Game Based Learning

According to John Hattie’s meta-analysis, Game Based Learning has a moderate effect size of .41, which suggests that it can be sometimes useful, but that on average the impact of using games is moderate. I have to admit, this is an influence on Hattie’s list, where I have always felt the research might be missing something. Personally as a teacher I use game based learning all the time. I especially use it to help make less engaging aspects of the learning process more appealing to my students, for example vocabulary work or math fluency work. Recently, I came across a really excellent meta-analysis by Kacmaz, Et al, conducted in 2022, on the subject of game based learning in math, which enabled me to really take a deeper dive into the topic. The meta-analysis used strict inclusion criteria and included 26 quasi-experimental and experimental studies. The study broke down results by instructional type and instructional goals. The authors also listed the effect size found for each individual study, which I used to conduct a secondary meta-analysis on the impact of game based learning, on grade. 

 

Meta-Analyses Results:

Definitions:

 

Direct Instruction

“Learning is linked with stimulus-response conditioning, rapid-pace drills, or structured lesson plans that generate student engagement through pacing and immediate feedback. Learning and instruction that entails rote memorization of facts and does not necessarily facilitate creative thought. The presentation of the game follows question, answer, and feedback. Repetitive practice is offered.”

 

Experiential Learning:

“Learning and teaching in games are based on learning by doing and solving real-life problems through experiencing and interacting with the environment. Learners gain understanding by engaging in simulated actions related to real-life experiences and learn by interacting with the objects in the game. The fundamental basis for experiential learning is the active role of the learner through interaction with the environment.”

 

Discovery Learning:

“Learning occurs as students discover concepts on their own through levels. Discovery learning builds on existing knowledge to discover new things, the learner applies inquiry-based reasoning, performs problem solving, makes the decision, and applies strategy. Students interact with game by exploring and manipulating objects or performing experiments”.

 

Situated Cognitive: 

“Learning is a product of engaging in contexts, activities and culture such that learning occurs in real situations. Students work on exercises or activities that relate to their social and cultural backgrounds. The game allows and encourages students to learn by interacting with others. Situated cognition can occur within game-based learning when learners access the context-specific knowledge by observing and becoming actors within games.” 

 

Constructivist:

“Learners are actively engaged in their own learning such that knowledge is assumed to be constructed by learners rather than transmitted. Constructivism closely relates to experiential and discovery learning. However, it adds the construction of personal meaning by the learner as a final step.”

 

Discussion:

Personally, I tend to use game-based learning in math to teach things that would normally be taught through rote-memorization. I have found this especially helpful, for increasing students' number-sense, and computational fluency. I tend to use this as a strategy to try and make the more mundane elements of math more entertaining and while these types of outcomes did fairly well in the meta-analysis, Experiential games aimed at developing students' problem solving abilities performed much better. This surprised me as this is not how I tend to teach problem solving. Personally, I tend to teach problem solving through situational problems. Overall game-based learning was a high yield strategy when the games were either direct instruction or experiential based. Game-based learning seemed least effective for Discovery based learning and Constructivist based learning, perhaps because designing a discovery based game requires greater expertise/planning time. 

 

When I did my secondary meta-analysis of the topic, I expected to find game-based learning to perform better in the younger grades, where fluency was more important and worse in the older grades where the math becomes more complex. However, my results did not fit my bias. Indeed, if any relationship exists between the efficacy of game-based learning in math and age, it appears that older students benefit more than younger students. However, admittedly, the effect size found for secondary students specifically, was based on a single study, as most studies were on intermediate and primary aged students.


 

References:

 

  Kacmaz. (2022). Examining pedagogical approaches and types of mathematics knowledge in educational games: A meta-analysis and critical review. Educational Research Review, 35, N.PAG.

 

J, Hattie. (2022). Meta-X. Visible Learning. Retrieved from <https://www.visiblelearningmetax.com/influences>.