1999-01 Spring 1999

Educational Advancements Through Video Games

Lucas A. Guerra

Educational Advancements Through Video Games Lucas A. Guerra

Senior Design Dr. Richard S. Barr

May 4, 1999

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To: Dr. Richard S. Barr

From: Lucas A. Guerra

Date: May 4, 1999

Re: Education Advancements Through Video Games

Executive Summary

• This report intends to inspire thought for teachers concerned about the current lack of initiative exhibited by today's students. Upon yielding that video games could represent a main factor concerning this epidemic, this report hopes to show that the video games can also lead to a cure. Rather than attempting to eradicate this menace to education, outlines have been created to turn the video

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game beast into a blessing. Through the use of statistical analysis, this report shows creative ways that teachers can take back the study time stolen by video games.

By isolating different factors that affect the outcomes of video games, variables can be created for use in statistical experiments. Two concrete examples show the application of this concept. Each combats a different set of problems, but each

• accomplishes the same goals. In order to complete these experiments, an understanding of the methods used is necessary. By exhibiting these skills, the student has unknowingly shown the teacher that the statistical concepts have been learned and can be applied to "real world" situations.

• Many conclusions and speculations are drawn from this procedure. Conclusions are made about what individual factors within a video game change the output, or score, of a game. Brief analysis shows that this information could feasibly be applied to linear programming models. Final conclusions lead to the speculation that this creative approach to subjects of analysis could reach students that may have difficulty learning statistical concepts. Performing this analysis has affected my study habits and learning curve in a positive way by allowing me to bridge the gap between "boring" subjects and fun games. By knowing what difficulties I used to encounter, an extension would speculate that this approach could help many students and teachers advance and enhance the educational capabilities of the current school system.

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Table of Contents

Title........................................................................... Page 1

ExecutiveSummary ...................................................... Page 2

Tableof Contents...... . . . . ............................................ . . .Page 3

Project Description.. •1••••• • • •• • • • . . . ......... .........................Page 4

Analysisof Situation ...................................................... Page 8

• Easy ...............................................................................Page 8 Hard .............................................................................. Page 16

Conclusions............................................................ .....Page 24

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Project Description

Many students of all ages play video games as a form of recreation.

Unfortunately, this form of recreation can lead to a dangerous addiction.

Constantly escaping reality to take part in digital play can lead to harmful

ends. Addicted players can forgo school work, friends, and even reality as

• shown by the Dungeons and Dragons epidemic of the early eighties.

Teachers find themselves competing for the attention of students on a

• daily basis. The allure of battling demons in order to save the bikini clad

maiden sounds far more exciting than examining the standard deviation of a

data group that was handed out at the beginning of class. One might even

infer that attention deficit disorder is nothing more than a student

concentrating on saving the maiden rather than paying attention in class. If

a person only absorbs 35% of a face-to-face conversation, imagine the

decrease in that number from the classroom environment and the distraction

of trying to figure out how to pass that one level in the video game at home.

A recommendation by teachers is that students spend three hours of

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study at home for every hour spent in the classroom. A recent poll by Time

Magazine shows that up to 86% of teenagers spend at least an hour a week

• playing video games while at least 4% play for more than ten hours a week.

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Students will think of their video games regardless of what occurs in the

• classroom. This analysis is an attempt to allow teachers to utilize those

thoughts to augment education. By associating video games with education,

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we capture the student's attention while working at school and we influence

the student when at play.

Video game players strive to master games by achieving the highest

score possible. Players turn to magazines, to electronic texts, and even 1-

900 pay telephone numbers in hopes of learning ways to increase their •

scores. Often these sources are used without questioning the validity of the

information. The nature of the sport usually provides for one "best" way to

master a video game based on a player's skill level. Some games, however,

show the tendency to have only one true path of victory. This tendency

opens the door to educational exposure.

Players use the aforementioned outlets to gather information about

• video games. This information may take the form of codes, joystick

movements, terrain maps, or even detailed level instructions. All of this

information is used to determine what weapons to use, what weapons to fire,

what attack to use, what method to take, even what game to play. This may

sound cryptic until it is translated into a form fit for use in the classroom. S

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Perhaps this may appear more familiar. An experiment is to be

designed to maximize output subject to the independent variables of

resources(ammunition), perishables (kills), and technology(interface).

Another possibility is to minimize the time associated with the

production(completion) of a given unit(level) subject to the dependent

variables of resources, perishables, and technology.

By transforming and modifying the perceptions of video games and

operations research, it is hoped that teachers may find new ways to stimulate

students to learn more efficiently the concepts in this course of study.

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Analysis of Situation

To show the different applications of video games for educational

purposes, the analysis must be broken into three parts; easy, hard, and

expert. Each part is named to reflect the overall difficulty the student or

teacher may face while attempting to integrate video games and education.

• The parts will be fully examined in their order of difficulty.

• Easy: Standard Multiple Factored Experiment

The easiest way to integrate video games with education is to allow

the student to analyze the game itself. By using a video game to create a

statistical experiment, the student is capable of creating a controlled

environment in which the variables of the game can be maintained or altered

with great ease. To illustrate this point, an experiment was run on the video

game Ray Storm in hopes of finding out what factors contribute to the

highest score.

The video game Ray Storm, for the Sony Playstation game console, is

t a vertically scrolling shoot-em-up. This translates as a game where the

player's character, usually a flying ship, is situated at the bottom 5% of the

television screen. All of the player's attacks are aimed towards the top of

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the screen. Most of the enemies, usually flying ships, appear at the top of

• the screen and move towards the player. The player may move in any

direction but may only fire upwards, while the enemies may only move in a

• single vector pattern and may fire directly at the player. More modern video

games, such as Ray Storm, also have a "boss" character to defeat at the end

of each level of play. The boss character has special forms of attack the

include powerful lasers, missiles, and machine guns, but its real power is

that it takes multiple shots to destroy. A typical boss character may take

hundreds of shots to defeat while standard enemies may take only one.

Before playing the game, the player has the ability to alter options

within the game. These may include brightness, volume, and others, but

only four of them truly affect game play. The first is the type of ship used;

this variable provides for different fighting styles. Ship type I uses a pulse

cannon and heat seeking missiles, while ship type II uses a weak laser and a

lighting missile attack. The second variable is the type of attack used.

Should the player use just the primary weapon, the missile, both, or auto

fire? Auto fire is a method of attack where the computer assists the player

by automatically firing the missile while the player concentrates on using

the primary cannon. The third variable is the difficulty of play. The player

has the ability to set this value at zero, the easiest, through integer values up S

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to seven, the hardest. The final variable is the type of game played. The

player may choose to play in arcade mode, utilizing the same programming

code as the arcade version of Ray Storm, or extra mode, a change from the

original code to alter enemy types and enemy attack patterns.

Easy: Experimental Procedure

The first level of Ray Storm will be used as the basis for comparison.

The score for subsequent levels depends on the score for the first, so the

most efficient experiment would analyze the first level as the basis for

scoring in future levels.

Ray Storm will be played on both game types using the following

criteria. First, the levels of difficulty will be set to either zero or seven,

chosen randomly, to achieve 16 runs each. The ship type will be I or II to

achieve four runs for each ship at each difficulty setting. Each shot type

will be applied no more than once to each of these four runs. The end result

is 32 runs.

The experiment is then repeated according to the preceding procedure

to provide for a total of 64 runs.

A premature analysis of variance allowed the experiment to be

terminated here. If an intermediate analysis had not been performed, the

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game would need to be played at each of the remaining difficulty levels.

This would have meant playing the first level of this game another 192

times to make a total of 256 runs.

Easy: Statistical Method

This study is performed using an analysis of variance on nested data

within a completely randomized block design. The type of shot data is

dependent of the ship chosen so it is said that shot type is nested within ship

type. The completely randomized block design became useful in

performing the experiment, for it dictated the running order of the different

variable combinations. Also, the completely randomized block design help

to conceptualize the data as being blocks determined by ship type, difficulty

setting, and game type.

The model for the experiment is:

score[ijk] = ship[i] + difficulty[j] + gametype[k] +

shot(ship[i])m + E[ijk)

Since shot type is nested within ship type and all other variable have

only two levels, the interaction terms are left out. Variables with only two

levels have one degree of freedom, meaning what could have been

interaction terms become error terms. The only variable left undefined is

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the "E" term which stands for the error term that signifies the variance

between the expected and measured values for score. Having defined the

model, the next step is translating it into a form that the Statistical Analysis

Software may understand.

The following file was used to run the SAS program.

filename game game.data; data one;

infile game; input ship$ difficul$ shot$ gametype$ score; proc ANOVA; CLASS ship difficul shot gametype; MODEL score = ship difficul shot(ship) gametype; TITLE Analysis of Ray Storm'; means ship difficul gametype shot/duncan;

run;Figure 1

This algorithm allowed the testing of the variables that influence the

response variable score. The parenthesis after the shot variable in the model

line tells SAS that shot type is nested within ship type. Also, note that the

error term is left out of the model when translating it to the SAS file.

The "$" after the variable names in the input line signify that those

variables are to be interpreted as character variables only. This prevents

SAS from trying to run a mean square on the word arcade, for example.

The class line shows which variables are independent variables. This

allows SAS to distinguish the dependent variable, score, from the dependent

variables when computing the model.

The means line allowed for the execution of Duncan's Multiple

Range. It may seem like overhead, but it proved useful as later noted.

Easy: Statistical Analysis

Figure 1 shows the output from running an analysis of variance on the

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Analysis of Variance Procedure

Dependent Variable: SCORE Sum of

Source DF Squares

Model 13 2.289642E+12

Error 50 3.706507E+ll

Corrected Total 63 2.660293E+12

Fig

Mean Square F Value Pr > F

1.761263E+ll 23.76 0.0001

7.413015E+09

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As shown here, by using an alpha of 0.05 reveals that there is an

effect that significantly affects the score. By having an F-value of 23.76,

the data shows that the likelihood of one or more variables is influencing

the score.

SThe following data in Figure 2 reveals the findings for the individual

variables.

• Source DF SHIP 1 DIFFICUL 1 SHOT(SHIP) 6 GANETYPE 1

Anova SS Mean Square F Value Pr > F

4.023384E+10 4.023384E+10 5.43 0.0239

7.896322E+09 7.896322E+09 1.07 0.3070

2.211168E+12 3.685280E+ll 49.71 0.0001

1.128204E+09 1.128204E+09 0.15 0.6981

Figure 3

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This data helps determine the exact cause for changes in score. What

is missing is the analysis of the interaction variables. The interactions

cannot be measured since the individual variables only have one degree of

freedom; therefore, what could have been interaction terms become error

terms. It is very clear that the type of shot used is the largest contributor to

changes in score. The probability of getting an F-value larger than. 49.71 is

so unlikely that shot type proves to be very significant with an alpha of

0.05. Another interesting note is that the type of ship shows significance at

the 0.05 alpha. It would appear that ship type is less significant than the

shot type unless the notation is understood. Having the parenthesis after the

word shot means that shot type is a nested variable, in this case within ship.

This would imply that shot type is very significant, but its significance is

directly tied to the type of ship chosen. It is not enough to know that the

ship type and shot type are significant; it is necessary to know which of each

variable leads to high scores.

According to the Duncan's Multiple Range analysis, ship type II is

classed higher than ship type one. This could have easily been proven by

examining the means, but this point sets up the next point. The same

analysis shows that using only the missile attack leads to much higher

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scores, while using only the primary gun attack leads to extremely low

scores.

The largest source of error would be the player. The game presents

obstacles in a set pattern; therefore, the error variable is directly related to

the player's responses during any given run. Also, the model does not

account for the player's skill level increasing after each run. After 64 times,

almost anyone would develop their skills.

Easy: Conclusions

The data has conclusively shown that for the video game Ray Storm,

the key to achieving the highest score possible is to use ship type II and only

its missiles. The analysis of variances and Duncan's Multiple Range

showed that the influence by these variables is not likely to be due to chance

alone.

Difficulty settings and game type have no direct influence on the

player's score. This is where the reliability of statistics fail. The ship type

and the shot type directly influence score; therefore, the effects of these

variable can be measured. Difficulty and game type are indirect variables;

they cannot be quantified. These two variables affect the way the player

reacts to the game thus possibly leading to a change in score. Playing at

difficulty level seven is not statistically different than difficulty level one.

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This implies that all of the other difficulties are not statistically different

according to Duncan's Multiple Range; however, it was more arduous to

finish the level at the higher difficulty. Elements such as these will continue

to cause errors in studies until creative ways of analyzing skill are

developed.

Easy: Prologue

This basic approach converts hours of frivolous game time into a

fruitful learning experience. The student has the satisfaction of learning

about a video game's score algorithm, and the teacher is shown that the

student has learned key concepts of statistical analysis.

Hard: Linear Programming and Optimization

Quake is a first person shooter video game. Imagine looking down

the barrel of a gun and seeing humans, monsters, and demons coming at

you. What you would see is characterized by the first person shooter game.

Games such as Doom, Duke Nukem, and Wolfenstein are all examples of

this genre.

Within the levels of Quake, the player must find weapons and solve

basic puzzles in order to continue on to the next level. By using fearful

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looking creatures and gory graphics, the computer hopes to either kill or

scare the player into submission. Quake's popularity does not stop after the

body count. The advent of portable code allowed the first person shooter

game to accomplish a forbidden dream of video game players. Players can

completely customize the game. New levels, weapons, and demons are

limited only by the imagination of the creator.

Customizing Quake includes a lengthy process of creating the battle

ground, adding enemies, choosing weapons, and engineering puzzles.

Advice should be taken from PSM Magazine, a Playstation console video

game magazine, that levels should be challenging, but they should not be so

difficult as to frustrate the player. Another consideration is that many

different computer systems may attempt to play your new level. What

requirements do those machines need to meet in order to play? All of these

factors influence the customization of a video game.

A teacher could not wish for an easier opportunity to integrate

education and video gaming. Customizing video games puts forth many

problems. First, an objective should be planned and systematically executed

to reduce wasted time. Following this design plan, a linear programming

model should be used to optimize the current level design. Careful analysis Iof the new level as performed on Ray Storm then precludes a final linear

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programming analysis to determine the quality of the level. Customizing a

level in Quake then becomes nothing more than creating a organized

process from scratch. The advantages are that all factors can be controlled,

unlike in the real world, and the video game helps to maintain interest in the

project.

Hard: Experimental Procedure

Completing this undertaking requires the gathering of diverse tools

and information. Four individual programs are needed to build a valid

Quake level. First, a 3D object rendering program is needed to create the

level's map. Second, the QSBP software is needed to convert the map into a

format recognizable by Quake. Then the program Light adds light to the

level according to the number of light sources in the map and the general

physics behind lighting. Finally, the program VIS performs a packaging

algorithm to place all information about the map, including colors and

textures, into a bulk file that represents a fully compiled level. Rather than

finding and using these files individually, the program Qoole, available at

http://www.qoole.com, facilitates the creation of levels by integrating all of

the needed software. Also, included with Qoole is a helpful tutorial on

creating Quake levels for beginners.

The following text assumes that the student has access to a fully

registered copy of Quake, by ID Software. Extensive research into the

game cannot be accomplished without having full access to the game.

Analysis should be run on any given level of Quake to the same

extent as was performed for Ray Storm. Different difficulty settings should

be examined along with weapon choices and differing paths to the exit.

Unlike Ray Storm, the player has full control over discovered weapons,

attempted kills, and the physical path to the exit gate. This information is to

be gathered as in the Ray Storm example for analysis.

At this point, a statistical analysis should be run to understand the

scoring algorithm for Quake. The student may then form a linear

programming model to base the new level on. By testing the level, the

model is also tested for validity. As the level approaches completion, the

collected data can be compared to the data on the prefabricated levels by

using multiple linear regression. If the comparison shows that the levels are

similar in output, then the new level can become the sole focus of analysis.

This new level can be considered a process that can be analyzed

according to the linear programming model used to create it. The general

student can determine what weapon combination creates the maximum

number of kills during the shortest time period. The level's portability

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allows for others to analyze and edit the level as they see fit. Thus, the

education and practical uses are kept alive and always changing.

Hard: Statistical Analysis

Developing the model involves measuring different values for

weaponry, health, kills, and game secrets with respect to the time elapsed

for the level. The figure 4 shows most of a SAS program that can be used to

run a multiple linear regression on the collected Quake data.

filename game'game-data'; data one;

infile game; input time difficul$ shotgun nails armor

health secrets kills; proc GLM; CLASS difficul shotgun nails armor health

secrets kills; MODEL time = difficul shotgun nails armor

• health secrets kills difficul*shotgun difficul*nails difficul*armor difficul*health difficul*secrets difficul*kills shotgun*nails shotgun*armor shotgun*health shotgun*secrets shotgun*kills nails*armor rlails*health nails*kills health*armor health*kills armor*kills;

TITLE Analysis of Quake; run;

Figure 4

This is a condensed version of the actual program used. To save

space, many of the interaction terms were deleted to save space. Also, the

extra tests on the means and of Duncan's Multiple Range were omitted

because the concern is placed more on the interaction of the variables with

respect to time rather than the statistical differences within variable groups.

The use of this model then becomes logical for this analysis.

Statistical Analysis

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Running the SAS program revealed an interesting problem. The

means were computed, but no F-values were generated. This meant that no

statistical inference could be made using this model with this data. A new

test was run to analyze the means of the data set. By doing so, visual

analysis could then be used to find tendencies of change within the data set

Figure 5 shows an excerpt from this new analysis approach.

Level of -------------TIME------------KILLS N Mean SD

4 3 37.000000 6 3 44.000000 7 6 39.000000 1.4142136 10 6 120.500000 0.7071068 23 9 158.000000 22.6274170 40 3 130.000000 4.2426407 41 6 204.000000 16.9705627

Figure 5

This data set clearly shows that having to kill more

enemies tends to increase the time necessary to complete the

level. It also shows that there is relatively little variance in the

average time needed to kill a certain number of enemies. Some

clustering of enemies may lead to simultaneous kills. That

would then explain that the marginal time to kill an extra

enemy drops after about 23 kills.

Using the same style of analysis for the remaining data

reveals that all of the data show this tendency. It appears that

as values for the variables increase, so does the amount of time

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necessary to conclude the level. Also, as each variable

approaches its mean value, the velocity of change decreases.

After reaching the mean value, the velocity of time associated

with completing the level may continue to decrease, stop

altogether, or may even negate itself.

Hard: Conclusions

Running subsequent analyses on more prefabricated

levels and on newly constructed levels show the same

tendencies. This leads to the conclusion that the construction

of the physical map of the level may influence time. If the

available resources such as weapons, enemies, and health all

show diminishing marginal returns, then the environment

associated with those variables may hold the reason why.

The creation of the linear programming model to

associate with this process should be created using the mean

values for the independent variables as the boundaries for the

equations. This would force every variable to be as efficient as

possible in preventing the player from completing the level in a

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timely fashion. The goal is to keep the player in the game

while having a good time not letting them whisk through the

game.

Hard: Prologue

This approach allows the student to be completely

immersed in the project. Every aspect of the game can be

modified to almost any end. The teacher may then relax in

knowing that the complicated workings of operations research

are being utilized by students that actually enjoy their projects.

Expert: Speculation

The expert project is beyond the scope of this project and

this student's abilities. It is the next generation of integrating

education and video gaming by adding programming into the

curriculum. This new level converts the player into the creator.

New visionary programs are released by using statistical and

operations analysis to optimize run time, game play, and

hundreds of other possibilities. It is this point that secondary

education should try to achieve with respect to each of its

individual degree programs.

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Conclusion

Integrating video games with statistical education could

lead to new understandings about software and about

individuals. Using the games can provide real world examples

that even young children can understand. Perhaps this would

draw students into learning these more complex math

algorithms at earlier age.

Speaking on a personal level, I see great possibilities in

this educational style. The number of hours I played video

games never dropped, but each time I played, it was for a

reason. Each play had to be noted so that analyses could be

run. The statistics involved became more intuitive as I saw the

effects clearly illustrated by the next game play. I thought

about school more in general as school and the game seemed to

S interact more. My attention in other classes improved in hopes

of applying that knowledge to the game. Albeit speculation, I

believe that this can be the first step in reaching some students

with learning difficulties. Codes can't be used if the student

Scan't read. Scores can't be analyzed without math. Inferences

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can't be made without logic. Perhaps playing games at home

and school is the way to bring students back into the classroom.

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