Certificate Course Roadmap

We highly recommend that you start with our Introduction to Learning Engineering certificate course. This course will teach you the basics of how to apply learning engineering guidelines in designing e-learning  as well as introduce you to the KLI framework. You will learn how to use the “KLI” framework to choose instructional principles that match the desired knowledge components and learning processes.

Follow up the Introduction to Learning Engineering course with Evidence-Based Backward Design to expand your foundational knowledge. In this course you will further your knowledge and practice of the KLI framework. You will learn how to employ agile and iterative methodologies to design innovative e-learning online interactions and technology to make learning more effective and efficient.

To complete your grounding in learning engineering, we suggest that you take Foster Active Learning as your third course. In this course, you will learn how to create effective, evidence-based instructional activities. Importantly, you will learn why active learning is effective as well as about the different types of active learning. After completing this course, you will know when and how to use each type to foster optimal learning.

For course and instructional designers, one of the most confounding issues in creating effective educational technology is combatting the “expert blind spot.” Experts develop “muscle memory” for their implicit tasks; they forget about and have difficulty articulating all the intermediate steps that are necessary to successfully complete a task. For effective instruction, you must draw this information out.

Learning engineers use a technique called cognitive task analysis (CTA) to uncover the expert’s underlying implicit knowledge. In the course Uncovering Implicit Knowledge with Cognitive Task Analysis (CTA) you will learn and practice CTA methods to uncover the implicit knowledge such as Clark’s five steps of CTA via structured interview, principles of contextual inquiry, think aloud, and difficulty factor assessment (DFA) . You will learn how to apply these methods in a practical context and interpret the results to design effective learning experiences.

Online learning has become widespread and many claim it will revolutionize education by adapting to the individual learner’s needs. Further, providing individualized experiences that optimize learning is growing in importance in delivering equitable, engaging learning experiences.Yet, this is a complex task. To meet this goal instruction must take into account how learners are different, how they are similar, and how they change as they learn.

In the course Introduction to Personalized Online Learning you will learn methods to adapt to individualized learner needs by taking into account multiple psychological realms, such as combinations of knowledge, path through problem, and affect. You will learn how advanced learning technologies that adapt to learners can provide individualized experiences that optimize learning. You will be exposed to a number of proven personalization techniques used in advanced learning technologies. We will also survey newer techniques, such as personalizing based on student metacognition, affect, and motivation. Finally, we will look at personalization approaches that are widely believed to be effective but have not proven to be so

Online learning has become widespread and many claim it will revolutionize education by adapting to the individual learner’s needs. Yet, this is a complex task. To meet this goal instruction must take into account how learners are different, how they are similar, and how they change as they learn.

In Data-driven knowledge tracing to improve learning outcomes you will learn how to to apply data-driven modeling to course, you will learn methods to adapt to learner needs that are supported by research taking into account multiple psychological realms, such as combinations of knowledge, path through problem, and affect. You will learn how advanced learning technologies that adapt to learners can provide individualized experiences that optimize learning. You will be exposed to a number of proven personalization techniques used in advanced learning technologies. We will also survey newer techniques, such as personalizing based on student metacognition, affect, and motivation. Finally, we will look at personalization approaches that are widely believed to be effective but have not proven to be so.

rack 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.

It is our contention that effective educational tools require well-designed interfaces that support actions, interactions, and the presentation of information to support student learning. Thus, these courses takes a simple perspective: that to improve learning at large scale, it is important to make better tools for learning. This series of courses will teach you how. We will examine what it means to make a “good” tool for learning, why it is hard, and how you can create and prototype them. 

We have three courses that we recommend that you take in the following order.

What you learn in Foundations for Online Tool Design forms the foundation for building tools for educational technology and provide you with a conceptual framework for thinking about tool design. You will learn what are and how to use the foundations and theoretical constructs that underlie tool design for effective online learning. You will learn practical skills for thinking about, building, and studying 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. 

In the next course, Designing Effective Online Tools, we expand on the foundations for online tool design and cover three additional principles that are often used when designing, improving and evaluating tools for online learning. 

• The first principle is the fundamental human activity of feedback. You will be thinking about and learning practical ways to provide information to students about their performance on tasks. We will look at what makes for good feedback, how it helps students learn, and when feedback may be harmful for learning.
• The second principle is guided discovery. More generally, this principle views learning as a learner constructive activity rather than the more traditional views of learning as transmission of knowledge from teacher to student. We will examine how to scaffold this process and focus on activities that ask students to think of solutions themselves before they know the correct solution.
• The third principle is deliberate practice. We will explore what it means and how to incorporate deliberate practice into the tools you build. 

The goal for this course is to help you develop the foundations for building almost any tool for learning and provide a deep understanding of why some tools help people learn and others do not.

In Designing Online Collaboration Tools you will learn collaborative learning strategies that can be applied when designing, improving and evaluating tools for online learning. The focus for this course is develop tools for learning in groups rather than the individual.  

You will learn effective cooperative learning strategies wherein students work in groups to accomplish a common learning goal. We will cover what cooperative learning means, it’s benefits, and you will gain understanding of the conditions for cooperative learning to be successful. Using these skills you will analyze cooperative learning scenarios for the active ingredients that really make it work. 

Second, we will learn about a particular cooperative learning activity known as Jigsaw. We will talk about the benefits of Jigsaw, how to predict when those benefits will occur, and distinguish between some superficially similar methods. Additionally, you will learn how to provide the necessary support for teachers to implement Jigsaw in the classroom.

Third, we will expand on collaborative learning by thinking about software design through design patterns through design patterns. You will learn what patterns are as well as the benefits and limitations of design patterns with a focus on the “beyond being there” pattern. 

Finally, you will learn about peer learning. You will be able to distinguish peer learning from cooperative learning and recommend effective design patterns for peer interactions. You will also learn the general about the requirements for peer learning to work in practice. 

How do you ensure that you are able to design effective instructional activities? Richard Mayer developed 6 powerful principles of multimedia learning that, if followed, will help you develop effective learning experiences for your learners. In UX Design for Effective Instruction  you will learn about these principles, why they work, and how to apply them in your own work. 

After completing this certificate course, you will be able to use multimedia principles in designing effective, engaging digital learning experiences whether it is a video, presentation, or a fully online course. You will learn how to apply each of these methods in a practical context beyond and interpret the result to design effective learning experiences.