The OEA Learning Analytics Package provides a set of assets to empower educators with insights that foster student well-being, drive student engagement, and improve learning outcomes.

This Learning Analytics package was primarily developed for higher education but can be modified for K-12 scenarios. It can provide educators, tutors, or leaders with insights on a group of learners' engagement, academic performance, and well-being at a class or course level.

1. Guidance and documentation:: This package provides guidance on the end-to-end process of developing a Learning Analytics use case project through the problem statement and package impact. The OEA Use Case Documentation should be completed when developing the production-level implementation of this package, including: how to engage stakeholders in the project, prior research on the use case problem domain and theory, how to map data sources to the theory of the problem, and how to implement Microsoft’s Principles of Responsible Data and AI.  It is highly recommended this document be reviewed and completed by any education system considering using this package, and that the documentation be revised to the specific data and decisions for that system’s context.

2. Technical assets: Various assets are freely available in this package to help accelerate implementation of Learning Analytics use cases. Assets include pipelines, notebooks for data processing, an initial data model, a sample Power BI dashboard, and data dictionary. See descriptions of technical assets below.

With varied modes of learning, learning platforms and learner needs, educators have challenges determining how students engage and learn in a class or course in-person, remotely and in hybrid learning contexts. Due to this, they do not have full visibility into student engagement in learning activities and resources. They may have trouble incorporating factors related to student well-being into their instructional process, and they cannot easily see the relationship between student engagement and academic progress.

This package brings together data signals on how students learn and complete a course to help educators improve instructional dynamics. Dashboards can be developed that help educators identify which learning activities and resources students engage with, and trends that relate to learning outcomes across digital and in-person learning contexts.

Data from student digital engagement apps like Microsoft Education Insights and Microsoft Graph can be combined with other data sources such as from a Student Information System, Learning Management System, or learning applications or platforms for different Learning Analytics use cases.

This package initially includes examples from Microsoft Education Insights and Microsoft Graph only, but other OEA modules and assets will be added to it soon from the OEA Community.

With this package, educators can:

• Visualize students’ digital engagement before, during, and after class
• See which students are late or missing class when those classes use Microsoft Teams
• Compare student progress and identify patterns within a course, like which assignments or assessments they struggle, and which ones might be too easy
• Identify students that might need support such as a tutor
• Identify which learning resources students use the most or least

The assets in this package can be combined with course completion, graduation rates, competency measures, or other outcome data to identify how these patterns relate to learning outcomes.

Preparation: Ensure you have an Azure subscription and setup v0.6.1 of the OEA framework. This module currently relies on v0.6.1 of the OEA framework.

1. Examine available data sources. See below for these related data sources. Choose which modules or data sources to implement.
   • This package was developed using the following modules: Microsoft Education Insights and Microsoft Graph.
   • Run each of the module data pipelines to ingest the data into stage 2.
2. Import and run the Learning Analytics pipeline.
3. Use the Power BI dashboard to explore the Learning Analytics use case. Note that all pipelines create SQL views which can be accessed via your Synapse workspace Serverless SQL endpoint. Example dashboard concepts and detailed information on the queries are provided in the Power BI folder.

This package can use several OEA Modules to help ingest data sources that are typically used to understand patterns seen in Learning Analytics (see below for list of relevant OEA modules).

Sample out-of-the box assets for this OEA package include:

1. Data: For understanding the data relationships and standardized schema mappings used for certain groups of data.
2. Documentation:
   • OEA Use Case Documentation Template.
3. Notebooks: For aggregating, enriching, and curating data within the data lake.
4. Pipeline: For the overarching data processing (i.e., aggregation, subsetting, schema transformation, etc.), and support for Power BI dashboards.
5. Power BI Template: For exploring, visualizing, and deriving insights from the data.

The Learning Analytics Package welcome contributions.

This package was developed by Microsoft Education. The architecture and reference implementation for all modules is built on Azure Synapse Analytics - with Azure Data Lake Storage as the storage backbone, and Azure Active Directory providing the role-based access control.

Microsoft and any contributors grant you a license to the Microsoft documentation and other content in this repository under the Creative Commons Attribution 4.0 International Public License, see the LICENSE file, and grant you a license to any code in the repository under the MIT License, see the LICENSE-CODE file.

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