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Build expertise in learning engineering

Self-Paced Certificate Courses

Learn from the world’s leading researchers in learning analytics, curriculum design, and educational data mining in the Human-Computer Interaction Institute and the Psychology Department. Courses are listed by their primary topic areas.

Fundamental E-Learning Methods

Introduction to Learning Engineering

Learn the basics on how to apply learning engineering guidelines in designing e-learning and how to use the “KLI” framework to choose instructional principles that match the desired knowledge components and learning processes.



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Evidence-Based Backward Design

Learn how to employ agile and iterative methodologies to design innovative e-learning online interactions and technology to make learning more effective and efficient.





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Uncovering Implicit Knowledge with Cognitive Task Analysis (CTA)

Learn CTA methods such as Clark’s five steps of CTA via structured interview, principles of contextual inquiry, think aloud, and difficulty factor assessment (DFA). Learn to apply these methods in a practical context and interpret the results to design effective learning experiences.

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Quantitative and Experimental Methods for Designing and Evaluating Learning

Learn to apply Quantitative CTA methods and Experimental design in a practical context and interpret the results to design effective learning experiences.



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E-Learning Principles & Techniques

Foster Active Learning

In this course, you will learn how to create effective, evidence-based instructional activities. Learn about the different types of active learning as well as when and how to use each type to foster optimal learning.


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UX Design for Effective Instruction

Learn about and how to apply the six multimedia principles key to designing effective, engaging digital instructional activities and learning experiences whether it is a video, presentation, or a fully online course.

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Techniques for Active Enriched Learning

Learn about and how to apply the five techniques for enriching active learning used for creating effective, engaging instructional activities and learning experiences.



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Individualized Adaptive Learning

Introduction to Personalized Online Learning

Learn how to create advanced learning solutions and technologies that adapt to learners and provide individualized experiences that optimize learning. Take into account multiple psychological realms, such as combinations of knowledge, path through problem, and affect.

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Data-driven knowledge tracing to improve learning outcomes

Learn how to to apply data-driven modeling to track students’ knowledge growth in advanced learning technologies and adapt the instructions based on that. Learn multiple techniques to perform KC Modeling, Cognitive Task Analysis and Knowledge Tracing to do data-driven design.

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Building Evidence-Based Educational Technology

Foundations for Online Tool Design

Learn practical skills for thinking about, building, and creating tools that improve learning on a large scale. These concepts will help you differentiate between tools as well as support your own design decisions when creating your own educational tools.

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Designing Effective Online Tools

Learn how to apply the principles most often used when designing, improving and evaluating tools for online learning while gaining a deep understanding why some tools are effective in helping people learn and others do not.

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Adaptation, Crowdsourcing, and Persuasion

This course takes a practical approach to applying a small set of advanced techniques to use when designing, improving, or evaluating new tools for online learning.


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Designing Online Collaboration Tools

Learn the practical skills and core principles necessary to design effective collaborative learning experiences for online learning. Understand the differences and when to apply peer learning and collaborative learning.

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Certificate Course Experience

Video Lectures

Hands-on Practice

Course Project

Discussion Forum

Instructor Support Available

Learning Engineering 

from the Leader in Learning Engineering

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