General Problem-Solving Styles and Problem-Solving Approaches in Video Games

Abstract

Video game play is a pervasive recreational activity, particularly among college students. While there is a large research base focused on educational video game play and uses of games in the classroom, there is much less research focused on cognitive strategies and entertainment video game play. The purpose of this study was to investigate potential relationships between general problem-solving styles and problem-solving approaches in video games. One hundred and thirty-eight undergraduate college students completed online surveys about their video game play and also an assessment of general problem-solving style. A multivariate linear regression revealed relationships between general problem-solving styles and problem-solving preferences in video games, with a few differences when looking at specific genres of games. This study provides evidence that approaches to video game play can be a reflection of real-life problem-solving styles.

Keywords

problem-solving games multivariate analysis cognitive survey research college students VIEW assessment

While research surrounding the potential negative effects of entertainment video game play tends to be more well known and reported in the media, there is also a broad research base focused on both positive aspects of video game play and also potential relationships between video game play and other facets of learning and development. Gee (2003) was among the first to reframe entertainment video games research to put less emphasis on effects—particularly negative effects—and to move toward a discourse about the way an individual learns in video games and what we might acquire from games in terms of understanding the learning process. While both educational video games and entertainment video games have been more extensively studied in the context of the classroom, there is less research investigating the role of recreational entertainment video game play in terms of an individual’s cognition, learning, and problem-solving choices.

Over the past decade, researchers have examined a wide range of variables relating to recreational entertainment video game play, including relationships between entertainment video game play and cognitive skills (Blumberg, Altschuler, Almonte, & Mileaf, 2013; Suziedelyte, 2015); effects of video game play on ability to perform virtual tasks (Murias, Kwok, Castillejo, Liu, & Iaria, 2016); active games and energy expenditure (Graf, Pratt, Hester, & Short, 2009); learning about culture and rules through video games (Jenny & Schart, 2014); and the potential positive cognitive, emotional, and social benefits of video game play (Granic, Lobel, & Engels, 2014). This study focused on an issue related to video game play and cognition but not represented in much of the literature in this area: relationships between problem-solving styles and video game play.

There are competing views among literature on video game play: One contending that video game “worlds” remain separate and disconnected from everything else in a player’s real life, and the opposing view that video game play can be a reflection of real-life attitudes and personality traits and that there can be transfer between video games and other areas of life (Stevens, Satwicz, & McCarthy, 2008). The second view is the basis for the hypothesis in this study—that students’ general problem-solving styles will correlate with their problem-solving styles in video games and that knowing about a person’s video game play can tell us a great deal about that person and how they approach problems and obstacles in everyday life. Beyond theory and conjecture, there is some related evidence from previous research that supports this position. For example, Chory and Goodboy (2011) concluded that personality traits may be more highly correlated with video game play than with that of other media. Additionally, university students with more prior video game experience demonstrated faster ability to solve problem in a new virtual environment (Sturz, Bodily, & Katz, 2009). There has been much speculation about the role of video game play in student cognition and problem-solving. Researchers have explored relationships between students’ gaming experiences and their real-life experiences, interests, and activities and have called for further research to analyze the experiences and activities of youth that are intertwined with their gaming experiences (Stevens et al., 2008) as is contributed by this study through the study of connections between problem-solving approaches in the two contexts.

Related Literature

Problem-Solving

Decision-making and problem-solving are not synonymous but are highly related. The decision-making process involves the identification and resolution of problems. Simon (1957) is credited for the theory of “bounded rationality,” which considers the decision-making process in light of the available information and the environment and culture of the decider. This theory assumes that an individual will make the most rational decision possible, given their preconceived inclinations, beliefs, and their sources of information and will find a solution that is satisfactory as it corresponds with their own reality. This theory has been applied to current studies of problem-solving and decision-making (Gavetti, Levinthal, & Ocasio, 2007).

While there are many ways to approach the study of problem-solving in individuals, this research is approached from the bounded rationality framework and focuses on varying preferences and approaches used to think about the problem and to gather information about the problem, which, at times, also correlate with personality traits. For example, one way to classify individual preferences in problem-solving is according to level of external versus internal processing (Miller & Miller, 2005). Classification of an individual’s decision-making style as social positively corresponds with a personality test measure of extroversion (Holland, 1996). Those who are more extroverted are more likely to approach decisions- and problem-solving through social means. Another way to classify preference related to problem-solving is the level of organization, structure, and order involved in the problem-solving process (Burke & Aytes, 2002; Bormann, 1975; Liu & McLeod, 2014). This refers to an individual’s inclination toward, and preference for, highly defined and structured problem-solving, whether alone or in discussions with others. This research examines problem-solving styles through the lens of approaches to information gathering and preferences for types of information as it relates to video game play and general contexts.

Video Game Play and Problem-Solving

Previous research has shown that approaches to video game play can be a reflection of, or possibly practice for, real-life behaviors (Hamlen, 2012), and there do seem to be relationships between video game play approaches and player personality. For example, those who display more physical aggression in their personalities apart from video game play tend to engage in a more aggressive style of video game play (Peng, Liu, & Mou, 2008) and those with particular personality traits such as lower agreeableness are more likely to choose games that contain more violence (Chory & Goodboy, 2011).

The literature specifically exploring relationships between problem-solving skills and recreational entertainment video game play is quite scarce, but we do have several studies exploring related constructs that can inform our understanding of how people approach video games and how this relates to their personalities or approaches to tasks and problems outside of video games. Blumberg and Sokol (2004) found that both age and video game play experience played a role in the types of strategies children used when learning a new video game, with a focus on internal versus external strategies. When looking specifically at strategy games, this type of game play is correlated with self-regulation, even when controlling for some personality traits and preferences (Gabbiadini & Greitemeyer, 2017). In other words, either individuals who already excel at self-regulation are more likely to play strategy games for longer periods of time or the use of strategy in video games tends to help the individual to practice self-regulation, which can then be used in other contexts. Experimental research has supported the concept of video game play causing changes in cognition. Researchers found that extensive training on a platform entertainment game resulted in gray matter changes in the brain when compared to a control group (Kühn, Gleich, Lorenz, Lindenberger, & Gallinat, 2014). These were areas of the brain that are also involved with strategic planning, which may also relate to problem-solving.

A few studies in the past decade have focused on problem-solving and entertainment video game play. Hancock (2010) explored the relationship between social problem-solving skills and time spent playing video games. She did not find relationships between these two variables but was looking solely at time spent playing video games, not at problem-solving within game play. Adachi and Willoughby (2013) used self-reported levels of strategic video game play and five items self-reporting problem-solving skills among adolescents to investigate relationships between strategic video game play and use of problem-solving skills. They found that, among high school students, strategic video game play positively predicted self-reported problem-solving skills. Two strengths of the study were a large sample size (n = 1,492) and reports over at least two time points. One potential limitation is that the measure evaluating problem-solving skills was brief and relied on a yes/no self-report for each item. While Adachi and Willoughby (2013) focused only on genres and games that qualified as strategic game play and explored relationships between levels of strategies used in each, this study expanded the scope to include all genres of games and investigated relationships between the types of strategies generally used in video games and in other contexts. Finally, in an experimental study, Glass, Maddox, and Love (2013) found that a real-time strategy game that focused on certain cognitive tasks such as task switching led to participants having more cognitive flexibility in nonvideo game tasks than those participants who played a different version of the game that did not emphasize these cognitive tasks.

The Current Study

Purpose and Research Questions

The purpose of this study was to investigate potential relationships between general problem-solving styles and problem-solving preferences in video games. It is hypothesized that that the obstacles encountered in video game play feel similar enough to “real-world” problems to the player that individuals will tend to utilize the same sorts of strategies that they would use in other contexts. It is hypothesized that general problem-solving methods are a category of behavior that may be reflected (or possibly practiced) in video game play. This study addressed the research questions:

Are there relationships between general problem-solving styles and problem-solving styles in video games?

Do relationships between general problem-solving styles and problem-solving styles in video games differ depending on the type of game played?

Definitions

Problem-solving styles

Problem-solving preferences are ways people choose to go about developing solutions to problems or overcoming obstacles. The term style refers to a preference that is generally stable or consistent within an individual. In this research, problem-solving styles refer to approaches that individuals generally use or prefer when addressing a problem or obstacle (Carver, Scheier, & Weintraub, 1989; Lazarus, 1993), including the extent to which they confer with others, explore many possibilities versus thinking through the pros and cons of fewer options, their preference for or against structure and intervention from authority figures, and the focus of their decision-making.

Video games

For purposes of this research, the term video games is synonymous with digital games. Video games are considered to be any sort of interactive electronic or digital game, including games of all genres and on all platforms (e.g., cell phones, tablets, games consoles). The survey used in this study was conducted just prior to the release of the more accessible virtual reality systems, so, while virtual reality was not necessarily excluded from the definition of video games, it was not mentioned on the survey and was unlikely to be used by survey takers at the time of administration.

Method

Participants

This study utilized online surveys to collect data from undergraduate U.S. college students. Participants were recruited from four colleges and universities via e-mail and posters. A gift card was offered to one randomly chosen participant from each college or university. Public, private, urban, suburban, and rural institutions were represented. There were 138 participants with complete data included in this study. The survey was given to college students ages 18 to 25, and the mean age of participants was 20.5. The mean year in college of participants was between sophomore and junior year.

Instruments

Two instruments were administered online to participants: (a) the VIEW assessment of general problem solving style (Selby, Treffinger, & Isaksen, 2002) and (b) a survey about video game play habits.

VIEW assessment of general problem-solving style

The VIEW assessment of problem-solving style was chosen to measure general problem-solving styles for this study for several reasons. First, the theory behind the assessment is that individuals differ in their preferred means of approaching and solving problems, and these preferences remain relatively stable over time, such that they can be considered a general style of approaching problems (Selby & Treffinger, 2008). This is consistent with the bounded rationality framework and is also compatible with problem-solving in video game play. Secondly, the instrument assesses three major categories of problem-solving preferences that can also parallel video game play problem-solving preferences: Orientation to change, manner of processing, and ways of deciding. Problems in video game play, like problems in everyday life, require dealing with change and obtaining new information, finding ways to process new information, and using methods to come to a decision about what to do. While this is not a complete and definitive measure of an individual’s many preferences for ways to solve problems, the categories it does assess are most appropriate for this study and for a comparison to video game problem-solving styles. As for practical test-taking concerns, the measure is long enough to provide reliable information but not so long that survey takers lose interest; it can also be administered and scored online.

The VIEW assessment includes three decision-making process scales: Orientation to Change, Manner of Processing, and Ways of Deciding. For each scale, the extremes are labeled, and an individual can fall anywhere on a continuum between the two extremes. The Orientation to Change Scale indicates level of preference for exploration versus structured development. A lower score on this scale represents preference for exploration, to seek out new possibilities, and to do this independently from authority. A higher score on this scale represents preference for organization, structure, and greater intervention from authority. The Manner of Processing Scale indicates level of preference for level of interaction with others when making decisions and taking action. A lower score on this scale represents more external processors, who prefer interacting with others and taking action quickly. A higher score on this scale represents more internal processors, who prefer reflection and thought before action. Finally, the Ways of Deciding Scale distinguishes between a “person-oriented” individual (lower score), who generally focuses on the impact of decisions on people and the “task-oriented” individual (higher score), who more often reacts to quality of ideas and decisions, independent of others’ feelings. Some evidence for the validity of the VIEW assessment has been provided by Burger, Marino, Ponterotto, and Houtz (2008) and Costello and Houtz (2004).

Survey

Participants completed an online survey about their video game play habits and preferences. They answered questions about how many hours they played video games in a typical week, what genre(s) of games they played. They also answered questions about how likely they were to use various strategies when learning to play a new video game and when stuck in a video game, and what their gaming preferences were in terms of interaction with others and structure in video games. The preference items were each presented on a 5-point Likert-type scale. Attention checks were included at various points throughout the survey, where the participant was guided to answer the question in a particular way; if they did not do so, the survey ended prematurely and the survey was not included in the final data.

Variables

The three scores from the VIEW assessment subscales: Orientation to Change, Manner of Processing, and Ways of Deciding were the primary three independent variables. These measured three different aspects of general problem-solving styles or preferences. Gender and number of hours in an average week spent playing video games were also included as independent variables because of existing literature showing that there may be differences in the way people play video games based on these two variables.

Two variables were calculated from the video games survey to summarize: (a) video game structure preference and (b) video game processing preference. These variables were created to measure similar preferences to the variables calculated in the VIEW assessment but in the context of video game play. Video game structure preference refers to the level of preference for structure and rules in video game play. Video game processing preference refers to the level of preference for interaction with others while solving problems during video game play and level of action versus thought when encountering a problem. The survey items used to calculate these two variables were chosen from a combination of methods. First, the survey items were matched to the VIEW subscale definitions and were categorized based on the problem-solving aspects they most closely seemed to represent. Then exploratory factor analysis was used to identify the items from each set that most closely related to one another to represent the two variables—structure preference and processing preference. Cronbach’s α reliability was calculated for each set of items used in the new variables. For the new video game structure preference variable, Cronbach’s α was .603, and for the new video game processing preference variable, Cronbach’s α was .613. These were slightly below the generally accepted α of .7, but considering that these variables were created for exploratory use in this study and to match definitions from a separate subscale, .6 was considered to be the acceptable cutoff point (Loewenthal, 2004).

Video game structure preference was a score created from the sum of the survey items measuring: general preference for structure in video games, preference for limits and rules in video games, whether or not the individual would choose to venture out and explore unknown territories if stuck in a video game, whether or not the individual uses the in-game tutorial as a general strategy for approaching video games, whether or not the person uses the game manual as a general strategy for approaching video game play, and whether or not the individual would turn to the manual for help when stuck in a game. For this video game structure preference variable, low structure preference is preference for freedom from rules, and high structure preference is preference for more structure and rules in game play.

The second calculated variable was video game processing preference. This was a sum of the survey items measuring: preference for playing video games alone or with others, whether or not the individual would ask for help if stuck in a video game, whether or not the individual would employ problem-solving methods when stuck in a video game, whether or not the person would choose to observe others when stuck in a video game, and whether or not the individual would choose to take action first, without following the guided game methods, as a general strategy in video games. Low video game processing preference is preference for interacting with others and taking action first and high video game processing preference is preference for reflecting alone and thinking through options before acting. Brief descriptions of the variables are given in Table 1.

Table 1.

Descriptions of Variables.

Variable	Description
Gender	Choices were male, female, transgender, do not wish to answer; self-reported on survey
Hours	Hours spent playing video games weekly; self-reported on survey
Orientation to change score	Indicates level of preference for structure and intervention from authority, where higher scores indicate more preference for structure/organization/intervention from authority, measured by VIEW assessment, Orientation to Change subscale
Manner of processing score	Indicates level of internal versus external preference for processing information, where higher scores indicate more preference for internal processing (reflection and thought before action); measured by VIEW assessment, Manner of Processing subscale
Ways of deciding score	Indicates level of person versus task orientation, where higher scores indicate more task-oriented individuals (tend to make decisions based on objective criteria rather than by the impact on people and their feelings); measured by VIEW assessment, Ways of Deciding subscale
Video game structure preference	Indicates level of preference for structure and rules in video games, where higher scores indicate more preference for structure/organization in video games; calculated from related questions on video game survey
Video game processing preference	Indicates level of internal versus external preference for processing and learning in video games, where higher scores indicate more preference for internal or solo processing/learning; calculated from related questions on video game survey

Analysis

A multivariate linear regression model was used to investigate potential relationships between approach to video game play and general problem-solving approaches. Specifically, the independent variables were gender, hours spent playing video games weekly, orientation to change, manner of processing, and ways of deciding scores. The dependent variables were video game structure preference and processing preference.

Results

Descriptive Statistics

A total of 138 undergraduate college students completed both the survey and the VIEW assessment, with 55.8% identifying themselves as female, 42.8% as male, and 1.4% as transgender. The majority of the sample (83.3%) identified themselves as Caucasian, 4.3% African American or Black, 5.8% Hispanic or Latino, 9.4% Asian or Pacific Islander, 4.3% Middle Eastern, 1.4% Native American or Alaskan, and 0.7% Other (note that individuals were instructed to choose as many as apply). There were many genres of video games provided, and survey takers could choose as many as they wanted, indicating that they play the genre on a regular basis. Table 2 indicates the genres played, examples of each genre, and the number and percentage of participants who chose that genre.

Table 2.

Genres Played.

Response	Examples	n	Percentage
Puzzle	Candy Crush, Tetris	79	57.2
Action, including Survival Horror	Tomb Raider	62	44.9
Shooter/First Person Shooter	Halo, Gears of War, Call of Duty	61	44.2
Racing	Need for Speed, Mario Kart	58	42.0
Role-playing	Final Fantasy, Elder Scrolls	57	41.3
Platform	New Super Mario Brothers	54	39.1
Casual/party	Wii Party	45	32.6
Dance/rhythm	Rock Band, Just Dance	43	31.2
Physically active	Kinect Sports	41	29.7
Simulation	Sims	34	24.6
Sports	Madden NFL	32	23.2
Strategy	Civilization World, Sid Meier’s Pirates	31	22.5
Fighting	Street Fighter, Mortal Kombat	30	21.7
Massively multiplayer online games	World of Warcraft	25	18.1

Participants’ video game play ranged from 0 to 105 hours per week, with a median of 6 hours per week, a mean of 11.5 hours per week, and a standard deviation of 14.8. While 105 hours sounds nearly impossible, this participant was not excluded because there are many games that can run continually on one’s phone and the player checks in to play or configure the game every few minutes or at various points throughout the day. Additionally, all analyses were rerun without this participant included to ensure that the outlier did not influence overall results. Normality of each of the variables was examined using the Shapiro–Wilk test of normality. One variable, video game processing preference did not meet the assumption of normality, as it was slightly skewed left. Log transformation was used to calculate a new variable, which did meet the assumption of normality.

Participants’ mean orientation to change score was 80.6 (SD = 15.2), manner of processing was 35.1 (SD = 9.7), and ways of deciding was 34.4 (SD = 9.1). These means were each very close to the midpoints of their respective scales. On the Orientation to Change Scale, the midpoint is 72 (possible scores are 18–126), with a higher mean falling on the developer side of the scale. The midpoint of the Manner of Processing Scale is 32 (possible scores are 8–56), so the mean of the sample fell slightly to the internal processor side, and the midpoint of the Ways of Deciding Scale is also 32 (possible scores are 8–56), so the mean of the sample fell slightly to the task-oriented side of the scale. Using the descriptive statistics provided in the VIEW technical manual (Selby, Treffinger, Isaksen, & Lauer, 2004), z tests for the population mean revealed that this sample did not significantly differ from the general population on any of these scales (p > .05).

Regression results

A multivariate linear regression with independent variables gender, hours spent playing video games weekly, orientation to change, manner of processing, and ways deciding scores, and dependent variables video game structure preference and processing preference revealed significant multivariate results for all three problem-solving variables, orientation to change: Pillai’s trace = .115, F(2, 126) = 8.201, p = .000; processing preference: Pillai’s trace = .157, F(2, 126) = 11.737, p = .000; ways of deciding: Pillai’s trace = .081, F(2, 126) =5.587, p = .005. There were not significant multivariate results for gender or hours spent playing video games. R² for the complete model was .231.

Univariate results (Table 3) showed that there was a significant positive relationship between orientation to change scores and video game structure preference, F(1, 127) = 16.475, p = .000. There was a significant positive relationship between manner of processing scores and video game processing preference, F(1, 127) = 23.136, p = .000, and between ways of deciding scores and video game processing preference, F(1, 127) = 8.816, p = .004. There were not significant relationships between gender or hours spent playing video games weekly and either structure preference or processing preference.

Table 3.

Univariate Effects.

Independent variable	Dependent variable	df	df error	F	Mean square	p
Gender	VG structure preference	1	127	1.856	24.454	.176
Gender	VG processing preference	1	127	1.332	0.004	.251
Hours	VG structure preference	1	127	0.137	1.806	.712
Hours	VG processing preference	1	127	0.621	0.002	.432
Orientation to Change	VG structure preference	1	127	16.475	217.069	.000
Orientation to Change	VG processing preference	1	127	0.039	0.000	.845
Manner of processing	VG structure preference	1	127	0.453	0.453	.502
Manner of processing	VG processing preference	1	127	23.136	23.136	.000
Ways of deciding	VG structure preference	1	127	2.349	2.349	.128
Ways of deciding	VG processing preference	1	127	8.816	8.816	.004

Note. VG = video game.

Relationships by Game Genre

Each of the genres that were played by at least 40% of the sample was analyzed with the same variables in a multivariate linear regression to determine whether the relationships were the same or different depending on genre of game. Results of these analyses showed some differing relationships, but the one relationship that remained significant for each genre was the positive relationship between manner of processing scores and video game processing preference scores. In other words, for all types of games examined, people who tend to be more internal processors of information when approaching problems in their daily lives are also more likely to approach problems in video games by reflecting alone before taking action. Conversely, those who tend to be external processors of information when approaching problems in their daily lives are more likely to approach problems in video games through discussion with others and quick action.

For those who play Action games, the relationship between manner of processing and video game processing preference remained significant, F(1, 55) = 12.475, p = .001. For those who play Puzzle games, there was a significant positive relationship between manner of processing scores and video game processing preference, F(1, 55) = 12.475, p = .001. For those who play Role Play games, there was a relationship between manner of processing and video game processing preference, F(1, 51) = 10.457, p = .002, and also a relationship between ways of deciding and video game processing preference, F(1, 51) = 10.457, p = .049. For those who play Shooter/First Person Shooter games, there was a negative relationship between ways of deciding scores and video game structure preference, F(1, 54) = 8.355, p = .006, and a positive relationship between manner of processing and video game processing preference, F(1, 54) = 10.228, p = .002. For those who play Racing games, there was a negative relationship between ways of deciding and video game structure preference, F(1, 50) = 8.532, p = .005, and a positive relationship between manner of processing and video game processing preference, F(1, 50) = 4.581, p = .037. These relationships are all summarized in Table 4. The blank cells represent no significant relationships found between these pairs of variables.

Table 4.

Summary of Significant Results for Various Subsets of Data.

Independent Variable	Video game structure preference	Video game processing preference
Gender	—	—
Hours	—	—
Orientation to change	All participants (positive)
Manner of processing	—	All participants (positive)
		Action games (positive)
		Puzzle games (positive)
		Role-play games (positive)
		Shooter games (positive)
		Racing games (positive)
Ways of deciding	Shooter games (negative)	All participants (positive)
Ways of deciding	Racing games (negative)	Role-play games (positive)

The negative relationship between ways of deciding scores and video game structure preference indicated that being more task oriented than people oriented was related to preference for less structure in video games, only for those who played Shooter and Racing games. Those who play Shooter and Racing game genres did not have significantly different ways of deciding scores than those who played other genres.

Conclusions

Higher orientation to change scores are associated with greater video game structure preference. This means that, in general, those who prefer organization and structure in problem-solving are more likely to have greater preference for structure in video games as well. Research on problem-solving suggests that a match between level of structure preference and the level of structure provided in a task results in greater effectiveness and speed of task completion (Liu & McLeod, 2014). Finding either a video game where the provided level of structure (e.g., in-game tutorials and guidance) matches the players’ preferences or a player intentionally seeking the guidance and structure to their preference level when problem-solving in a video game likely results in a more positive problem-solving experience or may even result in better game play with faster problem-solving processes throughout.

Higher manner of processing scores are related to higher video game processing preference. In other words, being an internal processor or preference for individual thought before action in general problem-solving and decision-making tasks is associated with preference for reflection and solitary thinking before action when playing video games. As in the case with structure preference, there is also research and theory supporting the match between preference for social versus individual problem-solving approaches and level of social interaction available in the decision-making space (Miller & Miller, 2005), where a match between preference and conditions is more likely to result in a smooth and successful decision-making experience. In this way, the individual playing the game is generally approaching the problem-solving experience in a way that creates a match between their preferences and their reality.

Higher ways of deciding scores are also related to higher video game processing preference. Those who tend to be more task oriented are more likely to prefer reflection and solitary thinking before action when playing video games. It seems logical that those who focus their decision-making more on tasks than on the impact on people would also be more likely to prefer individual problem-solving to social problem-solving, but prior literature was not found to confirm this association; it is possible that it is unique to video game play.

Finally, higher ways of deciding scores are related to lower video game structure preference scores for those who play Shooter and Racing games. Among people who play these two genres, those who tend to be more task oriented are likely to prefer less structure in video games and those who are more people oriented are likely to prefer more structure. While no previous research has considered links between these two game genres and problem-solving preferences of the players, there has been research specific to these two genres. Playing racing games has been shown to increase risk taking in real-life driving contexts (Fisher et al., 2009). While research on shooter games has traditionally focused on levels of violence and aggression, there has also been research demonstrating neural changes resulting from time playing shooter games (Wu et al., 2012). Interestingly, the players who had the greatest improvements in an attentional visual field task experienced the most noticeable neural changes. One of the particular challenges in video games research is dealing with the different genres of games. There are categories, or genres, of games as defined by the market, but these do not necessarily identify the differences in games relating to cognition (Apperley, 2006), and players respond cognitively to different types of games in differing ways (e.g., Green & Bavelier, 2006). Thus, drawing conclusions from this set of information is difficult, but there do seem to be some differences among these two genres, and it would be beneficial for future research to address these relationships in greater depth.

Gender and number of hours spent playing video games weekly are not significantly related to structure preference or processing preference in video game play when all participants are considered nor when common specific genres are considered. While there are some notions that there are gender differences in preferences for structure when problem-solving, the finding of this study is consistent with other research about children’s game play preferences, in which there were not significant gender differences among children in their structure preferences in game play (Kinzie & Joseph, 2008).

Discussion

These correlations between an individual’s approaches to solving problems in video games and their approaches to making decisions in other contexts may be expected for those who are familiar with video games, but to date, no other research had actually confirmed these relationships. Furthermore, the results if this study, in combination with other related research, offer the possibility that video game play can give us a glimpse into a person’s style, preferences, and personality and that video games offer a chance to practice approaches to problem-solving. While adults could gain personal insight by monitoring their own problem-solving methods in games, parents and educators watching a child solve problems in video games may then be able to anticipate how the child will tend to approach other problems or decision-making tasks.

The idea of video game approaches as a reflection of approaches to other tasks aligns with previous research. For example, those who tend to use cheat codes as a means to avoid doing the work to get through difficult portions of a video game are also more likely to use cheating methods to avoid work in academics (Hamlen, 2012). Conversely, those who use problem-solving methods to think through various possibilities or who practice parts over and over to master them are more likely to use problem-solving or practicing techniques in academic challenges as well. Video games seem to be a way to practice preferred strategies.

Finally, while experimental research would be needed to verify such conclusions, these findings provide the basis for a hypothesis that video game play has the potential to be a way for people to try out different problem-solving approaches than they are typically inclined to use, thereby giving them practice for uses of these strategies other contexts. For example, an individual who normally explores and takes quick action when problem-solving could use the context of video games to try a more reflective problem-solving method. This would be a less risky situation for trying new methods than real-life situations might be.

There are several limitations to this research, including the limits drawn by the instruments used, self-report data, and the correlational nature of the research. Measuring problem-solving in general and in video games is limited by the instruments used, and in this case, the definition of problem-solving is guided by the assessment given. Secondly, self-report data always have limitations, as participants may either remember inaccurately or may intentionally report incorrect information. The online video games survey contained a check to ensure that participants were at least reading each question to eliminate those who would just check random boxes to complete the survey. Finally, since this is correlational research, hypotheses can be made about cause and effect but cannot be confirmed. Experimental research would be needed to test causation, but such research is difficult to conduct with regard to recreational entertainment game play, which usually takes place at home or on mobile devices on the go.

Overall, findings of several similarities between problem-solving approaches in video games and in general contexts provide evidence that video game scenarios can feel enough like real life to allow the player to approach the game as they would approach general life situations. It is also possible that practicing particular problem-solving approaches in video games increases the same preferences for other contexts. The fact that individuals tend to react similarly in video games to the way they would react outside of video games also gives support for the current and potential uses of video games for training and practice.

Footnotes

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Faculty Scholarship Initiative of Cleveland State University.

Author Biography

Karla R. Hamlen is an associate professor in the College of Education and Human Services at Cleveland State University. She teaches graduate courses in Educational Research and Statistics and pursues a research agenda focused on relationships between entertainment video game and other aspects of cognition.

References

Adachi, P. J. C., & Willoughby, T. (2013). More than just fun and games: The longitudinal relationships between strategic video games, self-reported problem solving skills, and academic grades. Journal of Youth Adolescence, 42, 1041–1052.

Apperley

(2006) Genre and game studies: Toward critical approach to video game genres. Simulation & Gaming 37(1): 6–23.

Blumberg

F. C.

Altschuler

E. A.

Almonte

D. E.

Mileaf

M. I.

(2013) The impact of recreational video game play on children’s and adolescents’ cognition. New Directions for Child & Adolescent Development 139: 41–50.

Blumberg

F. C.

Sokol

L. M.

(2004) Boys’ and girls’ use of cognitive strategy when learning to play video games. The Journal of General Psychology 131(2): 151–158.

Bormann

E. G.

(1975) Discussion and group methods: Theory and practice, New York, NY: Harper and Row.

Burger

Marino

Ponterotto

Houtz

(2008) Problem solving style and multicultural personality dispositions. Creative Learning Today 16(1): 2–3.

Burke

Aytes

(2002) Do media really affect perceptions and procedural structuring among partially distributed groups? Journal on Systems and Information Technology 5(1): 10–23.

Carver

C. S.

Scheier

M. F.

Weintraub

K. J.

(1989) Assessing coping strategies: A theoretically based approach. Journal of Personality and Social Psychology 56(2): 267–283.

Chory

R. M.

Goodboy

A. K.

(2011) Is basic personality related to violent and non-violent video game play and preferences? Cyberpsychology, Behavior, and Social Networking 14(4): 191–198.

10.

Costello

Houtz

(2004) More on the factor structure of VIEW. Creative Learning Today 13(4): 5.

11.

Fisher

Greitemeyer

Morton

Kastenmüller

Postmes

Frey

Odenwälder

(2009) The racing-game effect: Why do video racing games increase risk-taking inclinations? Personality & Social Pscyhology Bulletin 35(10): 1395–1409.

12.

Gabbiadini

Greitemeyer

(2017) Uncovering the association between strategy video games and self-regulation: A correlational study. Personality & Individual Differences 104: 129–136.

13.

Gavetti

Levinthal

D. A.

Ocasio

(2007) Neo-Carnegie: The Carnegie school’s past, present, and reconstructing for the future. Organization Science 18(3): 523–536.

14.

Gee

J. P.

(2003) What video games have to teach us about learning and literacy, New York, NY: Palgrave Macmillan.

15.

Glass, B. D., Maddox, W. T., & Love, B. C. (2013). Real-time strategy game training: Emergence of a cognitive flexibility trait. Plos One. Retrieved July 21, 2017, from https://doi.org/10.1371/journal.pone.0070350.

16.

Graf

D. L.

Pratt

L. V.

Hester

C. N.

Short

K. R.

(2009) Playing active video games increases energy expenditure in children. Pediatrics 124(2): 534–540.

17.

Granic

Lobel

Engels

R. C. M. E.

(2014) The benefits of playing video games. American Psychologist 69(1): 66–78.

18.

Green

C. S.

Bavelier

(2006) Action-video-game experience alters the spatial resolution of vision. Psychological Science 18(1): 88–94.

19.

Hamlen

K. R.

(2012) Academic dishonesty and video game play: Is new media use changing conceptions of cheating? Computers & Education 59(4): 1145–1152.

20.

Hancock, F. (2010). Social problem solving and the video game player. In B. Meyer (Ed.), Proceedings of the 4th European Conference on Games Based Learning (pp. 447–453). Copenhagen, Denmark: Academic Publishing International.

21.

Holland

J. L.

(1996) The psychology of vocational choice: A theory of vocational personalities and environments, 2nd ed. Englewood Cliffs, NJ: Prentice Hall.

22.

Jenny

S. E.

Schary

(2014) Exploring the effectiveness of learning American football through playing the video game “Madden NFL”. International Journal of Technology in Teaching & Learning 10(1): 72–87.

23.

Kinzie

M. B.

Joseph

D. R. D.

(2008) Gender differences in game activity preferences of middle school children: Implications for educational game design. Educational Technology Research and Development 56(5): 643–663.

24.

Kühn

Gleich

Lorenz

R. C.

Lindenberger

Gallinat

(2014) Playing Super Mario induces structural brain plasticity: Gray matter changes resulting from training with a commercial video game. Molecular Psychiatry 19(2): 265–271.

25.

Lazarus

R. S.

(1993) Coping theory and research: Past, present, and future. Psychosomatic Medicine 55(3): 234–247.

26.

Liu

Y.-C.

McLeod

P. L.

(2014) Individual preference for procedural order and process accountability in group problem-solving. Small Group Research 45(2): 154–175.

27.

Loewenthal

K. M.

(2004) An introduction to psychological tests and scales, 2nd ed. Hove, England: Psychology Press.

28.

Miller

M. J.

Miller

T. A.

(2005) Theoretical application of Holland’s theory to individual decision-making styles: Implications for career counselors. Journal of Employment Counseling 42: 20–28.

29.

Murias

Kwok

Castillejo

A. G.

Liu

Iaria

(2016) The effects of video game use on performance in a virtual navigation task. Computers in Human Behavior 58: 398–406.

30.

Peng

Liu

Mou

(2008) Do aggressive people play violent computer games in a more aggressive way? Individual difference and idiosyncratic game-playing experience. CyberPsychology & Behavior 11(2): 157–161.

31.

Selby, E. C., & Treffinger, D. J. (2008). The development of VIEW: A new tool for assessing problem solving style. Retrieved July 26, 2017, from http://www.cpsb.com/research/articles/problem-solving-style/Development-of-VIEW.html.

32.

Selby

E. C.

Treffinger

D. J.

Isaksen

S. G.

(2002) VIEW: An assessment of problem solving style, Sarasota, FL: Center for Creative Learning.

33.

Selby

E. C.

Treffinger

D. J.

Isaksen

S. G.

Lauer

K. J.

(2004) VIEW Technical Manual, Sarasota, FL: Center for Creative Learning.

34.

Stevens

Satwicz

McCarthy

(2008) In-game, in-room, in-world: Reconnecting video game play to the rest of kids’ lives. In: Salen

The John

Catherine

(eds) The Ecology of Games: Connecting Youth, Games, and Learning (MacArthur Foundation Series on Digital Media and Learning), Cambridge, MA: The MIT Press, pp. 41–66.

35.

Sturz

B. R.

Bodily

K. D.

Katz

J. S.

(2009) Dissociation of past and present experience in problem solving using a virtual environment. Cyberpsychology & Behavior 12(1): 15–19.

36.

Suziedelyte

(2015) Media and human capital development: Can video game playing make you smarter? Economic Inquiry 53(2): 1140–1155.

37.

Cheng

C. K.

Feng

D’Angelo

Alain

Spence

(2012) Playing a first-person shooter video game induces neuroplastic change. Journal of Cognitive Neuroscience 24(6): 1286–1293.