Avatars, actors, and pedagogical characters are just three of the many terms describing characters that represent humans in an online environment. Prior to animation tools and interactive character solutions, such as CodeBaby®, characters primarily took the form of 2 D photorealistic cartoons or even anthropomorphized animals. In the past few years, learner expectations and technological advances in e Learning development make animated-character-mediated learning easier to implement, while at the same time employing more sophisticated instructional design techniques. Before you embark on a program to integrate animated characters into e-Learning, it’s useful to review the evidence pointing to the benefits of emotional animated characters in e-Learning.
In one study, The Benefits of Interactive Online Characters (2004), Byron Reeves concluded that the same social competencies that facilitate human-to-human interaction drive the success of human-media interactions.
Here are some of Reeves’ primary conclusions as to why animated characters provide serious advantages in e-Learning.
1. Emotional, interactive characters bring social intelligence to online learning.
2. Simulating a social exchange and enhancing the environment with an interactive character leads to an increase in memory and trust of information.
3. The degree of character interactivity leads to heightened realism improving the value of the learning and interaction.
Furthermore, characters are practical. While you can use other methods such as audio, video, and even conversational text to create a socially intelligent context, animated characters may be more cost effective and easier to replicate. Besides those advantages, they never tire, and they are always available.
Social Roles
What are the ways in which you can bring your character to life? A well-documented case study by Jennifer De Vries from Bersin and Associates, Character Based Simulations: What Works TM (2004), outlines the most common but effective roles for characters in e Learning. Here are three of them, with two examples.
Expert Instructor – The character is modeled after a knowledgeable human – most commonly the teacher, coach, or expert in the field such as a doctor or financial adviser. Effective use of this role ensures continual engagement between the character and the student through a conversational tone, interaction, and feedback based on the student’s answers.
This example, by w/ (Editor's Note: W/ (pronounced "w slash") is a company that produces immersive learning simulations. http://www.wslash.net), introduces us to Alex as the “Expert Instructor.” He’s a friendly company spokesperson leading new employees through orientation. While his tone is conversational, he appears credible by demonstrating extensive corporate and medical knowledge. Click the image to start the example.
Peer Instructor – Using characters as peer instructors is the most popular social role. By relating the character to the learner, you achieve an immediate social connection. The characters are used in one of two ways: as the peer coach for an additional character on screen, or as the sole character.
In the following example, the University of Arizona library system created the personas of Annie and Sam. Annie is the Peer Coach while Sam is the younger student, new to library research.
Through their discussions, students learn about library research. Although there’s no interaction, these discussion scenarios interspersed throughout modules create the social context important for learning transmission.
Click the image to start the demonstration.
Cooperative Co-Learner – Finally, there’s additional research challenging designers to expand social roles to include a “Cooperative Co-learner.” A Cooperative Co-learner differs from a Peer Coach, because the character provides support and motivation while taking the course alongside the student. This unique instructional design method includes an additional Expert or Peer Instructor, which teaches both Co-learner and student.
In the study, We Learn Better Together: Enhancing e-Learning with Emotional Characters (2005) by Heidi Maldonado et al., the researchers discovered that the presence of a Cooperative Co-learner resulted in learners performing considerably better. Students who had a Cooperative Co-learner scored significantly higher on fill-in-the-blank questions, earning as much as seven points more than a student with a “No Emotion Co-learner.” A No Emotion Co-learner may express human emotions and gestures, but no learner interaction takes place. From our examples above, Sam fits the profile of a No Emotion Co-learner. Although his presence still benefits the learner, according to the study, larger gains are experienced with a Cooperative Co-Learner.
Additionally, students rated the Cooperative Co-learner’s credibility and support ratings higher when compared to either a No Emotion Co-learner or “No Co-learner” (no character present).
From client examples, we have a few companies replicating this social role. However, they are few and far between. One accounting company provided an excellent example by weaving in an “Expert Instructor,” “Credible Authority Figure,” and a “Co-learner Peer.” We look forward to more examples in the future.
Summary
Animated characters enhance e-Learning by providing a social context that motivates learners, thereby improving cognition and recall. Well-designed social roles, in which the characters relate to, interact with, support, and work alongside the student, provide the best learning outcomes.
In future articles, we’ll provide best practices on designing your animated character scene.
References
De Vries, Jennifer. “Character-Based Simulations.” What Works TM :The Use of Character-Based Simulations in E-learning.” Bersin & Associates. March 2004.
Maldonado, Heidi, et al. “We Learn Better Together: Enhancing e Learning with Emotional Characters.” Computer Supported Collaborative Learning 2005: The Next 10 Years! (2005) International Society of the Learning Sciences.
Reeves, Byron. The Benefits of Interactive Online Characters. The Center for the Study of Language and Information. Stanford University. 2004.