Playing to Win: Applying Cognitive Theory and Gamification to Augmented Reality for Enhanced Mathematical Outcomes in Underrepresented Student Populations
National dialogue and scholarly research illustrate the need for engaging science, math, technology, and engineering (STEM) innovations in K-12 environments, most importantly in low-income communities (President's Council of Advisors on Science and Technology, 2012). According to Educating the Engineer of 2020, "current curricular material does not portray STEM in ways that seem likely to excite the interest of students from a variety of ethnic and cultural backgrounds" (Phase, 2005). The National Educational Technology Plan of 2010 believes that one of the most powerful ways to transform and improve K-12 STEM education it to instill a culture of innovation by leveraging cutting edge technology (Polly et al., 2010). Augmented reality (AR) is an emerging and promising educational intervention that has the potential to engage students and transform their learning of STEM concepts. AR blends the real and virtual worlds by overlaying computer-generated content such as images, animations, and 3D models directly onto the student's view of the real world. Visual representations of STEM concepts using AR produce new educational learning opportunities, for example, allowing students to visualize abstract concepts and make them concrete (Radu, 2014). Although evidence suggests that learning can be enhanced by implementing AR in the classroom, it is important to take into account how students are processing AR content. Therefore, this research aims to examine the unique benefits and challenges of utilizing augmented reality (AR) as a supplemental learning technique to reinforce mathematical concepts while concurrently responding to students' cognitive demands.
To examine and understand how cognitive demands affect students' information processing and creation of new knowledge, Mayer's Cognitive Theory of Multimedia Learning (CTML) is leveraged as a theoretical framework to ground the AR application and supporting research. Also, to enhance students' engagement, gamification was used to incorporate game elements (e.g. rewards and leaderboards) into the AR applications. This research applies gamification and CTML principles to tablet-based gamified learning AR (GLAR) applications as a supplemental tool to address three research objectives: (1) understanding the role of prior knowledge on cognitive performance, (2) examining if adherence to CTML principles applies to GLAR, and, (3) investigating the impact of cognitive style on cognitive performance. Each objective investigates how the inclusion of CTML in gamifying an AR experience influences students' perception of cognitive effects and how GLAR affects or enhances their ability to create new knowledge.
Significant results from objective one suggest, (1) there were no differences between novice and experienced students' cognitive load, and, (2) novice students' content-based learning gains can be improved through interaction with GLAR. Objective two found that high adherence to CTML's principles was effective at (1) lowering students' cognitive load, and, (2) improving GLAR performance. The key findings of objective three are (1) there was no difference in FID students' cognitive load when voice and coherence were manipulated, and, (2) both FID and FD students had content-based learning gains after engagement with GLAR.
The results of this research adds to the existing knowledge base for researchers, designers and practitioners to consider when creating gamified AR applications. Specifically, this research provides contributions to the field that include empirical evidence to suggest to what degree CTML is effective as an AR-based supplemental pedagogical tool for underrepresented students in southwest Virginia. And moreover, offers empirical data on the relationship between underrepresented students' perceived benefits of GLAR and it is impact on students' cognitive load. This research further offers recommendations as well as design considerations regarding the applicability of CTML when developing GLAR applications.