5 Top Learning Theories Driving Immersive Virtual Reality (IVR) and When to Use Them

5 Top Learning Theories Driving Immersive Virtual Reality (IVR) and When to Use Them - Kristin Torrence | TrainingPros Insider Training
Play Video about 5 Top Learning Theories Driving Immersive Virtual Reality (IVR) and When to Use Them - Kristin Torrence | TrainingPros Insider Training
  • Introduction
  • Video Transcript

One of the biggest challenges instructional designers face is creating training content that genuinely engages learners. That is where the power of immersive learning and the various learning theories that drive this type of content development really shines.

Through extended reality (XR) technologies like immersive virtual reality (IVR), learners can engage their senses in interactive environments without the distractions of more traditional learning modalities.

This kind of learning experience also makes it easier for learners to grasp skills that would otherwise be too dangerous, costly, or impossible to try any other way.

However, despite the many benefits of designing IVR training, the technology is only a tool. And tools by themselves cannot teach. They are a means to an end that must be implemented using sound learning principles to benefit the learning process.

The good news for learning and development (L&D) professionals is that the field of immersive learning is exploding. According to Kristin Torrence, Head of Learning Engineering at Talespin, "there are a number of learning theories that really drive immersive learning."

In this video, Kristin explores the five learning theories she considers to be the most effective for designing immersive types of learning:

Finally, she closes the information-packed episode, diving deeper into how learning science relates to design decisions by sharing examples of when each learning theory might best be used.

Do you need resources skilled in design for immersive virtual reality? Contact us and we can provide you with the right L&D consultant experienced in design for virtual reality so you can start your project with confidence.

Speaker: Kristin Torrence, Extended Reality (XR) Learning Experience Designer & Head of Learning Engineering at Talespin

Learning Theories That Drive Immersive Learning

There are a number of learning theories that really drive immersive learning, and here are what I consider to be the top five.

Situated Learning Theory (SLT)

From a situated cognition perspective, a learner's cognitive functions within a learning activity and the context in which they take place are interdependent.

What that means with VR (virtual reality) experiences is that it's a powerful method of modeling systems by situating a learner within a real-life setting.

So, this modality can really enhance that situated cognition.

Experiential Learning Theory (ELT)

(John) Dewey's experiential learning theory also claims that learners learn by doing and by constructing knowledge through active engagement in the learning environment.

I would argue that virtual reality provides an optimal environment for experiential learning. It enables learners to be really active participants in their learning process through interacting with the virtual world around them, transforming this experience into cognitive understanding.

Constructivism

Constructivists believe that Learners also must interpret their experiences and make meaning of them for learning to occur. Learning through trial and error is the basis for many virtual reality learning experiences.

You know, in VR, learners can explore and test out their solutions. They can receive feedback.

And they can interpret this experience and internalize the meaning of it by uncovering the inner relationships between concepts and the cause-and-effect relationships that they actually experience firsthand.

Flow Theory

There are also flow theories coined by Mihaly Csikszentmihaly, which is a state in which you're so completely absorbed or engaged in an activity that all else is ignored. It's achieved when you can strike a sweet balance in your design between challenge level and skill level.

When we design for virtual reality, one of our goals is to get learners to this flow state, this optimal state of mind, as quickly as possible.

You can find that this same sort of balance between challenge level and skill level required to both reach and maintain flow is similar to that of Lev Vygotsky's zone of proximal development (ZPD).

Cognitive Load Theory

Then there's Cognitive Load Theory (CLT). It's critical for us to really consider learners' information processing limitations.

And design to sort of limit the amount of extraneous cognitive load imparted on the learner within our virtual reality training.

Applying Learning Science to Design Decisions

We can apply what we know about learning science to really help us make decisions for our designs in virtual reality.

For instance, if we were trying to promote situated learning theory to maintain immersion and situated cognition, we may ensure that our spatial environment is authentic and realistic. We might also opt for diegetic interfaces.

For experiential learning theory, we might design for guided discovery, replayability, and implement space practice. We can also encourage knowledge and skill acquisition by designing for the right level of challenge, implementing just-in-time support, or formative feedback mechanisms.

Then facilitate reaching a flow state through

  • Very clear goals
  • A sense of control for the learner
  • Appropriate challenge level
  • Immediate feedback

Which are all precursors to reaching and maintaining flow.

And to limit the amount of extraneous cognitive load we might impart on a learner – we might limit the amount of text on the screen. Or ensure that our controller manipulations for our virtual reality training mirror real-life actions.

Picture of Kristin Torrence

Kristin Torrence

Kristin Torrence serves as the Head of Learning Engineering at Talespin. She focuses on applying learning sciences, instructional design, and data science practices to design, instrument, and validate XR learning solutions. Her background is in cognitive science, game-based learning, and instructional design, and she is particularly interested in the intersection of learning science, XR, and learning analytics.
TrainingPros Blog Rings Logo Icon | When You Have More Projects Than People...

You Might Also Like

Search

Follow Us

12.8kFollowers
865Followers
350Fans
990Subscribers
76Followers
15kTotal fans
Written By
Kristin Torrence serves as the Head of Learning Engineering at Talespin. She focuses on applying learning sciences, instructional design, and data science practices to design, instrument, and validate XR learning solutions. Her background is in cognitive science, game-based learning, and instructional design, and she is particularly interested in the intersection of learning science, XR, and learning analytics.

Recent Posts