The Journal of Psychology, 2010, 144(3), 221–242
2010 Taylor & Francis Group, LLC
The Role of a Vivid and Challenging
Personal Vision in Goal Hierarchies
ALINE D. MASUDA
EADA, Barcelona, Spain
THOMAS D. KANE
CAROL F. SHOPTAUGH
Missouri State University
KATHERINE A. MINOR
Ameren Services Corporation
ABSTRACT. This study examines personal vision and its role in human motivation. It
examines the concept of personal vision within goal hierarchies, describes the elements
that constitute goal hierarchies, and examines the effect of students’ compelling personal
vision on the quality of proximal goals. Asking participants to describe their expected or
compelling personal vision did not inﬂuence the difﬁculty and vividness of such vision.
Instead, individual differences overrode the manipulations with some students conceptu-
alizing a more challenging and vivid personal vision compared to others. Students who
naturally set a challenging and vivid personal vision also set more difﬁcult and speciﬁc
college goals. Students who conceptualized a vivid personal vision were more committed
to their semester goals.
Keywords: aspirations, compelling, goal hierarchies, goals, personal vision
BANDURA (1997) ARGUED THAT PEOPLE POSSESS multiple systems of
goals, hierarchically arranged from proximal goals to extreme distal goals. With
respect to goal hierarchies, he argued that distal goals (i.e., higher order goals) and
proximal goals serve different motivational functions. Proximal goals regulate im-
mediate motivation and action, which provide ongoing feedback and a sense of per-
sonal mastery. In contrast, distal goals deﬁne desired and enduring aspirations that
A version of this article was presented at the Society for Industrial Organizational Psychol-
ogy 2002 Congress, Toronto, Ontario, Canada. The authors thank Edwin Locke and Kevin
Williams for providing comments on earlier versions of this article.
Address correspondence to Aline D. Masuda, EADA, C/Arag´
o 204, Barcelona, Spain
CP 08011; email@example.com (e-mail).
222 The Journal of Psychology
attract individuals toward meaningful destinations. Bandura’s (p. 136) argument
that proximal goals “subserve broader goals that reﬂect matters of personal impor-
tance and value” is consistent with his notion of logically connected goal systems.
Despite theorists’ general recognition that both distal and proximal goals drive
motivated behavior (e.g., Carver & Sheier, 1981; Cropanzano, Citera, & Howes,
1995; Donovan & Williams, 2000; Kernan & Lord, 1990; Ohbuchi & Tedeschi,
1997), few studies have examined the role of meaningful distal goals within
goal hierarchies. Instead, most goal-setting studies have examined the role of
quantitative task goals on performance (Locke & Latham, 1990). Understanding
the relationships of higher order goals with proximal goals and clarifying the
differences among goal constructs is essential to advancing goal theory. Hence, the
current study examines the effect of higher order goals on goal-setting processes.
Based on Bandura’s (1997) social cognitive theory, we deﬁne higher order goals
as personal vision and argue that the primary role of a personal vision is to instill
purpose to move towards a meaningful destination. We further argue that personal
vision inﬂuences motivation indirectly via the setting of proximal task goals. We
draw from goal-setting theory (Locke & Latham, 1990) to identify the content of a
compelling personal vision. A compelling personal vision is vivid and challenging
and stimulates the setting of and commitment to difﬁcult and speciﬁc proximal
A Description of Goal Hierarchies
Research has shown that goal hierarchies play a fundamental role on human
motivation (Bandura, 1997; Locke & Latham, 1990). Central to the concept of
goal hierarchies is the property of goal proximity, which deﬁnes how far goals
are conceptualized into the future. At least three levels of goals exist within goal
hierarchies: peak goals, distal goals, and task goals. Peak goals are the most
distal outcome a person can imagine in any life domain (e.g., family, professional,
social). An example of one’s peak goal may be “I will own my own law practice
within 10 years of graduating from law school.” Individuals may have peak goals
in different life domains (e.g., family or work domain).
A set of distal goals can be subordinate to peak goals. For instance, “graduating
from law school, becoming a lawyer, and gaining name recognition” may be
conceived by an individual as necessary for owning his or her own law practice
in the future. Distal and proximal goal distinctions are relative; that is, a distal
goal (e.g., gain admittance to college) may subsume relatively long-term yet more
proximal goals (e.g., graduate from college). Hence, the proximal goal distinction
is not absolute and relies on another goal’s providing the temporal context. The
interconnected conglomeration of peak goals and distal goals (i.e., higher order
goals) are referred to in this study as personal vision.
Subservient to distal goals are task goals, which, when active, direct and
sustain immediate self-regulatory processes. Task goals are proximal goals that
Masuda, Kane, Shoptaugh, & Minor 223
“generate self satisfaction from personal accomplishments that operates on its
own reward during the pursuit of higher level goals” (Bandura, 1997, p. 136).
Task goals serve two functions. First, task goals stimulate the search for or use
of strategies needed to accomplish distal goals (Locke & Latham, 1990). Second,
task goals provide a standard for evaluating the effectiveness related to the strategy
used or the effort allocated to pursue such goals. For example, a task goal might
be deﬁned as “getting an ‘A’ on my next political science exam.” Once deﬁned,
task goals may promote the development of study strategies (e.g., reading the text
and knowing all term deﬁnitions), time management strategies (e.g., not going
out on Friday night), and effort allocation (e.g., spending more time studying
political science instead of math). Both effort and strategies can be anchored to a
speciﬁc task goal. Thus, progress toward task-goal attainment provides feedback
that permits self-regulation. That is, based on the nature of feedback to task-goal
discrepancies, one may choose to regulate effort, change strategies, change levels
of goal difﬁculty, or give up pursuing goals (Bandura, 1997; Carver & Sheier, 1981;
Williams, Donovan, & Dodge, 2000). Most research on goal setting investigates
task goals (Locke & Latham, 1990).
It is important to distinguish task goals and strategies. The former deﬁnes
what is to be accomplished, and the later deﬁnes how it is to be accomplished
(Wood & Bandura, 1989). Hence, strategies do not deﬁne future outcomes, but
rather they deﬁne behavioral or cognitive activities that, if employed, lead to the
attainment of such outcomes.
In deﬁning components of goal hierarchies, distinguishing between values
and goals is also important. Schwartz has blurred the distinction between values
and goals, by not only deﬁning values as “goals, varying in importance that
serve as guiding principles in people’s lives” (1994, p. 21), but also asserting
that values are more abstract “cognitive representations of motivation in the form
of goals” (Roccas, Sagiv, Schwartz, & Knafo, 2002, p. 793). In this article, we
adopt Roskeach’s distinction between goals and values that describes value as
deﬁned principles of conduct, which involves judgment of worth or goodness
(Roskeach, 1973). Adopting this view puts forth values and goals as related but
distinct constructs. Speciﬁcally, values are more abstract cognitions and guiding
personal principles that inﬂuence the setting of personal goals. According to our
framework, personal values not only tend to be embedded in higher order goals,
but also may guide the goal-setter’s cognition and action as one pursues one’s
goals (e.g., “I will not entertain cheating as a viable option for attaining my ‘A’ on
my political science exam”). Last, although we acknowledge the importance of
needs in motivation, it is not within the scope of this article to investigate the effect
of values (or needs) on proximal goals; instead, we focus on the arrangement of
goals that constitutes a person’s personal vision.
Hence, based on the deﬁnition of constructs within goal hierarchies, we argue
that personal vision is more likely to reﬂect the set of personal values compared
to task goals or strategies. Figure 1 illustrates one’s complete hierarchical goal
224 The Journal of Psychology
FIGURE 1. The model of personal vision within hierarchical goal structures.
Personal Vision is deﬁned as the group of Distal goals and Peak Goals repre-
sented above the dotted line.
structure and the distinctions among strategies, task goals, distal goals, peak goals,
values, and personal vision.
The Importance of Personal Vision
Despite the scarce empirical attention given to personal higher order goals
(Roberts & Robins, 2000), many theorists have agreed that higher order goals play
a substantial role in human motivated activity (Bandura, 1997; Cropanzano, James,
& Citera, 1993; Kanfer, 1990; Locke & Latham, 1990, 2002). For example, con-
structing long-term goals has appeared in (a) various literatures including those of
social cognitive theory (Bandura), personality theories (Cropanzano et al., 1993),
and goal theory (Locke & Latham, 1990); and (b) descriptions of companies’
organizational vision (Larwood, Falbe, Krieger, & Miesing, 1995). According
to Bandura’s social cognitive theory, possible futures and proximal goals that
aid in future goal attainments are key elements of human motivation. Peak and
distal goals that compose one’s personal vision direct, motivate, and sustain self-
regulated activity, effort, and planning (Bandura). In a similar vein, Cropanzano
et al. (1993) explained that higher order goals deﬁne relatively abstract values
and self-identities that guide one’s activities and plans. Cropanzano et al.’s (1993)
characterization of higher order goals is analogous to the concept of personal vi-
sion in that personal vision deﬁnes values and for this reason inﬂuences personal
Masuda, Kane, Shoptaugh, & Minor 225
Empirical evidence supports the content of higher order goals as related
to lower level goals. For example, Schepers and Beach (1998) found that high
discrepancy between one’s ideal future and one’s expected future led to revisions
in participant’s current goal-planning activities. Speciﬁcally, people who perceived
a high discrepancy between their ideal and expected futures changed their proximal
goals so that such goals facilitate the attainment of their idealized future.
The importance of distal goals is also emphasized in the literature on vision-
ary leadership. In this literature, a leader’s vision for organizations shares traits
with the concept of personal vision (Kirkpatrick, Locke, & Latham, 1996). Like
personal vision, a leader’s vision reﬂects values, and its enactment depends upon
subordinate goal systems in an organization. For example, Collins and Porras
(1991) deﬁned organizational vision as composted of (a) a system of fundamental
motivation assumptions, principles, values, and tenets (i.e., guiding philosophy)
and (b) goals that convey a sense of concreteness (i.e., tangible images). In ad-
dition, theories of organizational change (e.g., Lawsen & Shen, 1998) emphasize
the utility of a unifying organizational vision for aligning subordinate organiza-
tional goals. In fact, Kirkpatrick and Locke (1996) showed the importance of a
leader’s vision when motivating employees to set their goals. Speciﬁcally, those
researchers found that participants who were told by leaders about their organiza-
tional vision set more difﬁcult and speciﬁc goals compared with participants who
were not made aware of an organizational vision.
Despite personal vision’s important role in motivated activity, there have been
few empirical studies examining the content of one’s personal vision and how it in-
ﬂuences proximal goal setting. The research examining the effectiveness of vision
has been limited to leadership vision and its effects on employees (Kirkpatrick
& Locke, 1996) and goal setting (Locke & Latham, 1990). Hence, we borrowed
from this literature and identiﬁed qualities of a compelling personal vision that
will most likely lead to the setting of effective proximal goals.
Compelling Personal Vision
A challenging personal vision should motivate the setting of more difﬁcult
and speciﬁc proximal goals. According to goal-setting theory (Locke & Latham,
1990), motivated effort stems from anticipated satisfaction linked to attaining a
difﬁcult goal. In fact, more than 400 ﬁeld and laboratory studies have shown that
people who set difﬁcult and speciﬁc task goals are likely to perform better in a task
than those who set vague or do-your-best goals (Locke & Latham, 1990). Further,
social cognitive theory stresses the importance of both discrepancy production
and reduction in explaining motivated activity (Bandura, 1997), and control the-
ory suggests that the goal-to-reality discrepancy produced by a challenging goal
generates effort (e.g., Scheier & Carver, 1985).
226 The Journal of Psychology
Research on organizational vision has also shown that challenge is an im-
portant attribute of an effective organizational vision (Baum et al. 1998; Conger
& Kanungo, 1987; Kirkpatrick, Locke & Latham, 1996; Nanus, 1992). Simi-
lar to goals and organizational vision, personal vision may become challenging
when it is difﬁcult to attain compared to the vision of an average person (Baum,
Kirkpatrick, & Locke, 1998; Conger & Kanungo, 1987; Kirkpatrick et al., 1996;
Nanus, 1992). A challenging vision will serve an energizing function by stimulat-
ing effort and persistence. In addition, a challenging personal vision will increase
the discrepancy between one’s current situation and future state, thus motivating
action to reduce such discrepancy. People’s willingness to increase effort and per-
sistence should be evident in the content of their proximal goals. Hence, we argue
that just as one’s goals may lead to higher performance if they are speciﬁc and dif-
ﬁcult, one’s personal vision may be more effective if it contains similar attributes.
An effective personal vision, however, will not directly inﬂuence performance;
instead, it should indirectly relate with performance by stimulating the setting of
difﬁcult and speciﬁc proximal goals and by facilitating commitment to such goals.
Hypothesis 1 (H1): Challenge reﬂected in one’s personal-vision statement will
predict commitment to proximal task goals.
As previously stated, speciﬁc goals improve effort more than do vague or
do-your-best goals (Locke & Latham, 1990). Although higher order goals are
more likely to be abstract than task goals (Cropanzano et al., 1993), one’s personal
vision should be more compelling if it is high on imagery. A personal vision high
on imagery deﬁnes in detail a clear and vivid picture of one’s desired future (Bass,
1985; Baum et al., 1998; Kirkpatrick et al., 1996; Thoms & Blasko, 1999). By
clearly deﬁning one’s desired future, a personal vision should better direct one’s
attention and effort to relevant tasks that facilitate movement toward that vision.
Hence, those who clearly know what they want in their future are more likely to
set speciﬁc task goals that will lead to such a future.
A vivid personal vision may also reﬂect stronger, clear, and well-established
values. Research has shown that values are related with commitment to projects.
For example, Lydon (1996) found that the degree to which personal projects
afﬁrmed peoples’ core values predicted participants’ willingness to commit to
their projects, especially when participants perceived these projects as stressful
and difﬁcult. In his study, Lydon examined students’ commitment to an 8-week
volunteer work project. Results revealed that students were more committed to the
volunteer project if they reported that the project afﬁrmed their personal values.
The ﬁndings were more robust when students perceived the project as difﬁcult and
Because a vivid personal vision provides a clear picture of a future and reﬂects
well-established values, people who conceptualize a vivid personal vision will be
Masuda, Kane, Shoptaugh, & Minor 227
more committed to their proximal goals and will be more likely to set speciﬁc
proximal task goals.
H2: The imagery contained in one’s conceptualized vision statement will predict
the speciﬁcity of subordinate personal goals.
H3: The imagery contained in one’s conceptualized vision statement will predict
subordinate goal commitment.
Proximal Goals and Student Achievement
Consistent to Locke and Latham’s (1990) goal-setting theory, we expected
to ﬁnd that students who set difﬁcult and speciﬁc proximal goals would likely
achieve a higher semester grade point average (GPA) compared to those who
set easy and vague goals. Because in the current research, we employed novel
methodology for evaluating the goal difﬁculty of student’s freely reported goals
(i.e., rater’s judgments of freely reported goal), replicating an often cited goal-
setting principle in this research was important for establishing the validity of our
qualitative measure of goal difﬁculty.
H4: Difﬁculty and speciﬁcity semester goals will predict student achievement.
Undergraduate students from a university in the Midwest United States were
recruited from undergraduate psychology courses and participated in this study for
course credit. The sample consisted of 180 participants: Of them, 95 (51.4%) were
freshman, 48 (25.9%) were sophomores, 25 (13.5%) were juniors, and 8 (4.3%)
were seniors. The sample also consisted of 53 men (29.4%) and 124 women (68%).
This study was part of a broader study on personality and goals, and two
data collection periods were conducted in accordance with the ethical guidelines
put forth by the American Psychological Association and the University Human
Subjects Review for the protection of human research participants. Phase 1 took
place in a classroom with all students present. Students arrived and were given
a questionnaire with the study measures and informed consent. They read and
signed the inform consent letter and completed the questionnaire that measured
personality variables. A group of 50 participants in Phase 1 were randomly as-
signed to a repeated measures compelling vision condition, where they were asked
to report their visions during Phase 1.
In Phase 2 of the experiment, conducted approximately 3 weeks after Phase 1,
the same participants returned to complete the manipulations. Speciﬁcally, we
228 The Journal of Psychology
randomly assigned 50 students to the control condition, 51 to the descriptive
condition, and 49 to the compelling personal vision condition. Last, participants
who were assigned to the repeated measures vision condition during Phase 1 were
assigned to the same condition during Phase 2. However, of the 50 participants
assigned to this manipulation, only 29 participants returned for Phase 2 of the
study. The following were the instructions for each manipulation and the amount
of subjects included per condition.
Compelling Personal Vision (49 Participants)
Instructions for the condition of compelling personal vision were:
A compelling personal vision is a unique and ideal image of the future. Today, we
will ask you to write an optimistic portrayal of your professional future. Please
visualize the most compelling vision you can. Through visualization create a
picture of what you want most in your professional life. After visualizing your
ideal future, please describe your personal vision below. Here are some tips to
think about while you write your personal vision: Challenge yourself, be speciﬁc,
think positively. After you ﬁnished writing about your professional vision, please
complete the following questionnaire.
After participants wrote their vision, instructions directed participants to set
personal semester and proximal goals.
Descriptive Personal Vision (51 Participants)
Instructions for the condition of descriptive personal vision were:
In the space provided below, we ask that you fully describe what you believe
your professional future will look like. After you ﬁnished writing about your
professional vision, please complete the following questionnaire.
After participants wrote their vision, instructions directed participants to write
personal semester and proximal goals.
Repeated Measure Compelling Vision (29 Participants)
The instructions given in the condition of repeated measure compelling vi-
sion were similar to the instructions in the compelling vision condition. After
participants wrote their visions, instructions directed participants to write per-
sonal semester and proximal goals.
Control Condition (50 Participants)
In the control condition, participants were ﬁrst given instructions to set per-
sonal semester and proximal goals. After participants wrote their personal goals,
they were only asked to report a descriptive vision:
In the space provided below, we ask that you fully describe what you believe your
professional future will look like.
Masuda, Kane, Shoptaugh, & Minor 229
Operationally, personal vision was deﬁned as statements reported by partic-
ipants when asked to report their professional future. All participants wrote their
personal vision, and these statements were measured for the attributes of challenge
and imagery. Speciﬁcally, three raters rated the vision statements according to def-
initions of challenge and imagery. Each rater practiced rating a sample of vision
statements that contained extremes of each attribute. These vision statements were
used as prototypes when rating the remaining vision statements. Each dimension
was scored along an 8-point scale from 0 (“attribute absent”) to 7 (“attribute was
present at a higher level”). If participants indicated, by checking a box on the
questionnaire, that they did not have a vision, then they received a rating of 0. This
method of rating has been successfully implemented when rating organizational
vision (Baum et al., 1998) and has yielded respectable reliabilities. In our study,
interrater reliability was intraclass correlation coefﬁcient (ICC) =.93 for chal-
lenging and ICC =.87 for imagery. Imagery and challenge were highly correlated,
r=.81. Examples of challenging and imagery ratings are the following.
An example of a vivid (i.e., high on imagery) personal vision (7) is:
My vision of my professional life entails a number of areasin my life. I would like to
work abroad in diplomatic outpost of the United States. I would particularly enjoy
working in the political arena of the State Department. In the future, I visualize
myself speaking a number of foreign languages, such as French, Chinese, and
German. I hope to travel the world and absorb the “culture” of the UK, France,
Italy, Japan, and China. I hope to continue my passion for art and music. I will
be the guy that goes to a cafe in France on a crowed business street to drink
wine and enjoy life. I see myself participating in high adventure sports such as
mountain climbing, and kickboxing.
An example of low vivid personal vision (0) is:
I hope to choose a major that I will enjoy and ﬁnd a job where I can support
myself as well as my family with my earnings.
An example of a high challenging personal vision (7) is:
In the most compelling portrayal of my professional future I see myself in the
NFL. I see myself making millions and being wealthy enough to where I can
walk away from my job when I please to do. I see myself making it to numerous
pro bowls and playoffs.
An example of low challenging personal vision (0) is:
230 The Journal of Psychology
Academic Free-Set Goals
Students reported semester and college academic goals by writing responses
to the question “List academic goals you have set for yourself to accomplish by
the end of the semester.” This method allows the quality of student’s goals to vary.
Examples of academic goals were “Not procrastinate,” “Attend all classes,” “Get
As,” and “Get an internship.” Students were asked to list only goals set prior to
completion of the survey and were given the option to place a check mark beside
the statement “I have not set semester goals.” Space was provided for students
to list as many goals as they wished to report. Participants were asked to report
college goals in the same manner.
Goal speciﬁcity was assessed based on Locke, Chah, Harrison, and Lust-
garten’s (1989) deﬁnition that goal speciﬁcity is evident by the range and clarity
of outcomes that potentially satisfy goal accomplishment. Trained raters assessed
the goal speciﬁcity on a scale ranging from 1 (“extremely low clarity with wide
range of outcomes”) to 7 (“goal deﬁnes a concrete single outcome that deﬁnes
goal attainment, the outcome satisfying goal attainment is easily envisioned, and
behaviors required for attainment are clear”). The present goal speciﬁcity assess-
ment was devised and successfully implemented when rating goal speciﬁcity in
athletic settings (Kane, Baltes, & Moss, 2001). Raters considered two character-
istics when determining the level of goal speciﬁcity: (a) the clarity of behavior
and the range of possible outcomes that satisfy goal attainment and (b) whether
additional information could be (reasonably) reported to further reduce the range
of outcomes that satisfy goal attainment. Raters initially rated a sample of approx-
imately 50 goals from each level and discussed inconsistencies in rating. When
acceptable reliability was attained on the sample goals, the raters proceeded to rate
all goals. Interrater reliability for semester goals was ICC =.82 and for college
goals was ICC =.91 .
Trained raters assessed goal difﬁculty on 7-alternative scale ranging from 1
(“not difﬁcult”) to 7 (“very difﬁcult”). They used a norm-referenced approach to
assessment because goal difﬁculty judgments were referenced against the aca-
demically average student. The validity of norm-referenced assessment has been
supported across a broad range of settings (Wright, 1990) and in rater’s assess-
ments of free-set goals (Kane, Loughran, Shoptaugh, Nelson, & Reichard, 2002).
Researchers ﬁrst individually rated a sample of goals. Anchors were established
based on commonly reported goals for which raters consistently agreed. For exam-
ple, a goal received a rating of 1 if it was determined that it was easily attained by
anyone, even those who have below average academic ability, and included goals
such as “attend class” or “ﬁnd a major.” When acceptable reliability was attained
Masuda, Kane, Shoptaugh, & Minor 231
on the sample goals, the raters proceeded to rate all goals. Interrater reliability for
semester goal difﬁculty was ICC =.85 and for college goal difﬁculty was ICC =
Goal commitment was assessed by responses to four items attached to each
goal statement reported by the participant. Items were generated according to
conceptualizations of goal commitment that include willingness to put forth effort,
unwillingness to lower one’s goal, and goal importance (Locke & Latham, 1990).
For each goal reported, participants responded to each item on a 7-alternative scale
ranging from 1 (“Strongly agree”) to 7 (“Strongly disagree”). Internal consistency
reliability was α=.77 for semester goal commitment and α=.79 for college
Participants reported age, gender, ACT scores, class year, and major.
Student’s reported cumulative GPA was used to assess prior academic achieve-
ment, and their achieved GPA reported at the end of the semester was used to assess
To test whether our manipulations had an effect on the quality of personal
vision statements, we conducted an analysis of variance using conditions as inde-
pendent variables and challenge rated in the visions as dependent measure. Results
of the manipulations did not reveal effects on the quality of personal vision. There
were no signiﬁcant differences between mean ratings on the amount of challenge
across conditions, F(3, 173) =.51, p>.05: compelling personal vision (M=
3.47, SD =2.12), descriptive vision (M=3.63, SD =1.22), and control (M=
3.81, SD =1.07) conditions. For this reason, we used the ratings of challenge and
vividness done in all vision statements written by individuals across conditions as
independent variables. Speciﬁcally, we rated the amount of challenge or imagery
contained in each vision statement and used the composite of these ratings to
test our hypothesis within participants. For the repeated measures condition, we
analyzed the vision statements described during Phase 2.
These analyses are consistent with analyses done in previous studies of self-
regulation in the examination of the relationships among distal and proximal goals
(e.g., Kane et al., 2001), the relationship between assigned goal level and personal
232 The Journal of Psychology
goal levels (e.g., Early & Lituchy, 1991), and relationships between goals, self-
efﬁcacy, and achievement (e.g., Wood, Bandura, & Bailey, 1990).
Descriptive statistics and interrater reliability are shown in Table 1. Table 2
reports correlations among predictors and criteria for key study variables.
Students set a range of 1–11 goals. To test the hypotheses, we used two depen-
dent measures of goal difﬁculty. First, we averaged the difﬁculty and speciﬁcity of
semester and college goals across all goals reported by students. Second, we used
the most difﬁcult college and semester goals reported by students as dependent
variables in our analysis. This analysis is consistent with previous analyses of
free-set goals (e.g., Kane et al., 2002).
TABLE 1. Descriptive Statistics
Category & Variable N Range M SD r
Gender 177 1–2 1.69 0.46 —
Age 177 17–50 20.54 4.75 —
Class year 180 1–4 1.69 0.45 —
Declared major 180 0–2 — 0.45 —
Self-reported ACT 141 17–33 23.83.12 —
Number of goals 180 0–11 3.17 1.64 —
Average semester goal 176 1.73–6.17 3.49 0.92 .85a
Average college goal 174 1.22–6.33 3.45 0.97 .91a
Most college goals 174 1.33–7.00 4.36 1.2.91a
Most semester goal 175 1.33–6.33 4.44 0.93 .85a
Averaged semester 175 1.17–5.67 3.14 0.98 .82a
Averaged college 172 1.20–6.00 3.16 0.96 .91a
Semester goal 173 3.25–7.00 5.92 0.85 .77b
College goal 171 2.50–7.00 6.18 0.88 .79b
Imagery 175 0.00 –7.00 3.11 1.77 .87a
Challenging vision 177 0.00–5.78 3.25 1.39 .93a
Prior student achievement 163 1.57–4.00 3.14 3.1NA
Student achievement 138 0.69–4.00 0.66 0.7—
Note. ACT =scores in college entrance exam.
aIntraclass correlation coefﬁcient based on three raters.
bCronbach’s alpha was reported for individual member sale responses.
Masuda, Kane, Shoptaugh, & Minor 233
TABLE 2. Correlations Among Study Variables
Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
1. Gender 1
2. ACT score –.03 1
3. Age –.02 –.04 1
4. Class year .00 –.06 .31∗∗ 1
5. Number of goals .27∗∗ –.02 .10 –.04 1
6. Major undeclared –.01 –.13 –.02 .17∗.04 1
7. Most difﬁcult
.13 .29∗∗ –.03 .17∗.07 –.19∗1
8. Most difﬁcult college .09 .18∗–.10 .16∗.01 –.18∗.48∗∗ 1
9. Difﬁcult semester –.12 .18∗–.06 .18∗–.33∗∗ –.15 .62∗∗ .33∗∗ 1
10. Speciﬁcity semester –.07 .03 –.01 .16∗–.26∗∗ –.18∗.45∗∗ .30∗∗ .69∗∗ 1
11. Difﬁcult college –.04 .10 –.06 .23∗∗ –.25∗∗ –.18∗.40∗∗ .80∗∗ .46∗∗ .41∗∗ 1
12. Speciﬁcity college .02 .11 .06 .26∗∗ –.26∗∗ –.21∗∗ .36∗∗ .63∗∗ .40∗∗ .47∗∗ .76∗∗ 1
13. Semester commitment .16∗.05 –.05 .06 –.01 –.03 .02 .13 .12 .10 .15∗.20∗1
14. College commitment .15 –.05 –.06 .05 .09 –.01 .05 .14 .13 .09 .12 .14 .73∗∗ 1
15. Imagery –.01 .12 –.03 .12 .08 –.13 .17∗.27∗∗ .11 .02 .29∗∗ .22∗∗ .15 .00 1
16. Challenge –.06 .18∗–.04 .09 .02 –.06 .22∗∗ .32∗∗ .15 .06 .33∗∗ .31∗∗ .15∗.03 .81∗∗ 1
17. Prior GPA –.03 –.02 .16∗.10 .11 .06 –.04 –.06 –.10 –.05 –.05 –.02 –.09 –.08 –.01 –.02 1
18. Student achievement –.08 –.02 .01 –.04 –.08 .08 .05 –.07 –.02 –.07 .01 –.07 –.10 .00 –.11 –.03 .62∗∗ 1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Note.ACT=scores in college entrance exam.
∗p<.05. ∗∗ p<.01.
234 The Journal of Psychology
Four regression analyses were conducted. The ﬁrst two regressions predicted
semester goal difﬁculty. Results showed that prior achievement uniquely con-
tributed to the prediction of the most difﬁcult semester goal (ß =.43, p<.01) and
the averaged semester goal difﬁculty (ß =.24, p<.01), but challenging personal
vision did not add uniquely to the prediction of the semester goal difﬁcult (ß =
.03, ns) or the most difﬁcult semester goal (ß =.04, ns). (See Table 3.)
The third and fourth regression analyses predicted college goal difﬁculty.
Results indicated that challenging vision and covariates contributed 24% of the
variance in the prediction of college goal difﬁculty (R2=.24), F(4, 150) =11.32,
p<.01, with challenging vision (ß =.25, p<.01), total number of goals (ß =
–.24, p<.01), and prior GPA (ß =.16, p <.01) contributing uniquely. Last,
covariates and challenging personal vision accounted for 19% of the variance in
most difﬁcult college goals (R2=.19), F(3, 168) =9.23, p<.01. In that analysis,
only challenging vision (ß =.21, p<.01) and prior GPA (ß =.24, p<.01)
contributed uniquely to the prediction. In general, challenging vision predicted
college goal difﬁculty but not semester goal difﬁculty. (See Table 3.)
According to H1, challenging personal vision would predict goal commit-
ment. We tested this hypothesis by entering challenging vision and covariate (i.e.,
gender) in one block to predict semester and college goal commitments. Chal-
lenging personal vision and gender contributed 7% of the variance in predicting
semester goal commitment (R2=.07), F(2, 164) =6.81, p<.01, with challenging
vision (ß =.21, p<.01) and gender (ß =.20, p<.01) (i.e., men coded as 0 and
women coded as 1) contributing uniquely. In the second regression, challenging
personal vision and gender only marginally predicted college goal commitment
(R2=.03), F(2, 167) =2.63, p=.05, with only gender contributing uniquely
(ß =.17, p<.01). Hence, H1 was partially supported, with challenging vision
predicting semester goal commitment but not college goal commitment.
H2 stated that the imagery contained in one’s vision statement would be posi-
tively associated with the speciﬁcity of proximal task goals. Results showed that a
vivid personal vision and covariates contributed 11% of the variance in predicting
the mean speciﬁcity for semester goals (R2=.11), F(4, 150) =4.44, p<.01.
However, in that analysis, only number of goals reported by students (ß =–.24,
p>.01) and prior GPA (ß =.16, p>.05) contributed uniquely. In analysis
predicting college goal speciﬁcity, imagery and covariates contributed signiﬁ-
cantly (R2=.24), F(4, 148) =11.17, p<.01, with imagery vision (ß =.27,
p>.01), class year (ß =.17, p>.05), and total number of goals (ß =–.23,
p>.01) contributing uniquely. Hence, H2 was partially supported; a vivid
personal vision predicted college goal speciﬁcity but did not predict semester
H3 stated that the imagery component of personal vision would predict goal
commitment. Results showed that imagery and gender contributed 7% of the
variance in predicting semester goal commitment (R2=.070, F(2, 165) =6.63,
p<.01, with imagery vision (ß =.20, p<.01) and gender (ß =.19, p<.01)
Masuda, Kane, Shoptaugh, & Minor 235
TABLE 3. Regression Analysis: Challenge Vision as Predictors of Goal Difﬁculty
Semester goal difﬁculty College goal difﬁculty
Variable MßMostß MßMostß
Number of goals –.29∗∗ .13 –.24∗∗ —
Class year .13 .09 .20∗∗ —
ACT .09 .20∗∗ — .13
Declared major — — — –.01
Challenging vision .03 .04 .25∗∗ .21∗∗
Prior GPA .24∗∗ .43∗∗ .16∗∗ .24∗∗
R2=.20 R2=.14 R2=.24 R2=.19
F(5, 152) =7.70∗∗ F(5, 151) =14.91∗∗ F(4, 150) =11.32∗∗ F(4, 168) =9.23∗∗
Note. ACT =scores in college entrance exam.
236 The Journal of Psychology
TABLE 4. Regression Analysis: Imagery Vision as Predictors of Goal Speciﬁcity and Goal Commitment
Mgoal speciﬁcity Goal commitment
Variable Semester College Semester College
Predictors set ß ß ß ß
Number of goals –.24∗∗ –.23∗∗ NA NA
Class year 0.14 .19∗∗ NA NA
Gender NA NA .19∗∗ .22∗∗
Imagery vision 0.02 .27∗∗ .20∗∗ .08
Prior GPA .16∗.17∗NA NA
R2 =.11 R2=.24 R2=.07 R2 =.05
F(4, 150) =4.44∗∗ F(4, 148) =11.17∗∗ F(2, 165) =6.63∗∗ F(2, 163) =4.54
Note. For the variable of gender, men were coded as 1, and women were coded as 2.
Masuda, Kane, Shoptaugh, & Minor 237
contributing uniquely. In the second regression, imagery and gender did not predict
college goal commitment. Hence, H3 was partially supported with vivid vision
predicting semester goal commitment but not college goal commitment.
Lastly, H4 stated that the difﬁculty and speciﬁcity of subordinate goals would
predict student achievement. Because difﬁculty and speciﬁcity of goals were
highly related, we only tested the effects of goal difﬁculty on student achievement.
Consistent with goal-setting theory, difﬁcult goals predicted student achievement.
Results showed that the most difﬁcult semester goal and prior GPA predicted 39%
of the variance in student semester GPA (R2=.39), F(2, 108) =34.45, p<
.01, with prior GPA (ß =.53, p<.01) and most difﬁcult semester goal (ß =.16,
p<.05) predicting uniquely. A similar regression analysis was conducted using
average semester goal difﬁculty and prior GPA as independent variables. Results
showed that both variables predicted 38% of the variance in student GPA (R2=
.38), F(2, 109) =33.98, p<.01, with prior GPA (ß =.59, p<.01) and averaged
difﬁcult semester goal predicting uniquely (ß =.11, p=.05).
While goal hierarchies and meaningful distal goals occupy an important place
in motivational theories of self-regulation, the empirical study of such goal hierar-
chies has been rarely broached. A prime theoretical purpose of the present project
was to examine connections among goals in hierarchical structures and achieve-
ment. Bandura (1997) offered that higher order goals in hierarchical structures
provide meaning to the attainment of subordinate task goals. In support of this
assertion, we found that the attributes of one’s personal vision predicted students’
commitment to their semester goals. Speciﬁcally, the extent to which a student’s
personal vision is challenging and vivid positively related with his or her attach-
ment to semester task goals, unwillingness to lower these goals, and intended
effort to attain these goals. Note that challenge and speciﬁcity inherent to col-
lege goals were unrelated to semester goal commitment, providing evidence that
commitment to proximal goals is most potently affected by goals that are high in
one’s goal structure. This ﬁnding implied that the role of higher order goals in
motivational systems is different from the role of task goals.
Also theoretically relevant, ﬁndings indicated that challenge inherent in higher
order goals associated positively with challenge at a subordinate level of the
hierarchy. That is, one’s personal vision affected college goal difﬁculty, and college
goal difﬁculty was associated with the difﬁculty inherent to semester goals. Similar
pattern was found with the vividness and speciﬁcity of goals. These ﬁndings
provide support for Bandura’s (1997) contention that people possess logically
connected goal systems. However, a lack of relationship between the qualities
of one’s vision and semester goal difﬁculty indicates that college goals did not
mediate effects of personal vision on semester goals. Possibly, factors not measured
in our research inﬂuence the effects of goals atop goal structures on proximal
238 The Journal of Psychology
goals. A logical moderator is the perceived relevance of semester goals to the
advancement towards one’s personal vision. If the attainment of semester goals,
for instance, was unrelated to the realization of one’s personal vision, then it
would not be reasonable to expect a connection between the challenge contained
in one’s vision with the difﬁculty of semester goals. The perceived relevance of
subordinate goals to one’s personal vision might also strengthen the relationship
between the qualities of one’s vision and proximal goal commitment.
Although previous studies have investigated the effects of distal and prox-
imal goals (e.g., Donovan & Williams, 2003; Latham & Seijts, 1999, 2001) on
motivated behavior, our study was the ﬁrst to examine the nature of people’s ex-
tremely distal aspirations (i.e., personal vision) in relation to subordinate goals.
While we were unable to manipulate the content of personal vision, we observed
variation in the content of personal vision reported across individuals. Students
who described a challenging and vivid personal vision were naturally more likely
to set difﬁcult and speciﬁc college goals. That is, individuals who had a clear idea
of where they want to be in 10 years and who were also ambitious were more
likely to challenge themselves by setting difﬁcult and speciﬁc college goals. These
ﬁndings may suggest that compelling personal visions are difﬁcult to craft and
that individual differences are likely to relate with ones ability to craft a com-
pelling personal vision. Studies exploring antecedents of personal visions may be
Clearly deﬁning and differentiating goal concepts within goal hierarchies is
important so that we can better understand their role in human motivated activity.
The current study suggests that personal vision and goals should serve different
functions relative to motivated activity. Our ﬁndings encourage further studies ex-
amining the role of commitment across different levels of goals within hierarchies
to predict achievement. For example, it would be interesting to explore whether
commitment to one’s personal vision is more important in the self-regulation pro-
cess than commitment to task goals. The principle of equiﬁnality comes to mind
in that there are many different ways to reach an end. A study done by Donovan
and Williams (2003) on goal revisions of athletes showed that athletes tended to
revise proximal goals while keeping the level of difﬁculty of distal goals constant.
Thus, we can speculate whether commitment to personal vision may lead to higher
performance compared to commitment to proximal goals. Future studies examin-
ing the relationships among motivational variables such as goal commitment and
self-efﬁcacy at different levels of goal hierarchies may advance our knowledge of
The limitations of the present study must be acknowledged. Our attempt to
manipulate the quality of one’s personal vision failed. As such, we cannot assume
that a challenging and vivid image caused the setting of difﬁcult and speciﬁc
goals. It is also plausible that the content of proximal goals inﬂuenced the degree
Masuda, Kane, Shoptaugh, & Minor 239
of challenge or image inherent in one’s personal vision. For example, Weldon
and Yun’s (2000) study revealed that a team of nurses with both proximal and
distal goals performed better and tended to set more difﬁcult long-term goals
compared to those who had distal goals only. Also, it is equally possible that the
relationship between proximal goals and personal vision is one of reciprocity, such
that inﬂuencing either the top or bottom of the hierarchy will lead to changes in
self-regulation. For example, a person who sets difﬁcult proximal goals related to
a subject (e.g., getting an “A” in biology) and who succeeds may develop a more
vivid and challenging vision related to sciences (e.g., getting a Ph.D. in biology).
In this example, proximal goal setting and attainment inﬂuenced the vividness and
difﬁculty of a vision. Future studies exploring this relationship by using stronger
manipulations or longitudinal designs would be highly desirable. These studies
may provide insight on how individuals develop their aspirations and ambitions.
Further, because our sample consisted of undergraduate psychology students,
one should also be cautious when generalizing these results to other settings.
In business settings, the quality of one’s personal vision may vary according to
tenure, age, and job position. For example, workers may be less optimistic and
more realistic regarding their professional future based on their experiences.
Understanding the importance of personal vision in motivation may be of
utility to understand how individuals develop their career paths and their visions.
For example, career counselors may be more equipped to help students to plan
their career paths by understanding how individuals develop ambition and craft
a vivid personal vision. The fact that vividness was important for semester goal
commitment may be indicative of the importance of deﬁning one’s values and
learning about one’s priorities early in life.
Examining personal visions can also be useful when selecting employees for
managerial positions. Personal goals are commonly used as criteria for selection,
whereas applicants are asked to report their professional goals and often their
professional future (i.e., selection interview, assessment center). For example,
Howard and Bray (1988) found that the level of career aspiration was the single best
predictor of career progress in the 25-year longitudinal study of AT&T managers.
Because of the importance of personal vision for managerial success, training
recruiters to identify compelling personal visions may be of utility when selecting
Last, this article should encourage further studies to examine the content of
personal vision in goal hierarchies related to personality characteristics such as
ability, personality, and values. That is, which personality variables could explain
differences in people’s ability to conceptualize their personal future? Understand-
ing differences in people’s ability to craft a vivid vision of their future may proof
240 The Journal of Psychology
to be useful in training career counselors, coaches, or mentors on the best way to
help others to clarify and conceptualize their career paths.
Aline D. Masuda is a professor at EADA in Barcelona, Spain. Her research interests
are work motivation and self-regulation, the work–family interface, and organizational
attitudes and cross-cultural management. Thomas D. Kane is a professor of psychology
at Missouri State University in Springﬁeld, Missouri, USA. His current research interests
are team dynamics, motivation in work and sport, and leadership. Carol F. Shoptaugh is
a professor of psychology at Missouri State University in Springﬁeld, Missouri, USA. Her
current research interests are work motivation, workplace health and safety, and integrity.
Katherine A. Minor is a senior supply chain coordinator at Ameren Services Corporation.
Her interests include organizational change management and the human factors associated
with large-scale enterprise system implementation and change.
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Original manuscript received April 23, 2009
Final version accepted October 4, 2009