Learning Analytics at Texas A&M

At Texas A&M, learning analytics extends beyond quantitative algorithms or statistical modeling. It encompasses a comprehensive, evidence-based approach aimed at improving instructional design, teaching practices, and student outcomes. By providing actionable insights from course and curriculum data, teaching and learning staff are empowered to optimize digital learning environments, ultimately improving educational outcomes.

Optimize Your Teaching Experience and Learning Outcomes

Real-Time Analytics

Transform Canvas data into interactive reports for instant insights.

 

 

 

Proactive Course Design

Use predictive analytics to refine teaching methods and personalize learning experiences.

 

 

 

 

 

AI-Powered Understanding

Leverage machine learning to uncover key factors affecting student performance, engagement, and satisfaction.

 

 

 

 

 

Comprehensive Dashboards

Gain a clear view of student activity, submissions, grades, and participation trends.

 

 

 

 

 

Actionable Insights

Discover meaningful patterns through advanced analytics to optimize learning outcomes.

 

 

 

 

 

Collaborative Expertise

Work with a dedicated team as a single contact center for all your teaching needs.

Work With Us

Whether you're looking to enhance student engagement, refine teaching strategies, or gain deeper insights from learning data, we are here to support you!

Projects

These learning analytics projects offer a snapshot of available data-driven insights. Requests can be made for these topics or customized analyses to fit specific needs and support teaching and student success.

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Course Dashboard

• Course publish status
• Course Enrollment Trends Over Time

• Course Content Visualization
• LTI Usage
• Social Network Analysis
• Course Content Utilization and Insights

Student Reports

• Student Engagement
• Student Grade Distribution Dashboard
• Student Activity Summary

Predictive Analytics and Pattern Discovery:

• Student Grade Forecasting
• At-Risk Student Prediction
• Predicting Course Satisfaction & Key Influencing Factors
• Learner Profiling
• Course Discussion Sentiment Analysis

Data Policies and Principles

Texas A&M University follows established data policies and principles to ensure responsible data management, security, and compliance. Below are key categories guiding data governance in our work:

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Data Policies and Principles

• Data Classification (DC-1) – Defines data sensitivity levels to ensure proper handling and protection.
• Data Inventory (DC-2) – Maintains a comprehensive record of data assets for accountability and oversight.
• Data Ownership (DC-3) – Establishes responsibility for data stewardship and access control.
• Data Protection (DC-4) – Implements safeguards to prevent unauthorized access, loss, or misuse.
• Data Quality (DC-5) – Ensures accuracy, consistency, and reliability of institutional data.
• Data Retention and Disposal (DC-6) – Defines policies for securely storing and disposing of data in compliance with regulations.

For more details, visit the TAMU IT Controls Catalog.

Frequently Asked Questions

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What type of data can be accessed?

We host a diverse range of data that captures the digital learning environment, including Canvas data, student profiles, student trajectories, and data from third-party tools. We tailor the data to fit your specific study requirements, ensuring that the insights align with your goals and needs.

What if I need additional data or insights?

We are happy to assist with any additional data or insights you may need. While we specialize in the data we have access to, we are open to exploring new opportunities and customizing solutions to meet your specific learning analytics needs.

What services do you provide?

We collaborate with you to access and analyze educational data, providing insights that benefit not just student outcomes but also course design, teaching methods, and overall unit performance.

What approvals/authorizations do I require?

Our team will handle all raw data for reporting. Certain types of requests require approvals from the Office of the Registrar and Technology Services.

Meet the Team

• Dr. Justin T. Dellinger  
• Minh Dao Nguyen  
• Dorian Satuluri
• Jobin Varughese   
• Dr. Seung Won Yoon 
  
  

Partners 

•  Office of the Provost
• Technology Services

• Office of the Registrar