Game Studies

Grades on Games: Gaming Preferences and Weekly Studying on College GPAs

Abstract

While some researchers have argued that videogames negatively impact academic achievement, others have argued that videogames have no effect, or even improve academic achievement. In this study, 272 college undergraduates were surveyed to explore how videogame preferences can explain the relationships between time spent videogaming, time spent studying, and college grade point averages. First, the effects between weekly gaming, weekly studying and college GPA are explored. Time spent studying on the weekend was a significant predictor of academic performance. Furthermore, gamers spent significantly more time studying on the weekend than non-gamers. There was also a small but significant negative correlation between preferences for action videogames and academic performance. Relationships between videogame preferences, alternative activities, and game motivations are also explored. Results indicate that motivations for arousal positively correlated with preferences for action and logic games, and negatively correlated with preferences for leisure games. This was true for motivations for fantasy, diversion and social interactions as well. Preferences for logic games also positively correlated with time spent creating, cooking and coding and understanding technology weekly.

Keywords: academic achievement, genres, memory, motivation, videogame preferences

Introduction

Early studies are quick to blame videogames as harmful for academic performance. For example, Harris and Williams (1985) found that time spent playing videogames negatively correlated with students’ English grades (native English-speakers). And, time spent studying did not correlate significantly with students’ grades, suggesting that the negative relationship between time spent gaming and grades achieved is not simply a result of displacement. In another early study, self-reported time spent playing arcade games yielded a small but significant negative correlation with mathematic competence (Lin & Lepper, 1987). Since then, many other researchers have found similar trends. Anderson and Dill (2000) concluded that time spent playing violent videogames negatively impacts academic performance. Anand (2007) identified a negative correlation between time gaming and academic performance in a college-aged population, and Gentile et al. (2011) found a negative relationship between pathological gaming habits and academic performance.

Interestingly, other researchers have drawn different conclusions. In a large 4508-student sample, Sharif and Sargent (2006) reported no relationship between videogaming and school grades. Furthermore, positive relationships between gaming and certain types of information processing, including spatial abilities, visual attention (see Barlett, Anderson & Swing, 2008) and declarative memory (Prena et al., 2018) have been reported in literature. Skoric, Teo and Neo (2009) found a positive relationship between the time spent playing videogames weekly and the students’ grades in English class in Singapore. And, contrary to Lin and Lepper (1987), these researchers did not find a significant relationship between time spent gaming and grades in mathematics and sciences. They do report a negative relationship between score on participants’ videogame addiction assessments and academic performances for all subjects; English, mathematics and science. This assessment was based on feelings of desire to play videogames and not on actual time spent gaming.

In more recent research, Drummond et al. (2014) used a large, 192000-person sample to look for videogame effects on academic performance. They explained that lack of significant relationships between gaming and achievement could, in part, be due to personal decisions to focus more on school or spend less time gaming when grades are slipping. This conclusion was reconfirmed in a larger, follow-up 219000-person study (Drummond & Sauer, 2020), though they also suggested a small negative affect of gaming on academic performance for students who game in the morning during the week. Hartanto, Toh and Wang (2018) also demonstrated differential effects between weekday and weekend gaming in response to Drummond et al. (2014). Weekday gaming had negative effects on academic performance, while weekend gaming had positive effects on academic performance in adolescents. Furthermore, Posso (2016) established a quadratic relationship between playing Internet games and math, reading, and science achievement. Those who played games almost every day reported better grades than those who played once a week and those who play every single day.

Researchers have also found that learning games, or games intended to teach particular lessons or skills, can help students master specific academic topics. When games served the particular purpose of teaching children about computer science, students who played educational games had better memory for the lessons than those same lessons taught by a teacher (Papastergiou, 2009). Students assigned to game lessons were also more motivated to continue learning about the subject than students assigned to the teacher’s lessons. Similar results have been produced for other subjects with learning games targeting those areas, including math, reading, spelling (Rosas et al., 2003), grammar (Yolageldili, & Arikan, 2011), and teaching prosocial skills to children with Down syndrome (Whalen, Liden, Ingersoll, Dallaire & Liden, 2006).

Enhanced Memory Formation

We have some reason to believe that videogame play could have positive effects on academic performance. Particularly, some videogames activate the hippocampus, an area of the brain that is responsible for declarative memory, or the storage of facts, events, and semantic information (see Squire, Knowlton, & Musen, 1993). As hippocampal activation increases, so does declarative memory performance (Adcock, Thangavel, Whitfield-Gabrieli, Knutson, & Gabreieli, 2006). Furthermore, the effects of hippocampal dopamine on memory formation can last longer than achievement of the rewards players anticipate (memory’s penumbra hypothesis; Lisman, Grace & Duzel, 2011). Memory remains facilitated until activation returns to baseline. For instance, rats can experience heightened memory for up to 30 minutes after the presentation of a reward that stimulates the hippocampus (Bethus, Tse, & Morris, 2010). This suggests that after achieving rewards in videogames, memory formation in humans is facilitated during tasks that follow (see Miendlarzewska, Bavelier, & Schwartz, 2016). Heightened hippocampal activation has been associated with spatial learning (Pine et al., 2002), vocabulary acquisition (Mårtensson et al., 2012), verbal learning (Petersen et al., 2000), reward-related learning (Adcock et al., 2006) and associations (DeMaster & Ghetti, 2013), though an extension to actual academic performance is unclear.

Communication research has studied this phenomenon before, through the excitation transfer theory (see Bryant & Miron, 2003; Zillmann, 1971; Zillmann & Bryant, 1974). The excitation transfer theory suggests that arousal stimulated during media exposure can have lasting effects on events after exposure. These lasting effects can influence how the individual perceives, processes and responds to information acquired after media consumption has ended. Complimenting memory’s penumbra hypothesis, it is possible that hippocampal arousal caused by videogame play can lead to better memory of information that the individual is exposed to after gameplay. Wang and Lang (2012) used the excitation transfer theory to demonstrate that arousal and valence of a television show can influence memory of commercials that proceeded the television show. Similarly, Prena et al. (2018) found that those exposed to videogames with obvious rewards performed significantly better on a declarative memory task immediately after gaming than those exposed to videogames with no rewards. Further, weekly gaming was a positive predictor of declarative memory performance. In the current study, we were interested in further exploring the relationship between weekly gaming and declarative memory. We thought that it may be the case that while time spent gaming does not directly affect grades, gaming facilitates information retention; making studying more effective. We therefore asked the following research questions to better understand the relationship between gaming, studying and GPAs in our sample:

RQ1: Is time spent videogaming weekly a significant predictor of college GPA?

RQ2: Is time spent studying a significant predictor of college GPA?

RQ3: Can gaming status be used to predict college GPA?

Videogame Genre

Videogame effects may vary by what kinds of videogames people are playing. Videogame mechanics, or rules setting up how players will interact with the game (Boyan & Sherry, 2011), can vary greatly. For instance, action games may require players to track and respond to fast moving objects on the screen, while strategy games may have lengthened or unlimited response time. Research has indicated that these demands could lead to different effects on information processing. Kühn and Gallinat (2014) demonstrated that preferences for different videogame genres can explain variations in hippocampal formation volumes. The amount of time spent playing platform and puzzle games positively correlated with hippocampal formation (entorhinal cortex) volumes. Time spent playing different kinds of role-playing games had mixed effects. The researchers cautioned that differences in volume could be a result of game selection, or differences in game selection could be a result of volume. Ellis (2019) demonstrated that lifetime experience with games that require players to repeat a portion of a level after a failure (i.e., Super Mario Bros.) positively correlated with declarative memory performance. Lifetime experience with games that require object tracking, invincibility, spatial navigation and casual gaming did not correlate with declarative memory performance. Additionally, participants reported feeling as though they had better memory and cognitive skill after playing casual games in a survey about casual gaming preferences (Whitbourne, Ellenberg, & Akimoto, 2013). And Russoniello et al. (2009) reported that playing easily accessible short-term puzzle games with simple interfaces can reduce stress and anxiety, induce relaxation and improve mood. The following research questions were considered to explore the effects of videogame preferences and other interests on college GPA:

RQ4: Can videogame preferences predict college GPA?

RQ5: Can preferences for alternative activities predict college GPA?

How players anticipate and experience reward within videogames may vary according to the motivations for selecting which types of games they play. Lucas and Sherry (2004), and Sherry et al. (2006) identified six motivations for videogame play: arousal, challenge, competition, diversion, fantasy, and social interaction. Players driven by arousal desire changes in emotional state. Those driven by challenge desire to achieve a higher skill or pass an obstacle. Those motivated by competition hope to achieve a higher position of skill or timing compared to others. Diversion is the drive to distract oneself from stress or fulfill boredom. Fantasy drives players to experience something that they could not experience in the real world. And, social interaction is the drive to play games to connect with friends. The final research question was designed to explore the effects of motivations on genre preferences.

RQ6: How do gamer motivations correlate with videogame preferences?

The aim of this study was to look for potential evidence for the excitation transfer theory in the relationships between studying, videogaming, and academic performance. To do so, an online survey was made available to undergraduates. There were seven different categories of questions, including: gaming attitude, videogame genre preferences, time spent playing videogames, time spent studying, time spent performing alternative activities, academic performance and demographics. The questions included multiple choice, drop-down, and open-ended answers.

Method

Participants

Participants were recruited from three classes offered by a media studies department at a Midwestern university to participate in a survey. They received extra credit for participating. The survey itself was created and distributed using a version of Qualtrics Survey Software Online that was supplied by the university. In total, information was collected from 279 students. However, four responses that demonstrated misunderstanding of the items, one outlier (GPA), and two incomplete responses were removed, which resulted in 272 participants. The sample included 103 (37.9%) males and 169 females (62.1%) with a mean age of 19.39 (SD = 1.36) and had been playing videogames for 8.99 years (SD = 3.30). Most of the participants were in their first (59.2%) or second years of college (26.1%). Data was collected in the middle of the semester to avoid bias caused by low studying during school breaks or high studying during final exams.

Survey Variables

Videogame Genre Preferences

To identify the genres asked about in this survey, a list of 60 game genres was pulled from Wikipedia.com. This list was chosen because of how extensive it was. It provided full descriptions and examples for each of the genres. The public, not a gaming franchise, created the list and can contribute if there are any missing genres or if the information is incorrect. The game genres were condensed based on similarities in the cognitive tasks that gamers have to perform. A complete list of the genres used can be found in Table 1. The participants were shown the definition and not the name of the genre so that they consider the task, not the genre label. The survey asked participants to respond, on a five-point Likert scale, to “How often do you play [definition of game and example].” The order that these genres were presented in was randomized.

Table 1. Videogame Genre Definitions

Time Spent Videogaming

To measure time spent gaming, participants were told to think of an average week over the current academic semester and to think of games on all platforms (online, computers, phones, tablets and consoles). Each day was separated into three equal parts, and subjects filled in how much time they spend gaming in each segment for each day of the week (to the closest half an hour). The weekdays, M = 15.10, SD = 8.96, were separate from the weekends, M = 5.07, SD = 4.05. This is a modified version of The Videogame Questionnaire (Anderson & Dill, 2000). The answers were summed for a total time spent videogaming weekly, M = 20.17, SD = 11.38.

Time Spent Studying

This variable was measured with the same daily schedule that was used to determine time spent videogaming. Participants were asked to think about the amount of time they spend studying in the average week of school. They entered time for each day of the week (to the nearest half an hour on weekdays, M = 6.21, SD = 7.89, and on the weekend, M = 3.56, SD = 4.34, and the answers were summed together for a total amount of time they spend studying each week, M = 9.77, SD = 11.53.

College Grade Point Average

In a drop-down menu ranging from 1.0 to 4.0, which increased by intervals of 0.1, participants were asked to insert their current college grade-point averages (GPA), M = 3.16, SD = 0.49.

Videogame Motivations

A 20-item questionnaire, called the Analysis of Videogame Uses and Gratifications Instrument (Sherry et al., 2006, p. 219), was used to measure individuals’ motivations for videogame play. For each statement, participants selected from five responses ranging from “strongly disagree” to “strongly agree” that corresponded with scores (1 through 5). Arousal, challenge, competition, diversion, fantasy and social interaction were calculated using the average of two to four different items for each motivation.

Alternative Activities

Participants were asked to estimate how many hours (to the nearest half hour) they spend working, M = 3.35, SD = 7.31, exercising, M = 4.96, SD = 5.62, watching television, M = 6.22, SD = 6.44, coding or understanding technology, M = 1.34, SD = 7.85, studying religion or philosophy, M =1.12, SD =3.13, cooking, M = 1.10, SD = 2.03, traveling to and from work, M = 4.85, SD = 5.36, creating, M = 2.61, SD = 14.84 and reading each week, M = 2.57, SD = 4.71.

Demographics

Participants were asked their age, age they started playing videogames, gender and year in school. They were also asked for college majors and minors.

Results

The 272 participants included in the sample reported an average of 9.77 hours gaming each week (SD = 11.53), and an average of 20.17 hours studying each week (SD = 11.38). Their average college GPA was 3.16 (SD = 0.49). The females in the sample reported having a higher average GPA (M = 3.23, SD = 0.49) than the males in the sample (M = 3.05, SD = 0.48).

RQ1 & RQ2

The first two research questions asked if time spent gaming weekly and time spent studying weekly are significant predictors of GPA, respectively. To answer these questions, we conducted a linear regression model, using gender, weekday studying, weekend studying, weekday gaming and weekend gaming to predict college GPA. The results of this regression are included in Table 2. The model significantly explained a small portion of the variance in GPA, R²=.08, F(5,266) = 4.46, p < .001. Both gender, b = .15, p = .021, and weekend studying, b = .20, p = .004, were significant predictors of GPA.

Table 2. Entire Sample Regression Between Gender, Studying, Gaming, and GPA

Dependent Variable: College GPA

RQ3

The third research question asked if the relationship between the amount of time spent studying weekly and GPA varies between gamers and non-gamers. Results suggest a significant difference in weekend studying between the two groups. Further analysis indicates significant positive correlations between weekday studying, weekend studying and total studying for gamers but not for non-gamers. Weekly gaming (weekday, weekend and total) also positively correlated with weekend studying. To conduct this analysis, non-gamers were identified as those who reported spending absolutely no time playing videogames each week (n = 80, males = 9). Gamers were identified as those who reported spending at least half an hour playing videogames each week (n = 192, males = 94). Although weekday studying was not a significant predictor of GPA, we included in this analysis to see if it differed between gamers and non-gamers. For this reason, we also included total weekly studying. Two-tailed independent sample t-tests demonstrated no significant differences in between the groups in weekday studying, total weekly studying or college GPA (see Table 3). But gamers spent significantly more time studying on the weekend than non-gamers, t(270) = -2.77, p = .006, Cohen’s d = .37. Levene’s test for equality of variances was not significant in any of the cases, so equal variances were assumed.

Table 3. Weekly Studying and College GPA Between Non-Gamers and Gamers

Degrees of freedom (df) = 270.

A Pearson’s product-moment correlation coefficients matrix was used to analyze this research question further. This allowed us to look at differences in correlations between gamers and non-gamers. Results of the complete matrix are demonstrated in Table 4. Weekday studying, weekend studying and total weekly studying were not significant predictors of college GPA for non-gamers. However, weekday studying, r = .19, n = 192, p = .010, weekend studying, r = .30, n = 192, p < .001, and total studying, r = .26, n = 192, p < .001, positively correlated with college GPA for gamers.

Table 4. Correlations Between Studying, Gaming, and GPA for Non-Gamers and Gamers

** Correlation is significant at the 0.01 level (2-tailed).

* Correlation is significant at the 0.05 level (2-tailed).

RQ4 & RQ5

The fourth research question asked if preferences for each of the videogame types impact the effectiveness of studying on GPA. Results indicate that preference for action videogames correlate negatively with college GPA. The fifth research question asked if weekly time spent engaging in alternative activities could predict college GPA. Results demonstrate that only total weekend studying could predict college GPA. To analyze this question, we ran a principal component analysis (PCA) with varimax rotation to sort genre preferences into general types. For the analysis, genre preferences reported from all participants was used. The results of the PCA are displayed in Table 5.

Table 5. Results for PCA of Videogame Genre Preferences

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 8 iterations.

The PCA identified a three-component solution that explained 60.32% of the variance in genre preferences. Adventure, role-playing and strategy games all loaded onto a single component that we labeled, “logic games.” Fighter, shooter and sports games also loaded onto a single component that we labeled “action games.” Finally, casual, exercise, music, simulation and trivia games all loaded on a component that we labeled “leisure games.” Platform games loaded equally on logic and action game components, racing games loaded equally on action and leisure game components, and puzzle games loaded equally on logic and leisure games.

A Pearson’s product-moment correlation coefficients matrix (see Table 6) demonstrates a small but significant negative correlation between preference for action videogames and college GPA, r = -.13, p < .001. While none of the alternative activities were able to predict college GPA, preference for logic games positively correlated with time spent coding or understanding technology, r = .22, p < .001, time spent cooking, r = .15, p = .011, and time spent creating, r = .20, p < .001. It negatively correlated with time spent watching television, r = -.12, p = .042. Preference for action videogames negatively correlated with time spent traveling to and from work and school, r = -.15, p = .015. Interestingly, weekend studying positively correlated with time spent traveling to and from work or school, r = .15, p = .016, and time spent reading, r = .32, p < .001. And total weekly videogaming positively correlated with time spent cooking.

Table 6. Bivariate Correlations for Alternative Activities, College GPA and Game Preferences

** Correlation is significant at the 0.01 level (2-tailed).

* Correlation is significant at the 0.05 level (2-tailed).

RQ6

The sixth and final research question asked how videogame motivations correlate with preferences for different videogame types. This question was analyzed using two-tailed bivariate correlations which were calculated using Pearson’s correlation coefficients. Results are displayed in Table 6. For this analysis, only gamers from the sample were used, because they are the ones who reported playing games every week.

Table 7. Pearson’s Correlations for Uses and Gratifications and Gamer Residuals

** Correlation is significant at the 0.01 level (2-tailed).

* Correlation is significant at the 0.05 level (2-tailed).

While individuals’ residuals on the logic games component correlated strongest with motivations of fantasy, r(190) = .51, p < .001, residuals on the action games component correlated strongest with motivations of social interaction, r(191)= .45, p < .001, and competition, r(192) = .44, p < .001. Residuals for the leisure games component only correlated negatively with videogame motivations, of which social interaction had the strongest correlation, r(191) = -.31, p < 0.001.

Discussion

The goal of our paper was to consider potential evidence for the excitation transfer theory on hippocampal excitation through relationships between videogame play, studying and academic achievement. In doing so, we also hoped to explain some sort of the inconsistencies found in previous studies of gameplay and academic achievement. Although early studies suggest that hours of weekly gaming could negatively affect college GPA, the data in this study did not support that conclusion. Rather, only weekend studying could significantly predict college GPA. This complicates the literature suggesting that weekday morning gaming can negatively impact academic performance (Drummond & Sauer, 2020; Hartanto et al., 2018). However, one potential explanation for this difference could be in ages studied, as adolescents typically have a more regimented weekday schedule compared to college students. Drummond and Sauer (2020) identify other explanations for the relationship between weekday morning gaming and academic performance in children, including differences in parenting styles, and behavioral and mental health concerns. While the operationalization for weekly studying was identical for gamers and non-gamers, we also cannot rule out individual or group differences in this self-report measure as a possible cause for this relationship.

Interestingly, gamers reported significantly more time studying on the weekend than non-gamers. And, when gamers and non-gamers were analyzed separately, time spent studying was not a significant predictor of college GPA for non-gamers, but it was for gamers. It is possible to interpret this as videogaming could lead to more effective studying which results in a positive relationship between weekend studying and college GPA. Perhaps, there’s a difference in personality for those who prefer studying on the weekend that leads to better grades and videogaming. Furthermore, this conclusion could be the result of a self-report error, as research has suggested that people struggle to estimate just how much time they spend on various tasks (Hartley et al., 1977; for alternative measures see Richardson et al, 2012). Much more research needs to be conducted in order to rule out a myriad of other possible explanations and establish causality between gaming and studying effectivity. Because of the many possible explanations, the authors caution that readers should not take away from this article that they need to be gaming in order to perform well in school.

The study demonstrated that action gaming had a small negative effect on college GPA. There is some research that suggests that action gaming could have a positive effect on hippocampal processing (see Miendlarzewska et al., 2016), but academic success does not just depend on hippocampal processing. Future research should be conducted on how different videogame mechanics can influence learning and academic related skills. Preferences for logic games and leisure games could not significantly predict college GPA. However, this does not rule out possible effects of playing these types of games on information processing.

There were significant correlations across game type preferences and hours spent engaged in alternative activities. None of the alternative activities significantly correlated with college GPA. But time spent creating, time spent cooking and time spent coding or understanding technology positively correlated with logic game preferences. Logic game preferences also negatively predicted time spent watching television. Preference for leisure games was unrelated to any of the alternative activities included in this survey, while there was a negative correlation between action gaming and time spent driving to and from work or school weekly. There are various explanations for these associations. For instance, it is possible that those with an interest in coding and technology may find logic games more appealing. It is also possible that the logic games they are playing can be modified by coding. Perhaps, it requires more time practicing in order to be competitive in action gaming than the time people with longer drives to work have. While these are speculative explanations at best, it is interesting to consider the relationships across different activities and gaming preferences.

We were also interested in exploring how game type preferences might correlate with the videogame motivations for an indication of how reward might be perceived differently across players (Sherry et al., 2006). Our results suggest that motivations can predict preference for the different types of videogames. Fantasy motivations (experiencing something that the player cannot experience first-hand) were the strongest predictor of preference for logic games. Preference for action games correlated strongest with competition (desire to achieve higher status based on skill or timing than peers) and social interaction (using gaming to better connect with peers). Preference for leisure games correlated negatively with social interaction motivations. An interesting future study could see if videogame motivations could account for hippocampal activation during gaming, suggesting that perhaps gamers perceive in-game rewards differently.

There are many aspects of life that influence college GPA. The goal of this paper was to explore the potential for effects of the excitation transfer theory between videogaming, studying and academic performance. Unfortunately, the results of this study are inconclusive and do not contribute to a better understanding of how the excitation transfer theory could influence learning immediately after gameplay. However, this study does demonstrate some interesting effects between gaming preferences and college GPA, alternative activities and videogame motivations.

Further research is necessary to examine potential effects between videogame demands and learning. It is our hope that this study provides some insight into differences in academic achievement amongst gamers and non-gamers. And, we hope to encourage future researchers that it is still important to consider how gaming might relate to academic achievement. The relationship is clearly complex. Because videogames have the potential to improve memory for material processed immediately after gaming (Prena et al., 2018), more research needs to be conducted in order to understand how to potentially harness those effects for more long-term learning goals.

Acknowledgments

We would like to thank the reviewers at the journal who helped refine and improve this article.

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