Key Takeaway 

It is very easy to gamify or incorporate games (virtual or otherwise) into a lesson plan to improve learning and/or motivate learners to be engaged. How can we ensure that they not only improve learning but cause learning as well? Using the Universal Design for Learning framework in connection to a review of related literature on motivation and social learning, this study has identified several effective factors that need to be considered for developing serious games. —Nika Espinosa

Role of Games in Learning

Serious games are activities that “serve as mediators to directly cause learning,” as defined by Landers (2015).1 A lot of research into serious games has shown conflicting evidence on their impact on education. However, observed inconsistencies can be resolved. Drawing from theories on social learning, motivation, and the framework of Universal Design for Learning, Watt and Smith (2021) determine guidelines for designing serious games.

“Virtually all games explored in these studies were single-player computer games.” These games do not support the importance of social learning. The evidence from social constructivism tells us that learning is dependent on the interaction between the learners. “Participation in cooperative learning strongly predicts student achievement2 as well as increasing student motivation and self-efficacy and decreasing anxiety.”3 Furthermore, the literature strongly suggests that even when the game has a social component, cooperative games are found to be more effective as opposed to competitive games with leaderboards and social components. 

“Motivation and engagement have been shown to have a positive effect on learning,4,5,6 and so can be considered moderators of learning.” Glynn et. al (2011)7 would like us to view motivation as having four key components: intrinsic motivation, extrinsic motivation, self-efficacy, and self-determination. 

There were six social learning factors and eight motivation factors identified as effective serious game design guidelines based on the literature reviewed by Watt and Smith (2021) in connection to Universal Design for Learning. 

Social Learning Factors for Game Design

The social learning factors are:

  • Introducing team-building activities before the learning activities.8
  • When designing games, a team identity that encourages membership maintenance should be developed.8,2 
  • Game design should lean more towards cooperative rather than competitive play.9,10,11,12 
  • Ensured opportunities where each member can be an expert through developing specialties.13 
  • Ensured opportunities where each member can teach other members in their expertise,13,14,15,16,17,18 
  • Experiential learning should be supported with a level of teacher guidance.19,20,21,22,23,24,25 

Motivational Factors for Game Design

 The motivational factors are:

  • Considerations for themes or narratives that are compelling.26,7 
  • Promoting self-determination through adequate decision-making and freedom of movement.27,28 
  • Provision of multiple attempts and strategies as opposed to a punitive approach to failure.29,30
  • In order to encourage grade motivation, learners need to be assessed on content within the game.31
  • Rewarding learning as opposed to performance.7 
  • Student achievement must be evident in order to earn rewards.7,8 
  • In-game rewards for learning should be included in order to benefit later play.28 
  • Immersion and visual elements should be balanced so as not to add unnecessary cognitive load.32 

An impressive, well-developed game can take several years to develop. “These games often require budgets of over half a billion dollars and teams of hundreds of developers to produce.” Educators do not have the time nor capacity to create such games. What educators can do instead is to deliver content material in a fun and engaging manner, by using these proposed guidelines, to ensure that it does not only improve learning but that there is learning happening as well.

Summarized Article:

Watt, K., & Smith, T. (2021). Research-Based Game Design for Serious Games. Simulation & Gaming, 104687812110067. https://doi.org/10.1177/10468781211006758

Summary by: Nika Espinosa—Nika believes that personalized learning is at the heart of special education and strives to collaborate with educators in providing a holistic, personalized approach to supporting all learners through the MARIO Framework.

Additional References:

  1. Landers, R. N. (2015). Developing a theory of gamified learning: Linking serious games and gamification of learning. Simulation and Gaming. https://doi.org/10.1177/1046878114563660
  2. Tsay, M., & Brady, M. (2010). A case study of cooperative learning and communication pedagogy: Does working in teams make a difference? Journal of the Scholarship of Teaching & Learning, 10 (2), 78–89. http://mtsayvogel.com/wp-content/uploads/2015/07/Tsay-and-Brady-JOSOTL-2010.pdf
  3. Courtney, D. P., Courtney, M., & Nicholson, C. (1992). The effect of cooperative learning as an instructional practice at the college level. College Student Journal, 28 (4), 471–477. https:// files.eric.ed.gov/fulltext/ED354808.pdf
  4. Paas, F., Tuovinen, J. E., Van Merriënboer, J. J. G., & Darabi, A. A. (2005). A motivational perspective on the relation between mental effort and performance: Optimizing learner involvement in instruction. Educational Technology Research and Development, 53 (3), 25–34. https://doi.org/10.1007/BF02504795
  1. Zhao, C. M., & Kuh, G. D. (2004). Adding value: Learning communities and student engagement. Research in Higher Education, 45 (2), 115–138. https://doi.org/10.1023/ B:RIHE.0000015692.88534.de
  2. Carini, R. M., Kuh, G. D., & Klein, S. P. (2006). Student engagement and student learning: Testing the linkages. Research in Higher Education, 47 (1), 1–32. https://doi.org/10.1007/ s11162-005-8150-9
  3. Glynn, S. M., Brickman, P., Armstrong, N., & Taasoobshirazi, G. (2011). Science motivation questionnaire II: Validation with science majors and nonscience majors. Journal of Research in Science Teaching, 48 (10), 1159–1176. https://doi.org/10.1002/tea.20442
  4. Slavin, R. E. (2011). Instruction based on cooperative learning. In R. E. Mayer & P. A. Alexander (Eds.), Handbook of Research on Learning (pp. 344–360). https://doi.org/10.4324/9780203839089
  5. Abu-Dawood, S. (2016). The cognitive and social motivational affordances of gamification in E-Learning environment. Proceedings – IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016, (July 2016), 373–375. https://doi.org/10.1109/ ICALT.2016.126
  6. Johnson, D. W., Maruyama, G., Johnson, R., Nelson, D., & Skon, L. (1981). Effects of cooperative, competitive, and individualistic goal structures on achievement: A meta- analysis. Psychological Bulletin, 89 (1), 47–62. https://doi.org/10.1037/0033-2909.89.1.47
  7. Kolawole, E. B. (2008). Effects of competitive and cooperative learning strategies on academic performance of Nigerian students in mathematics. Educational Research and Reviews, 3 (1), 33–37. https://academicjournals.org/article/article1379584288_Kolawole.pdf
  8. Qin, Z., Johnson, D. W., & Johnson, R. T. (1995). Cooperative versus competitive efforts and problem solving. Review of Educational Research, 65 (2), 129–143. https://doi.org/10.3102/00346543065002129
  1. Vygotsky, L. S. (1978). Mind in society (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, eds.). Cambridge, MA: Harvard University Press.
  2. Devin-Sheehan, L., Feldman, R. S., & Allen, V. L. (1976). Research on children tutoring children: A critical review. Review of Educational Research, 46 (3), 355–383. https://doi. org/10.2307/1170008
  3. O’Donnell, A. M. (2006). The role of peers and group learning. In P. A. Alexander & P. H. Winne (Eds.), Handbook of educational psychology (pp. 781–802). Mahwah: Lawrence Erlbaum Associates Publishers.
  4. Palincsar, A. S., Brown, A. L., & Martin, S. M. (2011). Peer interaction in reading comprehension instruction. Educational Psychologist, 22 ( 3–4 ), 231–253. https://doi.org/10.1080/00461 520.1987.9653051
  5. Rosenshine, B., & Meister, C. (1994). Reciprocal teaching: A review of the research. Review of Educational Research, 64 (4), 479–530. https://doi.org/10.3102/00346543064004479
  6. Webb, N. M. (2008). Learning in small groups. In T. L. Good (Ed.), 21st Century education: A reference handbook (pp. 203–211). Los Angeles: Sage Publications.
  7. Brown, A., & Campione, J. (1994). Guided discovery in a community of learners. In K. McGilly (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice (pp. 229– 270). Cambridge, MA: MIT Press. https://psycnet.apa.org/record/1994-98346-008
  8. Hardiman, P. T., Pollatsek, A., & Well, A. D. (1986). Learning to understand the balance beam. Cognition and Instruction, 3 (1), 63–86. https://doi.org/10.1207/s1532690xci0301_3
  9. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41 (2), 75–86. https:// doi.org/10.1207/s15326985ep4102
  10. Mayer, R. E. (2004). Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. American Psychologist, 59 (1), 14–19. https://doi.org/10.1037/0003-066X.59.1.14
  11. Moreno, R. (2004). Decreasing cognitive load for novice students: Effects of explanatory versus corrective feedback in discovery-based multimedia. Instructional Science, 32 (1–2), 99–113. https://doi.org/10.1023/b:truc.0000021811.66966.1d
  12. Sweller, J., Mawer, R. F., & Howe, W. (1982). Consequences of history-cued and means-end strategies in problem solving. The American Journal of Psychology, 95 (3), 455–483. https://doi.org/http://psycnet.apa.org/doi/10.2307/1422136
  13. Tuovinen, J. E., & Sweller, J. (1999). A comparison of cognitive load associated with discovery learning and worked examples. Journal of Educational Psychology, 91 (2), 334–341. https://doi.org/10.1037/0022-0663.91.2.334
  14. Garris, R., Ahlers, R., & Driskell, J. E. (2002). Games, motivation, and learning: A research and practice model. Simulation and Gaming, 33 (4), 441–467. https://doi. org/10.1177/1046878102238607
  15. Black, A. E., & Deci, E. L. (2000). The effects of instructors’ autonomy support and students’ autonomous motivation on learning organic chemistry: A self-determination theory perspective. Science Education, 84 (6), 740–756. https://doi.org/10.1002/1098- 237X(200011)84:6<740::AID-SCE4>3.0.CO;2-3
  16. Westera, W. (2019). Why and how serious games can become far more effective: Accommodating productive learning experiences, learner motivation and the monitoring of learning gains. Educational Technology & Society, 22 (1), 59–69. Retrieved from https://www.jstor.org/ stable/26558828?seq=1#metadata_info_tab_contents
  17. Bandura, A. (1997). Self-efficacy: The exercise of control. Macmillan.
  18. Bandura, A., Barbaranelli, C., Caprara, G. V., & Pastorelli, C. (1996). Multifaceted impact of self-efficacy beliefs on academic functioning. Child Development, 67 (3), 1206–1222. https://doi.org/10.2307/1131888
  19. Herrington, J., Reeves, T. C., & Oliver, R. (2010). A guide to authentic e-Learning. In A Guide to Authentic e-Learning. https://doi.org/10.4324/9780203864265
  20. Cheng, M. T., Lin, Y. W., She, H. C., & Kuo, P. C. (2017). Is immersion of any value? Whether, and to what extent, game immersion experience during serious gaming affects science learning. British Journal of Educational Technology, 48 (2), 246–263. https://doi.org/10.1111/bjet.12386

Key Takeaway: There are some studies supporting the notion that learning with ease suggests fluency and can lead to better performance. However, this can lead to a misconception that learning has to be easy and facing challenges is problematic. It is important to establish that difficulties are part of learning and that disfluency can open up possibilities for identity exploration. Virtual learning environments (VLEs) can be designed in such a way that they support this exploration, by looking at features such as gamification, engagement and connection, and learning supports. —Nika Espinosa

In their article, Oyserman and Dawson look at the framework of identity-based motivation and how it connects to virtual learning environments (VLEs). Identity-based motivation is about the self and the motivational power behind it. This includes procedural readiness, action readiness, and dynamic construction. “Together, these core aspects provide a framework for understanding the interplay between people’s sense of who they are, their actions, their interpretations of experienced ease and difficulty, and how learning environments may frame these processes.” 

The authors used the identity-based motivation lens to examine how to enhance VLEs. With the current global context, digital learning platforms have boomed. According to Lenhart (2016), “almost all (92%) adolescents currently go online daily and nearly three in four (72%) play games, regardless of their socioeconomic status, age, race, or gender.”1 But even before the global pandemic, as technology aims to further enhance our lives, digital platforms are increasingly being used in education. Oyserman and Dawson believe that VLEs have the potential to provide opportunities for identity exploration because they are versatile and dynamic. “As such, they can scaffold either a learn-with-ease norm that diminishes engagement with schoolwork and forecloses identity exploration or a learn-through-difficulty norm that enhances both.” Moving forward, we need to understand how to effectively use VLEs and how they can complement face-to-face learning.

In connection with identity-based motivation and the research mentioned by the authors, it can be inferred that students in a difficulty-as-importance context outperform students who are in a difficulty-as-impossibility context or even students who are not posed with either context. This is a consideration when designing VLEs. When VLEs are successful, they have the potential to improve engagement and connection when learning. “This is more likely when the VLE learning norm does not conflate ease with learning but instead links learning and engaging with difficulty.” According to the authors, VLEs can be used to identify probable future identities in relation to identity-based motivation. For example, an activity that is science-based could encourage the learner to consider a possible future in the same field. 

Meaningful learning comes with effort.2,3 When students acknowledge and accept the notion of difficulty-as-important, engagement and connection increase. In the context of well-designed VLEs, these can also be used to promote self-discovery.  

Article Summarized: 

Oyserman, D., & Dawson, A. (2021). Successful learning environments support and harness students’ identity-based motivation: A primer. The Journal of Experimental Education, 1–15. https://doi.org/10.1080/00220973.2021.1873091

Summary by: Nika Espinosa—Nika believes that personalized learning is at the heart of special education and strives to collaborate with educators in providing a holistic, personalized approach to supporting all learners through the MARIO Framework.

Additional References:

  1. Lenhart, A. (2016). Teens, social media & technology overview, Pew Research Center, https://www.pewresearch.org/ internet/2018/05/31/teens-social-media-technology-2018/
  2. Kornell, N., & Bjork, R. A. (2007). The promise and perils of self-regulated study. Psychonomic Bulletin & Review, 14(2), 219–224. https://doi.org/10.3758/bf03194055
  3. Yan, V. X., Bjork, E. L., & Bjork, R. A. (2016). On the difficulty of mending metacognitive illusions: A priori theo- ries, fluency effects, and misattributions of the interleaving benefit. Journal of Experimental Psychology: General, 145(7), 918–933. https://doi.org/10.1037/xge0000177