This Learning Games Design Framework article is the first of the The Art of Learning Games Design series. Researchers and scholars agreed that learning games design framework can serve as an effective mechanism to define and share learning game design knowledge. A variety of learning games design frameworks were proposed, such as educational games (EG) design framework (Ibrahim & Jaafar, 2009), I’s framework (Annetta, 2010), RETAIN model (Gunter, Kenny, & Vick, 2008), extended MDA framework (Aleven, Myers, Easterday, & Ogan, 2010), and flow framework (Kiili et al., 2012). The current article will examine two learning game design frameworks including extended MDA framework (Aleven et al., 2010) and flow framework (Kiili et al., 2012).
Extended MDA Framework
Aleven et al. (2010) proposed a framework for designing and analyzing games for learning. This framework is built upon the foundation of the Mechanics-Dynamics-Aesthetics framework (Hunicke, LeBlanc, & Zubek, 2004). Three fundamental components for designing effective learning games were identified, including learning objectives, MDA (mechanics, dynamics and aesthetics), and instructional design principles (Figure 1).
Figure 1. Extended MDA framework for learning games design.
A clear specification and understanding of learning objectives allows instructional game designers to create games that can achieve the intended instructional objectives and goals effectively. The clear specifications of learning objectives should include information of prior knowledge requirement, intended learning outcomes and potential transfer effect. On the other hand, the MDA framework can help game designers to think and design using the three interrelated components (mechanics, dynamics and aesthetics) from both players and designers perspectives. According to the MDA framework, game mechanics determine game dynamics, which in turn influence aesthetic outcomes. Game mechanics are the basic building components of games (e.g., materials, rules, goals, moves, control options); dynamics are the behaviors resulted from player’s inputs to game mechanics; aesthetics refer to the subjective and emotional experience of the player (e.g., sensation, fantasy, narrative, challenge). Finally, instructional design principles allow learning sciences to be integrated into the design of learning games. The incorporation of instructional design principles can enhance the instructional effectiveness of learning games. The authors argued the most important task of instructional game designers are to fine tune game mechanics and dynamics to align with the underlying instructional principles for achieving instructional and aesthetic goals.
Flow Framework
Kiili et al. (2012) proposed a flow learning games design framework focusing on building flow experience with the incorporation of associative, cognitive and situative learning theories (Figure 2).
Figure 2. Flow framework for learning games design.
Flow describes a state when individuals are completely engaged or absorbed in an activity for enjoyment and pleasure voluntarily (Csikszentmihalyi, 2014). Flow experiences are often associated with the experience of concentration, time distortion and loss of self-consciousness. A crucial factor that contributes to flow experience is flow antecedents. Flow antecedents are elements that can contribute to flow state. Kiili et al. identified a list of flow antecedents, including clear goals, cognitive, immediate and guidance feedback, playability and sense of control.
Clear goals should be relevant to learning objectives to allow learners to stay focused on learning activities. These goals can be distinguished between short term and long term goals, and they should be customized to the pace and progress of individual learners. Cognitive and immediate feedback can inform learners about their performance and progress toward the goals to promote self-regulated learning. The cognitive feedback can stimulate players to develop their mental models and game playing strategies, while immediate feedback can keep players focused. Additional feedback can also be provided in the form of guidance, which can promote constructive, associative and situative learning. Playability concerns the relevancy of the game challenges to the main goals and whether these challenges match players’ skills level. These two dimensions are crucial in contributing to the flow experience. The chances of experiencing task-based flow decreases when players have to spend their limited attention and cognitive resources on irrelevant challenges. On the other hand, the challenge-skill dimension can keep players in the flow state through adapting game challenges to the increasing skill level of the players to avoid the experience of boredom or anxiety. Players may feel bored when the challenges are too easy. In contrast, players may feel anxious when the challenges become too difficult. Lastly, sense of control is considered to be closely related to the challenge-skill dimension. Sense of control refers to players perception of developing and perfecting their skills to overcome challenges in the game. This perception can enhance player’s motivation and enjoyment.
In conclusion, learning games design frameworks provide a pedagogical and empirically grounded approach for designing learning games. They allow learning games to be designed with an optimal balance between play and learning, which in turn can enhance their educational effectiveness. This is cruical in facilitating learning games to reach their educational potential and fulfill their promises of becoming an important instructional tool.
References
Aleven, V., Myers, E., Easterday, M., & Ogan, A. (2010, April). Toward a framework for the analysis and design of educational games. In 2010 third IEEE international conference on digital game and intelligent toy enhanced learning (pp. 69-76). IEEE.
Annetta, L. A. (2010). The “I’s” have it: A framework for serious educational game design. Review of General Psychology, 14(2), 105-113.
Csikszentmihalyi, M. (2014). Toward a psychology of optimal experience. In Flow and the foundations of positive psychology (pp. 209-226). Springer, Dordrecht.
Gunter, G. A., Kenny, R. F., & Vick, E. H. (2008). Taking educational games seriously: using the RETAIN model to design endogenous fantasy into standalone educational games. Educational technology research and Development, 56(5-6), 511-537.
Hunicke, R., LeBlanc, M., & Zubek, R. (2004, July). MDA: A formal approach to game design and game research. In Proceedings of the AAAI Workshop on Challenges in Game AI (Vol. 4, No. 1, p. 1722).
Ibrahim, R., & Jaafar, A. (2009, August). Educational games (EG) design framework: Combination of game design, pedagogy and content modeling. In 2009 international conference on electrical engineering and informatics (Vol. 1, pp. 293-298). IEEE.
Kiili, K., De Freitas, S., Arnab, S., & Lainema, T. (2012). The design principles for flow experience in educational games. Procedia Computer Science, 15, 78-91.
