EdOptimize–An Open-Source K-12 Learning Analytics Platform

Tirth Shah, Nirmal Patel, J.D. Lomas, Aditya Sharma

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Technology aided learning is becoming increasingly popular. In some of the countries, online learning has taken over for traditional classroom-based learning. With this, educational data is being generated in vast amounts. Knowing the potential of this data, many education stakeholders have turned to evidence-based decision making to improve the learning outcomes of the students. EdOptimize platform provides extensive actionable insights for a range of stakeholders through a suite of 3 data dashboards, each one intended for a certain type of stakeholder. We have designed a conceptual model and data architecture that can generalize across many different edtech implementation scenarios. Our source code
is available at https://github.com/PlaypowerLabs/EdOptimize
Original languageEnglish
Title of host publicationProceedings of the 12th International Conference on Learning Analytics & Knowledge (LAK22)
Number of pages1
ISBN (Electronic)978-1-4503-9573-1
Publication statusPublished - 2022
EventLAK 2022 : 12th International Learning Analytics & Knowledge Conference (LAK22) Online - , United States
Duration: 1 Mar 202225 Mar 2023


ConferenceLAK 2022 : 12th International Learning Analytics & Knowledge Conference (LAK22) Online
Country/TerritoryUnited States


  • earning analytics
  • digital learning
  • ashboards
  • assessment data
  • curriculum- analytics
  • platform-analytics
  • implementation-analytics


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