The Effect of Video Games on High School Students’ Grades

The Effect of Video Games on High School Students’ Grades







            Video games have been growing in popularity since the 1970s and are now a dominant social pastime for many adolescents. Consequently, the ramifications of playing video games by high school students have in recent times become a source of concern for educators and parents alike. This paper examines the existing literature on the effects of video games on society in general, and on high school students in particular. Furthermore, it synthesizes behavioral conditioning theory as it pertains to how young minds of high school students are affected by video games, and the rewards that video games offer that classroom subjects do not.

One key indicator of the impact of video games on students is its overall effect on their scholastic performance. Hart et al. (2009) examined the effects of excessive video game playing on social, occupational, and other school activities. Based on the data, the conclusion was that there was no relationship. The paucity of literature on the subject  stems from the lack of sufficient research to determine whether there is a link between video games and their effects on overall academic performance, as measured by the students’ GPA.

There is a general agreement that there has been a decline in the level of education in the United States. According to Castillo, Wakefield, and LeMaster, (2010), the decline over the years appears to be inversely proportional to the increase in the proliferation of video games; as the level of video games sales increase, the level of educational performance in schools declines.

People have always looked for ways to entertain themselves. While reading has been the main form of mass media-driven self entertainment for many generations, in the past decades, there has been a technological revolution that has changed that. It began with the radio; instead of reading, people could listen to music and other forms of aural entertainment. Then came television – this visual medium allowed people a wider variety of entertainment choices, like movies, news, plays, and documentaries to name a few – which dominated self entertainment, and still continues to do so. An offshoot of television was video games. Invented in the 1950s, the video game grew from a novelty in a laboratory to become a multibillion dollar industry (Gettler, nd). Video games are now the most used media entertainment for children in the US (Ferguson, 2010).

Behavioral Conditioning Theory

Even though Ballard, Hamby, Panee, and Nivens (2006) argued that the responses elicited by video games are instinctively visceral, it is also arguably a teleological response elicited by behavioral conditioning that can have far-reaching consequences on the developing minds of high school students (Dunst, Raab, Hawks, Wilson, & Parkey, 2007). Learning processes can be divided into two accounts, classical conditioning and operant conditioning. 


Classical Conditioning

There are several key principles and terminology that have been established since the inception of classical conditioning. According to Moore (2002), these are: Unconditioned Stimulus (UCS): This is a natural occurrence that triggers a biological response from environmental conditions. The natural occurrences may be aural, visual, olfactory in nature, or anything that stimulates the senses. The intensity and form of stimuli received will affect a response based on the specific nature of the stimuli; for example, the smell of cooking (the UCS) causing pangs of hunger; Unconditioned Response (UCR): Where a UCS elicits a natural response. For example, the response of hunger pangs to the scent of food (pp. 16-17).


Conditioned Stimulus (CS): When a previously neutral stimulus – such as the ringing of a bell – is paired with a UCS, it becomes associated with that UCS and evokes the same response. For example, if a bell is rung just before dinner, it becomes associated with food and evokes the same physiological response as the smell of food; Conditioned Response (CR): The response that comes from the pairing of a UCS and a CS (p. 17-19).


Operant Conditioning

In operant conditioning behavior is modified, either by the application of negative reinforcement to discourage a specific behavior, or by positive reinforcement to encourage the behavior. Once these behaviors are modified, they become known as habits. Habits can either be formed voluntarily, by using specific stimulus to create wanted outcomes, or involuntarily, as in the case of repetitive stimulus that produce learned behavior, such as associating the smell of cooking with hunger pangs. Operant conditioning, therefore, is essentially the use of rewards to encourage wanted behavior, or, conversely, the lack of rewards to discourage unwanted behavior (Weiten, 2008, p. 177-179).

Motivational Constructs

Pavlovian studies have shown that learning is achieved when a stimulus provides some type of behavioral conditioning. Even though classical conditioning is concerned with learned behavior from the continuing reinforcement of stimuli based on environmental conditions, according to Gershman, Blei, and Niv (2010), many of these learned behaviors have proven to be extinguishable when the reinforcement was removed; however, there are proven latent behaviors that resurface when the original conditions are reintroduced. One of the tenets of classical conditioning is the unconditioned response. Even after the unconditioned stimulus has ceased to exist, the unconditioned response to it may still linger, and could resurface at a later time. 

Video games are not simply for entertainment, according to Charsky and Mims (2008), they can be a valuable teaching tool. Not only do they provide a unique way of approaching various uninteresting subjects, students who use video games as a learning tool have been found to enjoy the material and retain the information to a greater extent than traditional learning within a teacher controlled environment. The games can provide an environment where learning is rewarded and getting the answers wrong is not – essentially operant conditioning.

There are several different types of video game equipment. They range from dedicated consoles that are designed to primarily play games – such as the Microsoft X Box 360, the Nintendo Wii, and the Sony Play Station – to games that are played on equipment that are not solely video game players, such as computers, cell phones, and other devices which have the ability to perform multiple tasks. 

With the advent of high definition television, 3D television and multichannel surround sound, video games designers have created a lifelike environment for a new generation of realistic games. The lifelike characteristic of these new generation games has made them irresistible to many. While there has been some research on the effects of video games on the social aspects of children and adults (Wood, et al, 2004), there has been a paucity of research seeking to examine how video games insidiously changes the lives of high schools students by having a negative impact on their grades. That is an important distinction because any impact on the academic performance of high school students can have long-term ramifications that could affect them for the rest of their lives.

Behavioral changes that occur in young children are ingrained in their psyche and can have an impact on life-changing decisions that they make; furthermore, these changes can have far-reaching consequences that would affect every part of their social and professional life.

Of particular interest is the theory of operant conditioning. The behavioral and psychological processes of operant conditioning are similar to those that occur in the learning styles of video game players (Bolling, Terry, & Kohlenberg, 2006). For example, some students may be more influenced by conditions, like violent actions, that exist in some video games than in others. Moreover, all students may not always be able to separate the video game world from the reality of everyday living (Ferguson & Rueda, 2010), thereby creating conditions for rewarding students for increasing their level of violent activity – the types of games that have been proven to be particularly addictive. These rewards could translate into unrealistic students’ expectations in the real world.

            While video games have their own reward structure endemic to the game, there are different reasons why students play. Possible motivational constructs that could determine the effects of video game playing on high school students’ grades are: intrinsic and, or, extrinsic rewards; social interactive situations with friends and family; autonomy; and self regulation. 

Extrinsic Rewards

            There are extrinsic rewards inherent to video games – for example, players can collect points, achieve improved capabilities, or get to the next level as a prerequisite for winning or completing the game – moreover, there are also online games where players can compete against other players for prizes. Furthermore, Wood, Gupta, Derevensky and Griffiths (2004), found that extrinsic rewards can be a strong motivational factor in playing video games, these same rewards can also be a precursor to other addictive behavior as adults. Indeed, gambling and alcoholic dependency has been seen as addictive behavior that has its roots in genetics and childhood upbringing (Lawrence Luty, Boodan, Sahakian, and Clark, 2009).

Intrinsic Rewards

            While the extrinsic rewards are a big part of the reason for playing, some players prefer peer approval which can be a huge incentive to video game players (King, Delfabbro, and Griffiths, 2010). Furthermore, they also theorize that completing the game, or even completing a particular part of the game can increase gratification enough for them to increase the time spent playing. An article by Kappes and Thompson (1985) suggested that those who play video games are motivated by their need to have a strong degree of control over events. Video games give them that sense of control and confidence.

Social Interaction

            A study by Ballard, Hamby, Panee, and Nivens (2006) suggests that players of violent video games are more likely to be antisocial and lack cognitive adaptability. Moreover, this study found that these players may have an increasingly decreased sensitivity to video games violence. While the study did not specifically deal with the effect that video games have on high school student’s grades, there was evidence that violent games increased aggression, anxiety, and arousal. Furthermore, a study by Moyer (2008) found that there was a correlation between video game playing and social cognitive behavior among fifth and eighth grade students, while an article by Wallenius, Rimpela, Punamaki, and Lintonen (2009) suggests that excessive video game playing by adolescents has an effect on their school performance, sleeping habits, and their communication with their parents. However, the study by Ballard et al. (2006) pointed out that the aggression effects on video games players was no different from the aggression brought about by watching violent television shows that children have been watching before the advent of video games. But children and teenagers today occupy their time with both violent television shows and violent video games. Furthermore, unlike video games, television could be considered a passive form of entertainment. The Ballard et al. ANOVA study had a sample size of 42 adolescents; variables measured were behavioral aggression, anger, and arousal during video game play. The experimental sessions were completed in three sessions conducted over three weeks. The results of the study found that the players would not have increased arousal during play, they would instead show signs of increased negative aggression after game play. Furthermore, they would become desensitized to the violence in the games and would increasingly need to have new and more violent games.





Video Games and Learning

Evidence of Problems

            Existing research has documented several areas where video games have caused problems for young players. According to Ballard, et al (2006), these problems include: poor grades, social deficits, aggression, and hostility. Pathological gaming, identified as players who experience severe life-style disruptions when video game playing consumes their time, affects their grades, social functioning, and psychological well being. Researchers used the Diagnostic and Statistical Manual of Mental Disorders (DSM) to define pathological gaming as a behavioral addiction that affects several areas of a person’s life (Gentile, 2009). 

            However, contrary to most of the research that found evidence of negative effects on children, a study by Chuang and Chen (2009) found that video games improved children’s cognitive learning skills by challenging and motivating them. Furthermore, in a study that measured the effects of violent video games, it was discovered that players were better able to cope with stress after playing violent video games for long periods; the same effect was not evident when games were only played for short durations (Ferguson and Rueda, 2010).

School performance

Several studies have looked at the effect of playing video games on the academic performance of students but none of them specifically examined the effect it has on the grades of high school students. For instance, Weis and Cerankosky (2010) studied the direct causal effect of owning a video game to the scholastic performance of young boys, ages 6 to 9 years old. Pretest and posttests that measure academic achievement were obtained among students in randomly divided groups, one group was given a video game system after taking the baseline assessment, the other group was promised to receive their video game system after four months. The results of the study showed significant difference among the control and experimental group in terms of academic achievement. Boys who were given the video game system immediately were seen to have lower scores in reading and writing, and were reported to spend less time in academic activities compared to those who had not received their video game system. More time spent by the student in playing video games predicted poorer academic achievement.

 This same principle was studied by Cummings and Vanderwater (2007). They postulated that playing video games would take up the time of people that could have been used in engaging in other activities like social interaction with family and friends and other school activities. They found that video game players spentd less time reading and doing homework compared to those who do not play video games. The participants, ages 10 to 19 years, used diaries to record time spent participating in various activities with parents and friends.  The researchers, however, clarified that this is not a direct measurement of school performance but suggested that these activities are signs of school engagement that could be related to school performance.

Gaming frequency was also the focus of a study by Ip, Jacobs, and Watkins (2007). They sought to establish whether there was any correlation between exam scores on various academic areas and the amount of time spent playing video games. The results found that all significant correlations to be were all negative, indicating that the frequency of playing video games is negatively related to academic performance, that is, as frequency of playing increases, the level of academic achievement decreases. They found that several subject areas such as physical sciences and language, showed more significant negative correlation between the two variables among the respondents. Another important conclusion of the study was that there are other factors that are predictors of low academic achievement such as time spent on social events, watching television, listening to music and other pastime. The researchers stressed that the low academic performance observed among frequent players could not be caused directly by playing video games. It is important to note that this study used a population of undergraduates; because of this, the results may not apply to high school students. Additionally, the time the students spend doing something other than academic activity might be directly correlated to low school performance among the college student respondents of this study.

Similarly, Sharif and Sargent (2006) concluded that media exposure, such as television, movies and video games, each have significant main effect relationship with lower school performance of middle school students. They found a stronger relationship between school performance and time spent on media exposure during weekdays. These findings suggest that it is the reduced time spent on homework or studying that has a detrimental effect on school performance and not the particular type of media to which students were exposed.

Although there is extensive research suggesting this negative correlation between playing video games and academic performance, all the previous research focused on the time spent playing video games or the time lost that could have been used doing educational activities that would increase learning. The particular and unique properties or qualities of video games that might cause the observed decreased scholastic achievement and school performance is yet to be established by the body of research on this topic.

Attitude to learning

            Children’s learning processes take different forms. Even though learning is typically thought of as something children accomplish in the classroom, they also learn during play. However, while schoolwork can be tracked and tested, video game play does not enjoy that same luxury (Hamlen, 2011). 

According to previous studies, intrinsic motivation to learn plays a key role in academic achievement in children (Linnenbrick, 2002) and this motivation persists in adolescents (Gottfried, et al., 2001). Intrinsic motivation to study and learn among grade school and high school students was not observed to change greatly over time. Gottfried and his colleagues (2001) posited that this level of motivation found among the young students is likely to persist when they grow older;  if students are initially enjoying school or learning and feel the pleasures of performing well in school, they are likely to have the same motivation during high school. Contrary to this, other studies have shown that students actually diminish their level of motivation as time passes (Bowman, 2004). This decrease in motivation can be apparent in the student’s diminishing interest and enthusiasm towards learning. Stipek (1988) suggested several reasons why a person would have a low motivation, and these reasons include the conflict between their long term goal and their present activities and the lack of association between their current activities and their goal. This suggests that, if students’ long term goal is to learn or succeed in school, but they engage in other activities that do not seem related to that goal, such as playing video games, their motivation in school would decrease. Interest and excitement of students are seen to be centered more on video games than school, as evidenced by the growing time spent on video games by students as compared to the time that they spend doing school work (Stipek, 1988). Cummings (2007) studied the effects of video game play on the time spent by adolescents in other activities, and concluded that those who play video games spent 30% less time reading than those who do not, and 34% less time on homework compared to non-gamers. This suggests that they are more motivated to play video games than to do school work. Research shows that motivation is related to the time an individual spends on a particular task (Marzano, 2003). As students spend more time doing something they are more motivated to do like playing video games, they spend less time on their school work, thus, decreasing their level of learning in school.

It can be noted that the rewards of playing, which include competition, challenge, diversion, social interaction and arousal (Sherry & Lucas, 2003 cited by Przybylski, et al., 2010) and the rewards for learning in school have some parallelism, which might suggest that some students could be substituting the rewards they feel when they achieved something in playing video games with the rewards that they could feel if they succeed in school. Przybylski and his colleagues (2010) found that the intrinsic motivation of gamers to play included a sense of competence and autonomy and relatedness, the same components of motivation that Ryan and Deci (2000) suggested in their Self Determination Theory that states that these three innate psychological needs of humans guide their behavior and actions. Williams and his colleagues (2008) also reported that achievement motivation is a very strong predictor of amount of time spent playing games, although social reasons and immersion also were seen to have a significant relationship with playing time.  This could be very dangerous for students who no longer seek their sense of achievement or competence in school but instead turn to video games to satisfy these needs for intrinsic rewards. It can be hypothesized that students that are initially low performing at school might turn to video games to achieve the mastery and superiority that they do not get from school, thus, further decreasing their school performance. Gamers also report that their motivation for playing video games is that it is enjoyable and entertaining (Przybylski, et al., 2010). This added intrinsic motivation that most students fail to attribute to school activities gives them more motivation to play than to spend their time doing homework that could lead to a higher GPA.


Aspirations or the ideal goals that people strongly desire to achieve are also altered by the changes in the media and prevalence of video games. Educational aspirations of adolescent students were assessed by Geckova, et al. (2010) who concluded that attitudes towards school or how much adolescents liked school had a significant effect on students’ educational aspirations. Based on previous research, video game players tend to have a diminished motivation to learn in school compared to those who do not play games as seen by the reduced amount of time gamers spend doing homework and reading (Cummings, 2007). This could mean that the lack of motivation and less positive attitude of gamers towards school could significantly affect their educational aspirations in the future. Ryan (2001) found that adolescents tend to form groups according to their academic characteristics, and researched the influence of peer groups on the development of adolescents’ motivation and achievement in school. He concluded that peers influenced each other on attitudes towards school such as liking and enjoyment of school. It might be hypothesized from these findings that students who bond together due to common interest in video games and common attitude towards school influence each other in their future education aspirations.

Negative Associations to Learning

Attention Deficit

Chan and Rabinowitz (2006) concluded that high school video game players who play more than one hour per day have more inattention, lack of notice or regard, and other symptoms of Attention Deficit Hyperactivity Disorder compared to those who do not play. However, the research did not clarify the causality of the variables. It is possible that the subjects that are already experiencing symptoms of ADHD spend more time on video games for a reason not yet established. Still, this association between video game playing and inattention could pose some problems for parents and teachers given the rapid escalation of the popularity of video games among students. Inattention has been seen to be negatively associated with several cognitive functions like mental processing speed and working memory. Both functions are seen to have a positive effect on learning rate and performance (Rast, 2011). This suggests that if playing video games causes inattention among students, then their school performances are likely to be affected because processing speed and memory, functions that are seen to be related to inattention, are important cognitive functions that contribute to learning.

Lack of concentration and focus

Extensive researches have linked lack of focus and concentration to television viewing. Anderson et al. (1977) have hypothesized that frequent television viewing could decrease a child’s sustained focus on other tasks that are less attention-grabbing. These tasks that do not have the attention grabbing characteristics of television may include school work. Thus, suggesting that early exposure to television among children may cause them to have a decreased ability to concentrate on homework and in school. Several other studies have shown that this same problem with attention and focus among children can be found among adolescents (Landhuis, et al, 2007; Johnson, et al., 2007), suggesting that the problem in focusing on tasks may extend to later years in students’ school life.

Given that television has been around longer than video games, very few studies have focused on the effect of playing video games and concentration. However, Swing and his colleagues (2010) hypothesized that television and video games are conceptually related because both share similar features like the excitement they elicit and the rapid shift in focus that the activities entail. They suggested that both activities could possibly cause similar pattern in attention and focus of television viewers and video game players. This could mean that video game exposure among children and adolescents could cause lack of focus in school work and other activities. Swing et al. (2010) concluded that grade school children and college students who spent too much time playing video games are twice as likely to have attention problems compared to those who did not. Using a longitudinal study with two different samples, one with 1323 middle childhood and another with 210 late adolescent participants, the research showed that spending too much time playing video games and watching television is associated with short attention span and lack of focus in school.


Carden, Bryant and Moss (2004) reported that students with lower GPA were found to show significantly higher academic procrastination, which suggests that procrastination, or the delay in execution of a task negatively affects school performance. Rabin et al. (2011) studied the executive functioning components related to academic procrastination among college students. They reported that procrastination affects achievement, academic efficacy and quality of life of a student.  They have found that working memory is one of the significant predictors of academic procrastination. Working memory and attention are some of the cognitive functions that were found to be negatively affected by playing video games. Thakkar (2009) mentioned in his research that video games offer a distraction to students that result in their procrastination with school work. These bodies of work show indirectly how video games are associated with procrastination and how procrastination may lead to lower academic achievement and performance.

Time management

It is logical to assume that youths who spend too much time playing video games would have less time for other activities such as homework, chores and social activities that may involve family and peers. Kline (2000) reported that adolescents who play video games excessively are more likely to delay doing homework and family activities than those who do not.

Tobin and Grondin (2009) studied how adolescent video game players perceived duration of time spent doing certain activities. They have reported that the subjects in general have a tendency to report the amount of time playing a video game as less than it actually was. They underestimated the time that they spent playing but overestimated the time that they spent reading. This suggests that the adolescents experience an altered sense of time that is not congruent with reality. This was explained by the amount of perceptual stimulation that they get from playing video games as compared to when they are reading. Furthermore, the subjects reported to be video game players showed an even more decreased estimation of time spent playing. The findings of this research suggest that the students who play video games are likely to be unaware of other considerations when it comes to time. They underestimate the time that they spend playing and over estimate the time that they spend doing school work. This poses a problem to students’ time management skills since they naturally tend to spend more time playing video games and lose track of time doing so, and spend very little time doing other activities that do not provide as much stimulation and do not grab their attention. 

Depression and Learning

A recent study by Gentile et al. (2011) looked at third, fourth, seventh and eighth graders in Singapore longitudinally and assessed pathological gaming inclinations and effects among them in a span of three years. They found that students who spent more time playing video games eventually become more impulsive and socially less competent and are more likely to develop pathological gaming or addiction to the game. As a result, the researchers concluded that pathological gamers were more likely to develop depression, anxiety and social phobias. These students were more likely to have lower grades in school as a result of poor performance and family relationship problems. 

Similarly, teenaged high school students in China who reported excessive internet use for gaming were also found to be more than twice as likely to suffer from depression after nine months according to a study by Lam and Peng (2010). Adolescents and school children were seen to be affected by depression, either major depression or mild cases, that were seen to affect school performance (Lamarine, 1995). These findings suggest that parents and teachers should not only be aware of negative school performance among video game players but also the possible depression that might develop as a result of excessive time spent playing video games.

Sleep pattern

If students spend more time playing video games, they have less time to spend doing other activities such as school work or even sleeping. Wallenius (2009) found that students who are ritualistically motivated to play video games, that is, they play to pass the time and entertain themselves, were seen to have a much later bed time and longer video game play time than those who play with instrumental motivation or the desire to experience and learn things through playing. Sleep continuity and sleep architecture after playing video games were assessed by Dworak et al. (2007) who found that both continuity and architecture of sleep were affected negatively by playing computer games. Lack of sleep was seen be associated with distractibility, inattention, lack of motivation and decreased ability to consolidate memories that are seen to affect learning negatively (Carskadon, 2011). Dewald and his colleagues (2010) assessed the relation between lack of sleep, poor sleep quality and sleepiness with the school performance of children and adolescents. They found that all three factors showed significant relation to school performance, with sleepiness being the strongest predictor of poor school performance. 

Reduced ability to exert executive control

One function of executive control is the inhibition of an automatic response that is not consistent with a specific personal goal (Barkley, 1988; McCloskey, 2001). Inhibiting behaviors that are not relevant to a specific task have been associated with attention problems, and several studies hypothesized that video game playing and reduced ability to exert executive control are significantly related (Mathews, et al., 2005; Kirsh, Olczak, & Mounts 2005). These studies have shown that aggressive behavior and hostility that are associated with playing violent video games may cause decreased executive control. However, a direct causal relationship between video game playing and decreased executive control has not been established. Other functions of executive control include short term and working memory, speed of information processing, and attention sustenance. These functions are all associated with video game playing as mentioned above, and are also important in learning and school performance.

Verbal memory

Verbal memory seemed to deteriorate after playing video games, in a study conducted by Dworak, Schierl, Bruns and Struder (2007). After assessing the effect of playing video games and media exposure to children, these researchers suggested a direct negative causal relationship between video game play and verbal memory test performance. Verbal memory skill is important in learning, especially in the school setting where language is a key subject and its mastery contributes to the measure of school performance such as GPA.

Positive associations to learning

Visual attention

Although research above showed that video game play is associated with inattention and ADHD symptoms, this specific type of attention – visual attention – is seen to be enhanced by playing video games according to studies. Green and Bavelier (2006) have seen that gamers did better than those who do not play video games in tasks such as serial counting of stimuli, and identifying stimuli using peripheral vision, both tasks that measure visual attention. Video game players were also seen to recognize stimuli faster than those who are not. Action video games that require rapid attention shifts were also seen to help elicit improved scores in the three measures mentioned as compared to games that require a singular focus or target (Green and Bavelier, 2003). These findings suggest an increased cognitive development that might be related to other cognitive functions that are associated with learning. Further research on this might be helpful.

Spatial Ability

Spatial ability, involving perception and cognition, is the ability of a person to mentally generate, arrange, rotate and transform visual images. An increased ability to do these tasks indicates general intelligence. This ability is measured in several standardized intelligence tests including the Scholastic Aptitude Test (SAT). Quantitative and verbal abilities are seen to be correlated with visual abilities, thus indicating that people with high visual ability scores tend to have high scores on verbal and mathematical assessment tests. 

Playing video games was seen to help improve spatial abilities (Passig & Eden, 2001). De Lisi & Wolford (2002) studied the effect on spatial abilities of playing video games that involve mental rotation skills among third graders. They found that those who played video games that involve mental rotation skills scored significantly higher than those who played video games that did not make use of their mental rotation (MR) skills. These MR skills were measured using an MR test. Those with a high MR ability were measured at 24; those with a low MR ability were 23. A marked improvement was seen in the pretest and posttest scores of the students in the group that played mental rotation related games. This suggests that in order to elicit this effect on a gamer, the choice of video game is also important. Greenfields, Brannon, and Lohr (1994), looked at the relation of playing a violent video game on spatial abilities, and found that video game performance is correlated to scores on the rotational task, that is, those who did well in the game also did well on the tests. This study, however is does not directly show that playing the video game causes the increase in the scores in spatial ability measure. 


The studies that showed significant results favoring the use of video games as predictors of heightened spatial abilities imply that playing certain types of video games may have an effect on or at least a relation with the player’s skills that could possibly result in improved school performance. Spatial ability and its relation to other educational domains were studied longitudinally for more than ten years among high school students by Wai, Lubinski, and Benbow (2009). They found that high spatial ability among adolescents is indicative of expertise, achievement, advancement in education and occupation in science, technology, engineering and mathematics in the future. This result suggests that the students who scored high in spatial ability assessment are likely to excel in these domains, which implies a positive academic performance.

Insight and problem solving skills

Blumberg, Rosenthal & Randall (2008) studied insight, game strategy, and problem solving skills of video game players. The study required the subjects to play a video game with an obstacle in the course of the game, and they were asked to comment aloud about their progress throughout the game. They found that subjects who played video games more frequently showed significantly more insight and strategies as compared to those who played less frequently. As the game progressed, all participants showed increased problem-solving skills along with increased insights, game strategies, and goal achievement. This suggests that playing video games might increase a person’s ability to solve problems and direct their observations and insights and actions towards achieving a specific goal. It also implied that the participants learned to utilize certain abilities as the course of the game progressed. This ability might prove to be useful in learning and in a school setting and could possibly help a student perform better in certain school tasks. 

Reaction speed

Several studies had compared the reaction speed of video game players with non players. Orosy-Fildes and Allan (1989) found that players have a significantly faster reaction time to visual stimuli than those who do not play video games. Similarly, Goldstein and his colleagues (1997) showed that playing video games significantly improved the reaction speed of elderly participants, comparing their pretest and post test scores after playing a video game for five weeks and comparing these scores to control subjects. Yuji (1996) showed similar results among kindergarten students who play video games; however, although video game players were found to react faster, their accuracy was not significantly different from those who did not play. Expert gamers were also found to have a more quick and accurate response to several tests of visual attention, mentally arranging objects, and short-term memory (Boot, et al., 2008). These studies show that video games cause a marked improvement in the player’s reaction time on several tasks.

Strang-Carlson, et al., (2010) studied reaction time in neurocognitive abilities such as associated learning, working memory and visual attention among adults who were prematurely born. They hypothesized that prematurely born infants were deprived of weeks of rapid brain development during infancy after their birth, thus, they are expected to have less cognitive abilities than those that were born at term. Results showed that preterm subjects showed significantly slower reaction times in all test domains including associated learning and even showed lower associated learning scores. Several other studies showed that preterm individuals have significantly lower mean IQ scores and lower academic achievement compared to full-term born individuals (Bhutta, 2002). This suggests that reaction time and learning abilities are related and that fast reaction time is a function of a healthier, and more developed brain. Another observation from this study is that faster reaction speed and learning and scholastic performance could be related somehow, and this association could be clarified in further research. 

Memory Consolidation

Computer games has been seen to elicit strong emotional experience and physiological responses with their thrilling and exciting nature characterized by the increased heart rate and respiratory rate found among video game players during and immediately after playing (Wang and Perry, 2006). These strong emotional experiences are theorized to facilitate memory consolidation and learning. Neuroscientific theories suggest that emotional experiences during the hours of learning strengthen consolidation of information in memory. Neurotransmitters in the brain that were believed to be involved in learning, behavior reinforcement and emotions such as dopamine and norepinephrine were seen to be released in significant quantities during game play (Koepp, 1998). The consolidation period right after playing video games when the player’s emotions are still strong; the level of these neurotransmitters is believed to facilitate learning among those who play video games (Stickgold, et al., 2001).

Stress reduction

A very common reported reason for engaging in video game play is that it is entertaining and relaxing (Wallenius, 2009). In fact, relaxation was the second most reported motivation of playing video games among 16 to 18 year old high school students. Voiskounsky, Mitina, and Avetisova (2009) also surveyed the same demographic population on their perceived effects of video games on people. They found that one of the widely believed influences of video games is that it promotes relaxation and gives pleasure to the player. Ferguson and Rueda (2010) found in their experiment that video game players can handle stress better than those who do not play. They gave a stress-inducing test to the participants and then randomly assigned them to groups that involved playing different kinds of video games and a group that did not get to play. All those who played video games, regardless of the kind of video game, showed significantly reduced hostility and depression levels. The researchers posited that video games have mood management properties that reduce stress and depression after a frustrating task. 

High levels of stress and anxiety has been seen to have a negative correlation with academic performance among college students (Fredericks and Mundy, (1969); Westerman, et al., (1986); Cecchini and Friedman, (1987). This suggests that the supposed stress-reducing property of video games might help students cope better with the stressors in their lives, and could possibly improve their academic performance. However, Walleius (2009) noted that even though playing video games can be relaxing, it still entails concentration and mental focus that might not be the optimal situation for a relaxed mind. He hypothesized that video games are lighter cognitive tasks compared to academic work and the stimulation the brain gets from playing is different due to its immersive nature that helps the brain to relax. 

Casual vs. hard core

There is no scientific distinction between the two categories of casual and hard core gamer. There is however, a growing consensus among players of what each category connotes, but the delineation between the two groups is usually vague. Ip and Jacobs (2005) investigated the customer segmentation of the video games market according to video game players. The factor analysis of the criteria for game segmentation showed three core components of gamers which can be used as criteria to identify them; these include gaming attitude and general knowledge, gamers’ playing habits and gamers’ buying habits. Further clustering identified two distinct categories of players– the hardcore and the casual gamers, that are distinguished based on their attitude, knowledge, habits on both playing and buying. 

Ip and Adams (2002), using previous literature and research, tried to clearly distinguish the difference between casual and hardcore gamers and came up with several factors that identified one group from the other. They highlighted fifteen variables to be considered in classifying a gamer into either category. They tried to create a scale that objectively measures the level of a particular gamer; the scale ranges from ultra casual to obsessive or ultra hardcore.

These criteria are arranged according to how important they are or their weight in identifying a gamer to be hardcore or casual. These criteria include (in order of weight) time spent playing, time spent discussing information about games, knowledge of the industry, tolerance of frustration, early adaptation of trends, desire to creatively extend games, technology savviness, ownership of latest and high-end computer and gaming systems, level of motivation to completing the game, level of competitiveness with self, game and other players, hunger for information about gaming,  willingness to spend money on gaming, preference of games that are deep and complex, onset age of playing, and lastly preference of a specific game genre (violent or action).

The total score of an individual on these scales considering the weight of each criterion would be an indicator of which category a gamer would fall under. The researchers have come up with five classifications of gamers, namely, the (1) ultracasual gamers which include non-gamers who obtained the lowest scores in this scale; (2) casual gamers who show a mild level of interest in gaming; (3) transitional or those who have a moderate or neutral score on the scale; (4) hardcore gamers with consistent scores on the factors in the scale; and lastly (5) the obsessive or the ultra hardcore, who obtained the highest possible scores on the scale. Ip and Adams (2002) further explained that the classification of gamers are not dichotomous but a continuum, suggesting that a gamer would not fall in either one or the other category but there are transitional and extreme categories to be considered. 

School performance

Given the criteria above in classifying a gamer, it is important to note several factors that might have an association with school performance. There is limited research that focuses on the type of gamer as an independent variable to assess which types of gamers are more prone to certain effects of playing video games. However, several researchers, mentioned earlier in this literature review, have tried to study the heaviest criterion that distinguishes a hardcore gamer from the rest, which is the amount of time spent playing video games (Cummings and Vanderwater, 2007; Weis and Cerankosky, 2010; Ip, Jacobs and Watkins, 2007). These studies confirmed that the amount of time spent playing video games is negatively associated with school performance. However, given these findings, a relation between school performance and hardcore gaming cannot be established because these studies are limited to only one criterion of hardcore gaming. 

Another specific criterion of hardcore gaming is the competitiveness against oneself, others and the game. There are several studies linking competitiveness with high levels of performance, however, most of these studies involve sport activities. On the other hand, a study by Frederick (2000) showed that the higher the competitiveness level of an individual, the lower his or her internal locus of control and GPA. This suggests a negative correlation between competitiveness and school performance. That may be translated to hardcore gamers given their competitive nature.

            Although it is more logical to assume that hardcore gamers would be more prone to the effects of video games, given the amount of exposure they experience with the medium, there are still other factors that can be considered with regard to academic performance and type of gamer. For instance, tolerance of frustration is one quality that is associated with hardcore gamers, suggesting that they do not get easily stressed or frustrated with a task, which is also a quality that is seen to be positively related to academic performance (Fredericks and Mundy, 1969; Westerman, et al., 1986; Cecchini and Friedman, 1987). Knowledge of the industry and technological savviness as qualities of a hardcore gamer might also be translated to a good academic performance on certain subjects like science and technology. In fact, although frequent gamers, who may or may not be hardcore gamers, were found to be less likely to score higher in biological sciences and language subjects compared to the less frequent gamers, there was no significant correlation found in other subjects like business and engineering (Ip, et al., 2008). 

These inferences from previous research, however, have not been established by actual research that tests the susceptibility of certain groups of gamers on the negative and positive effects of playing video games on academic performance, and a wide array of research is still needed to establish causation among these factors.

Pathological gamers

            A more serious classification of gamers that more experts are concerned about are the pathological gamers or the gamers that are believed to be dependent on or addicted to video games. This was proposed to be a psychological disorder but was rejected from being included in the DSM disorders, explaining that at the time more scientific studies were needed about the supposed disorder in order for the American Psychiatric Association to consider video game addiction as a psychological disorder on its own (ScienceDaily, 2007). However, studies show that this type of dependence on the internet and consequently on online games might be related to impulse control disorder (Aboujaoude, Koran, Gamel, Large, and Serpe, 2006). The researchers have nonetheless stressed that more research is needed to find out whether game addiction is indeed a clinical disorder or a manifestation of other disorders like depression, anxiety or obsessive-compulsive disorder.

Addictive Properties of Video games

            Studies on addictive video games have not been extensive, thus the addictive properties of video games have not been completely explored by the scientific community. However, the gaming industry continuously studies such properties as a guideline in developing games that would be more popular and addictive to their target demographic. Several inferences could be made based on existing literature about what makes a video game addictive. One possible property of video games that makes them addictive is the reward system. Most video games provide a list of high scores or have several levels that could be unlocked with a good game performance. Whatever these rewards are, a study has shown that people, especially males, react positively on a neurocognitive level. The study participants were 11 men and 11 women whose brain activity was measured using a functional magnetic imaging machine during game play (Reiss, 2008). As a result gamers want to play more and more as they progress through the game. Beating the highest score also feeds off the competitiveness of an individual, a characteristic associated with hardcore gamers (Ip & Adams, 2002). Olson (2010) postulated that competition and challenges in video games is in itself a rewarding experience to gamers, thus, playing against other people, or playing to beat oneself or just to complete the game, this motivation fuels the gamers to spend more time playing (Greenberg et al., 2008).

            Most video games offer role-playing and discovery as a way to attract and keep their customers playing. Olson, Kutner and Warner (2008) found among the top reasons why children play video games is to experience a fantastical world and role-play a character with fame and power. A variety of video games on the market offer this kind of experience to gamers. It can be deduced that playing these types of games are reinforcements enough for the gamers.

            Another possible addictive property of video games involves the social aspect of playing. Several games offer social interaction by allowing the players to compete or cooperate with other players from different locations through the internet (Przybylski, et al., 2010). Olson (2010) highlighted the social reasons why people are motivated to play video games, these include making friends, opportunities to lead and to teach and learn from one another. This apparent motivation among gamers is exacerbated by internet-based forums and communities as a place to discuss and chat with other individuals that are interested in a particular game and to build long term cohesion and relationships with each other (Przybylski, et al. 2010). It should be noted that one quality of hardcore gamers is that they want to discuss and gain information about the games and the industry, and these chat rooms and forums are possibly where hardcore gamers discuss their topic of interest.

            It is important to note that these qualities are just speculations according to previous studies on motivation of playing video games; they have not been studied in light of the possible video game addiction problem among gamers. Research that would closely analyze the common properties of the most popular and addictive video games is also needed to identify the qualities of video games that make them addictive.


            Previous research on pathological gaming used modified criteria for pathological gambling published by the American Psychiatric Association from the DSM (Griffiths & Hunts, 1998, Fisher, 1994). Looking at the DSM IV, 2000, replacing “gambling” with “gaming” on the applicable criteria would yield an accurate assessment of pathological gaming. This involves a repetitive and maladaptive gaming habits characterized by some of the following behaviors: preoccupation with gaming, several unsuccessful efforts to stop playing video games or at least reduce the amount of play time, irritability when trying to cut back on gaming, playing games as a way to escape from problems or to manage one’s mood, lying to people to hide the frequency of video game play, loss of a significant personal relationship, education or career as a result of gaming and financial problems due to gaming. 


            From a nationally representative sample of 1178 youths, Gentile (2010) found that 8.5% of the gaming population was assessed to be pathological gamers. In his review of previous research on different countries, a similar percentage of gamers were found to be addicted to gaming, ranging from 7.5% to 12% in China, Australia, Germany, and Taiwan, suggesting a fairly valid measure of pathological gaming, since all studies patterned their assessment scale with the DSM for pathological gambling. Other older studies showed different prevalence rates of pathological gamers, Fisher (1994) reported a 6% prevalence rate of pathological gamers in a sample of 460 gamers. Griffiths and Hunt (1998) came up with a proportion of one out of five gamers are dependent on computer games. This difference across different studies however could be attributed to many other factors like the assessment scale used, the rate of proliferation of video games, demographics of the sample, among others.

Negative effects

            As expected, a study showed that addicted adolescents have a higher playing frequency than others (Hauge & Gentile, 2003). Hostile attribution scores were significantly higher among video game addicts as was the occurrence of fights or arguments with friends and teachers. The same study reported that the adolescents that were classified as addicts had lower academic grades. Along with school performance, the addicted gamer’s level of depression and anxiety were observed to increase and social phobias were also associated with pathological gaming (Gentile, 2010). Gentile (2010) tried to explain through this longitudinal study of two years that as the subjects develop an addiction to video games, the tendency is for them to develop an unhealthy gaming habit causing them to develop mental problems and poorer relationships with their parents, and these problems motivate them even more to spend more time playing video games, causing a vicious cycle that worsens over time. However, he stressed that this inference was not proven in his research. The causations and comorbidity of pathological gaming and other symptoms or disorders have not been established and a longer longitudinal study was recommended by the researcher. He further explained that pathological gaming leads to higher exposure to violent games, making the addicted players more susceptible to the supposed aggression effect of violent video games. They tend to have higher levels of aggression, hostile attribution biases and aggressive imagination. They were also seen to engage more in physical aggression. It is of particular importance to note that once the students stopped playing video games pathologically; these negative effects were seen to decrease in level as well, indicating a strong relationship between pathological gaming and depression, anxiety, school performance and exposure to violent video games and aggression, consequently, further reinforcing the co morbidity or reciprocity of the factors studied.

Risk Factors

Gentile (2010) reported that some people with specific characteristics or habits are more susceptible to developing an addiction to video games. Increased risk factor was seen among those with high initial video game play frequency. The mean number of hours spent playing when adolescents became pathological gamers was 31 hours weekly. Another factor that might be a good predictor of development of addiction was impulsivity. Gentile (2010) reported that individuals who were initially impulsive exhibited initial symptoms of addiction which would, consequently predict increases in the levels of depression, anxiety and social phobias as mentioned above. Initial identification with video game characters also predicted pathological gaming development among the subjects. Lastly, low social competence and empathy were also considered as a risk factor for developing a video game addiction.

Gender Differences

            Several researchers have found significant gender differences on the effects, perception and practices involving playing video games. In general, the prevalence of video game players who are males is far greater than females. Initially, a survey by Entertainment Software Association in 2005 (cited by Khan, 2006) suggested that the average gamer is a male aged about 30 years old who spends 6.8 to7.6 hours per week playing video games. However this does not mean that females are no longer at risk of developing the supposed negative cognitive and behavioral effects of video games. It was found by Active Gamer Study (2005, cited by Khan, 2006) that adult males no longer constitute the majority of gamers; they found that the representation of 15-25 year old age group is increasing, and the female population of gamers was seen to increase as well but males still dominate the population of gamers.

            This is apparent in the sample obtained by Cummings and Vandewater (2007) that represents the population of 10 to 19 year old Americans involving 1491 subjects. Of this sample size, 36% were video game players, 80% of whom were males and only 20% were females, suggesting the very uneven distribution of video game players across the two genders, with significantly more males engaging in video games than females. They also reported the difference of reported amount of time spent playing video games with males reporting more video game play time than females during both weekdays and weekends. The researchers suggested that boys and girls differ with their social needs and therefore have differing motivations in playing video games.

            In relation to Cummings and Vandewater’s (2007) speculation on motives, Wallenius, Rimpelä, Punamäki and Lintonen (2009) also discovered a significant gender difference in motives of playing video games. Males reported to have more instrumentally-inclined motives in playing video games, that is, they play because they want to learn, experience, and develop certain skills involving video games. This difference suggests that males are more likely to seek stimulation in video games than females, making them spend more time playing video games as compared to females.

            In a focus group discussion of pre-adolescent boys conducted by Olson, Kutner and Warner (2008) to explore the reasons why boys play video games, these researchers found that males use games so they can experience power and fame in a fantastical setting, gain skills and mastery of something that they think is thrilling. Furthermore, it helps them to reduce stress, anxiety, and hostile feelings, and they also used games as a social tool. The respondents did not think that playing video games had affected them negatively but they thought that violent game behavior might cause some problems to younger children. Mössle, Kleimann, Rehbein and Pfeiffer (2010) postulated that children and adolescent males are more prone to the negative effects of video games and other electronic media given their gender-specific inclination to electronic devices. They added that a significant decrease in school performance was observed in school statistics among boys implying that there is general trend of decreasing academic achievement among males compared to females. 

            On the other hand, gender difference were also seen in one of the positive cognitive effects of playing video games that was discussed earlier which is the mental rotation as a function of spatial ability. De Lisi and Wolford (2007) found that boys initially scored higher than girls in the mental rotation test. However, after playing a video game that involves mental rotation skills, this difference was no longer observed. This suggests that the girls benefited more from playing the game as evidenced by their increased mental rotation score. Boys, however, did not gain as much benefit as the girls in this particular activity, implying that girls might be more susceptible to the cognitive improvement that playing video games entail.

            Similarly, Damarin and Mubirik (2003) found that females benefited more with the assumed positive effects of video game-oriented education in learning. Females were initially outperformed by males in various kinds of fourth grade mathematics games but after playing repeatedly, the scores of the girls were seen to increase significantly whereas the boys’ scores increased slightly. This is in line with the above speculation that females are more susceptible to the positive effects of video games than males. 

As might be expected, more males have reported to be frequent players (Ip, et al., 2008), suggesting that more males would possibly make up the hardcore gamer population. In contrast, the majority of casual gamers population is made up of females (Juul, 2009, cited by Begy & Consalvo, 2011). Females were also seen to be attracted more by the online multi-user games that provide a more social and public experience; however, casual gamers involving simple online puzzles and cell phone games are evenly represented by both genders, very few females have reported violent or action video games, typical of a hard core gamer (Vore, 2005 cited by Khan, 2006)

Reiss, Hoefta, Watsona, Keslera, and Bettingera (2007). offered a neurological explanation as to why males tend to get more “hooked” on video games, increasing their risk factors for developing pathological gaming behavior or making them more likely to become hardcore gamers than female. Males were found to be more motivated to play a game as they receive more rewards or reinforcement from the game that they play, that is extrinsic rewards for fulfilling the tasks that games require. This is evidenced by the increased activation of the mesocorticolimbic system of the male brain compared to the females as the subjects were examined using magnetic resonance imaging while they were playing a game that allows them to control the size of their territory in the computer screen. This area of increased activation among men is frequently associated with rewards and addiction. Another interesting finding in this study is that males were found to have a more activated reward circuit involving the connection between the nucleus accumbens, amygdala and orbitofrontal cortex. A strong connection with these three parts is an indicator of a good performance in the game. Thus, the better the males were in playing the game, the more rewards they experience making them more motivated to play. The researchers explained that success in the territoriality game is more rewarding for the male participants compared to the females. They further explained the difference not just in motivation but in reward prediction, reward values and cognitive functions. An implication of this research suggests also a hint of preferential difference among males and females with regard to the type game. Reiss (2007) explained that males are typically territorial in nature, thus, the rewards of the game might be more rewarding for them. On the other hand, it is possible that females may experience an increased sense of reinforcement if the extrinsic reward of the game is more female-oriented, but further research is needed to clarify this. The apparent increased motivation and reward system experienced by males in playing video games might offer an explanation for the higher prevalence of male pathological gamers and hardcore gamers; the better they play, the more rewards they get, and the more they want to play the game, hence, the cycle that may cause an addiction to a game might be worse for males.

This uneven gender demographic among casual and hardcore gamers and game preferences suggest that a certain gender might be more prone to engaging in video games more intensely than the other. It also suggests differences of taste in game genre and type. The preferential difference between the genders has implications on research on video games and their effects on individuals.

Relevance of the study

With the advent of technology, more and more students are spending their time playing video games rather than doing their homework or studying. Several studies have shown the negative effects of playing video games on several functions of an individual that may or may not have a detrimental effect on their school performance. This should be a cause of concern among students, parents and teachers considering that video games nowadays are considered a major pastime for a majority of students for several motivational reasons. With the increasing popularity of video games and innovations in technology more and more researchers are looking at the different aspects of video game play including its growing popularity and speed of proliferation. This phenomenon continues to puzzle the public as well as researchers in academe. Experts have pointed to changes in dynamics in the social and cultural environment where children can interact with their peers outside their home. Still it is the prevalence of computers and other forms of technology in a typical household that predisposes the children to accept computers and video games as a recreation that is worth doing. (Anderson and Bushman, 2001). In addition to this, it was postulated that early adoption of technological innovations, a characteristic of hardcore gamers, is related to the acceptance of new interactive services (Kangis and Rankin, 1996)

These findings suggest that many children, already exposed to technological advances at a very young age, tend to continue to seek innovations and further advancements in technology, making them more dependent on computers and technology in certain aspects of their lives, like their leisurely activities or hobbies. It can also be deduced that this early exposure to technology facilitates the hardcore gaming attitudes of children, as they continually seek developments in technology and video games starting at a very early age.

Video games are designed so they could attract a whole range of consumers; they cater to a wide range of video game tastes with the different selections of genres that the public could choose from. Games also give the players a choice of a character that they want; several video game developers tap the popularity of characters from other media, like television and movies to gain customer support. A study has shown that initial self identification with a video game character might be a good predictor of pathological gaming behavior in the future (Gentile, 2010). This suggests that the characters of a video game is one attraction of a video game, that somehow hooks the gamer to spend more time playing the game. The fantastical setting of video games also contributes to their growing popularity. As indicated in the literature above, a main motivation of video game players include experiencing a fantastical world different from reality (Olson, Kutner & Warner, 2008). Another possible reason of the prevalence of video games is its availability. With the development of technology, children’s access to video games gets easier. Video games can be played on cellular phones, computers, and gaming systems. Several establishments also offer gaming experience to children, adolescents and adults with limited access to personal gaming systems. According to past research, an early onset of video game play is one characteristic of hardcore gamers, and some studies also suggest that video games have addictive properties, suggesting that it only takes playing once or twice initially for a child to possibly develop an affinity to video games or possibly an addiction in the future. 

It is apparent in the current culture that some children would rather spend their time playing video games than doing other hobbies. It is also observable that games have become one of the favorite pastimes of children and adults alike. And it is only logical for the public to show concern about the impact of video games on children (Anderson and Bushman, 2001) given their age and that adolescents are more prone to external influences during these formative and impressionable years. However, the body of research presented here involves different age groups ranging from early childhood to late adulthood. This suggests that the wide spread use and effects of video games not only affects adolescents but different age groups as well. The early onset of video game playing and the prolonged exposure to video games are markers for hardcore gamers (Ip and Adams, 2002). Implications of past research suggest that hardcore gamers are more at risk in developing the strong negative and/or positive effects of video games.

            Playing games has been considered an important role in developing thoughts, identities, values and norms (Cole, 1996, cited by Arnseth, 2006). This suggests the importance of video game content in shaping the youths’ values, given that most children are spending their leisure time playing video games. One main concern of scientists and parents is the violence found on most video games and its effect on children’s aggressive behavior. Several studies have looked at the relation of playing video games and aggression among children and adolescents. Results of these earlier researches are often conflicting, either supporting the correlation of violent video game exposure and violent behavior or aggression (Dominick, 1984; Lin and Leper, 1987; Cooper and Mackie, 1986) or rejecting this particular hypothesis (Gibb, Bailey, Lambirth, and Wilson, 1983; Graybill, 1987)

            School performance is seen as one of the major areas affected by frequent exposure to video games. Academic performance clearly is one of the indicators of future success of an individual (Bartlett, 2009; Cummings, 2007; Gentile, Anderson, Yukawa, Ihori, Saleem, Lim, Shibuya, Liau, Khoo, Bushman, Huesmann, and Sakamoto, 2009). Academic performance could be measured in many ways including standardized exams and GPA in schools. These measures are quite important for high school students to get into a good college or get a good job in the future. Extensive research has shown that frequency of video game play and development of pathological gaming behavior has a negative relationship with school performance (Bartlett, 2009). This should be a cause of concern since several studies also suggest that associated negative and positive behavioral and cognitive effects of video games would likely persist for years. Looking at the demographic of gamers, frequent gamers are not only limited to adolescents and children but extend to adults as well, suggesting that the attractive and addictive properties of video games are not only targeting the youths but are diversifying to target the whole consumer market.

My research will attempt to fill the gap that exists in the current research by examining the effects of video games on children as they enter high school and see if there is any effect on their grades as they progress through high school. For example, do video games affect children’s grades that enter high school with limited video game playing time and increasingly become more addicted to playing?







Aboujaoude, E., Koran, L. M., Gamel, N. Large, M. D. & Serpe, R. T. (2006) . Potential Markers for Problematic Internet Use: A Telephone Survey of 2,513 Adults. CNS Spectrum:The International Journal of Neuropsychiatric Medicine. Retrieved from


American Psychiatric Association Considers ‘Video Game Addiction’. Science Daily. June 1, 2011.

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author.

Anand, V. (2007). A study of time management: The correlation between video game usage and academic performance markers. CyberPsychology & Behavior, 10(4), 552-559 

Anderson, C. & Bushman, B. (2001). Effects of violent video games on aggressive behaviour, aggressive cognition, aggressive affect, physiological arousal, and prosocial behaviour: A meta-analytic review of the scientific literature. Psychological Science, 12 (2): 353-359.

Anderson, D. R., Levin, S. R., and Lorch, E. P. (1997). The effects of TV program pacing on the behavior of preschool children.  AV Communication Review. 25(2), 159–166. 

Arnseth, C. (2006). Learning to Play or Playing to Learn – A Critical Account of the Models of Communication Informing Educational Research on Computer Gameplay. The International Journal of Computer Game Research. 6(1). Retrieved from

Artiga, M. (2010). Learning and selection processec. Theoria, 25(2), 197-209.

Ballard, M. E., Hamby, R. H., Panee, C. D., and Nivens, E. E. (2006). Repeated exposure to video game play results in decreased blood pressure responding. Media Psychology, 8(4), 323-341.

Barlett, C.P., Anderson, C.A., & Swing, E.L. (2009). Video game effects confirmed, suspected, and speculative: A review of the evidence. Simulation & Gaming, 40(3), pp. 377-403.


Begy, J. & Consalvo, M. (2011). Achievements, Motivations and Rewards in Faunasphere. The International Journal of Computer Game Research.11(1) Retrieved from

Bhutta, A, T., Cleves, M. A., Casey, P. H., Cradock, M. M. & Anand, K.J. (2002). Cognitive and behavioral outcomes of school-aged children who were born preterm: a meta-analysis. Journal of the American Medical Association. 288 (6):728– 737 Retrieved from


Bolling, M. Y., Terry, C. M. & Kohlenberg, R. J. (2006). Behavioral theories. Comprehensive Handbook of Personality and Psychopathology, Vol. 1, pp. 142-157.

Bong, M. (2004). Academic motivation in self-efficacy, task value, achievement goal orientations, and attributional beliefs. Journal of Educational Research, 97(6), 287-297.

Boot, W. R., Kramer, A. F., Simons, D. J., Fabiani, M. & Gratton, G. (2008) The effects of video game playing on attention, memory, and executive control. Acta Psychologica, 129, 387-398. 


Bracken, C. C., & Skalski, P. (2009). Telepresence and video games. PsychNology Journal, 7(1), 101-112.


Castillo, J., Wakefield, M., & LeMaster, J. (2010). Some observations from a very telling innocuous query: An essay on the state of higher education in America. American Journal of Business Education, Vol. 3, pp. 33-36.

Carden R., Bryant C., and Moss, R. (2004). Locus of control, test anxiety, academic procrastination, and achievement among college students. Psychological Reports. 95(2), 581-582.

Carskadon, M. A. (2011). Sleep’s effects on cognition and learning in adolescence. Prog Brain Res. 190: 37-43.

Cecchini, J. J. & Friedman, N. (1987). First-year dental students: relationship


 stress and performance. Interational Journal of Psychosomatic.34(3),17-19.

Cooper, J., & Mackie, D. (1986). Video games and aggression in children. Journal of Applied Social Psychology, 16, 726-744.

Dewald, J. F., Meijer, A. M., Oort, F. J., Kerkhof, G. A. & Bogels, S. M. (2010). The influence of sleep quality, sleep duration and sleepiness on school performance in children and adolescents: A meta-analytic review. Sleep Medical Review. 14(3), 179-89.

Chan, P. A., & Rabinowitz, T. (2006). A cross-sectional analysis of video games and attention deficit hyperactivity disorder symptoms in adolescents. Annals of General Psychiatry, 5(16), 5-16.


Charsky, D. & Mims, C. (2008). Integrating commercial off-the-shelf video games into school curriculums. Tech Trends: Linking Research and Practice to Improve Learning, 38-44.


Chuang, T. & Chen, W. (2009). Effect of computer-based video games on children: An experimental study. Journal of Educational Technology & Society, Vol. 12, pp. 1-10.

Cummings, H., Vandewater, E. (2007). Relation of adolescent video game play to time ppent in other activities. Archive of Pediatric Adolescent Medicine. 161(7):684-689. 

De Lisi, R., &Wolford, J. L. (2002). Improving children’s mental rotation accuracy with computer game playing. Journal of Genetic Psychology, 163, 272-282.


Dominick, J. R. (1984). Videogames, television, violence and aggression in teenagers. Journal of Communications, 34, 134-147.


Dunst, C. J., Raab, M., Hawks, O., Wilson, L. L. & Parkey, C. (2007). Relative efficiency of response-contingent and response-independent stimulation on child learning and concomitant behavior. Behavior Analyst Today, 8, 226-236.

Dworak, M., Schierl, T., Bruns, T. & Klaus, S. H. (2007). Impact of singular excessive computer game and television exposure on sleep patterns and memory performance of school-aged children. Pediatrics. 120(5), 978 -985.

Ferguson, C. J. (2010). Introduction to the special issue on video games. Review of General Psychology, Vol 14, 66-67.

Ferguson, C. J. & Rueda, S. M. (2010). The Hitman study: Violent video game exposure effects on aggressive behavior, hostile feelings, and depression. European Psychologist, 15(2), 99-108.

Ferguson, C. J., Rueda, S. M., Cruz, A. M., Feruguson, D. E., Fritz, S. & Smith, S. M. (2008). Violent video games and aggression:  Causal relationship or byproduct of family violence and intrinsic violence motivation? Criminal Justice and Behavior. 35(3), 311-332.

Fisher S. (1994). Identifying video game addiction in children and adolescents. Addict Behavior. 19(5), 545–553.

Frederick, C. M. (2000). Competitiveness: Relations with GPA, locus of control, sex, and         athletic status.  Perceptual and Motor Skills, 90, 413-414. 

Fredericks, M. A. & Mundy, P. (1969). Relations between social class, stress-anxiety responses, academic achievement, and professional attitudes of dental students. Journal of Dental Education.33(3),377-84.

Gibb, G. D., Bailey, J. R., Lambirth, T. T. & Wilson, W. P. (1983). Personality differences between high and low electronic video game users. Journal of Psychology, 114, 159-165.


Graybill, D., Strawniak, M., Hunter, T. & O’Leary, M. (1987). Effects of playing versus observing violent versus nonviolent video games on children’s aggression. Psychology: A Journal of Human Behavior, 24, 1-8.


Griffiths, M. (2005). A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use, 10(4), 191-197.


Hauge, M. R. & Douglas A. G. (2003). Video game addiction among adolescents: Associations with academic performance and aggression. Paper presented at a Society for Research in Child Development Conference, Tampa, Florida.

Geckova, A., Tavel, P., van Dijk, J., Abel, T., Reijneveld, S. (2010). Factors associated with educational aspirations among adolescents: cues to counteract socioeconomic differences? Public Health. 10, 154.

Gentile, D. A., Anderson, C. A., Yukawa, S., Ihori, N., Saleem, M., Lim, K. M., Shibuya, A., Liau, A. K., Khoo, A., Bushman, B. J., Huesmann, L. R. & Sakamoto, A. (2009). The effects of prosocial video games on prosocial behaviors: International evidence from correlational, longitudinal, and experimental studies. Personality & Social Psychology Bulletin. 35(6), 752-763.

Gentile, D., Choo, H., Liau, A., Sim, T., Li, D. Fung, D. & Khoo, A. (2011). Pathological video game use among youths: A two-year longitudinal study. Pediatrics. Retrieved from

Gentile, D. (2009). Pathological video-game use among youth ages 8 to 18: A national study. Psychological Science, Vol 20, pp. 785.

Gettler, J. (nd) The first video game? Before ‘Pong’ there was ‘Tennis for two’ Retrieved from the Brookhaven National Laboratory

Goldstein, J., Cajko, L., Oosterbroek, M., Michielsen, M., van Houten, O., & Salverda, F. (1997). Video games and elderly. Social Behavior and Personality, 25, 345-352.

Gottfried, E., Fleming, J.S. & Gottfried, A.W. (2001). Continuity of Academic Intrinsic Motivation From Childhood Through Late Adolescence: A Longitudinal Study. Journal of Educational Psychology. 93, 3–13.

Green, C. S., & Bavelier, D. (2003). Action video game modified visual selective attention. Nature, 423, 534-537.

Green, C. S., & Bavelier, D. (2006). Enumeration versus multiple object tracking: The case of action video game players. Cognition, 101, 217-245.

Greenberg, B. S., Sherry, J., Lachlan, K., Lucas, K., & Holmstrom, A. (2008). Orientations to video games among gender and age groups.

Simulation & Gaming. Advance online publication.

Greenfield, P. M., Brannon, C., & Lohr, D. (1994). Two-dimensional representation of movement through three-dimensional space: The role of video game expertise. Journal of Applied Developmental Psychology, 15, 87-103.

 Griffiths, M. D. & Hunt, N. (1998). Dependence on computer games by adolescents. Psychological  Report. 82(2):475–480.

Hamlen, K. R. (2011). Children’s choices and strategies in video games. Computers in Human Behavior, 27(1), 532-539.

Hart, G. M., Johnson, B., Stamm, B., Angers, N., Robinson, A., Lally, T., & Fagleye, W. H. (2009). Effects of video games on adolescents and adults. CyberPsychology & Behavior, 12(1), 63-65. 

Hoeft, F., Watson, C. L., Kesler, S. R., Bettinger. K. E. & Reiss, A. L. (2008). Gender differences in the mesocorticolimbic system during computer game-play. Journal of Psychiatric Research. 42(4), 253-258.

Ip, B. & Adams, E. (2002). From casual to core: A statistical mechanism for studying gamer dedication. Gamasutra. Retrieved from

Johnson, J. G., Cohen, P., Kasen, S. & Brook, J. S. (2007). Extensive television viewing and the development of attention and learning difficulties during adolescence. Archive of Pediatric Adolescent Medicine.161(5), 480–486.


Kangis, P. & Rankin, K. (1996). Interactive services: how to identify and target the new markets. Journal of Marketing Practice: Applied Marketing Science, 2 (3): 44 – 67.


Kappes, B. M. & Thompson, D. L. (1985). Biofeedback vs. video games. Effects on impulsivity, locus of control and self-concept with incarcerated juveniles. Journal of Clinical Psychology, Vol. 4, 698-706.


Khan, M. K. (2006). Report of the council on science and public health. 

King, D., Delfabbro, P. & Griffiths, M. (2010). The role of structural characteristics in problem video game playing: A review. Cyberpsychology, Vol. 4, 1-8.

Kline, S. (2000). Killing time? A Canadian meditation on video game culture. In: von Feilitzen, C. Carlsson, U., eds. Children in the New Media Landscape: Games, Pornography, and Perceptions. Kungalv, Sweden: UNESCO International Clearinghouse on Children and Violence on the Screen at Nordicom; 2000:35-59.

Koepp, M. J., Gunn, R. N. & Lawrence, A. D. Evidence for striatal dopamine release during a video game. Nature.1998;393 :266– 268.

Lamarine, R. (1995). Child and adolescent depression. Journal of School Health, 65, 390-394.

Landhuis, C. E., Poulton, R., Welch, D. & Hancox, R. J. (2007). Does childhood television viewing lead to attention problems in adolescence? Results from a prospective longitudinal study. Pediatrics.120(3), 532–537.

Lawrence, A. J., Luty, J., Boodan, N. A., Sahakian, B. J. & Clark, L. (2009). Problem gamblers share deficits in impulsive decision-making with alcohol-dependent individuals. Addiction, Vol. 104, 1006-1015.

Leung, L. (2004). Net-generation attributes and seductive properties of the internet as predictions of online activities and internet addiction. CyberPsychology & Behavior, 73(3), 333-348.

Lin, S. & Lepper, M. R. (1987). Correlates of children’s usage of video games and computers. Journal of Applied Social Psychology, 17, 72-93.

Linnenbrink, E. A., & Pintrich, P. (2002). Motivation as an enabler for academic success. School Psychology Review, 31(3), 313.

Mathews, V. P., Kronenberger, W. G., Wang,Y., Lurito, J. T., Lowe, M. J., & Dunn, D. W. (2005). Media violence exposure and frontal lobe activation measured by functional magnetic resonance imaging in aggressive and nonaggressive adolescents. Journal of Computer Assisted Tomography, 29, 287-292.

Miller, R. K. & Washington, K. (2011). Video Games. Media & Advertising Market Research Handbook, 11, 307-311.

Monke, L. (2009). Video Games. A Critical Analysis. Encounter, 22(3), 7-20.

Moore, J. W. (2002). A neuroscientist’s guide to classical conditioning. New York: Springer.

Mossle, T., Kleimann, M., Rehbein, F. & Pfeiffer, C. (2010). Media use and school achievement–boys at risk? British Journal of Developmental Psyhcology. 28(3), 699-725.

Moyer, V. S. (2008). The role of user motivations in moderating the relation between video game playinh and children’s adjustment. Ph.D. dissertation, Bowling Green State University, United States – Ohio. Retrieved from Dissertations & Theses: Full Text. (Publication No. AAT 3318261).

Mulder H., Pitchford, N. J. & Marlow, N. (2011). Inattentive behaviour is associated with poor working memory and slow processing speed in very pre-term children in middle childhood. British Journal of Education Psychology. 18(1), 147-160. 

Olson, C. K. (2010). Children’s Motivations for Video game play in the

context of normal development. Review of General Psychology. 14(2), 180–187.

Olson, C. K., Kutner, L. A. & Warner, D. E. (2008). The role of violent video game content in adolescent development: Boys’ perspectives. Journal of Adolescent Research. 23(1), 55-75.

Orosy-Fildes, C. & Allan, R.W. (1989). Psychology of computer use: XII.Videogame play: Human reaction time to visual stimuli. Perceptual and Motor Skills, 69, 243-247.

Passig, D. & Eden, S. (2001).Virtual reality as a tool for improving spatial rotation among deaf and hard of-hearing children. CyberPsychology and Behavior, 4, 681-686.

Przybylski, A., Rigby, S. & Ryan, R. (2010). Motivational model of video game engagement. Review of General Psychology. 14(2), 154–166. 

Stipek, D. (1988). Motivation to learn: From theory to practice. Englewood Cliffs, NJ: Prentice Hall. 

Rabin LA, Fogel J, Nutter-Upham KE. (2011). Academic procrastination in college students: the role of self-reported executive function. Journal of Clinical Experimental Neuropsychology. 33(3), 344-57.

Rast, P. (2011). Verbal knowledge, working memory, and processing speed as predictors of verbal learning in older adults. Developmental Psychology.

Ryan, R. M. & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68-78.

Ryan A. M. (2001). The peer group as a context for the development of young adolescent motivation and achievement. Child Development. 72:1135-1150.

Sharif, I. &Sargent, J. (2006). Association Between Television, Movie, and Video Game Exposure and School Performance. Pediatrics. 118(4), 1061-1070.

Stickgold, R., Hobson, J. A., Fosse, R. & Fosse, M. (2001). Sleep, learning, and dreams: off-line memory reprocessing. Science. 294, 1052– 1057.

Strang-Karlsson, S. (2010). Slower Reaction Times and Impaired Learning in Young Adults With Birth Weight <1500 g. Pediatrics. 125 (1) e74 -e82.

Swing, E., Gentile D., Anderson C. & Walsh D. (2010). Television and Video Game Exposure and the Development of Attention Problems. Pediatrics. 126(2), 214 -221.

Thakkar, N. (2009). Why Procrastinate: An Investigation of the Root Causes behind Procrastination. Lethbridge Undergraduate Research Journal. 4(2).

Tobin, S. & Grondin, S. (2009). Video games and the perception of very long durations by adolescents. Journal Computers in Human Behavior. 25(2).

Van Rooij, A. J., Meerkerk, G., Schoenmakers, T. M., Griffiths, M. & van de Mheen, D. (2010). Video game addiction and social responsibility. Addiction Research & Theory, 18(5), 489-493.

Voiskounsky, A., Mitina, O. & Avetisova, A. (2009). Gamers’ implicit knowledge on the psychological influence of game-playing. Proceeding: OCSC ’09 Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009.

Wai, J., Lubinski, D. & Benbow, C. P. (2009). Spatial ability for STEM domains: Aligning over 50 years of cumulative psychological knowledge solidifies its importance. Journal of Educational Psychology. 101(4), 817-835.

Wallenius, M., Rimpela, A., Punamaki, R. L., & Lintonen, T. (2009). Digital game playing among adolescents: Relationship to parent-child communication, school performance, sleeping habits, and perceived health. Journal of Applied Developmental Psychology, 30, 463-474.

Wang, X. & Perry, A. (2006). Metabolic and Physiologic Responses to Video Game Play in 7- to 10-Year-Old Boys. Archive of Pediatric Adolescent Medicine.160, 411-415.

Weis, R. & Cerankosky, B. C. (2010). Effects of video-game ownership on young boys’ academic and behavioral functioning: a randomized, controlled study. Psychological Science. 21(4), 463-70.

Weinstein, A. M. (2010). Computer and video game addiction-a comparison between game users and non-game users. American Journal of Drug and Alcohol Abuse. 36(5), 268-276.

Weiten, W. (2008). Psychology: Themes and Variations. Belmont, CA: Thomson.

Westerman, G. H., Grandy, T. G., Lupo, J. V. & Mitchell, R. E. (1986). Relationship of stress and performance among first-year dental students. Journal of Dental Education 50(5),264-267.

Williams, D., Yee, N. & Caplan, S. E. (2008). Who plays, how much, and why? Debunking the stereotypical gamer profile. Journal of Computer-Mediated Communication. 13, 993–1018.

Wood, R. T. A., Gupta, R., Derenvensky, J. L. & Griffiths, M. (2004). Video game playing in adolescents: Common risk factors. Journal of Child & Adolescent Substance Abuse, Vol. 14, 77-100.

Yuji, H. (1996). Computer games and information-processing skills. Perceptual and Motor Skills, 83, 643-647.

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