Learning Analytics for Teachers (FFHS)

Learning Analytics for Teachers (FFHS)

The course aims to provide teachers with information and skills on how they can use Learning Analytics to improve support for their current or next learner groups. They will also get familiar with basic methods, including their analytics literacy, and align their work with ethics and privacy standards.

Learning Analytics can provide teachers additional insights into their students' ways of learning (e.g., strengths or weaknesses). Existing systems showed that when teachers transform these insights into actions, it can improve student outcomes or their learning experience. Some teachers are aware of Learning Analytics, but they often do not know how to transform this information into actions and how this can contribute to students outcomes and their professional development. This gap limits the current usage of these systems. And that's why we designed this MOOC!

We aim to provide teachers with information and skills on how their instruction is mapped throughout the whole Learning Analytics cycle and how they can use Learning Analytics to improve support for their current or next learner groups. The teachers will also get familiar with basic methods, including their analytics literacy, and align their work with ethics and privacy standards. Our goal is that teachers will gain knowledge that they will apply in their day-to-day work. The examples will cover mostly Higher Education with online elements; however, the learned principles can be applied by teachers across all learning contexts.

Course Content

  • Week 1: Introduction to Learning Analytics
  • Week 2: Data and Ethics
  • Week 3: Basic Methods
  • Week 4: Frameworks and Evaluation
  • Week 5: Advanced methods and Future in Learning Analytics
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Literacy – What is it and why does it matter? (Coursera) Coursera
University of Copenhagen,Sorbonne University,University of Warsaw,University of Milan,Charles University,4EU+ Alliance

Data Literacy – What is it and why does it matter? (Coursera)

You might already know that data is not neutral. Our values and assumptions are influenced by the data surrounding us - the data we create, the data we collect, and the data we share with each other. Economic needs, social structures, or algorithmic biases can have profound consequences for the way we collect and use data. Most often, the result is an increase of inequity in the world. Data also changes the way we interact. It shapes our thoughts, our feelings, our preferences and actions.

Nov 9th 2026
3 Weeks
Analytics for the Classroom Teacher (edX) EdX
Curtin University,CurtinX

Analytics for the Classroom Teacher (edX)

This course is ideal for school teachers who want to improve their teaching through valuable data-driven insights. Do you want to be more reflective in your teaching practice and wonder if there are technologies that can help? Are you curious about how data-driven, evidence-based teaching practices can improve your students’ learning? This is the course for you!

No sessions available
5-12 Weeks
Decoding AI: A Deep Dive into AI Models and Predictions (Coursera) Coursera
University of Michigan

Decoding AI: A Deep Dive into AI Models and Predictions (Coursera)

Decoding AI: A Deep Dive into AI Models and Predictions explores the significance of large datasets, demystifies generative artificial intelligence (AI), and challenges common media myths about AI. By defining key terms and exploring how systems “learn” from data, you will gain a baseline understanding of how AI works. Work to understand different critiques of AI narratives, learn to navigate conversations with precision, discern conflicts of interest, and appreciate the multidisciplinary expertise needed to shape AI's impact on society. This course provides you with the strategies and frameworks to engage in better conversation about the role of AI in your work and beyond.

Oct 19th 2026
4 Weeks
Cluster Analysis (edX) EdX
University of Texas at Arlington,UTArlingtonX

Cluster Analysis (edX)

Learn how to conduct a cluster analysis to discover important patterns in student behavior using the popular Weka data mining toolkit. In this course, you will learn the basics of cluster analysis, one of the most popular data mining methods for the discovery of patterns in learning data, and its application in learning analytics.

No sessions available
3 Weeks
Getting Started with Teaching Data Science in Schools (FutureLearn) FutureLearn
University of Glasgow

Getting Started with Teaching Data Science in Schools (FutureLearn)

Learn the basics of data science and how to introduce data science in the classroom. Learn practical ways to teach data science. Understanding how to use and interpret data will be essential for the next generation, but many schools and teachers aren’t equipped to teach basic data science to students. This course will help you introduce data science in the classroom so that your students are prepared for the future.

Self Paced
3 Weeks
Digital Future Literacy - Fit für die digitale Zukunft (openHPI) OpenHPI
Hasso-Plattner-Institut

Digital Future Literacy - Fit für die digitale Zukunft (openHPI)

Im Zuge der Digitalisierung müssen sich viele heute im Erwerbsleben stehende Menschen beruflich weiterqualifizieren. Zunehmend gebraucht werden nicht nur technologische Fähigkeiten wie Umgang mit Software oder Programmierung, sondern die neuen digitalen Geschäfts- und Arbeitsprozesse erfordern verstärkt digitale und nicht-digitale Schlüsselfähigkeiten (digital future literacy). Dazu zählen u.a. Data Literacy, Kollaboration, digitales Lernen, Problemlösungsfähigkeit, Vorausschau und unternehmerisches Denken.

Feb 23rd 2022
4 Weeks
Digital Literacy (Coursera) Coursera
Higher School of Economics - HSE University

Digital Literacy (Coursera)

The online course in Digital Literacy offered by HSE University was designed to help the students acquire various competencies that will enable them to safely and effectively use digital technologies and Internet resources in an academic and professional context. The Digital Literacy course is a step-by-step guide covering various topics that will help you find your way around in the digital environment. We did our best to include the most essential insights and skills that can guarantee your success in the world of information technology.

Oct 19th 2026
5-12 Weeks
Introduction to Business Analytics (Coursera) Coursera
Tableau Learning Partner

Introduction to Business Analytics (Coursera)

The Introduction to Business Analytics teaches you the foundational skills in Tableau and business analytics. You will be introduced to essential concepts like analytics and insights and the foundational steps of the business analysis process. You’ll learn about the different types of analytics that businesses use, and you’ll be introduced to a data analytics lifecycle framework. You’ll also learn some of the foundational project management skills often used by analysts, and you’ll arrive at a greater understanding of data literacy.

Oct 26th 2026
4 Weeks
Experience Matters: A Crash Course in Learning Experience Design (HT2 Labs) Other Providers
HT2 Labs

Experience Matters: A Crash Course in Learning Experience Design (HT2 Labs)

This course will explore how you can create engaging, meaningful and data-driven learning experiences by combining Personalization, Gamification, Learning Analytics and Social Learning. We will focus on how learning professionals can leverage existing or free content, existing or new platforms, data, and, most importantly, people, to create engaging, data-driven and meaningful learning experiences.

No sessions available
4 Weeks
Data Literacy Foundations (edX) EdX
Rochester Institute of Technology,RITx

Data Literacy Foundations (edX)

Take the first step to becoming a leader in data-driven decision-making. In Data Literacy Foundations, you will learn how critical thinking is an essential data literacy skill in today’s data-driven world. You’ll begin by considering how you use data every day, discussing the value of data and examining the transformation of data from analogue to digital forms.

Self Paced
Self-Paced