Press Start Goal Orientation, Self-efficacy and Performance Challenge Accepted: The Impact of Goal Orientation and Self-Efficacy on Player Performance in a First-Person Shooter Game*

Abstract

The purpose of this study is to investigate how goal orientations and self-efficacy, as predictor variables, impact an individual player's performance in a First-Person Shooter (FPS) game. Online surveys were completed by 134 individuals who had played one of the pre-selected FPS games. A significant relationship between learning goal orientation (LGO), proving goal orientation (PGO) and player performance was found. There was no relationship found between avoiding goal orientation (AGO) and performance. Self-efficacy (SE) was also found to have a significant positive correlation to player performance. A mediator analysis further found that SE completely mediated the relationship between LGO, PGO and performance.

Full text

Press Start Goal Orientation, Self-efficacy and Performance
Challenge Accepted: The Impact of Goal
Orientation and Self-Ecacy on Player
Performance in a First-Person Shooter
Game*
Domenico Bellusci
SMU Guildhall
John Slocum Jr.
SMU Guildhall
Elizabeth Stringer
SMU Guildhall
Abstract
The purpose of this study is to investigate how goal orientations and
self-efficacy, as predictor variables, impact an individual player’s
performance in a First-Person Shooter (FPS) game. Online surveys were
completed by 134 individuals who had played one of the pre-selected
FPS games. A significant relationship between learning goal orientation
(LGO), proving goal orientation (PGO) and player performance was
found. There was no relationship found between avoiding goal
orientation (AGO) and performance. Self-efficacy (SE) was also found to
have a significant positive correlation to player performance. A mediator
analysis further found that SE completely mediated the relationship
between LGO, PGO and performance.
Keywords
goal orientation, self-efficacy, performance, first-person shooter,
mediation
*The authors acknowledge the constructive comments on an earlier
draft of this paper by William Cron, Don Hellriegel, Fred Luthans, Alex
Stajkovic and Don VandeWalle.
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
Introduction
First-Person Shooter (FPS) games are a video game genre where
the player must overcome a series of weapon-based combat challenges
(Evans-Thirlwell, 2017). FPS games allow the player to select the
difficulty of the game before attempting to play the game. These
difficulty settings adjust the gameplay in many ways, but ultimately
make the task at hand more challenging for the player. Applying
achievement motivational theories to the player’s choice of difficulty
setting is a potential way for FPS game designers to understand
different FPS player types and improve the balance in each difficulty
setting.
The first construct, goal orientation (GO), is based on an
achievement motivation theory that describes the genesis of an
individual’s perception towards their abilities and the effect that their
perception has on task selection (VandeWalle, Cron, & Slocum, 2001;
VandeWalle, et al., 2019). GO is distributed amongst three categories:
learning goal orientation (LGO), proving goal orientation (PGO), and
avoiding goal orientation (AGO) (Dweck & Leggett, 1988; Nicholls,
1984; VandeWalle, et al, 2019). Individuals inherently possess all three
GO categories, but usually demonstrate higher scores in one primary
category while the others play a secondary or tertiary role (Elliot &
Harackiewicz, 1996; VandeWalle, et al., 2019). The first category,
learning goal orientation (LGO), describes individuals who primarily
asses task choices as opportunities to practice their competencies in
order to improve their skills over time (Dweck & Leggett, 1988; Janssen
& Van Yperen, 2004; Nicholls, 1984; VandeWalle, et al. 2019). The
second category, proving goal orientation (PGO), describes individuals
who primarily asses task choices as opportunities to exhibit
competencies in order to receive external praise for their high
competencies (VandeWalle, 1997; VandeWalle, 2001; VandeWalle, et
al., 2001; Cron, et. al., 2005; VandeWalle, et al., 2019). The third
category, avoiding goal orientation (AGO), describes individuals who
primarily assess task choices as opportunities that could lead to failure
in order to not receive ridicule for their low competencies. GO is used to
predict….
The second motivation construct, self-efficacy (SE), is
characterized as the self-recognition of an individual’s confidence in their
inherent ability to overcome imposing challenges and achieve results
(Bandura, 1977; Kirsch, 1986; Lightsey, 1999). SE influences an
individual in three areas: task selection, effort expenditure on a task,
and task persistence. Individual SE is used to predict performance,
described as how successful an individual would be in completing a
specific task (Bandura, 1977; Bandura, 2011).
In order to determine if GO and SE are specifically applicable to a
FPS player’s performance, this study poses the following research
questions:
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
- Do a player’s goal orientations affect their performance in an FPS
game?
- Does a player’s self-efficacy affect their performance in an FPS
game?
- Does a player’s self-efficacy mediate the relationship between a
player’s goal orientations and their performance in an FPS game?
Situating the Study
Goal Orientation (GO)
The foundation of goal orientation is attributed to John Nicholls (Nicholls,
1984). Nicholls describes goal orientation as the genesis of an
individual’s perception towards their abilities and the effect that their
perception has on task selection.. Through subsequent studies, goal
orientation evolved the achievement motivation literature into a three-
category theory (VandeWalle, 1997; VandeWalle, et al., 2001; Cron,
Slocum, VandeWalle, & Fu, 2005; VandeWalle, et al., 2019). Individuals
inherently possess all three GO categories, but usually demonstrate
higher scores in one primary category while the others play a secondary
or tertiary role (Elliot & Harackiewicz, 1996; VandeWalle, et al., 2019).
Learning Goal Orientation (LGO)
LGO is a GO category that describes individuals that view their traits,
such as intelligence or persistence, as attributes that are capable of
changing through persistence over time and training. Individuals that
exemplify LGO are concerned with expanding their competencies and
focusing on continuous growth. These individuals are driven by intrinsic
motivations rather than extrinsic rewards. LGO individuals believe that
extending their effort is one vehicle for achieving success (VandeWalle,
2001). Their intrinsic motivation to continuously develop their
competencies motivate LGO individuals to select more difficult tasks
that are suited for their desired competencies.
Proving Goal Orientation (PGO)
PGO is a GO category that describes an individual who views their traits
as concrete or fixed competencies that can rarely be improved
regardless of time or effort (VandeWalle, 1997; VandeWalle, et al.,
2001; Cron, et. al., 2005; VandeWalle, et al., 2019). Individuals with
the PGO mindset are motivated by the approval of others, which comes
from the successful completion of a task more difficult than average.
These individuals are more likely to perceive imposing challenges as
opportunities to prove to others that they naturally possess the
competencies necessary to succeed. PGO individuals are not likely to
persist in difficult challenges that they believe they are failing or going
to fail.
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
Avoiding Goal Orientation (AGO)
AGO individuals possess similar attributes to PGO individuals. The
primary differentiator between the two is that AGO individuals fear social
ridicule. AGO describes an individual that views their competencies as
concrete. Competencies cannot be improved upon regardless of time or
effort (VandeWalle, 1997; VandeWalle, et al., 2001; Cron, et. al., 2005;
VandeWalle, et al., 2019). In contrast to PGO, AGO individuals do not
seek positive recognition from others. AGO individuals attempt to avoid
the invalidation of their competencies through the reception of negative
scrutiny derived from failing tasks. To avoid negative situations, AGO
individuals select tasks based on their interpretation of their
competencies.When AGO individuals perceive their competencies as
inadequate, they attribute their failure to the difficulty of the task itself
rather than their competencies. AGO individuals will also select the
easiest task available when they believe they are not equipped with the
necessary competencies to succeed in more challenging tasks. AGO
individuals, like PGO individuals, rarely develop the competencies
necessary to master challenging tasks, due to their fear of social ridicule
for failed attempts.
Self-Ecacy (SE)
Originally developed by Bandura, SE is characterized as the self-
recognition of an individual’s confidence in their inherent ability to
overcome imposing challenges and achieve results (Bandura, 1977;
Kirsch, 1986; Bandura et al., 1999). SE accounts for the regulation of
behavior, as well as the expectation of the outcome when an individual
is faced with a challenge . Individuals with high SE have a stronger
belief in their abilities and attempt more difficult tasks than low SE
individuals. Individuals with low SE have less confidence in their abilities
which limits the tasks they are willing to attempt. SE influences which
tasks an individual chooses to attempt (Bandura, 1977; Kirsch, 1986;
Stajkovic & Luthans, 1998; Bandura, 2011; Cooper et. al., 2018).
SE influences an individual’s behavior in three areas: task selection,
expenditure of effort on a task, and task persistence. High SE individuals
create stretch goals that they believe they can achieve. These
individuals are confident in their ability to perform at a high level.
Theseindividuals are more likely to persist, regardless of the setbacks or
obstacles they may encounter, than low SE individuals. High SE
individuals will take the opportunity presented and challenge themselves
to become better at that specific task. Individuals with low SE will
decline the opportunity to create a personal challenge. They do not
believe they possess the ability to achieve the goal. Low SE individuals
perceive their efforts as futile. This is because they believe that they do
not possess the competencies necessary to succeed. They are not likely
to persist through adversity. Low SE individuals are more likely to dwell
on a previous experience that inhibits their ability to perform (Bandura,
1977; Kirsch, 1986; Stajkovic & Luthans, 1998; Bandura, 2011; Cooper
et. al., 2018).
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
Mediation
Mediation is the process of a secondary variable that influences the
relationship between an independent variable and a dependent variable
(Baron & Kenny, 1986). The purpose of mediation is to explore the
possibility of external forces that can affect an outcome through process
analysis. The direct effect (c) between an independent variable (X) and
the dependent variable (Y) is explained through the unmediated model
shown in Figure 1.
Figure 1. Unmediated Model
The mediated model accounts for the change in the direct effect (c’)
between the two variables when a third variable (M) is introduced to the
relationship as shown in Figure 2. In the present study, X represents a
person’s GO, M represents a person’s SE, and Y represents a person’s
performance.
Figure 2. Mediated Model
There are four main steps to test mediated regression. First, the
independent variable must be related to the mediator variable,
represented by variable b in Figure 2 (Baron & Kenny, 1986). The
second requirement that must be met is the independent variable must
be significantly related to the dependent variable, represented by
variable c in Figure 1 . Third, the mediator must be related to the
dependent variable, represented by variable b in Figure 2 (Baron &
Kenny, 1986). Fourth, the relationship between the independent
variable on the dependent variable must be significantly influenced or
eliminated when considered in combination with the mediator variable .
This reaction is represented by variable c’ in Figure 2.
The three results of mediation are: complete mediation, partial
mediation and no mediation (Baron & Kenny, 1986). If the fourth step
returns with the relationship between the independent variable, the
dependent and the mediator are eliminated, this is known as complete
mediation. Complete mediation recognizes a mediator variable that
removes the cause and effect relationship between the independent and
dependent variables. Partial mediation recognizes a significant decrease
in the relationship but is still different from zero. No mediation
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
recognizes when there is little to no influence on the relationship
between the independent and dependent variables by the process
variable.
Hypothesis Development
This study’s hypotheses were developed around the initial research
questions:
Does a player’s goal orientation affect performance in an FPS game?
Does a player’s self-efficacy affect performance in an FPS game?
Does a player’s self-efficacy mediate the relationship between a
player’s goal orientation and performance in an FPS game?
To answer the first two research questions, researchers need to confirm
the presence of a significant association between the independent
variables, LGO, PGO, AGO, and SE, and the dependent variable,
performance.
Hypothesis One: Individuals with higher LGO have a higher
performance than those with lower LGO.
Hypothesis Two: Individuals with higher PGO have a higher
performance than those with lower PGO.
Hypothesis Three: Individuals with higher AGO have a higher
performance than those with lower AGO.
Hypothesis Four: Individuals with higher SE have a higher
performance than those with lower SE.
This study explores a single mediation variable: self-efficacy. The
selection of SE as the mediation variable was derived from
recommendations of previous case studies regarding motivation
literature (Elliot & McGregor, 1999; VandeWalle, 2001). A meta-study
by Luthans and Stajkovic (1998) examined 114 cases and concluded SE
improved performance by 28%. The fact that GO is understood as a trait
suggests that SE can influence the relationship between an individual’s
GO and their performance because SE is domain-specific. That is, an
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
individual’s SE can change depending on the situation. The mediation
model in Figure 3 proposes that self-efficacy mediates the relationship
between GO and performance.
Figure 3. Self-Efficacy Mediation Model
Hypothesis Five: The relationship between LGO and performance is
completely mediated by SE.
Hypothesis Five is based on LGO theory and the recognition of an
individual’s competencies during task selection. LGO individuals focus on
continuously improving their competencies towards mastery. Improving
those competencies requires recognition of an individual’s competencies
and their ability to utilize their competencies to overcome challenges.
Hypothesis Six: The relationship between PGO and performance is
completely mediated by SE.
Hypothesis Six is based on PGO theory and the recognition of an
individual’s competencies during task selection. PGO individuals focus on
setting goals that demonstrate to others that they are capable of
performing the task. PGO individuals are interested in showing their
competencies to others but take little interest in attempting difficult
tasks. They undertake tasks where success is ensured. The concept of
SE may influence how much time and effort PGO individuals spend
trying to impress others. PGO individuals would need to recognize not
only their competencies but also estimate their competitor’s
competencies.
Hypothesis Seven: The relationship between AGO and performance
is completely mediated by SE.
Hypothesis Seven is based on LGO theory and the recognition of an
individual’s competencies during task selection. AGO individuals seek to
avoid challenging tasks that might illustrate the failure to achieve their
performance goal. AGO individuals lack confidence in their ability to
succeed. Their lack of confidence consequently lowers their SE. Their
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
lower SE occurs due to their belief of likely failure, regardless of effort.
They are likely to dwell on obstacles, hindering their ability to perform or
complete the task.
Method
Overview
The study’s research methodology was based on previous research in
the fields of GO and SE. This study uses a web-based questionnaire to
measure GO, SE, and performance. The questionnaire included a GO
scale (VandeWalle, 1997) and a self-efficacy scale (NGSE) (Chen, 2001).
Participants were solicited at FPS domain-specific groups on the social
media website Facebook.com, as well as other domain-specific
subreddits on the forum website Reddit.com. These specific groups were
intentionally targeted for players who had played at least one of the
selected titles. All participants consented as 18 years or older while no
other demographic data was collected. Participant data was only
included if the participant had played a minimum of one title and
completed the entire survey. A total of 134 usable responses were
collected.
Goal Orientation
Learning, proving, and avoiding goal orientations were measured by a
13-item instrument developed by VandeWalle (1997). A 7-point Likert
scale ranging from strongly disagree (1) to strongly agree (7) was used.
The instrument consists of five items that are used to measure an
individual’s LGO, four items that measure an individual’s PGO, and four
items that measure an individual’s AGO. The internal reliabilities of each
scale are shown in Table 1.
Self-Ecacy
Self-efficacy was measured by Chen’s self-efficacy scale NGSE (Chen,
2001). The NGSE consists of 8-items measured on a 7-point Likert
scale. The items that explicitly stated “tasks” were substituted with the
wording “video games”. For example, “Compared to other people, I can
do most tasks very well.” was operationalized into “Compared to other
people, I can play most video games very well.” The internal reliabilities
of each scale are shown in Table 1.
Performance Operationalization
The titles selected for this study are Battlefield V (BFV), Bioshock
Infinite (BI), Call of Duty: WWII (COD), and Rage 2 (R) (2K Games,
2016; Activision, 2018; Electronic Arts, 2018; id Software, 2019). A
questionnaire was sent out to a sample of graduate students and faculty
at a video game development school; asking if these four titles were all
categorized as FPS titles. The questionnaire was measured on a 5-point
Likert scale, ranging from strongly disagree (1) to strongly agree (5). Of
the 36 participants, 29 strongly agreed with categorization, five slightly
agreed and two neither agreed nor disagreed. The survey had a mean of
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
4.75 indicating that the majority of participants agreed that these four
titles represented the FPS genre.
Each title contained four difficulty settings selections for the single-
player experience that were roughly equivalent across titles, ordered
from least to most difficult. Battlefield V’s difficulty settings were: Easy,
Medium, Hard, and Hardcore (Electronic arts, 2018). Bioshock Infinite’s
difficulty settings were: Easy, Normal, Hard, and 1999 Mode (2K Games,
2016). Call of Duty: WWII’s difficulty settings were: Recruit, Regular,
Hardened, and Veteran (Activision, 2018). Rage 2’s difficulty settings
were: Easy, Normal, Hard, and Nightmare (id Software, 2019).
FPS players encounter changes over time in the game environment with
no time limit nor a limit to the number of attempts or iterations taken to
complete the game. These difficulty settings are designated by the
properties associated with the enemies the player must face. At higher
difficulty levels, the number of enemies is increased, the enemies’ level
of health is increased, and the player receives increased damage. Once
the player suffers enough damage, the player fails and restarts from a
previous game checkpoint to attempt the challenge again. For this
study, we did not track the number of deaths or number of attempts,
only if the player completed the game.
The player’s performance was scored up to 5-points total per game
which included the difficulty setting selection and the player's
completion state. The difficulty settings were scored: Easy (1 point),
Normal (2 Points), Hard (3 points), Extra-Hard (4 points). The player
received 1 additional point if they completed that game. Each game’s
highest scored value was five. The individual’s score was determined
based on the number of answers a participant selected. The lowest
possible score an individual could achieve on any game they played was
a one and the maximum was a 20. The internal reliability of the
performance scale was α = .72 as shown in Table 1.
The descriptive statistics, reliability coefficients, and intercorrelation
coefficients of the variables in this study are given in Table 1.
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
Scale M SD 1. 2. 3. 4. 5.
1. Performance 5.60 2.88 (.72)
2. Learning Goal
Orientation 25.91 6.43 .197* (.87)
3. Proving Goal
Orientation 15.73 6.85 .187* .366** (.86)
4. Avoiding Goal
Orientation 11.00 4.93 -.015 -.179* .337** (.80)
5. Self-Efficacy 32.45 5.87 .318** .501** .308** -.267** (.88)
Note. *p < .05. **p < .01. Coefficient alpha reported on the diagonal.
Table 1. Intercorrelation and Scale Reliability
Results
Hypothesis One proposed a significant positive relationship between LGO
and performance. As reported in Table 1, the strength of LGO and
performance is statistically significant (r = .197, p < .05). This confirms
that individuals with higher LGO are more likely to have a higher
performance than those with lower LGO. Hypothesis One is accepted;
there is a significant relationship between LGO and performance.
Hypothesis Two proposed a significant relationship between PGO and
performance. As reported in Table 1, the strength of PGO and
performance is statistically significant (r = .187, p < .05). This confirms
that individuals with higher PGO are more likely to have a higher
performance than those with lower PGO. Hypothesis Two is accepted;
there is a significant relationship between PGO and performance.
Hypothesis Three proposed a significant relationship between AGO and
performance. As reported in Table 1, the strength of AGO and
performance is not statistically significant (r = -.015, p = ns).
Hypothesis Three is rejected; there is no association between AGO and
performance.
Hypothesis Four proposed a significant relationship between SE and
performance. As reported in Table 1, the strength of SE and
performance is statistically significant (r = .318, p < .01). This confirms
that individuals with higher SE are more likely to have a higher
performance than those with a lower SE. Hypothesis Four is accepted;
there is a significant relationship between SE and performance.
For testing of Hypothesis Five, six, and seven, the interaction terms for
learning, proving, and avoiding goal orientations with self-efficacy were
included. To minimize collinearity between the main effects of self-
efficacy, goal orientations, and their interactions while ensuring the
interpretability of the interaction term, the independent variables were
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
mean-centered as Aiken and West (1991) recommend. The beta
coefficients for these analyses are reported in Table 2
Predictors Performance
Step 1
Learning goal orientation .197*
Proving goal orientation .170*
Avoiding goal orientation -.015NS
Step 2
Self-Efficacy .318**
Step 3
Learn × Self-Efficacy .124NS
Prove × Self-Efficacy .053NS
Avoid × Self-Efficacy .006NS
The beta (β) weights for equation 3 are from the final regression
equation with all 3 steps included. *p < .05. **p < .01.
Table 2. Regression Equations of Self-Efficacy against Performance.
The mediated model proposed in Hypothesis Five, six and seven were
tested with the mediated regression procedure outlined by Baron and
Kenny (1986). To confirm mediation, the first three steps must result in
significant correlations. Only after the first three steps have met the
required conditions can the final step be tested through multiple
regression statistics.
First, the results of Hypothesis One as reported in Step 1 of Table 2
confirmed the presence of a significant relationship between LGO and
performance as required. Second, the relationship between LGO and SE
as reported in Table 1 resulted in a significant relationship that satisfied
the second step. Third, as presented in step 2 of Table 2, this condition
was met with the correlation of self-efficacy with performance (r = .318,
p < .01). Fourth, the effect of the independent variable on the
dependent variable must be significantly reduced or eliminated when
jointly considered with the mediator variable. Step 3 of Table 2 shows
that when SE was added to the equation, the statistically significant beta
for LGO in Step 1 became nonsignificant. These results suggest that
self-efficacy completely mediates the relationship between LGO and
performance. Hypothesis Five is accepted; there is complete mediation
when SE is introduced to the relationship between LGO and
performance.
First, the results of Hypothesis Two as reported in Step 1 of Table 2
confirmed the presence of a significant relationship between PGO and
performance as required. Second, the relationship between PGO and SE
as reported in Table 1 resulted in a significant relationship that satisfied
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
the second step. Third, as presented in step 2 of Table 2, this condition
was met with the correlation of self-efficacy with performance (r = .318,
p < .01). Fourth, the effect of the independent variable on the
dependent variable must be significantly reduced or eliminated when
jointly considered with the mediator variable. Step 3 of Table 2 shows
that when SE was added to the equation, the statistically significant beta
for PGO in Step 1 became nonsignificant. These results suggest that
self-efficacy completely mediates the relationship between a PGO and
performance. Hypothesis Six is accepted, there is complete mediation
when SE is introduced to the relationship between PGO and
performance.
The mediated regression procedure on Hypothesis Seven was unable to
be tested. The first step of the mediated regression procedure failed as
AGO had no relationship to performance as reported in table 1 (r =
-.015, p = ns). To compare the strength of the relationships found in
Hypothesis One, Two, and Four, the researchers used Fisher’s r to z
transformation formula. The results from the formula showed that the
relationships between each of them were non-significant, allowing no
further comparisons to be made.
Discussion
Goal Orientation
H1: Learning goal orientation
Hypothesis One confirms the positive association between LGO and
performance. This is consistent with the construct’s foundation; LGO
individuals are concerned with expanding their competencies and
focusing on continuous growth when faced with a challenge. The scores
attained by high LGO participants in this study suggest that LGO
individuals focus on learning by undertaking actions to test themselves
with more difficult challenges. LGO individuals recognize challenging
situations as an opportunity for their growth and learning. When LGO
players select a higher difficulty in the game, they are moving closer to
mastering the game. They are continuously striving to improve their
performance with every action completed through continuous effort. The
result of this study could explain why LGO individuals,compared to PGO
participants, continued to play games until completion at higher
difficulties.
Developers could utilize this information regarding LGO individuals to
understand their design decisions regarding the difficulty of the game.
To account for the mastery component of LGO, developers should create
overt tiered style challenges that are specific to mastering an in-game
competency. In other FPS games, developers have used challenges that
are identified as mastery challenges for each weapon, such as tracking
headshot kills for a specific weapon, or number of rapid kills for each
weapon. The tiered aspect would come from expanding a challenge,
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
such as number of headshots kills with a pistol, and creating multiple
values that increase as the player completes the previous. These
challenges could lead LGO individuals to mastery through continuous
effort and time with each specific challenge. Designing challenges like
these in single-player campaigns removes ambiguity and affords LGO
players to satisfy their drive to mastery, create increased engagement
and competencies in the game being played.
H2: Proving goal orientation
Hypothesis Two confirms the positive association between PGO
individuals and performance. The foundation of PGO resides in
individuals proving their competencies to other individuals (VandeWalle,
1997; VandeWalle, et al., 2019). The difficulty settings in the single-
player campaign represent player competencies. Higher difficulties
require stronger intellectual and manual dexterity competencies to
overcome the more difficult challenges posed by the game.
Accomplishing this feat afforded them to receive virtual praise for their
accomplishments from their peers. PGO individuals can receive social
praise from others following the completion of a more challenging game.
These results build on existing evidence of a PGO individual’s necessity
to justify their abilities to others and could explain why PGO individuals
continued to play games until completion at higher difficulties. .
Although there is no mechanism that allows one participant to play
directly with another player in an FPS single-player campaign, there is
an opportunity for every player to discuss their performance outside of
the game itself, such as social media, face to face conversation, etc.
Developers should design overt challenges with exclusive rewards for
the single-player game that appeals to PGO gamer. Developers have
used these challenges in other areas of gameplay within FPS games. An
example of an exclusive reward would be the weapon camouflage
available in the COD multiplayer known as dark matter or platinum
(Activision, 2018). These weapon camouflages are only accessible to the
players who have completed every challenge relating to all weapons
available at launch in the game. Designing of rewards such as these are
likely to entice PGO players into having a higher performance as they
have a tangible reward to represent their achievement and receive
praise from others.
H3: Avoiding goal orientation
The results regarding AGO confirm the existing evidence that there is no
relationship to performance. When AGO individuals perceive their
competencies as weak, they will select tasks where they can attribute
their failure to others or the task itself (Nicholls, 1984; VandeWalle, et
al., 2001; Cron, et al., 2005; VandeWalle, et al., 2019). When AGO
individuals believe they are not equipped with the necessary
competencies to succeed, they will select the easiest task possible. AGO
individuals, unlike LGO individuals, rarely develop the competencies
necessary to master challenging tasks because of their fear that failure
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
will reflect their lack of competencies and damage their self-esteem .
AGO players will select either the hardest difficulty or the easiest
difficulty in the game. AGO players will select the hardest option as a
vehicle to attribute the cause of their failure from their incompetence to
the difficulty of the game. This helps AGO players protect their ego and
their social reputation. Contrary, AGO players will also play games on
the easiest difficulty level as there is less chance of failure if the
difficulty is easier. This split in difficulty selection between the hardest
difficulty and the easiest difficulties explains the results of H3.
If the AGO player is avoiding the possibility of social ridicule, they are
shielded from negative perceptions about their abilities until they choose
to share their performance. The games selected for this study were
single-player games that present no immediate opportunity for AGO
players to be socially ridiculed. AGO players believe that selecting
difficult tasks can lead to a negative experience that they seek to avoid.
This negativity originates from the innate fear that they lack the
necessary competencies to be able to perform proficiently and as a
repercussion, may be socially ridiculed by others.
H4: Self-Ecacy
SE is important for three reasons. First, it influences the activities and
goals that players choose for themselves. High SE individuals set
challenging or stretch goals for themselves, for which they expect to be
positively rewarded for achieving (Schunk, 1984). Game developers
need to provide these individuals with accouterments (e.g. new pistols,
rifles, character uniforms) for achieving their goals. These
accouterments are outward symbols of success and serve as positive
reinforcements for high SE individuals. Second, SE influences how much
effort individuals exert when playing the game. Individuals with high SE
work hard to learn new tasks and are confident that these efforts will be
rewarded . Game developers, therefore, need to make sure that these
efforts will be positively rewarded. Third, SE influences the persistence
with which individuals stay with complex tasks. Because high SE players
are confident that they will perform well, they are likely to persist in the
face of temporary setbacks. Game developers need to ensure that
iterations will eventually be rewarded in successful game completion.
SE could be measured in-game through a tutorial mission that measures
a player’s competency and compares that competency to the player's
choice of difficulty. If a player chooses a lower difficulty than their
tutorial results, the designer could interpret that as lower SE and vice
versa. Players can improve their SE through goals and rewards . Game
developers should include challenges that represent goals and rewards
to entice these players as found in the other areas of FPS games. These
overt challenges can increase an individual’s SE when paired together,
thus, increasing the player's performance.
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
Mediation
As hypotheses 5, and 6, predicted SE mediates the relationship between
two of the goal orientations (LGO and PGO) and performance. These
results confirm the proposition that SE mediates the relationship
between GO and performance.
H5: Learning Goal Orientation (LGO) Mediation
Learning goal orientation individuals are motivated by the continuous
improvement of their competencies. Those with SE selected higher
difficulty tasks to improve their current abilities than those woith lower
SE. The recognition of an individual’s competencies allows LGO
individuals to position themselves from a clear perspective. Their
perspective isn’t driven by ego or success but rather the position that
the experience is enough to learn for future experiences. Concerning
games, the LGO player would check their competency before selecting
their difficulty for the title. If they don’t have a strong SE, they will
believe that they are not good at the game and select a lower challenge.
The lower selection would move the LGO player closer to mastery as
they are taking the next step.
H6: Proving Goal Orientation (PGO) Mediation
PGO individuals with higher self-efficacy have confidence in their abilities
but these abilities would be stretched for more difficult tasks. The
greater the challenge chosen, the greater the rewards once it is
completed. With SE driving PGO, these individuals would judge their
performance based on their ability. These individuals would also make
decisions motivated to proving their worth to others. Concerning the
FPS title, the fragility of the PGO player’s SE would be dependent on
their previous experience with the game. The domain specificity of SE on
FPS games, in this case, would be the driving factor behind their
difficulty selection. If the PGO player is new to FPS games, they would
be enticed to play the game at a lesser challenge. This might ensure
recognition and praise from their peers. If they weren’t an experienced
player, the PGO player would focus on finding a way to collect social
recognition following various successes in the title. That is, they might
ask others how well they played, or create a blog with performance data
shown. When SE was entered into the equation as a mediator variable,
the relationship between PGO and performance became mute. Only a
PGO players’ SE affected their performance.
Mediation: Self-Ecacy, LGO, PGO, and Performance
The strength of the relationships between the two valid predictor
variables (LGO, PGO) to performance were measured and compared. SE
had the greatest influence on performance. SE influenced the degree of
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
an individual’s goal orientation. The application SE is domain-specific
while GO is more general. This means an individual’s GO will not vary
from task to task, but an individual’s SE influences how the individual
perceives their abilities, selects, performs on those tasks in a particular
situation.
These results reveal that developers should recognize the importance of
creating a game that acknowledges and calibrates the game to a
player’s SE. If a player has just begun playing a game and has low SE,
the developer needs to adjust the gameplay to help promote an
individual’s SE. For an experienced gamer who has a high SE, the
developer should be able to maintain an individual’s SE by creating
meaningful experiences where the player can succeed earlier in the
game. Developing a difficulty system that adjusts based on a player’s
self-efficacy can improve player retention and player performance. The
gameplay difficulty should have a bell shaped curve that accounts for
the game’s gameplay throughout the story.
Starting the game with easier optional challenges that progressively
become more difficult would reinforce the player’s SE in a positive way.
These early challenges could help generate SE in players through
positive reinforcement. Giving direct opportunities, such as timed or
accuracy challenges, helps improve skill and gives a reward for
completion.Opportunities that are not tied to the story but allow the
player to create the understanding that they are capable of completing
future tasks, are needed. These satisfy the motivations of LGO and PGO
players while building their SE. Once players have increased SE, they
are more likely to then select higher difficulties and play longer. The
results of H5 and H6 both reinforce the idea that players want to play
games they believe they can win.
Limitations and Future Research
One of the limitations in this study is that the single-player experience
did not afford the social interactions that AGO individuals fear. The
single-player aspect of first-person shooters limited the study to socially
isolated experiences that lacked opportunity for social influence to be
placed upon the player. Future studies should explore different video
games that do not rely on single-player gameplay. For example, Rhythm
games have a unique opportunity for a future case study, due to their
inclusion of a social game mechanic that ties into all three GOs. Games
such as Rock Band 4, Dance Dance Revolution and Guitar Hero 3 allow
multiple people to play at the same time in the same location allowing
for social pressure or interaction to be created (Activision, 2007;
Harmonix Music Systems, 2015; Konami, 1998). Regarding Rock Band
4, each instrument has five difficulty settings that can be compared to
one another, if players played multiple instruments. There is a 5-star
scoring system integrated within the game that could be used to
measure performance as well as a numerical score. The control variable
(e.g. specific songs in a premade setlist) could represent various
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
difficulty categories for each instrument. Other rhythm games, such as
Dance Dance Revolution, pose the same potential in a more refined
domain for future research (Konami, 1998). However, the physicality of
these games may have an unknown effect on the results.
Another limitation of this study would be the performance measurement.
The development of a scale that increases the weight of task completion
would attest to the player’s persistence through adversity. No questions
were inquiring about the individual’s competency level, years spent
playing, or if the participant was an experienced gamer. Participants
were also not required to share their number of deaths, iterations or the
amount of time played. If these questions were posed, researchers could
have acknowledged or compared an individual’s difficulty selection in
each title to that individual’s previous experience, allowing further
exploration into goal setting and video games.
Another future study could explore the creation of a new measurement
that examines AGO & SE to performance. AGO individual’s preference to
offload failure onto the task, as well as select the easiest task, was not
implemented. Thus, researchers were unable to explore the possible
mediation application of SE as a mediator variable. A scale scored to
measure the highest and lowest difficulty settings in a game as larger
values than the difficulties in between would be a necessary
development for future research.
Conclusion
The impact of SE as a mediator of other achievement constructs
illustrates for developers that if their audience does not believe in their
competencies when playing their game, they will not play games at
higher difficulties or complete them. LGO & PGO can be used to
motivate players within the games to select more difficult tasks.
Developers who design challenges to increase a player’s SE in their
single-player FPS games should have players who perform better.
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Appendix A
Construct Item
Learning Goal Orientation (LGO) I am willing to select a
challenging video game that I
can learn a lot from.
I often look for opportunities to
develop new skills and
knowledge.
I enjoy challenging and difficult
tasks in video games where I'll
learn new skills.
For me, the development of my
gaming ability is important
enough to take risks.
I prefer to play games that
require a high level of ability
and talent.
Proving Goal Orientation (PGO) I'm concerned with showing
that I can perform better than
my friends.
I try to figure out what it takes
to prove my abilities to others
in the game.
I enjoy it when others are
aware of how well I am doing.
I prefer to play games where I
can prove my ability to others.
Avoiding Goal Orientation (AGO) I would avoid taking on a new
challenge if there was a chance
that I would appear rather
incompetent to others.
Avoiding a show of low ability is
more important to me than
learning a new skill.
I'm concerned about taking on a
challenge in a game if my
performance would reveal I had
a low ability.
I prefer to avoid situations in
games where I might perform
poorly.
Note. Items 6, 7, and 8 were operationalized to focus specifically on
tasks within video games.
Table 4. Video Game Goal Orientation Scale (Operationalized)
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Bellusci et al. Goal Orientation, Self-efficacy and Performance
Appendix B
Construct Item
New General Self Efficacy
I will be able to achieve most of
the goals that I have set for
myself.
When facing difficult tasks, I
am certain that I will
accomplish them.
In general, I think I can obtain
outcomes that are important to
me.
I believe I can succeed at
almost any endeavor to which I
set my mind.
I will be able to successfully
overcome many challenges
while playing video games.
I am confident that I can
perform effectively in many
different video games.
Compared to other people, I
can play most video games
very well.
Even when things are tough, I
can perform quite well.
Note. Items 5, 6, and 7 were operationalized to focus specifically on
tasks within video games.
Table 5. New General Self Efficacy Scale (Operationalized)
22