Analysis Strategy

Each google form was linked to its corresponding spreadsheet. 

The Video Game Skill Survey collected the ratings each student would mark per question. The first page of this sheet recorded the responses to each question, and the second page anonymized each student's data. All the responses per student were then averaged, resulting in (V). 

The second google form, labeled Informational Math Test, collected students’ names and emails, a timestamp, form timer, their overall math score, and individual answers to each of the questions. The form timer tracked, in minutes, how much time a student had remaining to submit their google form, from a 12 minute timer. On the second page of this sheet, student’s were labeled A-Z, corresponding to the labels created in the Video Game Skill Survey sheet.  (t) was calculated, then (t) and (a) were imputed here. Finally, the average was taken between (t) and (a) to calculate (M). 

Each students’ (V) was paired to their (M) to create an individualized data point. These data points were transferred to a final, third spreadsheet for graphic analysis. Using the google charts graphing application, these data points were graphed on a scatter plot. 

From here, the resulting scatter plot and data were analyzed according to both correlational and scatter plot analysis rules and concepts. Aside from visual representations of the correlation, such as a trend line, calculations were made to numerically represent the correlation. I used online tools to calculate these values, including the correlation coefficient (Pearson’s R), the significance level (alpha (a)), p-value, and the degrees of freedom. These values and the visual representation provided the needed results to draw final conclusions on the study. 

The trendline follows a basic linear pattern in the positive direction, with weak association. Of the data collected, no outliers were present. To describe what a ‘weak’ association represents, Pearson’s r, the correlation coefficient was calculated. 

r = .2375 or .24

N (degrees of freedom) = 13

α = .05

p-value = .434617 

r(13) = .24, p = .434617

Conclusion and Next Steps

Based upon the results and analysis in the previous sections, there is a correlation between video game skill and math skill of a student. My hypothesis, video game skill will share a positive correlation with math skill, was proven to be true, however, although true, the correlation is quite weak. Knowing that this correlation does exist answers one question, yet also creates more questions directed towards a deeper understanding on the topic overall. These include, “Is there a specific genre that impacts math skill the most?”, or “Which branch of math is most impacted by video game skill?”. With further development of this research, teachers, educators, and trainers may apply this knowledge towards creating more effective educational tools for students learning math. The next step in this research is to replicate the research with a larger cohort. With a larger cohort, the findings can be applied more generally, which then allows for new research to begin based on the findings. Although this research is only a small start, it serves as a starting point for other researchers. This research aided in filling knowledge gaps between video games and math relationships. This adds to the knowledge of human and technology interaction, along with connections between technology and human thinking. This knowledge becomes much more important because of technology’s rapid advancements. Understanding as much as possible about the correlations and relationships between humans and technology will better prepare us for the challenges and future ahead.

Key Sources

Andrews, E.L. (2016, June 24). Stanford study shows how digital math games can teach more  

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https://ed.stanford.edu/news/stanford-study-shows-how-digital-math-games-can-teach-m

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Hamid, A., Yusoff, A., & Mukari, S. (2011). Brain Activation during Addition and Subtraction 

Tasks In-Noise and In-Quiet. PubMed Central. 

Pagliaccio, D., Ramphal, B., Thomas, L., Dranovsky, A., &  Margolis, A. E. (2020). Altered 

Structure and Functional Connectivity of the Hippocampus are Associated with Social 

and Mathematical Difficulties in Nonverbal Learning Disability. Hippocampus, 31(1), 

79–88. https://doi.org/10.1002/hipo.23264 

Sayan, H. (2015). The effects of computer games on the achievement of basic mathematical 

skills. Educational Research and Reviews, 10(22). https://doi.org/10.5897/err2015.2172 

Yampolskiy, R. V. (2007). Game skill measure for mixed games - University of Louisville. 

Retrieved December 21, 2022, from http://cecs.louisville.edu/ry/Game.pdf