EdOptimize – An Open Source K-12 Learning Analytics Platform

[This article was first published on R-posts.com, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Important Links

  1. Open-source code of our platform –  https://github.com/PlaypowerLabs/EdOptimize
  2. Live Platform Analytics Dashboard – https://playpowerlabs.shinyapps.io/edopt_platform_analytics/
  3. Live Curriculum Analytics Dashboard – https://playpowerlabs.shinyapps.io/edopt_curriculum_analytics/
  4. Live Implementation Analytics Dashboard – https://playpowerlabs.shinyapps.io/edopt_implementation_analytics/

Data from EdTech platforms have a tremendous potential to positively impact student learning outcomes. EdTech leaders are now realizing that learning analytics data can be used to take decisive actions that make online learning more effective. By using the EdOptimize Platform, we can rapidly begin to observe the implementation of digital learning programs at scale. The data insights from the EdOptimize Platform can enable education stakeholders to make evidence-based decisions that are aimed at creating improved digital learning systems, programs, and their implementation.

EdOptimize Platform is a collection of 3 extensive data dashboards. All 3 Dashboards are devloped using R Shiny and all the code right from the beginning with data simulation and data processing is R native . These dashboards contain many actionable learning analytics that we have designed from our years of work with various school districts in the US.

Here are the brief descriptions of each of the dashboards:

  1. Platform Analytics: To discover trends and power users in the online learning platform. You can use the user behavior data in this platform to identify actions that can increase user retention and engagement. See the dashboard in action here: https://playpowerlabs.shinyapps.io/edopt_platform_analytics/
  2. Curriculum Analytics: To identify learning patterns in the digital curriculum products. Using this dashboard, you can locate content that needs change and see classroom pacing analytics. You can also look at assessment data, item analysis, and standards performance of the curriculum users. See the dashboard in action here: https://playpowerlabs.shinyapps.io/edopt_curriculum_analytics/
  3. Implementation Analytics: To track the implementation of the digital programs in school districts. This dashboard will help districts make the most out of their online learning programs. See the dashboard in action here: https://playpowerlabs.shinyapps.io/edopt_implementation_analytics/

    Data Processing Workflow :

    To learn more about the platform in detail please head over to – https://github.com/PlaypowerLabs/EdOptimize#readme

    About Playpower Labs
Playpower Labs is one of the world’s leading EdTech consulting companies. Our award-winning research team has worked with many different types of educational data. Examples include event data, assessment data, user behavior data, web analytics data, license and entitlement data, roster data, eText data, item response data, time-series data, panel data, hierarchical data, skill and standard data, assignment data, knowledge structure data, school demographic data, and more.

If you need a professional help with this platform or any other EdTech data project, please contact our Chief Data Scientist Nirmal Patel at [email protected] He will be happy to have a conversation with you!

EdOptimize – An Open Source K-12 Learning Analytics Platform was first posted on May 7, 2021 at 8:42 am.

To leave a comment for the author, please follow the link and comment on their blog: R-posts.com.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)