Developing goal orientations conducive to learning and performance: An intervention study

Abstract

Goal orientation is an important psychological attribute for employees, as it has been found to predict a wide range of work‐related outcomes. Although goal orientation has been well‐studied, little is known about the extent to which individuals’ stable, trait‐like goal orientation can be changed and about whether some individuals are more likely than others to engage in such intrapersonal change. In this study, we examined an intervention program designed to change individuals’ trait‐like goal orientation. The results from 132 full‐time managers and professionals participating in a part‐time MBA course revealed that, on average, participants’ performance‐avoid orientation was lessened as a result of the intervention, while there was no overall change in learning orientation, perhaps due to ceiling effects. Furthermore, evidence showed individual variation in these changes. Drawing on adult attachment theory, we investigated and showed the critical role of facilitator support and individuals’ attachment styles in shaping intrapersonal changes in goal orientation. Facilitator support resulted in fostering greater positive change, particularly for individuals with high levels of anxious attachment. Implications are discussed in terms of advancing theories on personality change and goal orientation, as well as designing interventions to support the development of positive psychological attributes.

Full text

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Developing goal orientations conducive to learning and performance:
An intervention study
Ying Wang
School of Management, RMIT University
Chia-Huei Wu
Department of Management and Marketing, Durham University
Sharon K. Parker
Centre for Transformative Work Design, Curtin Business School, Curtin University
Mark A. Griffin
Curtin Business School, Curtin University
Citation:
Wang, Y., Wu, C.-H., Parker, S. K., & Griffin, M. A. (forthcoming). Developing goal
orientations conducive to learning and performance: An intervention study. Journal of
Occupational and Organizational Psychology.

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Abstract
Goal orientation is an important psychological attribute for employees, as it has been found to
predict a wide range of work-related outcomes. While goal orientation has been well studied,
little is known about the extent to which individuals’ stable, trait-like goal orientation can be
changed and about whether some individuals are more likely than others to engage in such
intrapersonal change. In this study, we examined an intervention program designed to change
individuals’ trait-like goal orientation. The results from 132 full-time managers and
professionals participating in a part-time MBA course revealed that, on average, participants’
performance-avoid orientation was lessened as a result of the intervention, while there was no
overall change in learning orientation, perhaps due to ceiling effects. Further, evidence
showed individual variation in these changes. Drawing on adult attachment theory, we
investigated and showed the critical role of facilitator support and individuals’ attachment
styles in shaping intrapersonal changes in goal orientation. Facilitator support resulted in
fostering greater positive change, particularly for individuals with high levels of anxious
attachment. Implications are discussed in terms of advancing theories on personality change
and goal orientation, as well as designing interventions to support the development of
positive psychological attributes.
Keywords: Goal orientation; learning; personality change; personal development;
attachment style

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Practitioner points:
• Individuals’ trait-level goal orientation can be changed through a purposefully
designed intervention program.
• The program helps to significantly reduce participants’ performance-avoid orientation
while maintaining their learning orientation.
• Greater support from program facilitators means greater change in participants’ goal
orientation, especially for those with high attachment anxiety.

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Developing goal orientations conducive to learning and performance:
An intervention study
Goal orientation, a psychological construct that describes how individuals approach,
interpret, and respond to achievement situations, has been found to have significant impact on
employees’ performance. Notably, a learning goal orientation, the goal orientation that leads
employees to focus on developing new skills and mastering new situations (e.g., Dweck,
1986; Elliot, 1999; Farr, Hoffman, & Ringenbach, 1993), has been linked to various positive
outcomes, such as better job performance (see Payne, Youngcourt, & Beaubien, 2007; Van
Yperen, Blaga, & Postmes, 2014 for meta-analyses) and training outcomes (DeRue &
Wellmen, 2009; Bell & Kozlowski, 2002). In contrast, a performance goal orientation leads
employees to focus on demonstrating or validating their competence, either through seeking
favorable evaluations or through avoiding negative judgments about their competence (e.g.,
Dweck, 1986; Elliot, 1999; Farr et al., 1993). This goal orientation, especially performance-
avoid orientation, has been found less optimal for learning and work performance (Payne et
al., 2007; Van Yperen et al., 2014). Moreover, because individuals can hold multiple goal
orientations, research suggests that best results are achieved when individuals adopt a high
learning orientation and a low performance-avoid orientation simultaneously (e.g., Fortunato
& Goldblatt, 2006).
Although goal orientation has usually been conceptualized and operationalized in
organizational research as an individual trait-like attribute that is relatively stable (e.g.,
Button, Mathieu, & Zajac, 1996; Colquitt & Simmering, 1998; Payne et al., 2007), it is
potentially malleable. Indeed, research has shown that goal orientations can change during
important life-stage transitions (e.g., Anderman & Midgley, 1997; de Lange, Van Yperen,
Van der Heijden, & Bal, 2010; Duchesne, Ratelle, & Feng, 2014). This finding is in line with
research on personality that indicates that trait-like attributes can be changed by life and work

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experience (e.g., Mroczek & Spiro, 2007; Roberts, Walton, & Viechtbauer, 2006; Wu &
Griffin, 2012). For organizational researchers, it is therefore of great value to understand how
employees’ goal orientation can change into a more optimal form in order to bring positive
outcomes both for themselves and for the organization. However, research to date focuses
mainly on the differential effects of the trait-level learning and performance orientation (see
Payne et al., 2007; Van Yperen et al., 2014 for meta-analyses). Although laboratory studies
suggest that it is possible to temporarily induce state-level goal orientation (see Van Yperen,
Blaga, & Postmes, 2015 for a meta-analysis), there is no research on how to systemically
facilitate intrapersonal change in trait-level goal orientation. The aim of this study is thus to
understand whether and how we can facilitate such a change.
To design the intervention program, we drew on the personality development
framework (Hennecke, Bleidorn, Denissen, & Wood, 2014), which proposes that personality
change can be facilitated when individuals perceive such a change as desirable and feasible
and when such a change becomes habitual. The program content thus highlighted the value of
having a more optimal form of goal orientation (i.e., a high learning orientation and a low
performance-avoid orientation) and included exercises to enhance self-efficacy for change,
and the program structure provided multiple opportunities to enact new behaviors.
In addition to the content and structure of the program, we expected the relationship
between program facilitators and participants to be important for changing goal orientation.
Programs involving personal change can be challenging for participants, as they require
participants to deviate from how they currently perceive themselves and to believe that
change is desirable. Such a personal change requires a sense of security for participants to
expand and explore their possible selves (Markus & Nurius, 1986). Drawing on attachment
theory (Bowlby, 1969/1982), we explored whether facilitators can establish an environment
for self-exploration and whether participants are willing to rely on such support to achieve

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change. As elaborated below, we propose that facilitator support and participants’ attachment
style will interact to shape intrapersonal change in goal orientation.
We conducted the intervention with full-time managers and professionals who were
pursuing part-time MBA study. We consider this context appropriate because participants
were mid-career adult learners who were open to personal development and would therefore
likely respond to a purposefully designed intervention program. We also recognize that the
competitive nature of the MBA program and the workplace in general can impose a strong
performance orientation (e.g., Griffiths, Winstanley, & Gabriel, 2005; Latham & Brown,
2006); therefore, it is particularly important to mitigate this context by purposefully
facilitating individuals’ reduction of performance-avoid orientation while growing, or at least
maintaining, their learning orientation. In the following sections, we first discuss the
literature concerning goal orientation and the possibility to change goal orientation. Next, we
describe the intervention program as informed by the personality development framework
(Hennecke et al., 2014). Finally, we draw on attachment theory (Bowlby, 1969/1982) to
propose the joint effect of facilitator support and participants’ attachment style in shaping
individuals’ change in goal orientation.
Goal orientation as a critical psychological attribute
The concept of goal orientation has been widely studied in various domains. Two
main types of goal orientation that individuals adopt in achievement situations are a learning
goal orientation (also termed as mastery orientation) and a performance goal orientation (e.g.,
Dweck, 1986; Elliot, 1999; Farr et al., 1993). Researchers have suggested that a learning goal
orientation is more desirable because learning-oriented individuals tend to compare
themselves with their past performance and thus adopt an internal referent, whereas
performance-oriented individuals compare their performance with others’ performance and
adopt an external referent (e.g., Nicholls, 1975). Further, learning-oriented individuals tend to

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believe that intelligence and performance can be improved through increased effort and
practice, while performance-oriented individuals tend to have a fixed mindset in believing
intelligence cannot be changed (Dweck, 1986; Elliott & Dweck, 1988). As a result, learning-
oriented individuals tend to engage in activities that draw on their intrinsic motivation, which
enables them to seek and be energized by challenges and to sustain interest and effort in tasks.
In contrast, performance-oriented individuals tend to employ maladaptive strategies as a
result of focusing on ability. For example, they need to be certain that their ability to engage
in a specific task is high and are likely to avoid challenges and withdraw effort from novel
and challenging tasks (Dweck, 1986).
An advance in this literature has been for researchers to make a finer-grained
differentiation of the different manifestations of performance goal orientation. VandeWalle
(1997) described these orientations as “performance-prove”, or individuals’ focus on proving
their competence, and “performance-avoid”, or individuals’ focus on avoiding negative
judgment of their competence. This conceptualization is in line with other seminal models of
motivational orientation, such as the distinction between approach and avoidance (Elliot,
1999). Researchers have found that it is the performance-avoid orientation, rather than the
performance-prove orientation, that is dysfunctional. Performance-avoid individuals tend to
avoid and withdraw from tasks due to fear of appearing incompetent, which negatively
impacts their learning, performance and wellbeing (e.g., Elliot & Harackiewicz, 1994;
Pintrich, 2000). The performance-prove orientation is not necessarily maladaptive, as the
motivation to outperform others can enable individuals to invest affectively and cognitively
in tasks and thus work hard to achieve positive outcomes (Harackiewicz, Barron, & Elliot,
1998).
Since being applied to organizational research, goal orientation has been found to
shape various work-related outcomes. In two meta-analyses in which work domain was a

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focus, learning orientation has a positive impact, while performance-avoid orientation has a
negative impact on learning and performance outcomes (Payne et al., 2007; Van Yperen et al.,
2014). Regarding performance-prove orientation, the results are more mixed. Payne et al.
(2007) suggested that performance-prove orientation has little impact on learning and task
performance, while Van Yperen et al. (2014) revealed its positive association with both
learning outcomes and other-rated job performance. Overall, there is strong and consistent
evidence for the positive effect of learning orientation and the negative effect of
performance-avoid orientation, with somewhat mixed effects of performance-prove
orientation.
Research further shows that individuals hold multiple goal orientation dimensions
simultaneously and thereby provides insights on what type of goal orientation profile is most
ideal. Using the three dimensions of goal orientation, Fortunato and Goldblatt (2006) found
that a profile with a high learning orientation, a moderate performance-prove orientation, and
a low performance-avoid orientation appears most desirable, as these individuals demonstrate
a high locus of control, self-efficacy, and positive affectivity, while having low negative
affectivity and less fear of failure. It is noteworthy that such a profile is better than a profile
with a moderate to high learning orientation but a high performance-prove and performance-
avoid orientation, as such individuals demonstrate a high fear of failure and high negative
affectivity despite having high self-efficacy and motivation to learn. This study demonstrates
that having only a high learning orientation may not be sufficient, as the best outcomes occur
when a low performance-avoid orientation is also present. Overall, previous research from
various domains suggests that it is important to facilitate holistic development of goal
orientation by improving learning orientation while decreasing performance-avoid orientation.
Changing individuals’ trait-level goal orientation

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There are two broad perspectives on the malleability of goal orientations. First, most
research in organizational psychology has conceptualized and investigated goal orientation as
a relatively stable personality trait-like variable. Second, studies on how particular goal
orientations can be induced within an experimental setting (Van Yperen et al., 2015) focus on
the short-term change in orientations, with the primary aim being to compare differential
effects of distinct goal orientations. In this study, we take the trait-based perspective yet
endorse the potential to change trait-like goal orientations, such as through purposefully
designed interventions. Our conceptualization is in line with the argument that trait-like
variables are relatively stable but are amenable to systematic change over time through
factors such as maturation and significant experience.
In the general life domain, there is evidence that individuals’ goal orientations can
change, especially when they experience important life transitions. For instance, as
individuals transit from primary to middle school, their endorsement of learning (mastery)
goals tends to decrease (Anderman & Midgley, 1997). Additionally, as employees age, their
gradual diminution of physical and mental skills tends to switch their attention to loss
prevention, causing them to be more learning (mastery)-avoidant (de Lange et al., 2010).
These findings concur with the increasingly prominent line of research that focuses on
personality change. Despite early assumptions that personality traits are largely stable in
adulthood (Costa & McCrae, 1988), researchers have recognized that people do change their
personality throughout adulthood, such as by becoming more confident, agreeable,
conscientious, and emotionally stable as they get older (Roberts et al., 2006). In
organizational settings, increasing attention has been paid to the change in individual traits
through work experience. A series of studies has demonstrated that traits such as locus of
control, core self-evaluation, and the big five personality, can change over time as a result of
job characteristics and job experiences (Wu, 2016; Wu & Griffin, 2012; Wu, Griffin, &

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Parker, 2015). Goal orientation is particularly appropriate to investigate in this context
because it has previously been conceptualized as a relatively stable trait-like construct (e.g.,
Button et al., 1996; Colquitt & Simmering, 1998; Payne et al., 2007). In particular, Button et
al. (1996, p. 28) commented that goal orientation is a “somewhat stable individual difference
that may be influenced by situational characteristics”.
Although the above research highlights the potential for change in relatively stable
traits, most studies have focused on natural and slowly emerging change over long timespans,
with little information about how to actively facilitate and enable personality development
through interventions (Roberts, Luo, Briley, Chow, Su, & Hill, 2017). Given the importance
of goal orientation for work-related outcomes, it is important to understand the extent to
which a general trait-like goal orientation can be purposefully changed and how such change
occurs. To answer this question, we designed a personal development program to foster the
development of a more optimal goal orientation profile, that is, to develop learning
orientation while reducing performance-avoid orientation. To ensure and enhance the effect
of this intervention, we drew on a personality development framework (Hennecke et al., 2014)
to incorporate key conditions for evoking intrapersonal change.
Designing a personal development program for growth: A self-regulated personality
development perspective
A recent framework developed by Hennecke et al. (2014) suggests how personality
change is possible. This framework proposes that individuals play an active role in their
personality development through a goal-directed process whereby individuals employ self-
regulatory mechanisms to achieve a goal (i.e., changing themselves). To enable this self-
regulation process, three preconditions must be fulfilled. First, changing trait-related
behaviors must be considered desirable and necessary. Second, the person must consider the

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change to be feasible. Third, the person needs to frequently enact and practice trait-relevant
behaviors over time for the behaviors to become habitual.
The self-regulation framework is useful because it pinpoints key design factors for
enabling personality change. It first suggests that individuals need to consider certain traits as
valuable and desirable to take onboard the need to change. Following this logic, we designed
the program by educating participants from the outset about the benefits of learning
orientation and the detrimental effect of performance-avoid orientation. We present to
participants the wealth of research evidence concerning the impact of goal orientation on life
and work and provide participants their own goal orientation profiles and discuss their
implications. For example, after learning about their goal orientation (gathered via a self-
reported survey prior to the program), participants are asked to present reflections on their
goal orientation profile to their learning team. We also provide participants with numerous
readings on goal orientation and ask them to complete personal reflection diaries during their
working days. These efforts are designed to enable participants to appreciate the value of
having more desirable goal orientations and to understand the need for change.
Second, the framework suggests that changing certain traits must be considered
feasible. To increase participants’ subjective expectancy of the feasibility of change, we
educate participants about adopting the right mindset – a flexible, growth mindset rather than
a fixed mindset (Dweck, 1986). Such a mindset enables them to see goal orientation as
malleable and to see that change is possible and that the program is designed to help them
achieve this change. To improve participants’ self-efficacy, we allocate them to small cohorts
(15–20 participants per cohort) and small learning teams (3–4 per team) and facilitate them in
forming strong bonds with their learning team, who acted as peer mentors in providing
support and advice for them to progress toward their change goals. They are also trained to
set development goals that are relevant for their personal growth, rather than focusing merely

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on job or academic performance. These efforts help participants to believe change to be
achievable and feasible.
Third, the framework suggests that trait-relevant behaviors must be enacted over time
in order to become habitual. To meet this end, we designed the program to contain multiple
sessions spanning three months. Early in the program, participants set a personal
development goal, which they work on over the next three months. Throughout this process,
participants are encouraged to adopt a learning rather than a performance perspective and are
given practical tips to maintain this focus through constructive self-talk. In the last session,
participants are asked to present their overall development to the class and are encouraged to
reflect on their goal orientation. This repeated reflection and practice enables participants to
integrate the concept over time and to habitually focus on changing their goal orientation.
By incorporating the three elements necessary for personality change (Hennecke et al.,
2014), we expect that our program would facilitate an increase in participants’ learning
orientation whilst decreasing their performance-avoid orientation. We do not expect change
in their performance-prove orientation, given that we did not set out to change this goal
orientation, which has ambiguous learning and performance outcomes. It is worth noting that
because the construct under consideration is goal orientation, one may argue that individuals’
initial level of goal orientations has an impact on the degree of intrapersonal change, for
instance, those with a high initial learning orientation may be more open to learning and thus
change their goal orientation more. However, we argue that the extent of change can be
independent of one’s initial level of goal orientations because, even if someone starts with a
low learning orientation, this person can be persuaded and empowered through the
intervention and thus engage in intrapersonal change. Indeed, our intention was to design an
intervention that fosters meaningful change by conveying the desirability and possibility of
change, which provides a strong situation (Meyer, Dalal, & Hermida, 2010) that can

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overwrite one’s initial goal orientations. Nevertheless, we recognize the importance of
controlling for initial-level goal orientations to rule out their potential influence. In sum, we
hypothesize:
H1: Participants’ learning orientation will increase and performance-avoid
orientation will decrease as a result of the program, after controlling for their initial
level of goal orientation.
Although the program is designed to create appropriate conditions for intrapersonal
change, we also recognize that not all individuals will change in the same way. People do not
automatically learn from experience, and even with the same experience, people learn
fundamentally different lessons (e.g., Ashford & DeRue, 2012; Heslin & Keating, 2017). We
expect that whether effective personal change occurs as a result of the intervention will
depend on both the facilitators’ and the participants’ attributes.
The role of facilitator support and participants’ attachment style
We expect that the relationship between program facilitators and participants will be
an important element that shapes the supportive context required for personal change.
Because participants can establish and experience different relationship qualities with the
same facilitators (c.f., Dulebohn, Bommer, Liden, Brouer, & Ferris, 2012), it is essential to
look into the characteristics of participants and those of program facilitators to understand the
social context that facilitate personal change. We use attachment theory (Bowlby, 1969/1982)
to guide our examination of the social context of the program. Attachment theory outlines a
relational perspective of child development, which provides broader principles to understand
individual development and can thus be applied to the context of personal development
programs. Specifically, we draw on this theory to elaborate the importance of facilitator
support and participants’ attachment style. We first outline the rationale for expecting a

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positive effect of facilitator support and then discuss why individual differences in attachment
style are expected to moderate the effect of facilitator support.
Attachment theory posits that support from significant others is critical for
individuals to comfortably learn and explore the world. This theory focused initially on
support during childhood. According to Bowlby (1969/1982), a high level of support
provided by the primary caregiver is critical, as it enables children to confidently explore
novel and challenging environments knowing that there is a secure base to which they can
return when dangers and obstacles occur. The lack of such support can greatly hamper
children’s learning and exploration. These ideas have since been expanded beyond
attachment in childhood to contexts in which individuals have relationships with targets other
than parents. For instance, Wu and Parker (2017) showed that supportive leaders at work can
function as a secure base for employees to explore alternative approaches to their work.
Based on this theory, we expect that facilitator support will play a positive role in
guiding individuals’ change in goal orientation. Personality change is a challenging journey
because it requires individuals to confront their existing self-concept and explore uncharted
territory. In this context, facilitator support is critical for creating a positive and safe learning
environment so that participants can feel confident in changing themselves. In essence, we
expect that facilitator support provides a secure haven for participants – similar to that
originally proposed to be provided by parents – and hence have a positive effect on
participants’ development of goal orientation.
Attachment theory also suggests that due to their different attachment styles, people
vary in their response to, and reliance on, social support to explore. The attachment literature
suggests two primary attachment styles: attachment anxiety and attachment avoidance
(Brennan, Clark, & Shaver, 1998; Fraley & Shaver, 2000; Mikulincer & Shaver, 2003). High
attachment anxiety represents feeling anxious or fearful of social relationships, while low

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attachment anxiety represents feeling confident and assured of being accepted in social
relationships. High attachment avoidance represents the defensive avoidance of social
relationships, while low attachment avoidance represents feeling comfortable being in close
relationships and depending on others. We expect that people with higher attachment anxiety
will be especially responsive to facilitator support in a development program and thus will be
most likely to change their goal orientations.
Individuals with higher attachment anxiety want to explore and master the world, but
they can appear worried about their own curiosity, fearing that it might jeopardize their
relationships, which results in a conflicting approach toward exploration (Mikulincer, 1997).
Therefore, when attending a personal development program and presented with a less ideal
self-profile, they may have a desire to change themselves, but may be drawn to their own
negative attributes, such as being incapable (Mikulincer, 1995), and may feel anxious about
whether their change will be accepted by others (Dozier & Lee, 1995). Because individuals
with higher attachment anxiety tend to cope with insecurity by searching for warm
relationships when learning and exploring their new world (Bowlby, 1988; Shaver & Hazan,
1993), facilitator support in the program can be particularly critical by providing a secure
base to help these individuals feel confident and thus comfortably explore their change
journey.
On the other hand, individuals higher in attachment avoidance tend to be self-reliant
and hold a defensive, positive self-view (Mikulincer & Shaver, 2003), which means that these
individuals may be less likely to desire change when attending the program. In addition,
whether they will rely on facilitator support to embrace new change is also questionable.
Although it has been suggested that supervisor support can help those with higher attachment
avoidance to have higher autonomous motivation and thus be proactive at work (Wu &
Parker, 2017), studies also found that these people tend to reduce their desire for proximity

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and closeness with others (Shaver & Mikulincer, 2002) and choose not to trust and depend on
others (Brennan et al., 1998; Collins & Read, 1990) because they have learned that requests
for attachment often bring negative consequences, such as being rejected or alienated by their
caregivers (Cassidy & Kobak, 1988). Therefore, we do not expect participants high in
attachment avoidance to have a strong reaction to our program.
In summary, we expect a positive effect of facilitator support on participants’ change
in goal orientation, particularly in terms of an increase in learning orientation and a decrease
in performance-avoid orientation. Furthermore, we expect an interaction effect between
facilitator support and participants’ attachment anxiety in predicting change in goal
orientation, such that the positive effect of facilitator support will be especially strong for
participants with attachment anxiety. We include attachment avoidance for completeness but
do not expect a significant interaction effect between facilitator support and attachment
avoidance. We hypothesize:
H2: Facilitator support will have a significant main effect in facilitating a change in
goal orientation. A higher level of facilitator support will lead to a significant
increase in learning orientation and a decrease in performance-avoid orientation.
H3: There will be an interaction effect between facilitator support and attachment
anxiety such that the positive effect of facilitator support on the change in learning
orientation and performance-avoid orientation will be stronger for individuals with
high attachment anxiety.
Method
Sample and data collection procedures
Full-time managers and professionals attending a part-time MBA course in an
Australian business school participated in the personal development program. The program
was an optional offering in the MBA course. The program runs over three months, with

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multiple sessions in between to scaffold and reinforce learning. It should be noted that
although we developed the program to change goal orientation, goal orientation was not our
only focus, as we believe the program should have broader coverage for several reasons. First,
an over-emphasis on goal orientation would make the purpose of the intervention too obvious
and might sensitize participants to report change on this construct even though change might
not actually occur (Orne, 1962). Second, we aim to provide participants with well-rounded
development, with goal orientation being a core element. Moreover, a comprehensive
personal development program is more in line with programs that are typically used across
organizations and would thus have broader implications for supporting individuals’
development than a narrowly designed intervention that is focused solely on changing goal
orientation.
Prior to the start of the program, participants completed a pre-survey in which they
were asked to report their learning orientation, performance-prove orientation, performance-
avoid orientation, and attachment styles. At the end of the last learning session (i.e., three
months after the start of the program), participants were asked to report their learning and
performance orientation again as part of a wider survey. They were also asked to report on
the level of facilitator support they received in the program. To ensure the discriminant
validity of our intervention program, we also collected data on constructs that were not
targeted in the intervention. In particular, we measured participants’ mindfulness both before
and after the program. Mindfulness serves as a good construct for comparison purposes,
because while there are many interventions and practices targeted at fostering mindfulness
(e.g., Kiken, Garland, Bluth, Palsson, & Gaylord, 2015), this focus was not present in our
intervention. Furthermore, similar to goal orientation, mindfulness can be conceptualized and
measured at both the trait level and the state level, and the trait-level construct can be
changed through purposefully designed interventions (Kiken et al., 2015).

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The program was offered to part-time MBA candidates each semester, and over three
years, a total of 202 participants completed the program. Because completing the survey was
voluntary, not all participants completed both pre- and post-surveys. Completed responses
were available from 132 participants, representing a 65.34% response rate. The participants
had a mean age of 35.35 years old (SD = 6.89), and 57.8% were male.
Measures
All measures described below, unless otherwise indicated, used a response scale of 1–
5, with 1 indicating “strongly disagree” and 5 indicating “strongly agree”.
Goal orientation. We measured learning orientation, performance-prove orientation
and performance-avoid orientation using items from the trait-level goal orientation scale
developed by VandeWalle (1997). Four items were used to measure learning orientation (an
example item is “I am willing to select a challenging work assignment that I can learn a lot
from”)1; four items were used to measure performance-prove orientation (an example item is
“I like to show that I can perform better than my co-workers”); and four items were used to
measure performance-avoid orientation (an example item is “I would avoid taking on a new
task if there was a chance that I would appear rather incompetent to others”). To ensure we
solicited participants’ trait-level attributes, we asked participants to think of their general
tendency in answering these statements. The Cronbach’s alphas for the pre- and post-surveys
were .78 and .85 for learning orientation; .81 and .85 for performance-prove orientation;
and .84 and .89 for performance-avoid orientation, respectively.
Facilitator support. We measured facilitator support by two items selected from the
measure developed by Williams and Deci (1996). The items were “I am able to be open with
my facilitator during class” and “My facilitator encouraged me to ask questions”. The
Cronbach’s alpha was 0.87.
1 The lowest loaded item from the learning orientation scale was deleted for having a balanced coverage of the
three dimensions in terms of item numbers.

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Attachment style. We measured participants’ attachment anxiety and attachment
avoidance using the 10-item attachment style scale developed by Wu (2009), which has been
validated in different work settings (e.g., Wu & Parker, 2017; Wu, Parker, & De Jong, 2014).
Four items were used to measure attachment anxiety (an example item is “I often worry that
others don’t like me”). Six items were used to measure attachment avoidance (an example
item is “I am nervous when anyone gets too close”). The response scale was 1–7, with 1
indicating “strongly disagree” and 7 indicating “strongly agree”. Exploratory factor analysis
successfully differentiated the two factors, yet also showed that one item for attachment
anxiety and one item for attachment avoidance did not load highly on their corresponding
factor and were thus deleted to ensure satisfactory internal reliability. The Cronbach’s alpha
was .78 for attachment anxiety and .73 for attachment avoidance after deleting these two
items.
We conducted confirmatory factor analysis to examine the construct validity of the
key study variables. The fit of a 9-factor model (i.e., facilitator support, attachment anxiety,
attachment avoidance, three goal orientations at Time 1, and three goal orientations at Time 2)
was satisfactory (Chi-square = 741.61, df = 492, p < .001, CFI = .90, TLI = .89, RMSEA
= .05, SRMR = .07) and was significantly better than alternative models, including an 8-factor
model in which the two attachment style variables were combined into one factor (Chi-
square = 893.58, df = 500, p < .001, CFI = .84, TLI = .82, RMSEA = .06, SRMR = .08); and a
6-factor model in which the two time points of goal orientations were aggregated for each of
the three factors (Chi-square = 1223.18, df = 513, p < .001, CFI = .72, TLI = .69, RMSEA
= .08, SRMR = .11). These results confirm that the measurement model is satisfactory for
proceeding to hypothesis testing.
Demographic controls and discriminant variable. We controlled for participants’ age
and gender. As mentioned earlier, we also included mindfulness to demonstrate the

20
discriminant validity of our intervention. Mindfulness was measured by the three highest-
loaded items selected from Brown and Ryan’s (2003) mindfulness scale. An example item is
“It seems I am ‘running on automatic’ without much awareness of what I’m doing”. The
Cronbach’s alphas for the pre- and post-surveys were .95 and .96, respectively.
Data checking and analytical strategy
Before the main analysis, we first examined if it was necessary to pursue multilevel
analysis. Participants were nested within cohorts, and thus, those in the same cohort with the
same facilitator might share similar experiences with changing goal orientation. Examining
the variance components shows that between-cohort variances explained between only 0%
and 3.55% of the total variance on the key outcome variables, suggesting that it is not
necessary to control for the multilevel structure of the data. We also calculated the design
effect (i.e., the extent to which cluster sampling influences sampling variability, calculated as
1 + [average cluster size – 1] × ICC1). For all outcomes, the design effect was lower than 2 –
the suggested cut-off point for considering the use of multilevel modeling (Heck & Thomas,
2015). We thus treated the data as single level and used hierarchical regression analysis in
SPSS to test the hypotheses. We also conducted a supplementary analysis by using a different
approach to model change scores. In particular, we used latent differences score modeling
(LDSM) following the recommendation by McArdle (2009). This approach creates latent
difference scores between variables measured at different time points. Using a different
approach to model change could provide a cross-validation of our results.
Results
Table 1 presents the means, standard deviations, and inter-correlations among the
study variables. Among the control variables, age had no significant relationships with the
outcome variables, while gender had a negative relationship with performance-avoid
orientation at Time 2 (r = .21, p < .05), showing that females tend to have higher

21
performance-avoid scores than males after the program. An avoidant attachment style was
related negatively to learning orientation (r = -.23, p < .05) and positively related to
performance-avoid orientation (r = .24, p < .05) at Time 2, with those higher in attachment
avoidance being less learning-oriented and more performance-avoid-oriented after the
program. An anxious attachment style was related positively to performance-prove
orientation (r = .24, p < .01) and performance-avoid orientation (r = .26, p < .05) at Time 1,
with those higher in attachment anxiety being more performance-oriented before the program.
The inter-correlations among the three goal orientation outcomes were low to moderate.
************************
Insert Table 1 About Here
************************
Of the three goal orientations, participants had rather high learning orientations both
before and after the program (4.39 and 4.45, respectively). The small increase in learning
orientation was not significant based on the paired t-test (t = 1.06, n.s.). Participants had
generally low performance-avoid orientations both before and after the program (2.32 and
2.16, respectively), and the decrease was significant (t = -2.09, p < .05). Participants’ scores
on performance-prove orientation were medium both before and after the program (3.41 and
3.29, respectively), and this decrease was not significant (t = 1.73, n.s.). Overall, there was a
significant reduction in performance-avoid orientation for the entire group, as hypothesized.
Unexpectedly, there was no significant increase in learning orientation. One explanation
could be that scores at the outset were already high, causing a ceiling effect and making it
difficult to demonstrate a change. We also examined the intrapersonal change in mindfulness.
As expected, there was no significant change in mindfulness before and after the program
(mean = 3.60 and 3.66, respectively, t = -.70, n.s.). This result demonstrates good
discriminant validity for our intervention, showing that participants did not change in

22
constructs that were not targeted by the intervention. Overall, hypothesis 1 is partially
supported.
A lack of group mean change in learning orientation for the entire group does not
exclude the possibility that some individuals changed while others did not. We therefore
proceeded with the test on the effect of facilitator support and attachment style in predicting
intrapersonal change in goal orientation. We performed separate hierarchical regression
analyses for learning orientation and performance-avoid orientation. The dependent variable
was the goal orientation at Time 2. In Step 1, we entered the control variables, including age,
gender, and three goal orientations at Time 1. In Step 2, we entered attachment avoidance,
attachment anxiety and facilitator support. In the final step, we entered the interaction term of
attachment anxiety and facilitator support, as well as the interaction term of attachment
avoidance and facilitator support. The centered scores on these variables were used to
calculate the interaction terms. The results are shown in Table 2.
************************
Insert Table 2 About Here
************************
The results of this analysis support hypotheses 2 and 3. First, in Step 2, facilitator
support was significant in predicting learning orientation at Time 2 (B = .14, SE = .06, t =
2.43, p < .05) and performance-avoid orientation at Time 2 (B = -.19, SE = .08, t = -2.32, p
< .05) after demographic variables, initial goal orientations and attachment styles were
considered. This finding shows that higher facilitator support leads to a greater increase in
learning orientation, as reflected by the positive coefficient, and a greater decrease in
performance-avoid orientation, as reflected by the negative coefficient. Second, in Step 3, the
interaction term between facilitator support and anxious attachment was significant in
predicting an increase in learning orientation (B = .16, SE = .06, t = 2.80, p < .01) and a

23
decrease in performance-avoid orientation (B = -.22, SE = .09, t = -2.63, p < .01). These
interaction effects are plotted in Figures 1 and 2. Simple slope tests suggest that, with respect
to a positive change in learning orientation, facilitator support had a significant effect among
participants with high attachment anxiety (B = .37, SE = .10, t = 3.74, p < .01) but not among
participants with low attachment anxiety (B = .01, SE = .07, t = .10, n.s.). With respect to
decreasing participants’ performance-avoid orientation, facilitator support had a significant
effect among participants with high attachment anxiety (B = -.53, SE = .15, t = -3.49, p < .01),
but not among participants with low attachment anxiety (B = -.01, SE = .11, t = -.08, n.s.).
Finally, the interaction term between facilitator support and attachment avoidance was not
significant in predicting either outcome (B = -.07, SE = .05, t = -1.63, n.s., and B = .05, SE
= .07, t = .75, n.s., respectively), as we expected2.
************************
Insert Figure 1 & 2 About Here
************************
To cross-validate our results, we conducted a supplementary analysis using the LDSM
approach, following the recommendation of McArdle (2009). Using Mplus 7.0, we created
latent difference scores between Time 1 and Time 2 for each outcome. We then tested
separate path models in which the latent different scores were regressed on our hypothesized
variables. The results were largely similar. First, there was a positive effect of facilitator
support in predicting the latent difference score on learning orientation (B = .19, SE = .06, t =
3.46, p < .01) and performance-avoid orientation (B = -.27, SE = .08, t = -3.22, p < .05).
Furthermore, the interaction term between facilitator support and attachment anxiety was
2 To rule out the possibility that individuals with different initial goal orientations might experience
different change rates (i.e., initial goal orientation as a moderator of the change effect), we performed
a series of supplementary analyses by computing the quadratic terms for each goal orientation
dimension and included them in the regression analysis. This quadratic term represents the
moderation effect of Time 1 goal orientation on the association between Time 1 goal orientation and
Time 2 goal orientation. Our supplementary analysis showed that none of the quadratic terms
emerged as significant, and we obtained similar results for all hypothesized effects.

24
significant in predicting the latent difference score for learning orientation (B = .16, SE = .05,
t = 2.92, p < .01) and performance-avoid orientation (B = -.22, SE = .08, t = -2.75, p < .01).
The interaction term between facilitator support and attachment avoidance was not significant
in predicting the latent difference score for learning orientation (B = -.07, SE = .04, t = -1.70,
n.s.) and performance-avoid orientation (B = .05, SE = .07, t = .78, n.s.). The results thus hold
using different approaches to modeling change.
Discussion
Can we actively facilitate a change in individuals’ trait-level goal orientation so that
they benefit more from this important psychological attribute? Furthermore, who is more
likely to respond to interventions designed to change goal orientation? Through a carefully
designed personal development program and by collecting participants’ responses before and
after the program, we offer empirical evidence for these theoretically and practically
meaningful questions. We first discuss the implications of changing goal orientation through
intervention and then discuss the important contextual and individual factors that shape the
degree of personal change. Finally, we briefly discuss the implications of our research for
understanding personality change.
Given the broadly recognized importance of trait-level goal orientation for a wide
range of outcomes (e.g., DeRue & Wellmen, 2009; Bell & Kozlowski., 2002; Payne et al.,
2007), it seems imperative for organizations and training professionals to devise efforts to
purposefully facilitate employees’ development in goal orientation. However, little research
is available to understand if this change is possible and how it can occur. Drawing on the
personality development framework (Hennecke et al., 2014), we designed and conducted an
intervention program with the aim of meeting the three conditions that facilitate personality
change: to enable individuals to feel that changing particular traits is desirable or necessary;
to enable them to feel that change is feasible; and to provide time and space for them to form

25
new habits associated with the new traits through repeated and deliberate practice. We found
that the program indeed facilitated changes in goal orientation, even within a relatively short
period. After three months, participants significantly reduced their performance-avoid
orientation, and this change was particularly salient among participants with high levels of
attachment anxiety who perceived a high level of facilitator support. As we discussed earlier,
performance-avoid orientation has a detrimental impact on individuals’ learning and
performance (Payne et al., 2007; Van Yperen et al., 2014), and can even suppress the positive
impact of learning orientation (Fortunato & Goldblatt, 2006). Our finding provides positive
avenues that this negative aspect of goal orientation can indeed be managed and reduced
through deliberate training and practice.
We did not observe significant changes in learning orientation for the entire group,
which may be because participants already scored relatively high on this measure at the start
of the program, thus providing limited scope for further improvement. Given the participants’
already high learning orientation, performance-avoid orientation might have been an area that
was more susceptible to change, and as a result, participants may have chosen to focus more
on this development area and therefore improved significantly. Nevertheless, maintaining
high learning orientation can still be considered meaningful, as the competitive context of the
MBA program and the workplace in general often imposes strong performance pressure,
which can threaten individuals’ learning interests (e.g., Griffiths et al., 2005; Latham &
Brown, 2006). Furthermore, our results demonstrated that for individuals who had high levels
of attachment anxiety and who perceived a high level of facilitator support, learning
orientation did increase significantly as a result of the program. Overall, our results provide
confidence for changing individuals’ trait-level goal orientation through purposefully
designed programs.

26
Moreover, our study demonstrates that the extent of meaningful change in such
programs depends on whether individuals perceive themselves to be supported by the
facilitator and are sensitive to such support. We found that facilitator support provides a
critical role in enabling the increase in learning orientation and the decrease in performance-
avoid orientation. We further demonstrated that individuals with high levels of attachment
anxiety are more sensitive to the perceived support from the facilitator than those with lower
levels, as suggested by the significant two-way interaction between attachment anxiety and
facilitator support. Our results suggest that due to the very personal nature of these
development programs, it may be particularly important to understand participants’
attachment styles and to ensure that those with attachment anxiety receive adequate support
from facilitators; otherwise, these participants may be discouraged by the demands of the
program and be less likely to engage in meaningful change. This finding is consistent with
earlier findings that highlight the importance of providing a secure base of support to
encourage individuals with attachment anxiety in their exploration of new territories (e.g.,
Wu & Parker, 2017).
In contrast, we did not find that people with different levels of avoidance attachment
will respond differently to facilitator support, as suggested by the lack of significant two-way
interaction between avoidance attachment and facilitator support. Moreover, there was even
some evidence that those with high avoidance attachment may be less likely to change in
general, as suggested by the main effect of attachment avoidance on the change in
performance-avoid orientation. This finding is not unexpected. Individuals with attachment
avoidance have been suggested to adopt a self-defensive strategy such that they use an
idealization of the self to defend against potential rejection by others (Mikulincer, 1995). This
can lead to a “walling off” style as individuals distance themselves from the need to learn and
dismiss the importance of new information (Mikulincer, 1997). Our results suggest that such

27
self-defensiveness may make it particularly difficult to engage these individuals in a personal
change journey. Organizations and training professionals may need to pay particular attention
when engaging these individuals. For instance, recent studies on romantic relationships have
suggested that individuals with an avoidant attachment style can benefit from being
facilitated to reflect on positive experiences with their partner and to engage in intimacy-
promoting activities (e.g., Stanton, Campbell, & Pink, 2017). This finding suggests that while
building and relying on close relationships does not come naturally for these individuals, they
can benefit from activities that are purposefully designed to remind them of, and thus feel
appreciative of, positive interactions with others, thereby increasing their willingness to rely
on support from others. It would be useful for future research and practice to explore the
effect of such strategies in order to assist these individuals in personal development programs.
Finally, our study contributes to the literature on personality change. While in the past,
personality was considered a fixed trait that remained stable during one’s adulthood (Costa &
McCrae, 1988), research over the last decade has increasingly highlighted the changeability
of personality throughout adulthood (e.g., Mroczek & Spiro, 2007; Roberts et al., 2006),
often as a result of one’s life experiences, including work and career experiences (Wu, 2015;
Wu & Griffin, 2012; Wu et al., 2015). Nevertheless, these studies focused on naturally
occurring changes in individuals’ personality. Except for the results of studies in clinical
settings, little is known about how personality change can be facilitated through training and
interventions (Roberts et al., 2017). Our study is among the first to explore how to actively
facilitate such change in a professional context. We suggest that through a purposefully
designed personal development program, it is possible to change individuals’ personality
through training and that effective personality change can occur within as short a period as
three months. This finding is in line with Roberts et al.’s (2017) meta-analytical finding on
the effect size of intervention duration, which suggests that interventions targeted at

28
personality change can have a substantial effect in the first eight weeks; beyond that duration,
longer interventions do not necessarily induce greater personality change. Our results concur
with this finding that perhaps personality change requires only between two to three months
of dedicated and sustained effort. This finding provides implications for future interventions
in the work context regarding how long developmental programs should last to achieve
reasonable personality change.
Limitations and future directions
A number of limitations should be noted. First, while we used a pre-post design to
evaluate participants’ change on focal constructs, a more rigorous design would have
included a control group with data from individuals who did not participate in this program.
While we acknowledge the lack of a control group, we believe the program produced
meaningful and intended changes because while participants reduced performance-avoid
orientation on average, there was no significant change in performance-prove orientation –
the goal orientation dimension that we did not expect to change, as well as in mindfulness –
the construct that was not targeted in the intervention. This finding therefore provides some
validity check for our program effect.
Second, because our post-survey was collected immediately after the program, one
may argue that changes in performance-avoid orientation occurred purely because they were
called for by the researchers (demand characteristics). However, we believe that this situation
is unlikely for two reasons. First, there is no theoretical reason why some (i.e., anxiously
attached individuals with high support from facilitators) but not all individuals responded to
demand characteristics, whereas we have articulated a theoretical reason for why these
individuals were more likely to change their goal orientation. Second, individuals would need
to have a highly refined understanding of our hypotheses in order to generate a decrease in
performance-avoid orientation but not a change in performance-prove orientation or

29
mindfulness and they would need to detect subtle differences in item content. It is unlikely
that they were motivated to, or cognitively able to, generate theorized responses.
Nevertheless, we recognize that a more ideal design would be to follow up with
participants beyond the program in order to demonstrate the sustainability of the intervention
effect. This step can be achieved by, for instance, following up with participants at a certain
time after the completion of the program. However, it should be recognized that the
competitive and performance-oriented work context can make such sustainability difficult to
achieve. Therefore, future studies may consider purposefully collecting data on situational
characteristics in order to understand what context might sustain such an intrapersonal change
achieved during intervention programs.
Finally, while the self-regulated personality development framework (Hennecke et al.,
2014) offers a valuable theoretical framework for guiding the design of our program, we did
not specifically measure participants’ perceptions of the three conditions of personality
change. Therefore, our study provides only indirect support for the proposed framework.
Future studies could consider more directly measuring individuals’ perceptions of these
conditions to offer a more systematic and in-depth examination of their effect on personality
development.

30
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Table 1. Mean, standard deviation and intercorrelations of study variables (N=132).
Mean
SD
1
2
3
4
5
6
7
8
9
10
11
12
1.Age
35.32
6.93
2.Gender (1=male; 2=female)
1.43
0.50
-.01
3.Attachment avoidance
3.28
1.06
-.05
.23*
4.Attachment anxiety
3.00
1.16
-.12
.02
.28**
5.Facilitator support
4.34
0.73
.03
-.10
-.20*
.07
6.Learning orientation T1
4.39
0.47
.09
.02
-.09
-.03
.03
7.Learning orientation T2
4.45
0.49
.07
-.03
-.23*
-.12
.23**
.31**
8.Performance-prove T1
3.41
0.79
-.03
.12
.04
.24**
.02
.15
.10
9.Performance-prove T2
3.29
0.81
-.02
-.04
.00
.09
.03
.02
-.02
.46**
10.Performance-avoid T1
2.32
0.71
.11
.17
.01
.26*
-.02
-.21*
.02
.36**
.32**
11.Performance-avoid T2
2.16
0.78
.08
.21*
.24*
.13
-.23**
-.20*
-.28**
.21*
.25**
.43**
12.Mindfulness T1
3.60
1.60
-.02
-.04
-.03
.04
.18*
-.09
.08
-.03
.00
.05
-.11
13.Mindfulness T2
3.66
1.64
.07
-.11
-.03
.08
.13
.01
.09
-.02
.03
.08
-.08
.78**
Note: 1) ** p < .01, * p < .05; 2) Response scale was 1-7 for attachment styles, and 1-5 for other variables that used Likert-scales.

39
Table 2. Hierarchical regression on the change of goal orientations.
Learning orientation T2
Performance-avoid orientation T2
Step 1
Step 2
Step 3
Step 1
Step 2
Step 3
Constant
2.75 (.48)**
2.76 (.46)**
2.67 (.45)**
1.53 (.72)*
1.42 (.69)*
1.50 (.68)*
Age
.00 (.01)
.00 (.01)
.00 (.01)
.01 (.01)
.01 (.01)
.01 (.01)
Gender
-.05 (.08)
.00 (.08)
.00 (.08)
.24 (.13)
.14 (.13)
.14 (.12)
Learning orientation T1
.34 (.09)**
.32 (.09)**
.33 (.09)**
-.25 (.14)
-.21 (.14)
-.21 (.13)
Performance-prove orientation T1
.01 (.06)
.03 (.06)
.03 (.06)
.09 (.09)
.09 (.08)
.09 (.08)
Performance-avoid orientation T1
.06 (.07)
.08 (.07)
.08 (.07)
.36 (.10)**
.37 (.10)**
.38 (.10)**
Attachment avoidance
-.06 (.04)
-.06 (.04)
.13 (.06)*
.13 (.06)*
Attachment anxiety
-.06 (.04)
-.08 (.04)*
-.01 (.06)
.03 (.06)
Facilitator support
.14 (.06)*
.19 (.06)**
-.19 (.08)*
-.27 (.09)**
Facilitator support * attachment anxiety
.16 (.06)**
-.22 (.09)**
Facilitator support * attachment avoidance
-.07 (.05)
.05 (.07)
F
3.15 (5,126)*
4.27 (3,123)**
4.27 (2,121)*
7.29 (5,126)**
4.03 (3,123)**
3.47 (2,121)*
Model R2
.11
.20
.25
.22
.29
.33
ΔR2
.11**
.08*
.05*
.22**
.07**
.04*
Note: 1) ** p < .01, * p < .05; 2) values are unstandardized parameter estimates for regression weights (standard errors in parenthesis).

40
Figure 1. The interaction plot of facilitator support * attachment anxiety in predicting
learning orientation at T2, after controlling for goal orientations at T1.
1
2
3
4
5
Low Facilitator Support High Facilitator Support
Learning orienation at T2, controlling for
goal orientations at T1
Low Anxious
Attachment
High Anxious
Attachment

41
Figure 2. The interaction plot of facilitator support * attachment anxiety in predicting the
performance-avoid orientation at T2, after controlling for goal orientations at T1.
1
2
3
4
5
Low Facilitator Support High Facilitator Support
Performance-avoid orientation at T2,
controlling for goal orientations at T1
Low Anxious
Attachment
High Anxious
Attachment