The Science Behind Effective Digital Learning

15 January

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The Science Behind Effective Digital Learning

Digital learning is now big business. According to the latest statistics, the global eLearning market will be worth over US$ 848 billion by 2030. With that explosion has come an increased emphasis on online learning efficacy. How can instructional designers and course developers deliver online programs that maximise learning outcomes? To get the most out of digital learning environments, educators must understand the principles behind how we learn. That’s where the science of learning comes in.  

Learning science is an interdisciplinary field that draws on psychology, neuroscience and educational theory. It seeks to explain how people learn. And it’s vital to improving learning processes and optimising online courses.  

Today’s post explores how learning science principles are applied in digital learning. We discuss cognitive load theory, multimedia learning principles and how these can be used to optimise online learning. And we finish by sharing some practical tips to help you apply these theories effectively.  

Let’s kick off by looking at learning science in the context of effective eLearning.  

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Introduction to Learning Science in Digital Contexts

Researchers have been studying how we learn — the process of acquiring new knowledge and skills– for years. As we've seen, learning science draws on research from cognitive psychology, neuroscience and education. However, it recognises that emotional and contextual factors also impact learning. 

The advent of the knowledge economy and digital learning has transformed learning science. In traditional classroom settings, an educator leads instruction, which focuses on transferring facts and knowledge. Nowadays, we place more emphasis on developing higher-order, critical thinking skills.  

What’s more, digital learners are often self-directed and don’t have the same face-to-face interaction with fellow students or instructors.  

Learning science makes sense of how students learn generally and in digital environments. And this understanding helps instructional designers and educators develop engaging and impactful digital learning experiences.  

Several theories have been developed to help us, including cognitive load theory and Mayer’s multimedia learning principles. Let’s take a deep dive into each.  

Cognitive Load Theory

Developed by the psychologist John Seller, cognitive load theory explains how the brain processes and stores information. It’s based on the assumption that our brains have a limited capacity to absorb and remember information.  

According to the theory, there are three types of cognitive load:  

Intrinsic: relates to the difficulty of the content and reflects the student’s prior knowledge and the topic’s complexity. For example, learning calculus is more demanding than learning addition, so it has a higher intrinsic cognitive load.  

Extraneous: unnecessary or irrelevant information can distract learners and interfere with the learning process. Examples here include unclear instructions and a messy layout. The presentation of learning materials can add to the extraneous cognitive load.  

Germane: refers to productive and beneficial information that helps learners understand and absorb new knowledge. Visual learning elements like infographics and diagrams can help students more easily integrate new knowledge.  

Cognitive load theory has much to offer digital learning environments. It helps us understand how to design and deliver eLearning programs that are in sync with how we learn. The goal is to minimise the intrinsic and extraneous cognitive load and maximise the germane cognitive load.  

When it comes to optimising online courses, instructional designers must take steps to reduce cognitive load. Overloading learners reduces their ability to focus and impairs comprehension and retention. And it leads to frustration and low motivation.  

Multimedia Learning Principles

The multimedia learning theory explains how we learn from words and pictures. First published in 2001 by distinguished psychologist Richard Mayer, the multimedia learning theory is now a cornerstone of instructional design best practices.  

Here’s a handy summary of the main principles:  

Multimedia principle: states that students learn better from a combination of words and pictures than from text alone. For example, a video with narration and animation is more effective than a text-only document. 

Contiguity principle: learners learn best when words and pictures are presented closely on the screen. So, if you are explaining the different parts of a flower, label the parts directly on the image of the flower rather than using a separate key.  

Modality principle: learning outcomes are enhanced when words are presented as speech rather than on-screen text. So, a narrated animation is more effective than an animation with text captions. 

Coherence principle: people learn better when irrelevant material is excluded. For example, a module targeting only essential information is more effective than one packed with extra sounds, images or content.  

Personalisation principle: the learning experience is enhanced when information is presented in an everyday conversational style rather than a formal one. Digital learning that uses a friendly voice and informal language will be more effective than one with a robotic voice and technical jargon. 

There are more principles. We have highlighted the main ones only. Check out our dedicated blog to find out more about the multimedia learning theory.  

Incorporating these guidelines into digital learning environments helps to reduce extraneous cognitive load for students. And they will also ensure you maximise the germane cognitive load. 

Application of Learning Science in Online Courses

Learning science isn’t just an academic pursuit. It also has practical applications in the real world. Here are some examples of how cognitive load theory and multimedia learning principles are allied in online courses.  

Interactivity: quizzes, simulations and games are great ways to engage and involve students in their learning. Interactive elements like these allow learners to control the pace and sequencing of learning, reducing intrinsic overload. And it boosts germane load by providing feedback and encouraging active learning.  

Visuals: from infographics and diagrams to illustrations and videos, visual elements are crucial to effective eLearning strategies. A picture is indeed worth a thousand words. Visuals reduce extraneous cognitive load by doing away with unnecessary text. They help learners absorb new information more quickly, assisting with retention and increasing germane cognitive load.   

Narrative: incorporating stories into course development is a valuable technique for reducing cognitive load. Not only is a narrative more engaging, but it also makes new knowledge relatable by providing a meaningful context. Techniques like stories, case studies and anecdotes capture students’ interest and can engage their emotions. Narratives are a fantastic way to power up the germane cognitive load.  

Tips for Optimising Online Courses

This section will help course creators put the theory of learning science into practice. We share some actionable tips to bridge the gap between theory and practice and optimise course development.  

Effective use of multimedia elements: carefully select multimedia elements to enhance rather than distract from learning. Use the multimedia learning principles to choose elements that directly address learning objectives without overwhelming students.  

Chunk information: reduce cognitive load by breaking down complex information into bite-sized chunks so it’s more easily digested. Use clear and concise words and pictures, and avoid unnecessary text or images.  

Interactive learning: quizzes, discussions and simulations promote engagement and knowledge retention. They also contribute to reducing cognitive load.  

Provide straightforward navigation: a logical course structure and intuitive navigation go a long way to tackling extraneous cognitive load. Students enjoy a seamless learning experience that flows naturally between modules.  

Design for engagement: aim to grab learners’ attention and motivate them from the get-go. Visuals and interactive elements have a part to play. In addition, create a compelling narrative to engage learners’ emotions and provide valuable context. And remember to use personalisation and an easy conversational style to connect with learners. 

Offer collaborative learning opportunities: develop a sense of community and collaboration within online courses. Group discussions, chat forums and joint projects introduce that social element to learning that can be missing from digital environments.  

Learning Science Principles and Digital Learning: Conclusion

The bottom line is that learning science is a powerful tool for understanding and enhancing online learning. Applying the principles of cognitive load theory and multimedia theory ensures more effective, engaging learning. And it also results in digital learning that delivers on objectives and outcomes.   

However, the field of learning science is constantly changing. Embracing the science behind effective digital learning is not a one-off exercise. Educators and course designers must continually review their practice and keep up with emerging trends to stay ahead of the curve.  

And there’s no better place to start than the Digital Learning Institute’s Professional Diploma in Digital Learning Design. This leading qualification guided by expert tutors and informed by the latest best practices will help you plan, build, and deliver impactful online learning experiences.