results filtered by from the options listed. Be sure to use consistent, accurate, and “clean” data to ensure the dimension codes are valuable to your organization.

5. Click Run to generate your report. Tip: Almost every figure and chart is clickable in the dashboard, allowing you to dive deeper into the data and gain valuable insights. For example, if you’d like to view who was silent in the discussion activities, you can click the light blue portion of the Discussion graph.

Learn more about how to download a Current Courses report PDF and how to download a Current Courses report CSV.

This article describes the Learner Communication Report data, access, and uses.

What is the Learner Communication Report?

The Learner Communication Report is a tabular report that displays the details of each instance of learners’ communication with others in a cohort, including via attachments.  It allows administrators to analyze and audit all learner input in one view without navigating through a course to gather data.    

Learner activity types included in Learner Communication Report:

• Discussion
• Breakout Group Discussion
• Dropbox
• Private and Public Breakout Group Results
• Cohort Collaboration

Data fields for activity types included in Learner Communication Report:

• Activity Type
• Activity Name
• Breakout Group
• Date
• Post User
• Post
• Reply User
• Reply
• Likes
• Attachments

Notes:  

• Not all activities will have data for all fields, due certain functions only applying to certain activities.  
• For a discussion reply entry, the original post is restated in the row for context.
• Default table sort is by Date.

How to access the Learner Communication Report

1. Click on the bar chart icon in the website header (note: if you do not see the icon, you are likely not a site owner or site admin and should contact your Customer Success representative to request this permission). 

2. Click on the Learner Communication Report tile.   

3. Click to expand the Filters section.

4. Populate the filter(s) for course and cohort desired. Note: This report may be run for one cohort at a time.  

5. Click Run.

6. To export to csv, click the vertical ellipsis in the top right corner of the table, and ‘Download Data’. Note: please refrain from downloading as PDF from the gear icon.

What can I do with this data?

• Find compelling quotes from participants or moderators to use in a summary or for coaching purposes.
• Find themes in learner discussion to use in a summary and inform current or future initiatives. Consider using a word cloud generator to surface prominent keywords or phrases.  
• Determine what posts/replies had the most likes to understand conversations that were attracting the attention of the cohort.  
• Retain for compliance purposes.

When learners complete at least 70% of all required activities in a course, they receive our standard survey in-app to help measure their learning and gather their feedback. If any questions were not answered, the survey reappears at 90% completion as well. 

This survey helps populate the High Impact Learning Dashboard (HILD), contributes to our benchmarks, and allows our internal teams to continuously improve the course experience for learners.

This article provides instructions on how to navigate to the Current Courses dashboard and Completed Courses dashboard, where a site owner or site admin can generate a report and view analytics and insights from one or more cohorts.

Navigating to the Current Courses dashboard:

1. Click on the bar chart icon in the website header (note: if you do not see the icon, you are likely not a site owner or site admin and should contact your Customer Success representative to request this permission).

2. Next, click on the report you are looking for.

You are now in the dashboard. 

• Learn how to generate a report in the Current Courses dashboard
• Learn how to generate a report in the Completed Courses dashboard

Once you have navigated to the Completed Courses dashboard, you can run a report to track enrollments, participation, and collaboration across all courses that have completed. 

1. Click on Filters at the top of the page.

2. Next, from the dropdown, choose the initiative(s), course(s), and cohort(s) you would like to report on. You can include as many initiatives, courses, and cohorts as you’d like. Tip: If you have many to include, you can change any of the dropdowns to “excludes” and then select only the initiative(s), course(s), and/or cohort(s) you would like to exclude from the report. 

3. Next, choose the timeframe to include in the report. Tip: Best practice is to use the date range option.

4. Finally, select the dimension you would like the results filtered by from the options listed. Be sure to use consistent, accurate, and “clean” data to ensure the dimension codes are valuable to your organization.

5. Click Run to generate your report. Tip: Almost every figure and chart is clickable in the dashboard, allowing you to dive deeper into the data and gain valuable insights. For example, if you’d like to view who was silent in the discussion activities, you can click the light blue portion of the Discussion graph.

Learn more about how to download a Completed Courses report PDF and how to download a Completed Courses report CSV. 

As learners are added to the platform, there are important factors to keep in mind to ensure the accuracy and consistency of the data set for each learner. Data that is coded in a consistent manner without errors will result in what is frequently referred to as “clean data,” the lack of which will prevent you from experiencing the full benefits of the platform’s reporting and analytics features.

What data should you include?

Our platform offers the following data fields you can associate with each learner:

*Required in order to make an account

**Only required for organizations using Single Sign On. Consult your Customer Success representative for more information .

***Hire date format: YYYY-MM-DD

****Custom field that can include whatever data your organization prefers (e.g. division), but which stays the same across the organization. Learn more about how to configure custom Organization Unit data fields.

*****Completed by the learner when they update their profile.

******Used to designate the learner’s manager for use with the My Team feature.

Why does consistent data entry matter?

The data fields themselves are standard, but the codes you use for each learner within each of the fields is flexible. For example, what your organization wishes to regard as different regions or career levels is up to your organization; there are no standards you are forced to use. However, you must remember to stay consistent in your coding and use the same nomenclature for all learners you add to the system. If you are inconsistent, leading to “unclean data”, the analytics dashboards treat each variation as a separate code and the graphs and charts included will not provide the highest possible value without data cleanup.

Common examples of inconsistent data

Inconsistent data takes many forms and has many implications throughout the platform.

Inconsistencies that will lead to separate codes in all analytics reports:

• Using abbreviations sometimes and not others, e.g. “North America” vs. “NA”
• Variations in punctuation - e.g. “NA” vs. “N.A.”
• Variations in capitalization - e.g. “NA” vs. “na”
• Using different scope of measurement - e.g. “North America” vs. “United States” vs “California”
• Different cohorts using different units of measurement or different data categories altogether (i.e. one cohort’s roster being uploaded with Organization Unit 1 representing company division, while another cohort’s roster has Organization Unit 1 representing job function).

In the example above, the Organization Unit 1 field includes divisions (e.g. “Finance”), US states (e.g. “Cleveland”), and regions (e.g. “Asia Pacific”).

Inconsistencies that will lead to errors when bulk uploading users into the platform:

• Using column headings that do not exactly match the labels used by our platform (listed above), including proper use of underscores, spaces, and capitalization. Note: Even if your file is uploaded without errors, data could still be missing from learners’ profiles if the column headings are not labeled properly 
• Using special characters in any data field 
• Using your organization’s labels instead of the platform labels for the three custom fields, organization_unit1, organization_unit2, and organization_unit3
• Not completing external_guid if your organization uses Single Sign On
• Not using a CSV UTF-8 file
• Including special characters in your CSV file or having a very long file name

Therefore, we strongly encourage creating a data template and sharing that with all current and future groups at your organization using the cohort learning platform. Please speak with your Customer Success representative for more information.

What do I need to consider when setting up my data fields?

While it may seem unnecessary at first, it’s important to think long-term about how the data from the platform will be used to provide value to your organization. Without proper planning, you are likely to run into a situation where inconsistencies cause issues.

Questions to consider:

1. Will other groups within your organization use this cohort learning platform? If so, would they find value in the way you’d like to code custom data fields (i.e. Organization Units 1-3) and other data fields?

2. For the custom data fields, what data is most valuable to your company? Is it more important to distinguish learner performance data by division, for example, or is there another field that would be valuable and necessary to include?

3. How will the learner data be added to each course roster? Will all groups using the platform go through HR at your company, or will they build the roster themselves? If there is a consistent process to create rosters, you can work with the appropriate team members to ensure consistency.

Clean and consistent data is an extremely important component of the cohort learning process. If you are unsure about any aspect of the data management process, please contact your Customer Success representative.

Benchmarks provide a standard to which you can compare results on the High Impact Learning Dashboard (HILD) across organizations and courses. 

Our Benchmarks are dynamic and are updated once per week to reflect the most recent and most accurate information. Your benchmark score represents the average score among learners within our metrics of Engagement, Advocacy, and Understanding. The benchmarks add a great deal of value and represent a standard of comparison unrivaled in the industry.

All UBLA Courses Benchmark: Average score for that metric among learners from all courses, across all customers

UBLA Course Benchmark: Average score for that metric among all learners that have been enrolled in the course included in the report

In the screenshot example above, the average Engagement score among all courses is 43, while the average score for this particular course is around 42. The cohort(s) included in the report averaged 41.

In any organization, there are multiple problems and various challenges of different timescales and competing priorities.  Tackling these problems using the proper methods  – whether it be measured by stability, growth, or another measure – is one of the keys to organizational success.  In the past decade or so, one method to solve these issues are “analytics”.  This technique is the application of mathematical, statistical, and in some cases, computer science methods to business issues.  Recently, analytics has been the purview of data scientists, the profession that straddles the field between statistics and computer science. Data scientists typically wrangle large amounts of data from a variety of sources, prepare these data (correct, clean, fix, etc.) for analysis, develop and apply myriad analytic techniques (sometimes statistical, sometimes computer science, but usually both) to the data, and produce insights that illuminate the crucial components of the challenge.