To scrutinize the relationship of achievement in video games with performance on generalized visual cognition, this study utilized a change-detection based paradigm in which subjects attempted to accurately identify previously displayed images after a short period of processing time in order to discover a pre-established cognitive advantage that experienced video game players have over non-video game players in adolescents. This cognitive advantage will serve as evidence that video games possess variables that can improve visuospatial intelligence. Therefore, video games have the ability to differentiate individuals from their peers, and possibly alleviate cognitive deficits which will be discussed in the implications. To further validate the accuracy of this study a revised method was conducted after analyzing past investigations surrounding visual short term memory (VSTM). Participants were recruited through a high school Robotics program because those members are more likely than the general school population to play video games. They underwent both a pre-experiment and post-experiment survey giving information regarding their video game usage which was logged in a data table. Based on their video gameplay, they were divided into one of four categories ranging from true Action Video Game Players (AVGP) to true Non-Video Game Players (NVGP). Participants who fell in between the parameters were not excluded. The analysis of the data from the N-back task drew correlations based on accuracy, response time, and each Participant’s video game time. This study aimed to find a predisposed advantage among the individuals. A correlation between average video game time and excellence in the N-back task could provide sufficient evidence for further studies to investigate video games as an aid in VSTM which the N-back task gauges. With this new information, there can be future studies delving into how video games could be the vehicle to improve on VSTM and VWM to both distinguish individuals and correct visuospatial weakness.

The scores recorded by each player were correlationally linked to their video gameplay responses on both the surveys. Specifically, response time and accuracy were stressed for the analysis because these two factors are the most distinguishable characteristics between a gamer and a nongamer. Through the experiment software, each participant was given an identifier of two numbers. These identifiers were then matched with each Participants’ Google Form which was in chronological order. In order to do this, testing was one participant at a time. Once their responses were recorded, Participants were placed into 4 categories based on their game time. Then, their error/response rates were compared to the whole group at an individual level, and as an average for each group. Focusing on speed and accuracy was a move that Blacker and Curby endorsed with their own experiment, saying the emphasis on these factors would ensure that “performance differences between the groups would reflect the information available in VSTM rather than other factors.”
 

The N-back task response had a maximum display time of 1000 milliseconds. Therefore responses in the datasheet noted a 3 for exceeding the time. The responses earned a 1 for being correct and a 2 for an incorrect response. The N-Back response data is presented as a text file with each participant identifier. The spreadsheet discloses each Participant identifier and where they align on the spectrum of being an action video game player or a nonvideo game player. The following key is used to describe the textfile data for each participant.

1     correct (1=correct, 2=wrong, 3=too slow)

2     which key was pressed

3     reaction time (ms)

4     random number used for conditions (1=same as 3-back, 2-5 other letter)

5     trial number

6     the current letter

7     the letter of the previous trial

8     the letter of the trial before