1

GAMER’S PROFILE, DECISION-MAKING AND PROBLEM SOLVING SKILLS

OF THEADOLESCENTS IN CAVITE NATIONAL HIGH SCHOOL

Kenneth Percival C. Baro

Roden Michael B. Paraon

An undergraduate thesis manuscript submitted to the faculty of the Department of Social

Sciences and Humanities, Cavite State University, Imus City Cavite in partial fulfillment
of the requirementd for the degree of Bachelor of Science in Psychology with
Contribution No. _________. Prepared under the supervision of Ms. Diwata R. Parong.

INTRODUCTION

“Video games are either the divine instrument of education’s future or the

software of Satan himself” (Shaban, 2013). Playing video games provides a delightful

experience of entertainment ever since the release of the very first video game called

“Tennis for Two”, a very simple tennis game created by the physicist William

Higinbotham. Until then, new kinds of games continued to emerge, including games that

have mature content which contains violent or sexual content. Problems arise such as the

possibility of these games to cause negative effects on individuals,such as violence,

addiction, and depression. According to Hull, Brunelle, Prescott and Sargent (2014),

violent videogames affect teenage users’ self-image. These games that glorify anti-social

characters may encourage youths to identify the protagonists the game features which

may increase criminal and other risky behavior such as smoking and alcohol use.
 2

Video games are becoming more and more innovative as the years advance, but as

video games become more innovative, it also becomes more realistic. Some researchers

show that as the games become more realistic, it produces various effects.

A statement of an associate professor of communication, Krcmar (2010), who

studied the impact of video games on children and teens at the Wake Forest University in

North Carolina, was quoted on the website of its university; “greater realism leads to

greater immersion; greater immersion leads to greater effects. One of those effects can be

increased aggression” (Krcmar, 2010) and low verbal IQ (Takeuchi, 2016).

But behind the social stigma and the disapprovals of society against video games,

which is obviously caused by the negative effects it gives to the ones who play it, there

are some good effects that can be harbored in gaming. “Important research has already

been conducted for decades on the negative effects of gaming, including addiction,

depression and aggression, and we are certainly not suggesting that this should be

ignored, However, to understand the impact of video games on children’s and

adolescents’ development, a more balanced perspective is needed” (Granic, 2014).

On the other hand, educators around the world are starting to recognize the

potential of video games as a tool for learning. Jacqui Murray, A teacher of K-8

technology for 15 years says that playing video games like Minecraft develops reading,

writing, and problem solving skills (Murray, 2013.).

Helena Bergstrand, a teacher at Tanto International School in Central Stockholm,

Sweden uses game apps on iPads and Tablets to help motivate children to learn. Ninety

percent of teachers in their city believed in the same idea according to the conducted poll

of their city council (Sullivan, 2014). The award-winning Filipino educator Ramil
 3

Buenaventura uses game apps to teach statistics at the Renaissance Charter School in

Jackson Heights, New York (Tagala, 2014).

In general, adolescents have poor decision-making skills than adults. According to

Talukder (2013), adolescents’ frontal lobe is less active than the adults. The frontal lobe

is involved in various functions of a human brain and one of those is decision-making

and problem solving (Bailey, 2016). If it left untended, adolescents are inclined to behave

in impulsive, irrational, or even in a dangerous way (American Academy of Child &

Adolescent Psychiatry, 2016).

In addition, educators view the decision-making skills as a critical factor in a

student’s learning process. The educators think that a student who has good decision-

making skills has an improved study habit and aid classroom learning objectives

(Gregory & Clemen, 2004). While problem solving skills helps in empowering the

adolescent to look at a problem objectively concerning the different options for solutions

and would help them come to a solution after weighing the pros and cons of the different

options available (Srivastava, 2015).

According to Jaffee and D’Zurilla (2009), lack of problem-solving skills is

associated with aggression among adolescents. They further stated that others may view

these strategies as ways to cope with problems, in the same way, which anger may be

dealt with negatively. Problem solving, as well as like fact learning, are both necessary to

create a system where learning capacity is in full potential (Sahlfeld, 2011). Furthermore,

helping a child learn how to solve a problem is a critical skill for school readiness.

Parents and caregivers are a child’s first and most important teacher; therefore, modeling

good problem solving skills is very important. If a guardian does not provide situations
 4

and valuable insights, there would be no example for the child to learn from. The child

could have low problem-solving skills and thus affect its academic success (Gutierrez,

2012).

Many factors such as the amount of hours spent playing video games, the active

onset age when they played video games and the genre of video games helps in

improving the skills like the problem solving skills of the adolescents (Adachi &

Willoughby, 2013) and the cortical thickness of left dorsolateral and left frontal eye field

of the brain (Kühn, Lorenz, Banachewski, Barker, Büchel, Conrod, Flor, Garavan,

Itterman, Loth, Mann, Nees, Artiges, Paus, Rietschl, Smolka,Ströhle, Walaszek,

Schumann, Heinz andGallinat(2014) which is responsible for making decisions (DiSalvo,

2014).

In light of these facts, the researchers believe that it is important to know the

positive side of playing video games in order to understand its impact fully and so the

researchers developed the Gamer’s Profile where the respondents’ estimated number of

hours spent playing video games per week, the academic level of the respondents when

they started playing video games continuously and their most preferred genre of video

games will be reported and measured. Knowing all these and also driven by other factors,

the researchers aimed to discover if there is a significant relationship between the

respondents’ Gamer’s Profile to their decision-making, and problem solving skills.

Statement of the Problem

The researchers identified if there was a relationship between the Gamer’s Profile

to the decision-making and problem solving skills of the respondents. Specifically, it

aimed to look into the following problems:

 5

1.) what is the Gamer’s Profile in terms of the following:

1.1 estimated number of hours spent playing video games per week;

1.2 academic level when they started playing video games continuously; and

1.3 most preferred genre of video games.

2.) what is the level of decision-making skills of the respondents?

3.) what is the level of problem solving skills of the respondents?

4.) is there a significant relationship between the Gamer’s Profile and the decision-

making skills of the respondents?

5.) is there a significant relationship between the Gamer’s Profile and the problem-

solving skills of the respondents?

Objectives of the Study

In line with the problems presented above, the research aimed to achieve the

following:

1.) to determine the Gamer’s Profile in terms of the following:

1.1 estimated number of hours spent playing video games per week;

1.2 academic level when they started playing video games continuously; and

1.3 most preferred genre of video games

2.) to determine the level of decision-making skills of the respondents.

3.) to determine the level of problem solving skills of the respondents.

4.) to identify if there is a significant relationship between the Gamer’s Profile and

the decision-making skills of the respondents.

5.) to identify if there is a significant relationship between the Gamer’s Profile and

the problem solving skills of the respondents.

 6

Significance of the Study

The study will be of great help to the following:

Adolescents. This study mayprovide benefits for the adolescents to use video

games as a training tool in order to improve their decision-making and problem solving

skills.

Educators. This study might be a ladder towards new ways of learning, learning

techniques and strategies fit into the modern society and will be of immense help to

teachers, school administrators and other stakeholders.

Parents. This study could raise awareness about the possible effects of playing

video games to their children’s decision making and problem-solving skills. The findings

of this study could contribute to the idea that video games have the potential to be

beneficial and thus, reduce the social stigma of videogames to society.

Society. The findings of this study might redound to the benefit of society

considering that video games are growing up to be a large part of the entertainment of

ever-changing society, especially to adolescents. Video games could provide help to

improve the decision-making, and problem solving skills of individuals and not solely for

entertainment purposes.

Future researchers. The study could add new topics of interest to be pursued and

will provide a good source of literature in relation to the topic being studied. Moreover,

the study can contribute to the actualization that in order to understand the impacts on

playing video games, there must have a balanced perspective. Not just considering the

negative effects of gaming but also the possibility of its positive effects.
 7

Time and Place of the Study

The study was conducted and accomplished from August 2016 – May 2017 at

Cavite National High School in Cavite City, Cavite. The researchers selected the locale

because Cavite City, Cavite is classified as a fourth-class income city according to

Philippine Statistics Authority (nap.psa.gov.ph) where Labucay (2014) indicated that

online gaming is prevalent among those who live in fourth income class cities.

Scope and Limitation of the Study

The study was conducted atCavite National High School in Cavite City, Cavite

from August 2016 to May 2017. Theparticipants of the study were the adolescents that

possess the following criteria: age ranging from 12 to 18 years oldand must be an active

video game player. The study comprised of 178 respondents from Cavite National High

School. The researchers used the descriptive-correlational research design to determine

the level of decision-making and problem solving skills of the respondents and to identify

if their decision-making and problem solving skills have a significant relationship with

their Gamer’s Profile. Furthermore, the researchers used the purposive and convenience

sampling technique.

The Gamer’s Profile was used in order to determine the estimated number of

hours spent playing video games per week of the respondents, the academic level of the

respondents when they started playing video games continuously and their most preferred

genre of video games. Moreover, the Making Decisions in Everyday Life scale was used

by the researchers to measure the decision-making skills of the respondents and the

Solving Problems Survey scale was used to measure the problem solving skills of the

respondents.
 8

Lastly, the respondents are limited only to the adolescents (12 to 18 years old)

who were actively playing video games; those who fail to meet the criteria established by

the researchers was excluded from the samples.

Definition of Terms

To understand and clarify the terms used in the study, the following are hereby

defined formally and operationally.

Actiongenre - games with a heavy emphasis on a series of actions performed by the

player in order to meet a certain set of objectives (Lee, Karlova, Clarke, Thornton &Perti,

2014).

Action–adventuregenre- games which are set in a world for the player to explore and

complete a certain set of objectives through a series of actions (Lee et al., 2014).

Audiovisual apparatus – it was defined as the means to play video games with an

electronic system that has computing capabilities, input (controllers, mouse, keyboards,

etc.), and output devices (screen, loudspeakers, etc.). It can be any kind of video game

console, a computer, and even a phone (Esposito, 2005).

Decision-making – it was defined as the skill to define a problem, select between

alternatives, identify the risk and magnitudes for each alternative, selection of an

alternative, and lastly, evaluating the circumstances (Mincemoyer& Perkins, 2003).

Driving genre- games involving driving various types of vehicles as the main action,

sometimes with an objective of winning a race against an opponent (Lee et al., 2014).

Fighting genre - games involving the player to control a game character to engage in a

combat against an opponent (Lee et al., 2014).

 9

Online video games – it was defined as a video game that is partly or mainly played by

means of internet. It is played mostly by Filipinos that belong to fourth income class

cities (Labucay, 2014).

Problem solving – it was defined as “the self-directed cognitive behavioral process by

which a person attempts to identify or discover effective or adaptive ways of coping with

problematic situations encountered in everyday living” (D'Zurilla&Maydeu-Olivares,

1995, p. 410).

Puzzle genre - games with an objective of figuring out the solution by solving enigmas,

navigating, and manipulating and reconfiguring objects (Wolf, 2001).

Role-playing game (RPG) genre - games with an emphasis on the player’s character

development and narrative components (Lee et al., 2014).

Shooter genre - games involving shooting at, and often destroying, a series of opponents

or objects (Wolf, 2001).

Simulation genre - games intending to recreate an experience of a real world activity in

the game world (Lee et al., 2014).

Sports genre - games featuring a simulation of particular sports in the game world (Lee

et al., 2014).

Strategy genre - Games characterized by players’ strategic decisions and interventions to

bring the desired outcome (Lee et al., 2014).

Video game – it is defined as any kind of game that can be played through the means of

an audiovisual apparatus (Esposito, 2005).

 10

Theoretical Framework of the Study

In this study, the researchers used the law of exercise proposed by Edward

Thorndike and the learning by doing principle proposed by John Dewey.These

theorieswereselected to understand the relationship between the Gamer’s Profile to the

respondents’ decision-making, and problem solving skills.

Law of Exercise by Edward Thorndike

The law of exercise has two elements that are associated with exercising a

specific skill. The first is that learning is improved through practice and repetition.

Secondly, is that feedback is essential in learning. In particular, this law stresses practice

and feedback must exist together for the best learning results (Murphy, 2011). It is one of

the most efficient ways to aid the students to master a skill (Cabigas, 2014).

To begin with, games make broad use of practice and repetition as a part of a

normal gameplay to help promote mastery (Koster, 2005). According to Murphy (2011),

time on task is the fundamental requirement of learning and mastery. Games generally

require you to master a rudimentary set of skills by making the players repeat their

actions until they master it by overcoming a chain of challenges that intensifies in

difficulty and variety over time.

Secondly, video games are particularly adept at using feedback (Kaufman, 2008).

Basically, games operate on a feedback loop (Goetz, 2011). More specifically, the

feedback loop consists of four stages: 1.) measure behavior; 2.) convey the measurement

to the user; 3.) realize some sort of consequence, and 4.) provide opportunities for

alternative action.
 11

Learning by Doing Principle by John Dewey

The learning by doing principle “means learning from experiences resulting

directly from one’s own actions, as contrasted with learning from watching others

perform, reading others’ instructions or descriptions or listening to others’ instructions or

lectures(Reese, 2011). Watching, reading and listening, although considered as an action,

is not the kind of ‘doing’ that the principle implies, this is because these actions acquire

learning through descriptions and demonstrations rather than actual performance.

Conceptual Framework of the Study

The researchers, in line with the hypothesis presented, designed these conceptual

frameworks that will help in the easier understanding of the study’s aim. These

frameworks served as a guide to the researchers as they made progress on their study.

Gamer’s Profile
Level of decision-
 Estimated number of
making skills
hours spent playing
video games per week
of the respondents.
 Academic level of the
respondents when
started playing video
games continuously. Level of problem
 Most preferred genre of solving skills
video gamesof the
respondents.

Figure 1. Gamer’s profile, decision-making and problem solving skills of the

adolescents at Cavite National High School in Cavite City, Cavite
 12

The figure above displays the researchers’ guide in conducting the study. The

diagram represents the relationship between the Gamer’s Profile to their decision-

making, and problem solving skills of the adolescents.

After obtaining the data of the respondents’ decision-making and problem solving

skills, the researchers determined the level of decision-making and problem solving skills

of the respondents. Subsequently, the results were analyzed to identifyif there wasa

significant relationship to the respondents’ Gamer’s Profile.

 13

REVIEW OF RELATED LITERATURE

This review of related literature and study contains information taken from

various sources that serve to expand and deepen the reader’s understanding of the topics

that underlie in this study. This chapter contains literatures and studies about the

research’s underlying variables.

Video Games

“Video games are sports that take place in a computer. They’re interactive TV

shows and interactive movies. They’re digital board games and card games. They’re

rough simulations of everyday life including, probably, whatever you do for a living”

(Owen, 2016).

A more precise definition of a video game is that a video game is any kind of

game that can be played through the means of an audiovisual apparatus (Esposito, 2005).

The audiovisual apparatus is an electronic system with computing capabilities, input

devices (controllers, mouse, keyboards, etc.), and output devices (screen, loudspeakers,

etc.). It can be an arcade video game, a video game console, a handheld console, a

computer, a personal digital assistant, a phone, etc. (Esposito, 2005).

This notion implies that there is an interactivity that takes place between the

player and the game. Video games are more interactive and absorbing than passive forms

of entertainment like movies and TV, it promotes a higher level of engagement because

observers are actively and enthusiastically involved with on-screen activity (Steinberg,

2011).
 14

There are a number of factors that could explain why adolescents are encouraged

to play video games. One of them is that adolescents might view video games as a new

tool for connecting with their friends. According to Ito, Horst, Boyd, Herr-Stephenson,

Lange, Robinson and Bittanti (2009), playing video games became the evolution of other

casual activities such as board games. Video games could also be an interesting topic

among children and adolescents. Olson, Kutner, and Warner (2008) stated that most of

the adolescent boys from their focus groups agreed that video games are a frequent topic

of conversation among their friends. Moreover, according to Trotter (2011), media

influences and popular culture strongly affects the peer activities of children ages 8 to 11.

Bearing this in mind, the researchers had come up with possible predictors that

may have a significant correlation with the decision-making and problem solving skills of

the respondents.

First, the researchers believed that acquiring the number of hours spent playing

video game per week of the respondents is essential in determining any existing

relationship between their decision making and problem solving skills. A considerable

number of researches gave emphasis on the notion that the number of hours spent playing

video games is a key factor in determining the relationship of video games to various

variables (e.g., Gentile, 2011; Kühn et al., 2014).

According to Gentile (2011), there is a significant positive correlation between the

numbers of hours of video game play per week and with a number of pathological

symptoms of video-gaming. Furthermore, video gaming hours was found to be

significantly correlated with the cortical thickness of the left dorsolateral prefrontal

cortex and left frontal eye field (Kühn et. al, 2014).
 15

Secondly, it is also important to know when the respondents started playing video

games. According to Hartanto, Toh, and Yang (2016), studying the active onset age of

the respondents’ video game play “captures both how long a person has played video

games and whether the individual began playing during periods of high cognitive

plasticity”. According to Greenwood (2010), cognitive plasticity refers to adaptive

changes in patterns of cognition related to brain activity (e.g., increased dependence on

executive function).

Developmental studies have demonstrated that cognitive plasticity and training-

induced cognitive improvements generally decline with age (Baltes & Kliegl, 1992).

According to Spear (2002) late childhood and preadolescence – which occur prior to age

12, represents phases where the brain undergoes widespread development. Therefore,

Hartanto, Toh and Yang (2016) made this as the basis of their categorization of their

samples into three, namely: Early Video Game Player (EVGP), Late Video Game Player

(LVGP) and Non-Video Game Player (NVGP). Early video game players were the

respondents that played video games continuously prior to age 12 while the LVGP’s were

those who played video games continuously during or after 13 years old.

Lastly, further studies are needed in order to fully grasp the understanding of the

effects of different genre of video games not only to the problem solving skills of the

adolescents but also to diverse skills that the video games can offer to the adolescents

(Adachi & Willoughby, 2013). There are a number of researches which suggests that

certain genres could provide cognitive benefits. According to Green and Bavelier (2012),

certain video game genres provide more cognitive benefits such as reaction time than

other genres do.

 16

Basically, there are two kinds of video games: offline and online video games.

Both kinds use audiovisual apparatus but an online game needs an internet connection in

order to be played (Adams, 2014). A study by Spil Games (2013) reported that 1.2 billion

people are now playing video games worldwide and 700 million of them are playing

online video games.

According to the study of Kowert (2013), where the participants of her study

consisted of non-video game players and video game players and mostly from the United

States and the United Kingdom and mostly consisted of adult participants. The result of

her study found that the highest percentage (11.7%) of the video gamers prefer to play for

“6 to 10 hours per week”.

Even though many of the Filipinos do not have the luxury to buy a computer set,

they can still access computers and the internet through cyber café. Filipinos are very

well-known when it comes to tingi-tingi culture or retail (Danganan, 2013). Tingi-tingi is

the practice of selling and buying goods in amount less than smallest retail packaging

(Veneracion, 2013). While buying in bulk is cheaper, in the long run, it is more realistic

to buy only what the majority of Filipino consumers need for the moment (Veneracion,

2013).

Many of the internet users in the Philippines go to cyber café to access the

internet for their own purposes since it is cheaper (Dizon, 2009) than buying a computer

set and subscribing to certain telecommunication company and paying the bills monthly

to connect through the internet. Tingi-tingi is still present in high school students because

they only save a very small amount of their pocket money. According to Patria (2012),
 17

tend to go to cyber cafés in order to play video games since high school students receive

only an average of P157.60 per week.

Recent statistics by NIKO media showed the number of PC online gamers in the

Philippines to be 28.72 million in 2014, 28 percent of the Philippines’ total population of

100.5 million in that year. Specifically, Labucay (2014) stated that online video gaming is

prevalent among Filipinos living in fourth income class cities in the Philippines. Asian

Institute of Journalism and Communication, stated that an average of 77 percent or nearly

8 out of 10 teenagers (12 – 18 years old) play online games in the Philippines, with

Luzon reporting the highest number of gamers (Benigno, 2014). Recent statistics of

Entertainment Software Association (2016) states that puzzle games were one of the

highest ranking games played on wireless or mobile devices. Puzzle video games are

games with an objective of figuring out the solution by solving enigmas, navigating, and

manipulating and reconfiguring objects (Wolf, 2001).

To get back to the subject, Trybus (2015) stated that when a player progress in a

game, learning ensues. Being involved in a game, a player’s mind goes through the

pleasure of grasping with a new system. This is also true whether the game is considered

“entertainment” (e.g., World of Warcraft) or “serious” (e.g., FAA – approved flight

simulator). Moreover, she said that in order to achieve efficient and interactive

experiences that motivate them and engage people in the learning process, game-based

learning is needed.

Gee (2007) proposed “challenge and consolidation principle” in which a good

video game offers the players a challenging problem and then letting them solve these

problems repeatedly but with variations until they routinized their solutions. Eventually,
 18

the game tosses a new set of a problem at the players (usually this is called a “boss”),

expecting them to test their newly routinized solution in order to learn something new

and integrate this new learning with their former mastery.

Indeed, this principle uses the law of exercise to promote learning during

gameplay. By using repetition and feedback, the player is exercising the necessary skills

to master the game and eventually, the game throws another challenging task to ensue

learning to the player. According to Murphy (2011), time on task is the fundamental

requirement of learning and mastery. Video games use the law of exercise through

practice, repetition and feedback.

First, video games use the concept of practice and repetition to promote mastery

by giving the players set of challenges to overcome. Video games teach the players the

suitable skill to overcome the challenge until the player finds a way to routinize that skill

in order to master it. Secondly, videos game conveys feedback to the players through the

scoring system, giving rewards, growth indicators or death outcomes. Each of these gives

feedback about your progression, performance, or skill growth. They show the outcomes

your actions (Murphy, 2011).

Decision-making

According to Mincemoyer and Perkins (2003), the skills needed to make sound

decisions can be taught. Making a decision entails that there are alternate varieties to be

reflected, and in such a case an individual wants not only to recognize as many of these

alternatives as possible but to choose the one that has the highest chance of success or

efficiency and best correspond with the individual’s goals, desires, lifestyle, values, and

so on (Harris, 2012).
 19

Adolescence is a “time of increased pressure for problem solving and personal

decision” (Worell & Danner, 1989). According to Shultz and Shultz (2010), adolescence

is the period where “identity confusion versus identity cohesion" proposed by Erik

Erikson occur. Adolescents go through various experimentations of ideologies to

determine the most compatible fit for their roles and it is often filled with anxiety in this

stage.

“Adolescents are called upon to make many difficult decisions including

decisions regarding career, sexuality, school involvement and risk behaviors” (Scott,

1998). According to Schultz and Schultz (2010), making decisions is very hard for

adolescents during this period because they are faced with many choices in order to

establish their own identity that is why they are often filled with anxiety during this

period. Furthermore, Mann, Harmoni and Power (1989) noted that younger adolescents

are less skilled in identifying alternatives, identify a range of risks and benefits,

understand or predict the risks and benefits and accurately evaluate the information

received from sources that may have vested interests in the decision.

It is imperative for the adolescents to improve their decision-making skills

because unlike adults, the brain of an adolescent is not yet developed to make good

decisions as adults can (Talukder, 2013). Specifically, the amygdalae of the adolescents

have higher activity than the adults have. According to Bailey (2017), the amygdala is

involved in several functions of the body including arousal, autonomic responses

associated with fear, emotional responses, hormonal secretions and memory.

Furthermore, she stated that higher activity in this part of the brain could lead adolescents

to become emotional when making decisions.

 20

In terms of the importance of the decision-making skill in a school setting,

Gregory and Clemen (2004) developed curricula for six schools that aid the students in

improving their decision-making skills. Afterward, they interviewed the teachers of each

classroom they implemented their curricula and found that those students that were

involved in the curricula became better listeners, demonstrating improved skills to

organize and structure subject-based tasks, and are better able to designate

responsibilities in a group setting. Moreover, the students became more active

questioners of the information they are provided, less eager to receive data at face value

and better equipped to search for and fill in the data that are needed.

”All genres of video games involve some form of decision-making. In fact,

nothing else forces the player to make decisions like no other than video games do”

(Burgun, 2012). According to Gee (2007), video games rely on the individual in order for

it to work. There must be an interactive relationship between the player and the game.

Nothing happens until a player acts and makes decisions. Then the game responds back,

providing the player feedback and new challenges. Likewise, good learning requires that

learners feel like active agents, not just passive receivers (Gee, 2007).

Video games create situations where players not only must make decisions, they

must make them rapidly and they must persistently adjust to shifting circumstances and

rules (Rutledge, 2012). Indeed, these conditions encourage cognitive flexibility, the

lenience of equivocalness and comfort with decision-making without full facts, which is

remarkable for dealing with real-world situations on a daily basis of work, at school, and

at home (Reeves, Malone & O’Driscoll, 2008). In addition, Reeves et al. (2008) also

stated that even video games like World of Warcraft (massive multiplayer role-playing
 21

game) provide an outstanding training ground for efficient leadership strategies, in large

part because it imparts a discernment of the types of environments that assist adaptive

decision-making.

There are various factors that affect the decision-making of an individual. One of

those is cognitive biases. Cognitive biases are thinking patterns grounded on observations

and generalizations that may result to memory errors, inaccurate judgments, and incorrect

logic (Evans, Barston, & Pollard, 1983; West, Toplak, & Stanovich, 2008). According to

Dietrich (2010), cognitive biases lead to poor decision-making. By causing them to over

be dependent on or lend more credence to expected observations and prior knowledge,

while disregarding information or observations that are perceived as uncertain, without

looking at the bigger picture. Thus, reducing these cognitive biases leads to better

decision-making.

In an attempt to reduce the six well-known cognitive biases namely: bias blind

spot, confirmation bias, fundamental attribution error, anchoring, projection, and

representativeness. Morewedge, Scopelliti, Symborski, Korris and Kassam (2015)

developed two video games (Missing: The Pursuit of Terry Hughes and Missing: The

Final Secret) intended to reduce cognitive biases. After each episode of the game is

played there is an After Action Review (AAR), where the player was taught about the

biases, offers feedback on the player’s performance, and strengthens the point with a

story.

The study comprises of two experiments. The first experiment consists of 243

adult participants. Group A watched a 30-minute video, “Unbiasing Your Biases”, while

group B played a computer game developed by the researchers, “Missing: The Pursuit of
 22

Terry Hughes” where game players make decisions and judgments during the course of

the game. At the end of each level, participants were given feedbacks about how biased

they were during the game, and they were taught strategies to reduce the tendency to

commit each of the biases.

Researchers measured the biases of the participants before and after the

interventions were implemented. Playing the video game reduced the three biases

namely: bias blind spot, confirmation bias, and fundamental attribution error by 46

percent immediately and 35 percent over the long term (at least two months later).

Watching the video only reduced the three biases by 19 percent immediately and 20

percent over the long term.

The second experiment includes 238 adult participants. Group A watched a video,

“Unbiasing Your Biases 2” to address three biases: anchoring, projection, and

representativeness. While group B played a video game that the researchers developed,

“Missing: The Final Pursuit”. Again, after each level of the game, participants were given

feedback and taught strategies on how to reduce their biases. Like the first results, the

video game was proven to be more effective than the video in reducing the biases of the

participants. Playing the game decreased the three biases by 32 percent immediately and

24 percent over the long term while watching the video only reduced the three biases by

25 percent immediately and 19 percent over the long term. Video games proved to be an

effective tool in order to reduce these cognitive biases.

There was also evidence found that playing video games have a strong correlation

with the cortical thickness in left Dorsolateral Prefrontal Cortex (DLPFC) and left Frontal

Eye Field (FEF) of the brain. An experiment conducted by Kühn et al. (2014) on 152
 23

adolescents, both male and female to know if video gaming hours affect the cortical

thickness – a term used by neuroscientists that means greater density in particular brain

areas.

The experimenters used CSV-S to measure the computer gaming behavior of the

participants. On average the participants reported playing video games for an average of

12.6 hours and after measuring the computer gaming behavior of the participants, the

experimenters scanned the brain of the participants by using General Electric Signa

Excite 3 T scanner and Siemens Verio 3 T. The experimenters found a positive

correlation between the self-reported hours of video gaming per week and the cortical

thickness in the left DLPFC and the left FEF.

According to DiSalvo (2014), the prefrontal cortex is also referred as the

command and control center. It is where the executive function takes place, like decision-

making and self-control. While the FEF handles the processing of visual-motor

information and makes judgments to the external stimuli. It also plays a role in decision-

making because it aids an individual to identify what kind of reaction will be the most

applicable in the individual’s environment. Furthermore, he also stated that greater

“thickness” in this brain (implies more connection between brain cells) areas indicate a

greater ability to manage multiple variables, whether those variables have immediate or

long-term repercussions or both.

He concluded, that the findings of Kühn et al. (2014) may not explain that the

playing hours of video games causes DLPFC and FEF to grow thicker, the correlation is

“strong enough to consider the possibility that gaming is sort of like weight lifting for the

brain” (DiSalvo, 2014).

 24

Problem Solving

According to Cherry (2016), which she stated that problem solving, as defined in

cognitive psychology, refers to the “mental process that people go through to discover,

analyze and solve problems”. It involves the steps in the problem process which are the

discovery of the problem, the decision to tackle the issue, understanding the problem,

researching available options and taking actions to achieve your goals (Cherry, 2016).

There have been found evidence that the adolescents are having difficulties in

solving problems. According to Talukder (2013), that at the point when processing

emotions, adults have greater activity in their frontal lobe than adolescents and could

makes their judgment and objectivity more reliable than the adolescents could. The

frontal lobe is responsible for movement, decision-making, problem solving and planning

(Bailey, 2016).

Problem solving helps in empowering the adolescent to look at a problem

objectively about the different options for solutions and would help them come to a

solution after weighing the pros and cons of the different options available (Srivastava,

2015). Problem solving, as well as like fact learning, are both necessary to create a

system where learning capacity is in full potential (Sahlfeld, 2011).

Experimentation is essential in problem solving, and experimentation relies on

current beliefs and past knowledge which are clearly, the product of fact learning.

Gutierrez (2012) also stated that problem solving skills are a critical tool for school

readiness as having low-level problem solving skills affects children’s academic success.

Researchers such as Dewey (1910), Newell and Simon (1972) who works on the

research of problem solving accepts the notion that “a problem occurs only when
 25

someone is confronted with a difficulty for which an immediate answer is not available”

(Gok, 2010). However, a problem’s difficulty depends on the solver’s knowledge and

experience, which means ‘difficulty’ is not an internal factor of a problem (Garrett, 1986;

Gil-Perez et al., 1990).

There are a number of theories that explains how problem solving occurs.

Wolfgang Kohler, one of the original Gestalt psychologists, proposed the theory of

“insight learning”. The theory implies that learning a solution to a problem requires a

completely cognitive experience that requires the ability to visualize the problem and the

solution internally.

Although problem solving and decision-making have always been mistakenly

defined interchangeably, “problem solving always involves decision-making” (Effective

Problem Solving & Decision Making, 2014, p. 4). As stated in the literature, there are

four steps involved in problem solving: defining the problem, creating alternative

solutions, evaluating alternatives and selecting one, and the implementation and follow-

up of the solution. The literature states that decision making happens in the third step.

Other interpretations of how the problem solving process occurs differ from each source,

like the one stated by Cherry (2016). Although there are differences in sequence, the

steps and the goal is identical.

According to Prensky (2012), scholars speculated that video games could be an

excellent tool for developing problem solving. The notion is not far from impossible

because of numerous factors, As Rutger C.M.E. Engels (2014) stated in the article The

Benefits of Playing Video Games, “problem solving seems central to all genres of video

games” (p. 69).

 26

In-game puzzles provide a range of difficulties. From a simple puzzle of finding

the quickest route from point A to B to a more complex one of acquiring complex

sequences that require analyzation and memorization. Engels also said that game

designers often create in-game problems with a little instruction of how to solve them,

letting the players be exposed to a wide range of possible solutions that can be utilized by

their intuition and past experiences.

But while what Prensky (2012) stated might be true, playing certain kinds of

video games could cause the improvement of problem solving skills. A recent study by

Oei and Patterson (2014) concluded that playing the video game “Cut the Rope” could

improve higher-order executive function skills, including problem solving skills. The

researchers used the process of elimination in order to pick the popular phone and tablet

games, shooting game “Modern Combat,” arcade-style “Fruit Ninja,” strategy game

“StarFront Collision,” and puzzle game “Cut the Rope”, From most effective to least. The

video game “Cut the Rope” ranked first among the games for improving executive

functions of the brain, which involves memory, decision-making, planning, and problem

solving. The other games have no detected benefits.

The researchers used the process of elimination in order to pick the popular phone

and tablet games, shooting game “Modern Combat,” arcade-style “Fruit Ninja,” strategy

game “StarFront Collision,” and puzzle game “Cut the Rope”, From most effective to

least. The game “Cut the Rope” ranked first among the games for improving executive

functions of the brain, which is memory, decision-making, planning, and problem

solving. The other games have no detected benefits.

 27

Moreover, other than operating the video game itself, there are other elements

associated in video games that can help improve problem solving skills and other

functions. In massively multi-player video games like “World of Warcraft”, scientific

habits are being exercised constantly as being guild member or being affiliated to

organized player groups, who must collaborate with each other to work on various in-

game challenges or problems, these players do research known solutions and collaborate

with other players to solve the complex challenges.

Adjusting and being better and creating hypotheses that can be considered as trial

and error. These players are creative; a collective intelligence. In order to find out more

about this, an official forum of the game “World of Warcraft” has been analyzed by

Steinkuehler (2008). The discussion on the forum focuses on the skillset of a particular

character class in “World of Warcraft”.

Almost 2,000 posts by 1,087 players have been analyzed and categorized based

on different codes or forms of scientific research, and their direct application to problem

solving in-game. A large 86 percent of the posts build “social knowledge construction” or

“the collective development of understanding (Steinkuehler, 2008, pp. 534). It involves

different ways such as sharing ideas and using counterarguments against these ideas,

using evidence to prove arguments, offering alternative solutions for the evidence shared

by the others and bringing in evidence from outside sources. Steinkuehler then concludes

that game forums provide rich examples of scientific discussion.

The discussions are collective, with a lot of players communicating and

collaborating with each other in order to solve in-game problems, which promotes

scientific habits and problem solving. Now one of the biggest concerns is how to avoid
 28

over-using these new technologies. Although it promotes problem solving and scientific

habits, over-usage of these games may lead to other negative effects.

According to Takeuchi (2016), more hours of gaming for children is linked to

lower verbal IQ and other negative changes in the brain’s white matter, which actively

affects learning and other brain functions. They gathered data on 240 Japanese grade four

children and younger (ranging 6-18 years old; average of 12 years old) and ranked their

video game play from 0 to 4 hours.

But contrary to this study is the one by Posso (2016) of Royal Melbourne Institute

of Technology (RMIT) which stated that teenagers who play video games are more likely

to get better grades at school. Posso acquired data from the Program for International

Student Assessment (PISA) to analyze the online habits of 12,000 Australian 15-year-

olds. Then he compared the data from their academic results. According to Posso’s

statement on News Limited, Students who play online games almost every day received a

score of 17 points above the average in Science and 15 points above the average in

Mathematics. Posso also said that online gaming could help young people develop

problem solving skills.

Another study which proves that video games could be a helpful tool for the

development of problem solving skills is the study of Adachi and Willoughby (2013)

which concludes that the more the adolescents reported playing strategy video games, the

more increase in improvements in their self-reported problem-solving skills. The 1492

Canadian grade 9 to 12 adolescents from Ontario, Canada were asked what games they

play. The choices include role-playing, strategy (combined as strategic), fighting, action

and racing (combined as fast-paced) video games.

 29

A second measure was used on grade 11 to 12 students where they are asked on a

five-point frequency scale for each game genre. The participants were then asked for self-

report on a five-point scale for their problem solving skills and another five-point scale to

report their typical school grades for their academic performance. The data gathering

process were conducted each year for four years.

Synthesis

Video games are any kind of game that can be played through the means of an

audio-visual apparatus, which could be any kind of console, a computer or even a phone.

When utilizing video games, it is possible to promote learning as the player is exercising

the necessary skills to master the game and eventually, the game throws another

challenging task to ensue learning to the player.

This could be explained by Edward Thorndike’s law of exercise by which

learning is improved through repetition and feedback. As video games become more and

more common to the world, its possible effects also become an area of concern. Although

there are already a number of researches which suggest that video games produces

negative effects, the possibility that it could cause positive effects cannot be ignored.,

such as its effects to decision-making and problem solving skills.

Decision-making is a skill to define a problem, select between alternatives,

identify the risk and magnitudes for each alternative, selection of an alternative, and

lastly, evaluating the circumstances and this particular skill can also be taught to

adolescents.

There must be an interactive relationship between the player and the video game.

Therefore, decision-making occurs every time a player plays video games. Furthermore,
 30

there are studies that imply that decision-making is linked to video gaming such as the

cortical thickness of the DLPFC and the reduced cognitive biases.

Problem solving is a process which an individual undergoes when identifying and

solving a problem. So it is a given fact that the process could only be accessed in a

presence of a problem. One of the many possible factors that could affect problem

solving skills is the difficulty of each problem being analyzed and solved. A problem’s

difficulty depends on the solver’s knowledge and experience. This could mean that if a

problem’s difficulty is not sufficient enough to challenge the individual’s knowledge and

experience; it may not initiate the problem solving process. Thus, problem solving skills

may not be exercised or improved.

As this study focuses on the possibility that video games might improve problem

solving skills, the possible impact of a problem’s difficulty to problem solving skills

might also be applied to playing video games as problem solving could be considered

central to all genres of video games because of the in-game puzzles which could provide

a range of difficulties. These puzzles require analyzation and memorization from the

player in order to be solved. Theoretically, the difficulty of the problems provided by

video games could generate a problem solving effort which in turn, may improve

problem solving skills.

Another factor that could affect problem solving skills in terms of playing video

games is the genres that are being played. Specific genres such as puzzle games could

improve higher-order executive function skills, which include problem solving skills. Oei

and Patterson (2014) found that the puzzle game “Cut the Rope” is the only one that

produces an effect on higher-order executive function skills while the shooting game
 31

“Modern Combat,” arcade-style “Fruit Ninja,” and the strategy game “StarFront

Collision,” did not produce any effect.

 32

METHODOLOGY

This chapter includes the research design, the participants, the sampling technique

used, research locale, data gathering procedures, and statistical tool. This specific chapter

discusses the process that this study had undergone to obtain its results.

Research Design

The study determined the level of decision-making and problem solving skills and

identified the relationship of the Gamer’s Profile to the variability of the respondents’

decision-making and problem solving skills.

The researchers utilized the descriptive-correlational research design in this study.

A descriptive research design is used to describe the data and characteristics about what

is being studied and a correlational study is a quantitative method of research in which

you have two or more quantitative variables from the same group of subjects. It helps

determine if there is a covariation between the selected variables.

Bearing this in mind, the researchers used the descriptive-correlational research

design to determine the level of decision-making and problem solving skills of the

respondents and if there is a significant relationship between the Gamer’s Profile to the

decision-making and problem solving skills of the respondents.

Hypotheses

In the light of the problems presented, the researchers have come up with these

null hypotheses:

H01: There is no significant relationship between the Gamer’s Profile and the decision-

making skills of the adolescents in Cavite National High School.

 33

H02: There is no significant relationship between the Gamer’s Profile and the problem

solving skills of the adolescents in Cavite National High School.

Sources of Data

The target samples of the study were the adolescents that actively playing video

games in Cavite National High School. The primary sources of data were gathered using

Gamer’s Profile, Making Decisions in Everyday Life, and Solving Problems Survey

scales.

The secondary sources of data were the related literatures that the researchers

gathered in order to support the notion that the Gamer’s Profile will have a significant

relationship to the decision-making and problem solving skills of the respondents.

Participants of the Study

The participants of the study were the selected adolescents (12 to 18 years old)

and active video game players in Cavite National High School. The researchers gathered

178 respondents for their study. Originally, there were 200 respondents gathered but, the

researchers excluded 22 of the respondents because of their incomplete answers in their

scale. The participants of the study were the adolescents is because according to a survey

by the Asian Institute of Journalism and Communication, an average of 77 percent or

nearly 8 out of 10 teenagers plays video games in the Philippines, with Luzon, reporting

the highest number of gamers (Benigno, 2014). It implies that there is a need to

understand video game playing both of its positive and negative effects.

Sampling Technique

The researchers used purposive and convenience sampling technique in the study

because the researchers established criteria that the adolescents must possess in order to
 34

be selected as respondents of the study namely: an active video game player and age

ranging from 12 to 18 years old. Furthermore, the researchers used convenience sampling

technique because there was no available census pertaining to the population of active

adolescent video game players in Cavite National High School.

The researchers went to Cavite National High School. Subsequently, the

researchers gathered the respondents by roaming the school grounds then employed

purposive and convenience sampling technique by asking who met the criteria that were

needed in order to be selected as the respondents of the study.

Data Gathering Procedure

The researchers conducted the data gathering procedure on February 2017 in

Cavite National High School.

Initially, the researchers sent letters (i.e. letter of consent) to the corresponding

authorities in order to receive the permission to conduct the study. Upon the approval of

the authorities, the researchers used purposive and convenience sampling technique by

roaming around in school grounds and asked the students if they meet the criteria

established by the researchers and if they are willing to be the respondents of the study.

Then the researchers provided a letter of consent to each respondent to gain their

permission and state the benefits it may provide to them.

Afterward, the researchers administered the Gamer’s Profile to the respondents.

Subsequently, the researchers administered the Making Decisions in Everyday Life and

Solving Problems Survey scales to measure decision-making and problem solving skills

of the respondents. The assistance was provided by the researchers when the respondents

needed it while answering the survey questionnaires.

 35

Lastly, after the researchers gathered the survey results, the researchers identified

the relationship between the Gamer’s Profile of the respondents to their decision-making,

and problem solving skills. The data was tallied, examined, and interpreted by particular

objectives set forth.

 36

Send letters to the corresponding authorities.

Use purposive and convenience sampling

technique.

Provide letter of consent to the respondents.

Administration of Gamer's Profile, Making

Decisions in Everyday Life and
Solving Problems Survey scales.

Gathering of survey results

Data analysis

Figure 2. Data gathering flow chart

 37

Research Instrument

The following instruments were used in the study to identify the estimated

number of hours spent playing video games per week, the academic level when they

started playing video games continuously and the most preferred genre of video games of

the respondents and to measure their decision-making and problem solving skills.

Gamer’s Profile. The researchers prepared a survey questionnaire to determine

the estimated time spent playing video games per week, the academic level when the

respondents started playing video games continuously and their most preferred genre of

video games. The amount of time spent playing video games was adopted from Kowert

(2015). She categorized the play frequency into weeks in order to avoid inaccurate

reporting of the amount of video game playing sessions and the length of those sessions.

While the academic level when the respondents started playing video games

continuously was adopted from the study of Gackenbach and Brown (2011) Video Game

History Questionnaire. Gackenbach and Brown (2011) divided the academic level

brackets based on each school level; primary school (Kinder to Grade 3), intermediate

school (Grades 4 to 6), junior high school (Grades 7 to 9) and senior high school (Grades

10 to 12).

Lastly, the genre of the games was adopted from Lee, Karlova, Clarke, Thornton,

and Perti (2014) from their ten chosen foci of gameplay.

Making Decisions in Everyday Life. The scale was developed by Perkins D., and

Mincemoyer, C. Making decisions in Everyday Life is a 20-item scale that measures an

adolescent’s (12 to 18 years old) decision-making skills. The instrument assesses

adolescents’ decision-making skill by analyzing the frequency of practice of the

 38

following skills that are required to employ thorough decision-making: defining the

problem (items 1 to 4), identifying alternatives (items 5 to 8), identifying risks and

consequences (items 9 to 12), selecting an alternative (items 13 to 16) and evaluation

(items 17 to 20).

Validity and Reliability .The instrument underwent content and convergent

validity (Duerden, Fernandez, Bryant, Witt & Theriault, 2012). Along with other

measures that assess the life skills of the adolescents such as the Solving Problems

Survey scale (Duerden et al., 2012), the study showed mild to strong positive correlations

provides evidence of concurrent validity. The Making Decisions in Everyday Life scale

have an internal consistency of .91 Cronbach’s Alpha (Duerden et al., 2012).

Furthermore, the researchers translated the items in the scale into Filipino in the

Making Decisions in Everyday Life scale. Afterward, the researchers seek the aid of three

professionals to establish face and content validity. The three validators helped the

researchers to establish the validity of the scale by suggesting revising some items to

become more applicable for the Filipino adolescents.

To establish local reliability, the researchers conducted a pilot test with 50

adolescents in Cavite City, Cavite which produced an internal consistency of .88

Cronbach’s alpha and was accepted by the researchers because it exceeded the minimum

threshold of .70 Cronbach’s alpha, which according to Nunnally (1978) that a Cronbach’s

alpha that is equal or greater than .70 is acceptable.

Scoring and Interpretation. The scale consists of 20 statements with five-point

Likert-scale namely: 1 = never, 2 = rarely, 3 = sometimes, 4 = often, and 5 = always.

 39

Scores range from 20 to 100. The results can be taken by summing the item ratings

together. Higher scores indicate greater decision-making skills.

Furthermore, the data gathered by the researchers were normal, which is why

researchers categorized the data scores using mean and sample standard deviation. The

researchers have come up with five categories namely: high average, above average,

average, low average and below average in order to categorize the scores of the

respondents.

Table 1. Categorized score range of making decisions in everyday life scale.

SCORE RANGE LEVEL
20 – 59 Below Average
60 – 70 Low Average
71 – 81 Average
82 – 92 Above Average
93 – Above High Average

Table 1 shows the categorized scores of the respondents in Making Decisions in

Everyday Life scale using the mean and the sample standard deviation from the raw data

obtained by the researchers.

 40

Table 2. Interpretation of the levels in Making Decisions in Everyday Life scale.

LEVEL INTERPRETATION
Below Average Individuals who fall under in this level have minimal foresight. They
don't consider the outcomes of their activities before they accomplish
something. Thus, they make snap judgments when it comes to making
decisions.
Low Average Individuals that belong in this level have decision-making skills that
are not fully matured yet. They are not objective enough, and they rely
too much on luck, instinct or timing to make reliable decisions.

Average Individuals that fall under in level have a good understanding of the
basics regarding the five steps in a decision-making process, namely:
defining the problem, identifying the alternatives, identifying risks and
consequences, selecting an alternative and lastly, evaluation of the
whole process.
Above Average Individuals with this level of decision-making skills know how to set
up the process and generate lots of potential solutions. From there, they
analyze the options carefully, and they make the best decisions possible
based on what they know.
High Average Those who belong in this level are able to retrieve courses of action
based on situation or action matching rules, self-diagnose their
performance, identify weaknesses in their knowledge and processes,
and correct them.

Table 2 shows the interpretation of the levels of decision-making skills

established by the researchers to categorize the decision-making skills scores of the

respondents in their study.

Individuals with below average level of decision-making tend to make poorly

informed decisions. Subsequently, they make snap judgments when it comes to making

decisions. Thus, short term gratification is the only thing that matters to them (Potton,

2012).
 41

According to MindTools (2013), those with low level of decision-making skills

tend to depend excessively on luck, impulse or timing to make reliable decisions. Thus,

individuals who have low average decision-making skills are not objective when they

have to make decisions.

Average level decision-makers have a good comprehension of the basics

pertaining to the five steps in a decision-making process, namely: defining the problem,

identifying the alternatives, identifying risks and consequences, selecting an alternative

and lastly, evaluation of the whole process (MindTools, 2013).

According to MindTools (2013), individuals with above average level of

decision-making skills know how to set up the process and generate lots of potential

solutions. From that point, they investigate the alternatives precisely, and they settle on

the most ideal choices in view of what they know. As they gain more and more

experience, they use that information to evaluate their decisions and continue to build on

their decision-making success.

According to Rosen, Salas, Lyons and Fiore (2008), individuals that have high

level of decision-making skills retrieve courses of action based on situation or action

matching rules, self-diagnose their performance, identify weaknesses in their knowledge

and processes, and correct them. Furthermore, they create deeper, more conceptual, more

functional, and more abstracted situation representations. Moreover, they anticipate what

information will be needed in the decision making. Subsequently, they judge the

consistency, reliability, and completeness of their information. Lastly, they evaluate their

understanding of a situation.
 42

Solving Problems Survey. The scale was developed by Barkman S. and

Machtmes, K. (2002). Solving Problems Survey is a 24-item scale that assesses the

adolescents’ (12 to 18 years old) problem solving skills by analyzing the frequency of use

of the several skills that are required to engage in problem solving: identify/define

problems (items 1 to 4), analyze possible causes or assumptions (items 5 to 8), identify

the possible solutions (items 9 to 12), select best solutions (items 13 to 16), implement

solution (items 17 to 20), and evaluate progress and revise as needed (items 21 to 24).

Validity and Reliability. The scale had undergone content and convergent validity

(Duerdent et al., 2012). Along with other measures that assess the life skills of the

adolescents such as the Making Decisions in Everyday Life scale (Duerden et al., 2012),

the study showed mild to strong positive correlations provides evidence of concurrent

validity. The Making Decisions in Everyday Life scale has an internal consistency of .88

Cronbach’s Alpha (Duerden et al., 2012).

Furthermore, the researchers translated the items of Solving Problems Survey

scale into Filipino. Subsequently, the researchers seek the aid of three professionals to

establish face and content validity. The three validators helped the researchers to

establish the validity of the scale by suggesting revising some items to become more

applicable for the Filipino adolescents.

To establish local reliability, the researchers conducted a pilot test with 50

adolescents in Cavite City, Cavite which produced an internal consistency of .81

Cronbach’s alpha and was accepted by the researchers because it exceeded the minimum

threshold of .70 Cronbach’s alpha, which according to Nunnally (1978) that a Cronbach’s

alpha that is equal or greater than .70 is acceptable.

 43

Scoring and Interpretation. The scale consists of 24 statements with a five-point

Likert-scale: never = 1, rarely = 2, sometimes = 3, often = 4, and always = 5. Items: 5, 9

15, 17, 20 and 22 will be reversed scored when getting the results (5 = never to 1 =

always). All other items will be scored by summing item ratings together. The score

ranges from 24 to 120. Higher scores indicate greater skill at problem solving.

Furthermore, the data gathered by the researchers were normal, which is why

researchers categorized the data scores using mean and sample standard deviation. The

researchers have come up with five categories namely: high average, above average,

average, low average and below average in order to categorize the scores of the

respondents.

Table 3. Categorized score range of Solving Problems Survey scale.

SCORE RANGE LEVEL
24 – 72 Below Average
73 – 82 Low Average
83 – 92 Average
93 – 102 Above Average
103 – Above High Average

Table 3 shows the categorized scores of the respondents in Solving Problems

Survey scale using the mean and the sample standard deviation from the raw data

obtained by the researchers.

 44

Table 4. Interpretation of the levels in Solving Problems Survey scale.

LEVEL INTERPRETATION
Below Average Individuals that belong at this level tend to have emotional problems and
are unable to get along well with others. They are having trouble
introducing themselves and lack assertiveness. They are also having
difficulties living up to their responsibilities and might have a consistently
poor academic performance.
Low Average Those who belong to this level tend to view problems as negatives, instead
of seeing it as opportunities to make beneficial changes. Their approach to
problem solving is more intuitive than systematic.

Average The individuals who fall under this level understands what they should do
about the problem and understands the importance of having a structured
problem process. However, they still lack consistency following this
process.
Above Average Those who are under this level are confident problem solvers.
Approaching the problems systematically gives them good ideas. They
take time to understand the problem and the criteria for a good decision. In
turn, it is well thought out and well executed.

High Average Those individuals that belong to this level know when to do a systematic
and complex thinking when identifying problems. In turn, they come up
with productive ways on how to solve it. They usually have alternatives at
the ready when initial solution does not work and can ask for advice when
needed.

Table 4 shows the interpretation of the levels of problem solving skills established

by the researchers to categorize the problem solving skills scores of the respondents in

their study.

According to Bean (2015), individuals that belong at the level “low” may tend to

have emotional problems. They can’t easily figure out how to deal with their emotions.

Furthermore, she stated that those who fall under this level are unable to get along well

with others, specifically people with their own age. They don’t know how to introduce
 45

themselves to someone, how to be assertive. Lastly, those individuals that belong to this

level are having troubles to meet their responsibilities. They might consistently have a

poor academic performance, refuse to do chores and talk out of turn in class or talk back

to teachers.

According to MindTools (2013), those who belong in the “below average” level

tend to view problems as negatives, instead of seeing it as opportunities to make

beneficial changes. The approach of people who fall under this level to problem solving

is more intuitive than systematic.

The individuals who fall under the “average” level understand what they should

do about the problem, and they understand the importance of having a structured problem

process. However, following this process still lacks consistency among the individuals

who fall under this level (MindTools, 2013).

According to MindTools (2013), those who are under the “above average” level

are confident problem solvers. They generate good ideas because they approach problems

systematically. These individuals take time to understand the problem and the criteria for

a good decision. In turn, it is well thought out and well executed.

According to Rad (2013), those individuals that belong to the level “high” knows

when to do a systematic and complex thinking and when to go through shortcuts and find

an easy solution and are able to identify the specific problem that they are facing. Lastly,

they see more than one solution to a problem and find new and productive ways to deal

with new problems as they arise and also have a backup plan if the first solution does not

work and can ask for support and advice when needed.
 46

Statistical Treatment of Data

The researcher utilized the following statistical tools to help them organize and

interpret the data obtained from the procedures.

Frequency - it is the number of times the data values occur. In the study, it was used to

compute the percentage of data regarding Gamer’s Profile of the respondents and their

level of decision-making and problem solving skills.

Percentage - a percentage is another way of expressing a proportion. A percentage is

equal to the proportion times 100. In the study, the percentage was used to provide the

percentage of the samples in each category in the Gamer’s Profile and the percentage in

each category that they belonged into based on their results of decision-making and

problem solving skills.

Formula:

% = (f/n) / 100

Whereas,

f = frequency

n = total population

Mean - it is the quantity obtained by summing two or more numbers or variables and

then dividing by the number of numbers or variables. In the study, the researchers used

the mean when they were categorizing the sum of the responses of the respondents.

Furthermore, the mean was computed to itemize each Likert-item in the scale that was

used.

Formula:
 47

Whereas,

x = number of frequency

Σ = summation of x

N = total population

Sample Standard Deviation - is a measure that is used to quantify the amount of

variation or dispersion of a set of data values. Specifically, the sample standard deviation

was used in order to categorize the scores of the respondents in Making Decisions in

Everyday Life and Solving Problems Survey scales.

Formula:

Whereas,

s = sample standard deviation

∑ = sum of x and 𝑥̅

x = each value of dataset

𝑥̅ = sample mean

n = number of scores in a sample

Chi-square Test of Independence - Chi-square test of independence was used to

determine the relationship of gamer’s profile to the decision-making and problem solving

skills of the respondents. Specifically, it was used to answer the fourth and fifth statement

of the problem of the study.

 48

Formula:

Whereas,

X2 = Chi-square value

∑ = summation

O = observed score

E = expected score
 49

RESULTS AND DISCUSSION

This chapter has overseen the presentation, analysis and interpretation of data

gathered by the researchers. The study aims to discover if there is a relationship between

the respondents’ Gamer’s Profile to their decision-making and problem solving skills.

Present data were studied and documents were examined to answer the questions

communicated in the statement of the problem. The analytical procedures are arranged

according to the sequence of specific questions.

Table 5. Frequency and percentage distribution of the respondents according to their

estimated number of hours spent playing video games per week
NUMBER OF HOURS FREQUENCY PERCENTAGE
(f) (%)
1 – 5 hours per week 122 68.5
6 – 10 hours per week 34 19.1
10 – 20 hours per week 12 6.7
20+ hours per week 10 5.6
TOTAL 178 100

Table 5 shows the respondents’ estimated number of hours spent playing video

games per week. According to the data gathered, the range “1 to 5 hours per week” has

the highest frequency of 122 respondents (68.5%), while range “6 to 10 hours per week”

has a frequency of 34 respondents (19.1%) and range “10 to 20 hours per week” having a

frequency of 12 respondents (6.7%) and lastly, the range “20+ hours per week” with the

lowest frequency of 10 respondents (5.6%).

The finding was not in line with the result of Kowert (2013) where the majority of

her participants of her study were from United States and United Kingdom. The result of

her study found out that “6 to 10 hours per week” playing video games has the highest
 50

percentage (11.7 %) excluding the percentage of the non-video game players in her study.

Since the culture of tingi-tingi is prevalent among Filipinos (Danganan, 2013), it might

be possible to explain why the most reported estimated number of hours spent playing

video games is the category “1 to 5 hours per week” is because the respondents in this

study are adolescent Filipinos. Tingi-tingi is the practice of selling and buying goods in

amount less than smallest retail packaging (Veneracion, 2013). This culture could still be

present when it comes to video game playing. According to the study of Patria (2012), 88

percent of high school students are motivated to save money in order to purchase

computer-related products or services. Since high school students only save a very small

amount of their pocket money because they only get an average of P157.60 allowance per

week (Patria, 2012), they tend to go to cyber cafés in order to play video games for a few

hours.

The result may implicate that the availability of resources that the respondents

possess such as their allowance that they receive might be one of the factors why the

category “1 to 5 hours per week” has the highest frequency. It could be because they

want to play immediately rather than to save a bigger amount of money in order to play

video games for long hours. Thus, the culture of tingi-tingi might still be present among

the respondents of the study.

 51

Table 6. Frequency and percentage distribution of the respondents according to

their academic level when they started playing video games continuously
ACADEMIC LEVEL FREQUENCY PERCENTAGE
(f) (%)
Before Kindergarten 8 4.5
Kindergarten – grade 3 26 14.6
Grade 4 – 6 101 55.7
Grade 7 – 9 40 22.5
Grade 10 – 12 3 1.7
TOTAL 178 100

Table 6 shows that the “grades 4 to 6” has the highest frequency of 101 (55.7%),

followed by “grades 7 to 9” which has a frequency of 40 (22.5%), “kindergarten to grade

3” with a frequency of 26 (14.6%), “before kindergarten” with a frequency of 8 (4.5%)

and lastly, “grades 10 to 12” has the lowest frequency of 3 (1.7%).

A number of researches could explain some of the factors that might be causing

the prevalence of video game play among grades 4 to 6. One of these factors could be the

efficiency of video games as a tool for connecting or structuring time spent with friends.

According to Ito & Bittani (2009), playing video games are the evolution of the role

played by other casual activities such as board games or bowling to children. Another

factor is that video games could be topical for casual conversation among young

adolescents as according to the findings of Olson, Cutner, & Warner (2008), most of the

adolescent boys in their focus group agrees that video games are a frequent topic of

conversation among their peers. In turn, these topics might fuel encouragement to play

video games among these peers. Also according to Trotter (2011), media influences and

popular culture strongly affects the peer activities of children usually aging from 8 to 11.
 52

This implies that aside from enjoyment, the inclination of fourth to sixth graders

to video games could also be influenced by their ways of connecting to their peers as

right now; video games could also serve as an interesting way of children to connect with

their friends and could also be an interesting topic of conversation. Additionally, the

increasing effect of media to the children’s peer activities could also be a factor why they

are encouraged to play. Considering that video games are one of the leading sources of

entertainment today with more than 1.2 billion users worldwide according to Spil Games

(2013), it is also possible that as media influences affect children’s peer activities, a child

who is playing video games might influence other children in his circle of friends.

Table 7. Frequency and percentage distribution of the respondents according to

their most preferred genre of video games
GENRE FREQUENCY PERCENTAGE
(f) (%)
Action 13 7.3
Action – adventure 18 10.1
Driving 6 3.4
Fighting 17 9.6
Puzzle 36 20.2
Role-playing 9 5.1
Shooter 22 12.4
Sports 21 11.8
Simulation 10 5.6
Strategy 26 14.6
TOTAL 178 100

Table 7 shows the most preferred genres of video games of the respondents.

According to the table, “puzzle” games has the highest frequency of 36 (20.2 %),

followed by “strategy” games which have a frequency of 26 (14.6%), and then “shooter”
 53

games which has a frequency of 22 (12.4 %), “sports” games with a frequency of 21

(11.8%), “action – adventure” games with a frequency of 18 (10.1%), “fighting” games

with a frequency of 17 (9.6 %), “action” games with a frequency of 13 (7.3%),

“simulation” games with a frequency of 10 (5.6 %), “role-playing” games with a

frequency of 9 (5.1%) and lastly, “driving/racing games” which has the lowest frequency

of 6 (3.4%).

The results were aligned to the recent statistics of Entertainment Software

Association (2016) which states that puzzle games were one of the highest ranking games

played on wireless or mobile devices. Puzzle video games are games with an objective of

figuring out the solution by solving enigmas, navigating, and manipulating and

reconfiguring objects and usually only takes a small amount of time to understand the

rules and mechanics of the gameplay (Wolf, 2001). Unlike any other genres such as role-

playing video games where the player must explore and progress throughout the game in

order to access the full extent of that video game, the majority of puzzle video games

consumes less time than any other genre of video games because there is no progressive

storyline or development of character to pursue (Adams, 2014).

Most of the respondents prefer to play puzzle games maybe because the rules are

simple, easy to follow and most importantly it consumes less time, unlike any other

genres where the player must ingest the mechanics, rules and explore various world or

stage in the game in order to access the full extent of the game. It implies that the

respondents play puzzle video games maybe because it fits their current available

resources since puzzle video games only take less time than other genre of video games.

Therefore, the respondents might have thought that if they play puzzle video games they
 54

would spend less money to spend in cyber cafés. Thus, playing puzzle games would still

fulfill their need to play video games while still spend less money on cyber cafés.

Table 8. Frequency and percentage distribution of the respondents according to

their level of decision-making skills.
LEVEL OF DECISION-MAKING FREQUENCY PERCENTAGE
SKILLS (f) (%)
Below Average 28 15.7
Low Average 54 30.3
Average 65 36.5
Above Average 28 15.7
High Average 3 1.7
TOTAL 178 100

Table 8 shows the frequency and percentage of level of decision-making skills of

the respondents in making decisions in everyday life scale. According to the table, the

level “average” has the highest frequency of 65 (36.5%), followed by “low average” with

a frequency of 54 (30.3%), while both “below average” and “above average” has a

frequency of 28 (15.7%), for “below average”, as for “above average”. Lastly, the “high

average” has the lowest frequency of 3 (1.7%).

Although the highest frequencies of respondents fall under “average” level, there

are still many of the decision-making skills scores belonged to “low average” level than

to “above average” and “high average” levels. The result could be explained by the

statement of Talukder (2013), where she stated that the brain of an adolescent is not yet

fully developed to make good decisions as adults can. Specifically, she stated that the

amygdala of the adolescents is more active than the adults. The amygdala is involved in

several functions of the body including arousal, autonomic responses associated with

fear, emotional responses, hormonal secretions and memory (Bailey, 2017).

 55

The result implicates that since many of the respondents have low average

decision-making skills, the amygdala could play a role in their decision-making skills.

Maybe they experience difficulty in making decisions because of their higher activity in

their amygdala. Since one of the functions of the amygdala is emotional responses, it

might be that the respondents were having difficulty in making decisions is because they

tend to become more emotional that may lead to being subjective rather than being

objective decision-makers.

Table 9. Frequency and percentage distribution of the respondents according to their

level of problem solving skills.
LEVEL OF PROBLEM SOLVING FREQUENCY PERCENTAGE
SKILLS (f) (%)
Below Average 28 15.7
Low Average 60 33.7
Average 61 34.3
Above Average 24 13.5
High Average 5 2.8
TOTAL 178 100

Table 9 shows the frequency and percentage of level of problem solving skills of

the respondents in solving problems survey scale. According to the table, the level

“average” has the highest frequency of 61 (34.3%), followed by “low average” with a

frequency of 60 (33.7%), “below average” with a frequency of 28 (15.7%), and then

“above average” with a frequency of 24 (13.5%). Lastly, the “high average” has the

lowest frequency of 5 (2.8%).

The findings were identical to that of the study of Sumitha & Jose (2016).

According to the findings of their analyzation of 100 early adolescent respondents, 68

 56

percent of the respondents have medium problem solving skill, while 15 percent of it

have high and 17 percent have low problem solving skills.

The results might imply that the activity in the adolescents’ frontal lobe might

have been affected their problem solving skills in which according to Talukder (2013),

lower than the frontal lobe’s activity of adults. The frontal lobe according to (Bailey,

2016) is responsible for movement, decision-making, planning and problem solving of

adolescents. Thus, being affected by their frontal lobe’s activity, the problem solving

skills of the adolescents might be lower than adults.

 57

Table 10. Making Decisions in Everyday Life scale itemization

ITEMS MEAN QD
1.) I can easily identify my problem. 3.24 Ss
Madali kong natutukoy ang aking problema.
2.) I think about my problem before I take action. 3.80 O
Pinag-iisipan ko ang aking problema bago ako kumilos.
3.) I look for information to help me understand the problem. 3.60 O
Naghahanap ako ng impormasyon upang matulungan o intindihin ang
problema.
4.) I ask others to help me understand my problem. 3.43 Ss
Nagpapatulong ako sa iba upang maintindihan ko ang aking problema.
5.) I think about ways of dealing with my problem. 3.84 O
Nag-iisip ako ng mga paraan para harapin ko ang aking problema.
6. I think before making a choice 4.06 O
Nag-iisip muna ako bago ako pumili 3.52 O
7.) I discuss choices with my friends before making a decision.
Tinatalakay ko muna ang mga solusyong maaaring pagpipilian sa aking mga
kaibigan bago ako gumawa ng desisyon.
8.) I discuss choices with my parents before making a decision. 3.42 Ss
Tinatalakay ko muna sa aking mga magulang ang mga solusyong maaaring
pagpipilian bago ako gumawa ng desisyon.
9.) I look for the positive side of the options I have. 3.67 O
Naghahanap ako ng mga positibong katangian sa aking mga posibleng
pagpipilian.
10.) I look for the negative side of the options I have. 3.01 Ss
Naghahanap ako ng mga negatibong katangian sa aking mga posibleng
pagpipilian.
11.) I consider the risks of a choice before making a decision. 3.76 O
Isinasaalang-alang ko muna ang mga nakataya sa bawat pagpipilian bago ako
gumawa ng desisyon.

12.) I consider the benefits of a choice before making a decision. 3.62 O

Isinasaalang-alang ko muna ang mga pakinabang ng bawat pagpipilian bago
ako gumawa ng desisyon.
 58

Table 10. Continued.

3.) I make decisions based on what my parents tell me. 3.70 O
Gumagawa ako ng desisyon batay sa payo ng aking mga magulang.
14.) When faced with a problem, I realize that some choices are better than 3.63 O
others.
Kapag may kinakaharap na problema, aking napagtatanto na may mga
pagpipiliang mas mabuti kaysa sa iba.
15.) I decide by considering all the information I have about different choices. 3.37 Ss
Gumagawa ako ng desisyon sa pamamagitan ng pagsusuri ng mga
impormasyon na mayroon ako patungkol sa ibat ibang pagpipilian.
16.) I prioritize my choices before making a decision. Binibigyan ko ng 3.69 O
prayoridad ang aking mga pinagpipilian bago ako gumawa ng desisyon.
17.) Before making another decision, I think about how the last one turned out. 3.51 O
Bago ako gumawa ng desisyon, inaalala ko muna ang naging resulta ng aking
nakaraang pagdedesisyon.
18.) I do think of past choices when making new decisions. 3.65 O
Inaalala ko ang mga nakaraan kong pinagpilian bago ako gumawa ng
panibagong desisyon.
19.) If I experience negative consequences, I change my decision the next time. 3.74 O
Kapag nakaranas ako ng negatibong resulta, babaguhin ko ang aking desisyon
sa susunod.
20.) Decision-making is easy for me. 2.90 Ss
Ang pag dedesisyon ay madali lang para sa akin.
Legend: Qualitative Description (QD) of the computed mean:

4.50-5.00= Always (A)

3.50-4.49= Often (O)
2.50-3.49= Sometimes (Ss)
1.50-2.49= Rarely (R)
1.00-1.49= Never (Nr)

Table 10 shows the itemization of Making Decisions in Everyday Life scale. “I

think before making a choice” (item six) has the highest mean score (4.06) in the whole

scale while “Decision-making is easy for me” (item 20) have the lowest (2.90) mean

score.
 59

The result of item six and item 20 is aligned with the concept of Erik Erikson’s

“identity cohesion versus identity confusion”. According to Schultz and Schultz (2010),

this is the period where adolescents (12 to 18 years old) go through various

experimentations of ideologies to determine the most compatible fit for their roles and the

identities that they want to cultivate. Furthermore, they stated that making decisions is

very difficult for the adolescents during this period because they face numerous choices

in their lives and that is why in this period adolescents tend to become anxious.

The result may implicate why item six has the highest mean score is because the

respondent might be spending a lot of time making choices since they are in the period of

“identity cohesion vs. identity confusion, where they experiment various choices in their

lives in order to develop their own identity. On the other hand, maybe the reason why

item 20 received the lowest mean score is because they feel anxious when making

decisions from the many choices that they have to make in order for them to build their

own identities.
 60

Table 11. Solving Problems Survey scale itemization

ITEMS MEAN QD
1) When I have a problem, I first figure out exactly what the problem is. 3.81 O
Kapag ako ay may problema, inaalam ko muna kung ano ang talagang
problema.
2.) I try to get all the facts before trying to solve a problem. 3.76 O
Sinusubukan ko munang alamin ang lahat ng katunayan bago ko subukang
lutasin ang problema.
3.) When I have a problem, I look at what is really happening and what 3.84 O
should be done.
Kapag ako ay may problema, tinitingnan ko ang nangyayari at kung ano
ang dapat mangyari.
4.) As much as possible, I try to prevent problems before they happen. 3.69 O
Hangga’t maaari, iniiwasan ko ang magkaroon ng problema bago pa ito
mangyari.
5.) When faced with a problem, I wait to see if it will go away. 2.98 Ss
Kapag may kinakaharap akong problema, naghihintay ako kung ito ba ay
mawawala.
6.) I look at a problem from many different viewpoints. 3.58 O
Tinitignan ko ang aking problema mula sa iba’t ibang pananaw.
7.) I keep an open mind about what caused a problem. 3.73 O
Pinapanatili kong bukas ang aking isipan tungkol sa mga bagay na naging
sanhi ng aking problema.
8.) When faced with a problem, I try to determine what caused it. 3.80 O
Kapag may kinakaharap akong problema, sinusubukan kong alamin ang
naging sanhi nito.
9.) When solving a problem, I do the first thing that comes into my head. 2.58 Ss
Kapag may nilulutas akong problema, ginagawa ko agad ang unang
pumapasok sa isip ko.
10.) I look at the likely results for each possible solution. 3.84 O
Tinitingnan ko ang mga maaaring maging resulta sa bawat posibleng
solusyon.
11.) When solving a problem, I look at all possible solutions. 3.58 O
Kapag may nilulutas na problema, tinitingnan ko ang lahat ng posibleng
solusyon.
12.) When I have a problem, I do what worked for me in the past to solve it. 3.62 O
Kapag may problema ako, ginagawa ko ang mga bagay na ginawa ko sa
nakaraan upang malutas ito.
 61

Table 11. Continued.

13.) I try to look at the long term results of each possible solution. 3.52 O
Sinusubukan kong tingnan ang mga pangmatagalang resulta ng bawat
posibleng solusyon.
14.) When comparing solutions, I look how each solution will affect the 3.67 O
people involved.
Kapag ako ay nagkukumpara ng mga solusyon tinitignan ko kung paano
makakaapekto ang bawat solusyon sa mga tao.
15.) When I am solving a problem, I choose the easiest solution. 2.40 Sm
Kapag may nilulutas akong problema, pinipili ko ang pinaka madaling
solusyon.
16.) I compare each possible solution with the others to find the best one to 3.54 O
solve my problem.
Kinukumpura ko ang bawat posibleng solusyon upang malaman ko ang
pinakamainam sa paglutas ng aking problema.
17.) After putting my solution into action, I forget about it. 2.92 Ss
Pagkatapos kong isagawa ang aking solusyon, kinakalimutan ko na ito.
18.) After choosing a solution, I put it into action. 3.76 O
Pagkatapos pumili ng solusyon, isinasagawa ko ito.
19.) After selecting a solution, I think about it for a while before I put it into 3.71 O
action.
Pagkatapos kong pumili ng solusyon, pinagiisipan ko muna ito bago ko ito
isagawa.
20.) I tend to doubt my decision after it has been made. 2.53 Ss
Madalas kong pinagdududahan ang aking desisyon pagkatapos nitong
maisagawa.
21.) If my solution is not working, I will try another solution. 3.62 O
Kapag ang aking solusyon ay hindi mabisa, susubok ako ng mga bagong
solusyon.
22.) Once I carry out a solution, I never look back. 2.69 Ss
Matapos kong isagawa ang isang solusyon, hindi ko na ito iniisip pa.
23.) When a solution is not working, I try to figure out what is wrong. 3.68 O
Kapag hindi gumagana ang aking solusyon, sinusubukan kong alamin kung
ano ang naging mali.
24.) Once I have solved a problem, I step back to see how my solution is 3.87 O
working.
Kapag nalutas ko na ang isang problema, sinusuri ko kung mabisa ba ito.
 62

Table 11. Continued

Legend: Qualitative Description (QD) of the computed mean:

4.50-5.00= Always (A)

3.50-4.49= Often (O)
2.50-3.49= Sometimes (Ss)
1.50-2.49= Rarely (Ry)
1.00-1.49= Never (Nr)
4.50-5.00= Always (A)
3.50-4.49= Often (O)
2.50-3.49= Sometimes (Ss)
1.50-2.49= Rarely (Ry)
1.00-1.49= Never (Nr)

Table 11 shows that Item 24 (“Once I have solved a problem, I step back to see

how my solution is working”) which falls under the subscale “evaluate progress and

revise as needed” has the highest mean score of 3.87 in the itemization of the Solving

Problems Survey scale while Item 15 (“When I am solving a problem, I choose the

easiest solution.”) has the lowest mean score of 2.40.

The findings concerning the item that has the highest mean score might explain

the statement of Worell & Danner (1989, P. 3.), in which they said that adolescence is a

time of increased pressure for problem solving and personal decision. Difficulties in

problem solving might be causing adolescents to evaluate their actions as according to

Scott (n.d.), adolescents are called upon to make difficult decisions regarding career,

sexuality, school involvement and risk behaviors.

Given the level of problem solving skills of the respondents, this might implicate

that due to their time of increased pressure for problem solving, the respondents might

have experienced difficulties in solving problems which might have caused them to

evaluate their actions. The findings regarding the item that has the lowest mean score

suggest that the respondents when choosing a solution to a problem do not just choose the

easiest solution. It is aligned to Wolfgang Kohler’s theory “insight learning” in which he

 63

stated that learning a problem’s solution requires a completely cognitive experience that

requires the ability to visualize the problem and the solution internally. By having a clear

understanding of the problem’s situation, the respondents do not just select the easiest

solution to a problem but the one that will be suitable for solving it. This implies that the

respondents do not just choose the easiest solution to a problem. Instead, they visualize

the problem and its possible solutions. However, the likelihood of the problem to be

solved still depends on the situation.

Table 12. Test of relationship between the decision-making skills and estimated number
of hours of playing video games per week
χ2 P-VALUE DECISION SIGNIFICANCE
Chi-square test 23.28 .025* Reject null Significant
hypothesis
*significant at p < 0.05

Table 12 illustrates the results of chi-square test between decision-making skills

and the reported estimated number of hours spent playing video games per week. A

statistically significant relationship χ2 (12, N = 178) = 23.38, p = .025, was found to exist

between these variables. Therefore, the researchers reject the null hypothesis.

This result is consistent with the experiment conducted by Kuhn et al. (2014)

where video gaming hours is correlated with the cortical thickness in the prefrontal cortex

of the brain which is responsible for the executive functions such as decision-making

(DiSalvo, 2014). It might be that the law of exercise might have an impact in the result of

Kuhn et. al. (2014) and this finding, since time on task is the fundamental requirement of

learning and mastery and the law of exercise states that practice, repetition and feedback

must exist together for the best learning results (Murphy, 2011).
 64

The result implicates that although the most reported estimated number of hours

spent playing video games of the respondents are “1 to 5 hours per week” (68.5%) and

the frequencies of the levels preceding the “average” level are much higher than the

levels that are succeeding the “average” level respondents might have obtained higher

level of decision-making skills if they played video games for more than 1 to 5 hours but

being mindful of the over-usage of video games as it may lead to other negative effects

on the adolescents such as lower verbal IQ (Takeuchi, 2016). Bearing this in mind, it

might be really possible for the educators to use video games as an instructional material

by utilizing the law of exercise in terms of video gaming hours.

Table 13. Test of relationship between the level of decision-making skills and the academic
level when the respondents started playing video games continuously
χ2 P-VALUE DECISION SIGNIFICANCE
Chi-square test 27.35 .038* Reject null Significant
hypothesis
*significant at p < 0.05

Table 13 shows the chi-square test result between the decision-making skills and

the academic level when they started playing video games continuously. A statistically

significant relationship χ2 (16, N = 178) = 27.35, p = .038, was found to exist between

these variables. Therefore, the researchers reject the null hypothesis.

This result is consistent with the findings of the study conducted by Hartanto, Toh

and Yang (2016), where the onset age of active gameplay is significantly correlated with

task-switching abilities – one of the many executive functions (Diamond, 2012). Since

decision-making is one of the executive functions (DiSalvo, 2014), it may be that the

players have started playing video games continuously during their high cognitive

plasticity. According to Greenwoord (2010), cognitive plasticity refers to adaptive

 65

changes in patterns of cognition related to brain activity (e.g., increased dependence on

executive functions).

The results may implicate that a longer experience of video game experience and

training may have impacts on decision-making skills to the adolescents. It may be that the

respondents started playing video games continuously during periods of high cognitive

plasticity. Although the most reported academic level when the respondents started

playing video games continuously is grades 4 to 6 (55.7%) and the frequencies that are

preceding the “average” level are much higher than the levels that are succeeding the

“average” level, it might be possible that the respondents might have acquired higher

level of decision-making skills if they started playing video games continuously in the

academic levels preceding grades 4 to 6. It might be that the law of exercise is applicable

in this result since the academic level when the respondents started playing video games

continuously is aligned with the law of exercise in which it states that learning ensues

when practice, repetition and feedback occur.

Table 14. Test of relationship between the level of decision-making skills and the most
preferred genre of video games of the respondents
χ2 P-VALUE DECISION SIGNIFICANCE
Chi-square test 50.29 .057* Accept null Not Significant
hypothesis
*significant at p < 0.05

Table 14 illustrates the chi-square test result between the decision-making skills

and the most preferred genre of video games. There were no statistically significant

relationship found between these variables, χ2 (36, N = 178) = 50.29, p = .057. Therefore,

the researchers accept the null hypothesis.

 66

Since all video game genres involve some form of decision-making (Burgun,

2012), it may imply that specific genre of video game might not have an impact to the

decision-making skills of the adolescents. Bearing this in mind, incorporating practice,

repetition and feedback in video games may still the most effective factor to consider

improving the decision-making skills of the adolescents.

Table 15. Test of relationship between the level of problem solving skills and estimated
number of hours of playing video games per week
χ2 P-VALUE DECISION SIGNIFICANCE
Chi-square test 13.23 .353* Accept null Not Significant
hypothesis
*significant at p < 0.05

Table 15 illustrates the chi-square test result between the problem solving skills

and the estimated number of hours spent playing video games per week. The relationship

found between these variables was not significant, χ2 (12, N = 178) = 13.23, p = .353.

Therefore, the researchers accept the null hypothesis.

The finding shows that the relationship between problem solving skills and the

number of hours spent playing video games per week was not significant. This may

imply that the number of hours of video game play of the respondents was not affecting

their problem solving skills at all. The results were not aligned to the study of Oei &

Patterson (2014) in which 52 respondents were asked to play the game “cut the rope for 1

hour a day, 5 times a week for a total 20 hours. They concluded later on that after 20

hours of playing the puzzle video game “Cut the Rope”, the participants improved in

terms of higher-order executive function skills, including problem solving skills. On the

other hand, based on the Gamer’s Profile of the respondents, 68.5 percent reported that

they play video games 1-5 hours a week and only 20.2 % of the respondents play puzzle
 67

games whereas, in the study of Oei & Patterson (2013), all of the respondents played the

puzzle video game “Cut the Rope” for 5 hours a week. This might implicate that although

68.5 percent of the respondents play video games 1-5 hours a week, not all of them play

puzzle games. Assuming that puzzle games might really have an effect on problem

solving skills, it is possible that most of the 13.5 % of the respondents who scored above

average and the 2.8 % who scored high on the solving problems survey scale played

puzzle games.

This might implicate that in terms of improving problem solving skills, the type of

game might be more effective than the frequency of gameplay as according to Oei

(2013), “to improve the specific ability you are looking for, you need to play the right

game”. It is possible that although most of the respondents play video games 1-5 hours a

week, the type of game that some of them are playing was not producing enough impact

on their problem solving skills.

Table 16. Test of relationship between the level of problem solving skills and the academic
level when the respondents started playing video games continuously
χ2 P-VALUE DECISION SIGNIFICANCE
Chi-square test 20.49 .199* Accept null Not Significant
hypothesis
*significant at p < 0.05

Table 16 illustrates the chi-square test result between the problem solving skills

and the academic level of the respondents when they started playing video games

continuously. The relationship between these variables was not significant, χ2 (16, N =

178) = 20.49, p = .199. Therefore, the researchers accept the null hypothesis.

The findings show that the relationship between the academic level when the

respondents started playing video games continuously and their problem solving skills
 68

was not significant. This means that the academic level of the respondents when they

started to play video games continuously has not really affected their problem solving

skills. According to Gok (2010), a problem’s difficulty depends on the solver’s

knowledge and experience. One way to put it is that if the difficulty of the problem is not

enough for an individual to consider it as a problem, it might have an only little impact on

that individual’s problem solving skills. The same could also be applied in playing video

games. The possible explanation for the findings is that the difficulty level of the games

being utilized by the respondents was not enough to generate an effect on their problem

solving skills.

This implies that the adequate difficulty level of the game being utilized could

still be more effective than continuous and regular game play over time as no matter how

long or frequent an individual plays video games, if the difficulty level of the game was

not able to generate a problem solving effort, it might have only little impact on the

individual’s problem solving skills.

Table 17. Test of relationship between the level of problem solving skills and the most
preferred genre of video games of the respondents
χ2 P-VALUE DECISION SIGNIFICANCE
Chi-square test 54.69 .024* Reject null Significant
hypothesis
*significant at p < 0.05

Table 17 illustrates the chi-square test result between the problem solving skills

and the most preferred genre of video games. The relationship between these variables

was significant, χ2 (36, N = 178) = 54.69, p = .024. Therefore, the researchers reject the

null hypothesis.
 69

The research finding shows a significant relationship between the most preferred

genre of video games and the problem solving skills of the respondents. According to

Green et al. (2012), certain video game genres such as puzzle games provide more

cognitive benefits. One of these cognitive benefits could be problem solving skills as

according to the study of Oei & Patterson (2014) where they concluded that playing

certain genres of video games such as puzzle video game genre like “Cut the Rope” could

improve higher-order executive function skills, including problem solving skills.

This implies that there might be certain genres such as puzzle games that could

have more impact on problem solving skills than other genres. These kinds of games

might be used as tools for improving one’s problem solving skills given their

effectiveness and level of engagement it produces to its users, especially on children, as

according to Gutierrez (2012), having low-level problem solving skills affects children’s

academic success. Thus problem solving skills are indeed important to the development

of children.
 70

SUMMARY, CONCLUSION AND RECOMMENDATIONS

This chapter summarizes the findings, generated the conclusion and

recommendation based on the analysis of the results of the study Gamer’s Profile,

decision-making and problem solving skills of the adolescents in Cavite National High

School.

Summary

The primary purpose of this study is to identify the relationship between the

respondents’ Gamer’s Profile to their decision-making and problem solving skills. The

accomplishment of the objectives plays an essential part in attaining the results.

Determining the Gamer’s Profile of the respondents was the first objective of the

researchers, doing this would help them identify the frequency, the active onset academic

level and their most preferred genre of video games.

The second and third objective would be to identify the decision-making and

problem solving skills of the respondents. The completion of these objectives will be

critical to achieving the fourth and fifth objective, which would be to identify if there is a

significant relationship between the Gamer’s Profile of the respondents to their decision-

making and problem solving skills.

 71

The study was conducted on Cavite National High School in Cavite City, Cavite

from August 2016 to March 2017. The researchers used the descriptive-correlational

research design and purposive and convenience sampling technique for their research,

establishing criteria that are limited for those who are active video game players with age

ranging from 12 to 18 years old.

The researchers used the Gamer’s Profile in identifying the number of hours spent

on playing video games, the academic level during the onset of active video game

playing, and the most preferred genre of video games of the respondents. The making

decisions in everyday life and solving problems scale, which has been modified by the

researchers and validated by 3 professionals, were used in identifying the decision-

making and problem solving skills of the respondents.

The following are the salient findings of the study:

1.) Gamer’s Profile

1.1 The findings on the Gamer’s Profile of the respondents are arranged

according to the statement of the problem. Based on the data retrieved

from the Gamer’s Profile of the respondents concerning the number of

hours spent on playing video games of the respondents, the range “1 to

5 hours per week” has the highest frequency of 122 respondents

(68.5%), while range “6 to 10 hours per week” has a frequency of 34

respondents (19.1%) and range “10 to 20 hours per week” having a

frequency of 12 respondents (6.7%) and lastly, the range “20+ hours

per week” with the lowest frequency of 10 respondents (5.6%).

 72

1.2 According to the data gathered from the Gamer’s Profile regarding the

academic level during the onset of active video game playing of the

respondents, “grades 4 to 6” has the highest frequency of 101 (55.7%),

followed by “grades 7 to 9” which has a frequency of 40 (22.5%),

“kindergarten to grade 3” with a frequency of 26 (14.6%), “before

kindergarten” with a frequency of 8 (4.5%) and lastly, “grades 10 to

12” has the lowest frequency of 3 (1.7%).

1.3 Lastly, the data gathered from the Gamer’s Profile concerning the

most preferred genre of video games of the respondents show that

“puzzle” games have the highest frequency of 36 (20.2%), followed by

“strategy” games which have a frequency of 26 (14.6%), and then

“shooter” games which has a frequency of 22 (12.4%), “sports” games

with a frequency of 21 (11.8%), “action – adventure” games with a

frequency of 18 (10.1%), “fighting” games with a frequency of 17

(9.6%), “action” games with a frequency of 13 (7.3%), “simulation”

games with a frequency of 10 (5.6%), “role-playing” games with a

frequency of 9 (5.1%) and lastly, “driving/racing games” which has

the lowest frequency of 6 (3.4%).

2.) Based on the data acquired from the results of the making decisions in

everyday life scale of the respondents, the range “average” has the highest

frequency of 65 (36.5%) with a mean of 75. 68, followed by “low average”

with a frequency of 54 (30.3%) and mean 66.09, while both “below average”

and “above average” has a frequency of 28 (15.7%) but with means scores of
 73

53.32 for “below average” and 85.61 for “above average”. Lastly, the “high

average” has the lowest frequency of 3 (1.7%) and a mean of 95.00.

3.) Based on the data acquired from the results of the solving problems survey

scale of the respondents, the range “average” has the highest frequency of 61

(34.3%) with a mean of 87.15, followed by “low average” with a frequency of

60 (33.7%) and a mean of 77.85, “below average” with a frequency of 28

(15.7%) and a mean of 67.61, and then “above average” with a frequency of

24 (13.5%) and a mean of 96.83. Lastly, the “high average” has the lowest

frequency of 5 (2.8%) and a mean of 104.40.

4.) There is a significant relationship between the Gamer’s Profile and the

decision-making skills of the respondents in terms of their estimated number

of hours spent playing video games per week. There is a significant

relationship between the Gamer’s Profile and the decision-making skills of the

respondents in terms of their academic level when they started playing video

games continuously. And lastly, there is no significant relationship between

the Gamer’s Profile and the decision- making skills of the respondents in

terms of their most preferred genre of video games.

5.) The finding presented about the relationship between the Gamer’s Profile and

problem solving skills of the respondents are arranged according to the

Gamer’s Profile given order. There is no significant relationship between the

Gamer’s Profile and the problem solving skills of the respondents in terms of

their estimated number of hours spent playing video games per week. There is

no significant relationship between the Gamer’s Profile and the problem

 74

solving skills of the respondents in terms of their academic level when playing

video games continuously. Lastly, there is no significant relationship between

the Gamer’s Profile and the problem solving skills of the respondents in terms

of their most preferred genre of video games.

Conclusion

The findings of this study expanded the work of previous researchers in the area

of video games and its effects.

1.) Gamer’s Profile

1.1 The data gathered suggests that the Filipino culture “tingi-tingi” may still

be prevalent among the respondents as many of the adolescents in Cavite

National High School still preferred playing for a couple of hours rather

than to play for extended periods of time.

1.2 The data acquired from the Gamer’s Profile regarding the academic level

during the onset of active video game playing of the respondents suggests

that the onset of video game playing of the respondents might be

influenced by these factors; The efficiency of video games as a casual

activity substituting the role of other activities such as board games and

bowling, The possibility of video games to be a frequent topic of

conversation among adolescent peers that could result to encouragement

of playing it, and lastly, the influence of media on adolescent peer group

activities.

1.3 The availability of resources that the respondents possess such as their

allowance may possibly explain why many of the respondents prefer

 75

playing puzzle games as it requires less time to learn its mechanics than

any other genre of video games.

2.) The respondents might have encountered difficulty in making decisions as a result

of their higher activity in their amygdala. It may be that the respondents were

experiencing difficulty in decision-making is because they may tend to become

more emotional instead of being objective when making decisions. Thus, the

levels preceding the “average” level of decision-making skills were higher

frequencies than the levels succeeding the “average” level.

3.) Regarding the level of problem solving skills of the participants, it is possible that

the adolescent’s brain development might be affecting their problem solving

skills. Thus, the frequencies of the levels before the “average” level of problem

solving skills were higher than the levels succeeding the “average” level.

4.) It is possible that continuous and regular gameplay is more effective than playing

a specific genre in terms of improving decision-making skills. Moreover, utilizing

video games as instructional materials might be beneficial to the decision-making

skills of the students, specifically to those who are still in their late childhood or

pre-adolescence period.

5.) The genre and the difficulty level of the video game played might be more

influential on the problem solving skills of the adolescents than the time spent and

onset of gameplay.

Recommendations
 76

The following statements are the recommendations, advices and suggestions of

the researchers relating to this field of study.

1.) The researchers recommend to the educators that they may incorporate the law of

exercise to video games in order to serve as an instructional material in terms of

improving decision-making skills by using the video gaming hours and the active

onset academic level as a factor. Furthermore, the specific genre of video games

may provide benefits to improve the problem solving skills of the students.

2.) Video game designers and developers could also develop educational video

games in which the negative factors that may lead to negative effects such as

aggression or low verbal IQ to the adolescents are removed. Furthermore, they

should develop educational video games that could improve the decision-making

and problem solving skills of the adolescents.

3.) The researchers recommend to future researchers to treat the estimated number of

hours spent playing video games per week as continuous data and use appropriate

statistical tools to identify the direction of correlation if it is negative or positive

since the reported estimated number of hours spent playing video games per week

was categorized through various ranges.

4.) Future researchers should find literature pertaining to the genre of video games

where it is categorized to the smallest number of category and still has a

distinction between the genres. This may minimalize or even totally avoid

confusion among their respondents when reporting for their most preferred genre

of video games.
 77

5.) Future researchers could use various statistical methods and research designs in

order to explore the complex relationship of the video gaming profile of the

adolescents to their decision-making and problem solving skills. Furthermore,

qualitative studies can be used to map specific examples of the relationship

between the variables. Subsequently, this might allow future researchers to delve

far deeper into the factors causing the relationship.

6.) The researchers also recommend to the future researchers to include the level or

degree of immersion to video games as a variable and analyze the relationship

between decision-making and problem solving skills since it may lead to a more

accurate or detailed data when it comes to the effects of video games to the

adolescents.

7.) The researchers recommend to future researchers to use different age group as

their samples in their study and analyze the relationship of Gamer’s Profile of

their respondents to their decision-making and problem solving skills.

8.) Future researchers could identify the relationship between Gamer’s Profile to

other life skills such as critical thinking skills, self-esteem or teamwork.

 78

REFERENCES

Adachi, P., & Willoughby T. (2013, January 24). More than just fun and games: The
longitudinal relationships between strategic video games, self-reported problem
solving skills, and academic grades. J Youth Adolescence, 42, 1041 – 1052. Doi:
10.1007/s10964-013-9913-9.

Adams, E. (2014). Fundamentals of Game Design (3rd ed.). New Jersey: Pearson
Education, Inc.

Bailey, R. (2016, May 11). Frontal Lobes. Retrieved: February 2017 from
http://biology/about.com/od/anatomy/p/Frontal-Lobes.htm

Bailey, R. (2017). Amygdala: Fear and the Amygdala. Retrieved February 2017 from:
https://www.thoughtco.com/amygdala-anatomy-373211

Baltes, P. B., & Kliegl, R. (1992). Further testing of limits of cognitive plasticity:
Negative age differences in a mnemonic skill are robust. Developmental
Psychology, 28(1), 121–125. https://doi.org/10.1037/0012-1649.28.1.121

Barkman, S., & Machtmes, K. (2002). Four-fold: A research model for designing and
evaluating the impact of youth development programs. News and Views, 4 (4), 4-
6.

Bean, S. (2015). The Surprising Reason for Bad Child Behavior: “I Can’t Solve
Problems”. Retrieved September 2016 from
https://www.empoweringparents.com/article/the-surprising-reason-for-bad-child-
behavior-i-cant-solve-problems/

Benigno, K. (2014, April 24). Video Games Can Be Good, Proves Scientific Study.
Retrieved November 2016 from http://www.wheninmanila.com/video-games-can-
be-good/
 79

Burgun, K. (2012, March 29). What Makes a Game?. Retrieved September 2016 from
http://www.gamasutra.com/view/feature/167418/what_makes_a_game.php

Cherry, K. (2016, August 31). Problem-solving strategies and obstacles. Challenges that
can make problem-solving more difficult. Retrieved September 2016 from
https://www.verywell.com/problem-solving-2795008

Danganan, A. (2013, January 7). The Philippine Culture of Tingi. Retrieved March 2017
from http://www.vagabondjourney.com/the-philippine-culture-of-tingi/

Dewey, J. (1910). How we think. Retrieved October 2016 from:

https://archive.org/details/howwethink000838mbp

Dewey, J. (1938). (1997 Edition) Experience and education. Retrieved

September 2016 from
https://books.google.com.ph/books?id=UE2EusaU53IC&printsec=frontcover&d
q=experience+and+education&hl=en&sa=X&redir_esc=y#v=onepage&q=expe
rience%20and%20education&f=false

Dietrich, C. (2010). "Decision Making: Factors that Influence Decision Making,

Heuristics Used, and Decision Outcomes." Inquiries Journal/Student Pulse, 2(02).
Retrieved from http://www.inquiriesjournal.com/a?id=180

DiSalvo, D. (2014, April 06). The Surprising Connection between Playing Video Games
and a Thicker Brain. Retrieved November 2016 from
http://www.forbes.com/sites/daviddisalvo/2014/04/06/the-surprising-connection-
between-playing-video-games-and-a-thicker-brain/#5e8746155501

Dizon, D. (2009, March 26). Internet use in RP expanding to lower income groups.
Retrieved February 2016 from http://news.abs-cbn.com/nation/03/26/09/internet-
use-rp-expanding-lower-income-groups

Duerden, M. D., Witt, P. A., Fernandez, M., Bryant, M. J., & Theriault, D. (2012).
Measuring life skills: Standardizing the assessment of youth development
indicators. Journal of Youth Development, 7(1), 100–115.

D'Zurilla, T.J., & Maydeu-Olivares, A. (1995). Conceptual and methodological issues in

social problem-solving assessment. Behavior Therapy, 26, 409-432.

Entertainment Software Association (2016). Essential facts about the computer and video
game industries. Retrieved October 2016 from:
http://essentialfacts.theesa.com/Essential-Facts-2016.pdf
 80

Esposito, N. (n.d.). A short and simple definition of what a videogame is, presented at
DiGRA Conference, Vancouver, Canada, June 2005. Unpublished conference
paper. University of Technology of Compiègne, Compiègne, France, 2016.

Evans, J.ST., Barston, J.L., & Pollard, P. (1983). On the conflict between logic and belief
in syllogistic reasoning. Memory & Cognition, 11(3), 295-306.

Gackenbach, J. & Bown, J. (2011). Video Game Presence as a Function of Genre.

Loading...The Journal of the Canadian Game Studies Association, 5(8), 4–28.

Garrett, R.M. (1986, January). Problem Solving in Science Education. Studies in Science
Education Vol. 13. DOI: 10.1080/03057268608559931

Gee, J. P. (2007). What video games have to teach us about learning and literacy (2nd
ed.). New York: Palgrave Macmillan.

Gee, J. P. (2008). Good video games and good learning. Retrieved October 2016 from
http://www.academiccolab.org/resources/documents/Good_Learning.pdf

Gentile, D. A. (2011). The multiple dimensions of video game effects. Child

Development Perspectives, 5(2), 75–81. https://doi.org/10.1111/j.1750-
8606.2011.00159.x

Gil-Perez, D., Dumas-Carre, A., Caillot, M., & Martinez-Torregrosa, J. (1990). Paper and
pencil problem solving in the physical sciences as a research activity. Studies in
Science Education, 18, 137-151.

Goetz, T. (2011). Harnessing the power of feedback loops. Wired.

http://www.wired.com/magazine/2011/06/ff_feedbackloop/

Gok, T., & Silay, I. (2010). The effects of problem solving strategies on student
achievement, attitude and motivation. Retrieved February 2017 from:
http://www.lajpe.org/jan10/02_Tolga_Gok.pdf

Gok. T (2010, December) Problem Solving. Asia-Pacific Forum on Science Learning and
Teaching, Vol. 11, Issue 2, Article 10. Retrieved Febreuary 2017 from:
https://www.ied.edu.hk/apfslt/v11_issue2/gok/page3.htm

Granic, I., Lobel, A., and Engels, R., C.M.E. (2014). The Benefits of Playing Video
Games. American Psychologist Vol. 69, no.1, 66 – 96. Doi: 10.1037/a0034857

Green, C.S., & Bavelier, D. (2012). Learning, Attentional Control and Action Video
Games. Current Biology, 22, 197-206, DOI: 10.1016/j.cub.2012.02.012
 81

Greenwood, P. M., & Parasuraman, R. (2010). Neuronal and cognitive plasticity: A

neurocognitive framework for ameliorating cognitive aging. Frontiers in Aging
Neuroscience, 2, 150. http://doi.org/10.3389/fnagi.2010.00150

Gregory, R. S., & Clemen, R. T. (2004). Improving Students’ Decision Making Skills.

Gutierrez E. (2012, May 11). Problem-solving skills are an important factor in academic
success. Retrieved September 2016 from
http://msue.anr.msu.edu/news/problem_solving_skills_are_an_important_factor_i
n_academic_success

Harris, R. (2012, June 9). Introduction to Decision Making. Retrieved September 2016
from http://www.virtualsalt.com/crebook5.htm

Hartanto, A., Toh, W. X., & Yang, H. (2016). Age matters: The effect of onset age of
video game play on task-switching abilities. Attention, Perception, &
Psychophysics, 78(4), 1125–1136.
https://doi.org/http://dx.doi.org/10.3758/s13414-016-1068-9

Hull, J. G., Brunelle, T. J., Prescott, A. T., & Sargent, J. D. (2014). A longitudinal study
of risk-glorifying video games and behavioral deviance. Journal of Personality
and Social Psychology, 107(2), 300–325. http://doi.org/10.1037/a0036058

Ito, M., Horst, H., Bittanti, M., Boyd, D., Herr-Stephenson, B., Lange, P., Robinson, L.
(2009). Living and learning with new media: Summary of findings from the
digital youth project. Digital Media, November (November), 58.
https://doi.org/10.1111/j.1548-1379.2010.01107.x

Jaffee, W.B., & D'Zurilla, T.J.(2009). Personality, Problem Solving, and Adolescent
Substance Use. Behavior Therapy 40(1), 93-101.

Jesse Schell. (2008). The art of game design. The effects of brief mindfulness intervention
on acute pain experience: An examination of individual difference (Vol. 1).
https://doi.org/10.1017/CBO9781107415324.004

Jose N.M., & Thomas R.P., (2011). Problem solving ability and scholastic achievement
of secondary students. GCTE Journal of Research and Extension in Education,
Vol. 6, No. 1, pp. 145-148.

Kohler, W. (1999). The Mentality of Apes, Vol 3. IBSN: 041520979X, 9780415209793.

Retrieved January 2017 from:
https://www.google.com.ph/url?sa=t&source=web&rct=j&url=https%3A%2F%
2Fbooks.google.com%2Fbooks%2Fabout%2FThe_Mentality_of_Apes.html%3Fi
 82

d%3DhOFJysQuHIYC&ved=0ahUKEwi84LLd09vSAhUHjJQKHXnlCYUQFghd
MA4&usg=AFQjCNEvPxOQkPTJh1pC3ASSIHUEha5IXw

Kowert, R. ., & Oldmeadow, J. A. . (2013). (A) Social reputation: Exploring the

relationship between online video game involvement and social competence.
Computers in Human Behavior, 29(4), 1872–1878.
https://doi.org/10.1016/j.chb.2013.03.003

Kühn S., Lorenz R., Banaschewski T., Barker G. J., Bu¨chel C., Conrod P. J., … Gallinat,
J. (2014) Positive association of video game playing with left frontal cortical
thickness in adolescents. PLoS ONE 9(3): e91506.
doi:10.1371/journal.pone.0091506
Labucay, I. D. (2014). Patterns of internet usage in the philippines. In J. D. James (Ed.),
The Internet and the Google age: Prospects and perils (pp. 27-49). Dublin:
Research-publishing.net. doi: 10.14705/rpnet.2014.000176

Lee, J. H., Karlova, N., Clarke, R. I., Thornton, K. & Perti, A. (2014). Facet Analysis of
Video Game Genres. iConference 2014 Proceedings, 1–13.
https://doi.org/10.9776/14057

Louisiana State Civil Service (2014). Effective Problem Solving & Decision Making
(p.4), 9499.

Mann, L., Harmoni R., and Power C. 1989. Adolescent decision-making: the
development of competence. Journal of Adolescence, 12: 265-278.

Mincemoyer, C., & Perkins, D.F. (2003). Assessing decision making skills of youth. The
Forum for Family and Consumer Issues [On-line], 8(2). Retrieved November
2016 from http://ncsu.edu/ffci/publications/2003/v8-n1-2003-january/ar-1-
accessing.

MindTools (2013). How Good Is Your Decision Making? Retrieved January 2017 from
https://www.mindtools.com/pages/article/newTED_79.htm

MindTools (2013). How Good Is Your Problem Solving Skills? Retrieved January 2017
from https://www.mindtools.com/pages/article/newTMC_72.htm

Morewedge, C. K., Yoon, H., Scopelliti, I., Symborski, C. W., Korris, J. H., & Kassam,
K. S. (2015). Debiasing Decisions Improved Decision Making With a Single
Training Intervention. Policy Insights from the Behavioral and Brain Sciences,
vol. 2(1) 129 –140. doi: 10.1177/2372732215600886

Murphy C. (2011) Why Games Work and the Science of Learning. Published/Presented
at I/ITSEC Tutorial 1113, 2011.
 83

Murray, J. (2013) Minecraft in the classroom teaches reading and more. Retrieved
September 2016 from http://www.teachhub.com/minecraft-classroom-teaches-
reading-writing-problem-solving

Newell, A., and Simon, H. A. (1972) Human problem solving, Englewood Cliffs, NJ:
Prentice-Hall

Number of PC online gamers in the Philippines from 2012 to 2014 (in millions). (2015).
Retrieved October 2016 from https://www.statista.com/statistics/323776/pc-
online-gamer-numbers-philippines/

Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.

Oei, A. C., & Patterson, M. D. (2014). Are videogame training gains specific or
general? Frontiers in Systems Neuroscience, 8, 54.
http://doi.org/10.3389/fnsys.2014.00054

Olson, C. K., Kutner, L. A, & Warner, D. E. (2008). The Role of Violent Video Game
Content in Adolescent Development. Journal of Adolescent Research, 23(1), 55–
75. https://doi.org/10.1177/0743558407310713

Ord. J. (2012). John Dewey and Experiential Learning: Developing the Theory of Youth
Work. Youth & Policy, 108, 60 – 62. Retrieved November 2, 2016, from
youthandpolicy.org

Owen, P. (2016, March 9). What Is a Video Game? A Short Explainer. Retrieved
September 2016 from http://www.thewrap.com/what-is-a-video-game-a-short-
explainer/

Patria, K. (2012, November 08). Study bares Pinoy kids' average allowance, spending
habits. Retrieved February 2017 from https://sg.news.yahoo.com/study-bares-
pinoy-kids--average-allowance--spending-habits.html

Philippine Statistics Authority (2010, May 1). Philippine Standard Geographic Code.
Retrieved October 25, 2016, from
http://nap.psa.gov.ph/activestats/psgc/municipality.asp?muncode=042105000&re
gcode=04&provcode=21

Philippines Population 1960-2016 | Data | Chart | Calendar | Forecast. (2017). Retrieved

September 2016 from http://www.tradingeconomics.com/philippines/population

Potton, L. (2012). Problems only people who always make bad decisions will understand.
Retrieved October 2016 from http://www.viralthread.com/12-problems-only-
people-who-always-make-bad-decisions-will-understand/
 84

Prensky, M. (2012). From digital natives to digital wisdom: Hopeful essays from 21st
century learning. Retrieved October 2016 from:
http://marcprensky.com/writing/Prensky-Intro_to_From_DN_to_DW.pdf

Rad, M.R. (2013, November, 24). Characteristics of good problem solvers. Retrieved
February 2017 from http://www.huffingtonpost.com/roya-r-rad-ma-psyd/problem-
solving_b_4302935.html

Reese, H. (2011). The Learning-by-doing principle. Behavioral Development Bulletin

Vol. 11, p. 1.

Reeves, B., & Malone, T. W. T. O’Driscoll, (2008). Leadership’s Online Labs. Harvard
Business Review, 86(5).

Rosen, M.A., Salas, E., Lyons, R., and Fiore, S.M. (2008). Expertise and naturalistic
decision making in organizations: Mechanisms of effective decision making.

Rutledge, P. (2012, August 28). Video Games, Problem-Solving and Self-Efficacy.

Retrieved October 2016 from https://www.psychologytoday.com/blog/positively-
media/201208/video-games-problem-solving-and-self-efficacy-part-3

Sahlfeld, M. (2011). The Importance of Problem Solving In Education. Retrieved

September 2016 from http://enduringlearner.com/2011/08/06/the-importance-of-
problem-solving-in-education/

Schultz, D. P., & Schultz, S. E. (2010). Theories of personality (10th ed.). Australia:
Wadsworth/Cengage Learning.

Scott, D. (1998). Decision Making. Retrieved September 2016 from

http://cals.arizona.edu/sfcs/cyfernet/nowg/sc_decision.html

Shaban, H. (2013, October 10). Playing War: How the military uses video games.
Retrieved January 2017 from
http://www.theatlantic.com/technology/archive/2013/10/playing-war-how-the-
military-uses-video-games/280486/

Shaver, E. (2014, April 3). Characteristics of expert decision makers. Retrieved February
2017 from http://www.ericshaver.com/characteristics-of-expert-decision-makers/

Spear, L. P. (2002). Alcohol’s effects on adolescents. Alcohol Research and Health,

26(4), 287–291.
 85

Srivastava, G. (2015). The importance of life skills in adolescents. Retrieved October

2016 from http://www.whiteswanfoundation.org/article/the-importance-of-
teaching-your-adolescent-life-skill/

Steinberg, S. (2011, January 31). How video games can make you smarter. Retrieved
October 2016 from
http://edition.cnn.com/2011/TECH/gaming.gadgets/01/31/video.games.smarter.st
einberg/

Steinkuehler, C., & Duncan S. (2008). Scientific Habits of Mind in Virtual

Worlds. Journal of Science Education and Technology 17.6, 530–543.

Sullivan, T. (2014, March 6). App thrills toddlers as schools go digital. Retrieved
November 2016 from ABS-CBN Website: http://news.abs-
cbn.com/lifestyle/gadgets-and-tech/03/06/14/apps-thrill-toddlers-schools-go-
digital

Tagala, D. (2014, August 8). Meet award-winning Pinoy teacher who is making math
cool. Retrieved November 2016 from ABS-CBN North America News Bureau:
http://k2.abs-cbnnews.com/global-filipino/08/08/14/award-winning-pinoy-
teacher-ny-makes-math-cool

Takahashi, D. (2013, November, 25). More than 1.2 billion people are playing games.
Retrieved October 2016 from http://venturebeat.com/2013/11/25/more-than-1-2-
billion-people-are-playing-games/

Takeuchi, H., Taki, Y., Hashizume, H., Asano, K., Asano, M., Sassa, Y., Kawashima, R.
(2016). Impact of videogame play on the brain/’s microstructural properties:
cross-sectional and longitudinal analyses. Mol Psychiatry. JOUR , Macmillan
Publishers Limited. Retrieved from http://dx.doi.org/10.1038/mp.2015.193

Talukder, G. (2013, March 20). Decision-making is still a work in progress for teenagers.
Retrieved October 2016 from
http://brainconnection.brainhq.com/2013/03/20/decision-making-is-still-a-work-
in-progress-for-teenagers/

Tasks of Childhood – Late Childhood Development Ages 8-11 (2011). Retrieved

November 2017 from http://www.kaytrotter.com/tasks-of-childhood-late-
childhood-development-ages-8-11/

Teen Brain: Behavior, Problem Solving, and Decision Making (2016, September).
Retrieved October 25, 2016 from
http://www.aacap.org/aacap/families_and_youth/facts_for_families/fff-guide/The-
Teen-Brain-Behavior-Problem-Solving-and-Decision-Making-095.aspx
 86

Trybus, J. (2015). Game-based learning: What it is, why it works, and where it's going.
Retrieved October 2016 from http://www.newmedia.org/game-based-learning--
what-it-is-why-it-works-and-where-its-going.html

Venercacion. (2013, March 3). Filipino shopping habits and the “tingi” culture. Retrieved
November 2016 from http://casaveneracion.com/filipino-shopping-habits-and-
the-tingi-culture/

Walker, C. (2010, December 22). Video games and realism. Retrieved September 2016
from http://news.wfu.edu/2010/12/22/video-games-and-realism/

West, R.F., Toplak, M.E., & Stanovich, K.E. (2008). Heuristics and Biases as Measures
of Critical Thinking: Associations with Cognitive Ability and Thinking
Dispositions. Journal of Educational Psychology, 100(4), 930-941. DOI:
10.1037/a0012842.

Wolf, M. J. P. (2001). Genre and the video game. The medium of the video game.
University of Texas Press, Austin, TX, 113-234.

Worell, J. & Danner, F. (1989). The adolescent as decision-maker: Applications to

development and education. San Diego, CA: Academic Press, Inc.

Xinhua (2016, August 23). Video Game players likely to perform better at school. Manila
Bulletin, p. 12.