Rivers of ink, both actual and digital, decry the lack of “diversity” in the gaming industry. Learning Solutions columnist Matt Sparks suggests that this reveals an opportunity: VR and eLearning can do better at increasing diversity in learning games than commercial game developers have done.
That may well be true. But whether eLearning succeeds in improving on the diversity record of commercial games has as much—or more—to do with how “diversity” is defined as it has to do with the demographics of the characters in learning games. That is, authenticity and diversity are about much more than whether a virtual environment has strong African-American characters, or whether the female characters are “real” or sexualized stereotypes whose role is limited and largely decorative—although much of the discussion of diversity in video games emphasizes these essential but woefully insufficient measures.
Whether targeted to K–12 students or adult learners, eLearning games, simulations, and immersive experiences are effective only if learners engage with them. And learners are more likely to engage with eLearning that reflects their experience or has characters with whom they can identify.
True diversity reflects a variety of races and genders, sure; it also reflects different life experiences, educational and cultural backgrounds, and more. Decades of study have led researchers to the conclusion that authentically diverse teams are more creative, productive, and successful.
In a 1999 article from the Stanford Graduate School of Business, the authors state, “People tend to think of diversity as simply demographic, a matter of color, gender, or age. However, groups can be disparate in many ways. Diversity is also based on informational differences, reflecting a person’s education and experience, as well as on values or goals that can influence what one perceives to be the mission of something as small as a single meeting or as large as a whole company” (see References at the end of this article).
To engage learners—and, even more important, to accomplish key learning goals—eLearning games and simulations have to reflect reality: a plethora of backgrounds, experiences, and cultures. And the best way to build that diversity into eLearning is to have a diverse group of developers intentionally seeking diverse individuals and experiences to serve as the foundation of their simulations and immersive stories.
Simulations intended to prepare employees to face actual customers have to reflect the customer base—at an emergency call dispatch center, for example, or first responders, hospital workers, sales personnel, or fast-food prep line workers. Hospital patients and fast-food customers come in all shapes, sizes, ages, and colors. The families that EMTs-in-training will pull out of future car wrecks won’t be smiling and perfectly coiffed like the models in stock image collections. It stands to reason that the characters populating eLearning should reflect these realities, but characters’ and avatars’ appearance is only a starting point.
Authentic eLearning has to not only look realistic, but also pose actual problems in realistic contexts or provide learners with projects for real clients, according to researcher Jan Herrington. What matters is “cognitive realism,” Herrington says, which is essential, whether the task is a simulation or a work product for a genuine customer.
Characteristics of authentic tasks that Herrington distilled from research on authentic learning environments include:
- They require learners to define the steps needed to complete the task, rather than provide step-by-step instructions
- Learners are encouraged or required to collaborate
- Learners are able to explore a variety of perspectives and approaches to solving the problem, rather than being instructed to follow a single method
- Different groups of learners might come up with different—equally viable—solutions; there is not one correct answer or end product
Note that these descriptions of authentic learning don’t even mention the demographics of characters; these “authentic tasks” might not include simulations. Herrington’s focus in seeking authenticity emphasizes learning that provides “contexts that reflect the way the knowledge will be used in real life.”
In fact, she argues that aiming for completely realistic simulations and virtual environments is not always necessary, writing, “Our own research proposes that the physical reality of the learning situation is of less importance than the characteristics of the task design, and the engagement of students in the learning environment.”
But the goals of diversity and authenticity are complementary. Engaging eLearning that includes authentic, collaborative tasks that teach and reinforce skills used on the job is ideal for some types of training. Simulations, games, and immersive environments that allow learners to practice interactions or complex skills are the ideal framework for many types of training. In all instances, the characters, scenarios, and language used in training exercises should reflect the makeup of the company and the community. Authentic eLearning demands a diversity of characters, pseudo-customers, and learner avatars.
References
Herrington, Jan. “Authentic e-learning in higher education: Design principles for authentic learning environments and tasks.” World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, 2006.
Herrington, Jan. “Authentic Learning.”
Herrington, Jan, T.C. Reeves, and R. Oliver. “Immersive learning technologies: Realism and online authentic learning.” Journal of Computing in Higher Education, Vol. 19, No. 1. 2007.
Stanford Graduate School of Business. “Diversity and Work Group Performance.” 1 November 1999.