Learning and Individual Differences 22 (2012) 290–305
Contents lists available at SciVerse ScienceDirect
Learning and Individual Differences
journal homepage: www.elsevier.com/locate/lindif
Achievement goal orientations and academic well-being across the transition to upper
secondary education
Heta Tuominen-Soini a, b,⁎, Katariina Salmela-Aro b, Markku Niemivirta a
a
b
Institute of Behavioural Sciences, P.O. Box 9, 00014 University of Helsinki, Finland
Helsinki Collegium for Advanced Studies, P.O. Box 4, 00014 University of Helsinki, Finland
a r t i c l e
i n f o
Article history:
Received 16 June 2011
Received in revised form 11 November 2011
Accepted 28 January 2012
Keywords:
Achievement goal orientation
Well-being
Stability
Educational transition
Person-centered approach
a b s t r a c t
The aim of this study was to examine students' (N = 579) achievement goal orientation profiles, the temporal
stability of these profiles across the transition to upper secondary education, and profile differences in academic well-being (i.e., school value, school burnout, schoolwork engagement, satisfaction with educational
choice). By means of latent profile analysis, four groups of students with distinct motivational profiles
were identified: indifferent, success-oriented, mastery-oriented, and avoidance-oriented. Motivational profiles were relatively stable across the transition; half of the students displayed identical profiles over time
and most of the changes in the group memberships were directed towards neighboring groups. Regarding
group differences, indifferent and avoidance-oriented students showed less adaptive patterns of motivation
and academic well-being than did mastery- and success-oriented students. Both mastery- and successoriented students were highly engaged in studying and found their schoolwork meaningful, although
success-oriented students' stronger concerns with performance seemed to make them more vulnerable to
school burnout.
© 2012 Elsevier Inc. All rights reserved.
1. Introduction
Educational transitions can be a risk factor for students' academic
motivation and well-being. They have been often associated with
negative outcomes such as decreased academic value and interest,
decreased mastery goals, increased stress, and lower academic
achievement (Anderman & Anderman, 1999; Isakson & Jarvis, 1999;
Roeser, Eccles, & Freedman-Doan, 1999; Rudolph, Lambert, Clark, &
Kurlakowsky, 2001; Wigfield, Eccles, Schiefele, Roeser, & DavisKean, 2006). The fit between the person (student) and the environment (school) is a crucial factor affecting student's school adjustment
and well-being during an educational transition. As parallel changes
are occurring in both the individual and the context (see Eccles &
Roeser, 2009), the stage-environment fit (Eccles & Midgley, 1989) is
unbalanced and repeatedly reassessed. However, only some of the
students seem to encounter adjustment problems and declining motivation, while others go through this phase without these problems
(Ratelle, Guay, Larose, & Senécal, 2004; Roeser et al., 1999). Students'
well-being is associated with the goals they pursue in achievement
⁎ Corresponding author at: Helsinki Collegium for Advanced Studies, P.O. Box 4,
00014 University of Helsinki, Finland. Tel.: + 358 40 7679099; fax: + 358 9 19124509.
E-mail addresses: heta.tuominen@helsinki.fi (H. Tuominen-Soini),
katariina.salmela-aro@helsinki.fi (K. Salmela-Aro), markku.niemivirta@helsinki.fi
(M. Niemivirta).
1041-6080/$ – see front matter © 2012 Elsevier Inc. All rights reserved.
doi:10.1016/j.lindif.2012.01.002
situations, that is, goals related to self-improvement and growth are
associated with better socio-emotional functioning and more positive
self-evaluations, whereas goals related to validating and demonstrating
competence are more linked with adjustment problems and socioemotional vulnerability (e.g., Daniels et al., 2008; Dykman, 1998;
Kaplan & Maehr, 1999; Tuominen-Soini, Salmela-Aro, & Niemivirta,
2008). Grounding on these findings, we sought to expand prior research
by examining the longitudinal stability and changes in secondary school
students' achievement goal orientations and academic well-being during
an educational transition. Using a longitudinal person-centered approach, we examined whether students' motivational profiles and possible change in those profiles moderated the influence of educational
transition on students' academic well-being.
1.1. Achievement goal orientations
A prominent area in the study of student motivation over the past
several decades has been achievement goal research (see Kaplan &
Maehr, 2007; Urdan, 1997). Originally, the central distinction drawn
by achievement goal theorists was between mastery and performance
goals (Ames, 1992; Dweck, 1986; Nicholls, 1989), but later research has
expanded this dichotomous scheme by describing other goals related to
achievement behavior. A mastery goal refers to a striving to learn, understand, and improve skills based on an intrapersonal evaluative standard,
while a performance goal is seen as a striving to outperform others and
appear competent based on an interpersonal standard. Nicholls and his
colleagues (Nicholls, Patashnick, & Nolen, 1985; Nolen, 1988) identified
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
another class of goal, namely work-avoidant goals, which refer to avoiding challenging tasks, putting forth as little effort as possible and trying
to get away with it.
Elliot and Harackiewicz (1996) argued that the nature and function of
performance goals would be more accurately understood if they were
further differentiated into separate approach and avoidance components. Accordingly, performance-approach goals are directed at demonstrating competence, while performance-avoidance goals are directed at
avoiding the demonstration of incompetence (Elliot & Harackiewicz,
1996; see also Murayama, Elliot, & Yamagata, 2011; Skaalvik, 1997). Unlike work avoidance goals, which refer to the aim of avoiding schoolrelated work altogether, performance-avoidance goals reflect the aim
of avoiding signs of incompetence.
Recently, it has been suggested that also mastery goals could be
separated into approach and avoidance forms–avoidance mastery orientation referring to avoiding misunderstanding and not mastering
the task (Elliot & McGregor, 2001; Pintrich, 2000; see also Elliot,
Murayama, & Pekrun, 2011). Other mastery-related nuances include
mastery-extrinsic goals (Niemivirta, 2002b) and outcome goals
(Grant & Dweck, 2003). The mastery-extrinsic goals refer to the tendency of relying on external criteria such as grades or explicit feedback when evaluating whether one has attained the given goal of
mastering a subject or learning a new thing (Niemivirta, 2002b). Students holding this tendency seek to master school subjects and they
focus on absolute success (i.e., getting good grades) instead of relative
success (i.e., outperforming others), not necessarily due to its instrumental value, but rather due to the fact that from their viewpoint
good grades imply mastery and learning. In other words, masteryextrinsic orientation emphasizes achievement but not competition
(see also Brophy, 2005).
Despite the general consensus, some notable differences exist in
how achievement goals have been conceptualized and operationalized.
Basically, research seems to follow two approaches: one that looks at
the dispositions (i.e., achievement goal orientations) that are likely to
predict goal choices, and the other that places more emphasis on the
situation- and task-specific nature of particular goals (see Kaplan &
Maehr, 2007; Urdan, 1997). The present study builds on the former, a
conception already put forward by Nicholls (1989) and Dweck
(1986), and defines achievement goal orientation as a disposition that
reflects students' generalized tendencies to select certain goals and
favor certain outcomes in an achievement context (Niemivirta, 2002b;
see also Tuominen-Soini et al., 2008, Tuominen-Soini, Salmela-Aro, &
Niemivirta, 2011).
The multiple goals perspective (Pintrich, 2000; see also
Niemivirta, 2002b; Seifert, 1996; Tuominen-Soini et al., 2008, 2011)
states that students can and do pursue multiple goals simultaneously
in school settings. Echoing this perspective, we deem that individuals'
goal preferences can be described in terms of several dimensions that
all students share (i.e., all different classes of goals or types of orientations), but which vary in terms of individual importance or weight.
Thus, the relative emphasis on one or more of them becomes more
relevant than an individual dimension (cf., Dweck, 1996). Although
some debate exists regarding which combination of goals or goal orientations leads to the most adaptive outcomes, it is generally accepted
that students oriented towards learning and understanding (e.g.,
learning-oriented students, Niemivirta, 2002b; Tapola & Niemivirta,
2008; Turner, Thorpe, & Meyer, 1998; mastery-oriented students,
Roeser, Strobel, & Quihuis, 2002; Seifert, 1996) show a more adaptive
pattern of motivation and achievement than those weakly oriented towards mastery. With respect to the simultaneous emphasis on both
mastery and performance tendencies (e.g., multiple goals cluster,
Daniels et al., 2008; success-oriented students, Tuominen-Soini
et al., 2008, 2011; Turner et al., 1998; approach group, Luo, Paris,
Hogan, & Luo, 2011), the findings are twofold. Some studies show
that students inclined towards both mastery and performance use
more cognitive strategies and obtain better academic performance
291
than high-mastery/low-performance students (Bouffard, Boisvert,
Vezeau, & Larouche, 1995; Harackiewicz, Barron, Tauer, & Elliot,
2002; Pintrich, 2000), while some other studies demonstrate that
students endorsing dominantly mastery goals display the most
adaptive pattern of motivation and achievement (Meece & Holt,
1993; Roeser et al., 2002; Turner et al., 1998). The latter findings
suggest that strivings towards performance and success might,
even in the presence of mastery strivings, entail some unfavorable
outcomes, such as anxiety and vulnerability to emotional distress
(Daniels et al., 2008; Tuominen-Soini et al., 2008). Research also
shows that students who are only slightly preoccupied with both
mastery and performance (e.g., low-mastery/low-performance
group, Bouffard et al., 1995; Pintrich, 2000; low-motivation cluster,
Daniels et al., 2008; indifferent students, Tuominen-Soini et al.,
2008, 2011; uncommitted students, Turner et al., 1998) or who emphasize mainly avoidance tendencies (e.g., avoidance-oriented students, Tapola & Niemivirta, 2008; Tuominen-Soini et al., 2011;
Turner et al., 1998) have the least adaptive profile in terms of motivation and learning.
1.2. The development of achievement goal orientations
Relatively few empirical studies have explicitly investigated the longitudinal stability of either goals or goal orientations (see, however,
Fryer & Elliot, 2007; Muis & Edwards, 2009; Tuominen-Soini et al.,
2011). Further, even fewer studies have examined the development of
achievement goal orientations across educational transitions. The existing results concerning goal stability are diverse. On one hand, studies
evidence moderate to high stability (i.e., stability indexed by a correlation between two measurement points) in students' achievement
goals or goal orientations between school years (e.g., Meece & Miller,
2001; Middleton, Kaplan, & Midgley, 2004; Tuominen-Soini et al.,
2011) and even moderate stability in goal orientations across an educational transition (Anderman & Anderman, 1999; Anderman & Midgley,
1997). On the other hand, the presence of moderate to high rank-order
stability does not exclude the possibility of mean level changes even
within the same samples, and, accordingly, research has also suggested
that achievement goal endorsement varies over time.
Studies investigating goal stability across educational transitions
suggest that mastery goals are strongly endorsed in elementary
school, but that, after the transition to middle school, students become less oriented towards mastery goals (Anderman & Anderman,
1999; Anderman & Midgley, 1997; Shim, Ryan, & Anderson, 2008).
In contrast, performance goals have shown to increase (Anderman
& Anderman, 1999) or remain stable (Anderman & Midgley, 1997)
during the transition to middle school. Differentiating performance
orientation into separate approach and avoidance components,
Shim et al. (2008) found that mastery, performance-approach, and
performance-avoidance goals all declined during the middle school
transition; however, the major source of the overall decline was within year (i.e., from fall to spring in both sixth and seventh grades), not
between years (i.e., from spring of sixth grade to fall of seventh
grade). Hence, they concluded that moving into a new, larger school
environment does not necessarily lead to dramatic shifts in level of
goals. Less is known about the developmental shifts in work avoidance goals during educational transitions, but some evidence exists
about these shifts within and between school years, suggesting that
the endorsement of these goals remains moderately stable over
time (Chouinard & Roy, 2008; Tuominen-Soini et al., 2011).
More generally, studies have revealed that educational transitions
are a risk factor for academic motivation as they are often associated
with negative effects, such as decreased academic value and interest,
lower academic achievement, diminished feelings of competence,
and increased stress (Isakson & Jarvis, 1999; Roeser et al., 1999;
Rudolph et al., 2001; Wigfield et al., 2006). Then again, not all students experience the declining motivation. The risk appears to be
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higher among students, who perceive low ability, are poorly adjusted,
and are in competitive classrooms (Anderman, Maehr, & Midgley,
1999; Fredricks & Eccles, 2002; Roeser et al., 1999). It has been suggested that the undermining of motivation is most pronounced
right after the transition and tends to continue thereafter (Wigfield
& Eccles, 2000). According to the stage-environment fit theory
(Eccles & Midgley, 1989), this might be due to the fact that many of
the changes associated with educational transitions are at odds with
the developmental needs of adolescents (e.g., increased emphasis
on grades and competition, declines in adolescents' perception of
emotional support from teachers and sense of belonging in their
classrooms). If schools do not provide developmentally appropriate
educational environments for adolescents, they do not offer the
kind of social context that would continue to motivate students' interest and engagement and, consequently, negative developmental
changes may result. Negative developmental fit may lead to alienation from school and cynicism, but, in case the context fits well
with students' interests, goals, and psychological needs, the end result should be high engagement, adaptive motivation, and wellbeing (Eccles & Midgley, 1989; Salmela-Aro, Kiuru, & Nurmi, 2008).
A straightforward interpretation of the results concerning goal
stability is difficult due to the several sources of conceptual and empirical variation found in the research (see Kaplan & Maehr, 2007).
For example, if the dispositional view of achievement goal orientations is emphasized, one would expect relative stability in students'
goal orientations, but when the focus is on situation- and taskspecific goals, the role and meaning of stability is less clear. In addition to different conceptualizations and operationalizations, also the
educational contexts alter, the intervals between the measurement
points differ, and the age of participants varies across studies. Also,
most studies deploy a variable-centered approach, which might
mask important individual patterns of achievement goal orientations
among subgroups of individuals. Accordingly, there is a lack of research examining the individual development of achievement goal
orientations, especially across educational transitions.
1.3. Achievement goal orientations and well-being
Dweck (1986) previously suggested that the endorsement of certain goals is likely to be associated with different patterns of coping
and emotion. She found that students who adopted performance
goals tended to manifest a helpless pattern of responses when they
encountered failure. These students were characterized by disengagement from the task, negative self-evaluations, and negative affect. In
contrast, mastery-oriented students pursued learning goals and
were characterized by engagement with the task, optimistic orientation, and positive affect (see also Boekaerts, 1993).
Also, later research has consistently showed that students' focus
on mastery and learning is associated with various positive and adaptive patterns of coping and affect. For example, mastery goals have
been linked with experiencing pleasant emotions (e.g., enjoyment
of learning, pride, positive affect) and being less likely to experience
debilitating emotions (e.g., boredom, anger, negative affect)
(Daniels et al., 2008; Kaplan & Maehr, 1999; Linnenbrink, 2005;
Pekrun, Elliot, & Maier, 2006; Roeser et al., 2002; Turner et al.,
1998), and displaying high level of self-esteem and low levels of depressive symptoms and anxiety (Daniels et al., 2008; Dykman,
1998; Sideridis, 2005; Skaalvik, 1997; Tuominen-Soini et al., 2008).
Mastery-extrinsic goals, in turn, seem to be associated with some
adaptive patterns of coping and behavior (e.g., self-esteem, commitment, effort) and some signs of psychological distress (e.g., stress,
fear of failure) (Niemivirta, 2002b; Tuominen-Soini et al., 2008,
2011).
The findings concerning performance goals have been more
mixed. Many studies suggest that endorsing performance goals is associated with lower levels of psychological well-being when
compared to pursuing mastery goals (Daniels et al., 2008; Dykman,
1998; Kaplan & Maehr, 1999). For example, performance-approach
goals have been associated with test anxiety (Daniels et al., 2008;
Linnenbrink, 2005), negative affect (Smith, Sinclair, & Chapman,
2002; Turner et al., 1998), and stress (Smith et al., 2002; TuominenSoini et al., 2008). However, some studies suggest that
performance-approach goals are not that maladaptive with respect
to well-being; they have been associated positively with feelings of
pride (Pekrun et al., 2006) and negatively with anxiety and depression (Sideridis, 2005). Performance-avoidance goals have been systematically linked with maladaptive outcomes, such as hopelessness
and shame (Pekrun et al., 2006), anxiety, depressive symptoms,
stress, lower self-esteem (Sideridis, 2005; Skaalvik, 1997; Smith et
al., 2002; Tuominen-Soini et al., 2008), feelings of sadness, and internalizing and externalizing problems (Roeser et al., 2002). It seems
that even though performance goals may be beneficial for cognitive
engagement and achievement, they come at a cost. Work avoidance
goals have been studied less, but they have been consistently associated with passivity and other negative outcomes, such as anxiety and
lower self-esteem (Skaalvik, 1997).
Following a multiple goals perspective, Pintrich (2000) found that
those in the high mastery and high performance goals category
showed the highest levels of positive affect, whereas those characterized by high performance and low mastery reported less positive affect. This suggests that performance goals may undermine positive
affect unless paired with mastery goals. Also, Daniels et al. (2008)
found that students who endorsed mastery goals, either on their
own or with performance goals, experienced greater enjoyment and
less boredom compared to students endorsing predominantly performance goals. Further, students who pursued performance goals, even
in combination with mastery goals, were more susceptible to anxiety
than those who focused primarily on mastery goals or were low on
both goals (Daniels et al., 2008). Similarly, Tuominen-Soini et al.
(2008) found that, compared to students without strong performance
tendencies (mastery-oriented students), students holding performance
tendencies along with strivings toward mastery (success-oriented students) were more susceptible to psychological distress despite their apparently positive motivational profile, high commitment, and excellent
academic achievement. Students aiming mainly at effort reduction
(avoidance-oriented students) showed the most maladaptive pattern
of motivation and well-being.
In the present study, taking into account the centrality of school in
the lives of adolescents (Eccles & Roeser, 2009), well-being is defined
in relation to the school context. Both negative and positive aspects of
academic well-being are examined and, consequently, we focus on
school value, school burnout, and schoolwork engagement, which
we consider to be central indicators of well-being at school. Following
Eccles' and her colleagues' work on task value (e.g., Eccles et al., 1983;
Wigfield & Eccles, 2000), school value is defined as the perceived
meaningfulness of schooling in general. The constructs of attainment
value, intrinsic value, and utility value are used to reflect school value
(Niemivirta, 2004). In several studies, students' mastery goals and
task values have been found to relate positively to one another in different academic domains (e.g., Bråten & Olaussen, 2005; Wolters, Yu,
& Pintrich, 1996). A study employing a broader set of achievement
goal orientations, suggested that general school value was associated
positively with both mastery-intrinsic and mastery-extrinsic orientations and negatively with performance-avoidance and avoidance orientations (Tuominen-Soini et al., 2008).
School burnout is defined as consisting of exhaustion due to school
demands, cynical and detached attitude toward one's school, and feelings of inadequacy as a student (Salmela-Aro, Kiuru, Leskinen, &
Nurmi, 2009). Emotional exhaustion and cynicism are initial predictors
of feelings of inadequacy (Parker & Salmela-Aro, 2011). A study investigating students' achievement goal orientations and school burnout
(Tuominen-Soini et al., 2008) suggested that all performance-focused
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
tendencies (i.e., performance-approach, performance-avoidance, and
mastery-extrinsic orientations) were associated with exhaustion.
Mastery-intrinsic and mastery-extrinsic orientations were negatively associated and performance-avoidance and avoidance orientations were positively associated with cynicism and inadequacy.
When looking at motivational profiles, success-oriented students
reported more exhaustion and feelings of inadequacy than
mastery-oriented students.
Schoolwork engagement is defined as a positive, fulfilling,
study-related state of mind that is characterized by vigor, dedication, and absorption (Salmela-Aro & Upadyaya, 2012). Vigor refers
to high levels of energy and mental resilience while studying, the
willingness to invest effort in one's schoolwork, and persistence
also in the face of difficulties. Dedication is characterized by a
sense of significance, enthusiasm, inspiration, pride, and challenge
in relation to schoolwork. Absorption is characterized by being
fully concentrated and happily engrossed in one's schoolwork,
whereby time passes quickly and one has difficulties with detaching oneself from schoolwork. In prior research, achievement goal
orientations have not been studied in relation to this particular theoretical framework, but goal theorists have commonly argued that
a mastery orientation sustains school engagement better than does
a performance orientation (e.g., Gonida, Voulala, & Kiosseoglou,
2009; Midgley, 2002).
2. The present study
Despite the extensive research on achievement goal orientations,
there are several limitations, which the present study aims to complement. First, since there are varying results concerning the stability
and change in achievement goal orientations and since there is a
lack of knowledge on the development of achievement goal orientations during educational transitions, the present study used a longitudinal design and examined the issue of goal stability during the upper
secondary transition. Second, as the majority of studies have utilized
a variable-centered approach, we addressed the question concerning
individual development and utilized a person-centered approach in
order to identify distinct motivational profiles. This way, we could examine the developmental change in motivation as a function of multiple goals, that is, with regard to shifts within a person's goal
configurations. Third, considering the centrality of school in the
lives of adolescents and the importance of school and academic
achievement to adolescents' socio-emotional functioning (Eccles &
Roeser, 2009), the relation between motivation and academic wellbeing has not yet been examined thoroughly enough. Therefore, as
suggested by Roeser and his colleagues (Roeser, Eccles, & Strobel,
1998; Roeser et al., 1999), we linked the study of academic and emotional functioning and tried to examine the complex interplay between motivation and well-being in changing educational contexts.
Instead of using concepts reflecting general well-being (e.g., selfesteem, depressive symptoms), we used context-specific indices of
well-being that are directly linked with school and studying. To conclude, given the demanding nature and importance of the transition
to upper secondary education, we followed students over the course
of this transition and focused on students' motivation and academic
well-being. Specifically, we addressed the following research
questions:
(1) What kinds of achievement goal orientation profiles can be identified among students during the transition to upper secondary
education?
(2) How stable are achievement goal orientation profiles and how
do they change across the educational transition?
(3) How students with different achievement goal orientation profiles
differ with respect to academic well-being (i.e., school value,
293
school burnout, schoolwork engagement, and satisfaction with
educational choice)?
(4) How are the changes in achievement goal orientation profiles
related to parallel changes in academic well-being?
We propose that students endorse multiple, even competing,
goals simultaneously and that the patterns of these goals are rather
stable over time and differentially related to academic well-being.
Four general hypotheses were formulated. First, based on prior
work (Niemivirta, 2002b; Tuominen-Soini et al., 2008, 2011), we
expected to find groups of students who dominantly display mastery
tendencies (mastery-oriented students), who emphasize both mastery and performance (success- and/or performance-oriented students), and who primarily display avoidance tendencies (avoidanceoriented students), as well as a group of students without a dominant
tendency towards any specific goal orientation (indifferent students).
Second, as previous studies have exhibited moderate to high stability
in goal orientations between school years (Meece & Miller, 2001;
Middleton et al., 2004; Tuominen-Soini et al., 2011) and even moderate stability in goal orientations across an educational transition
(Anderman & Anderman, 1999; Anderman & Midgley, 1997), we
expected relatively high normative stability in goal orientations
across the transition to upper secondary education. Since in a previous study (Tuominen-Soini et al., 2011) utilizing a similar theoretical
approach and methodology and partly same participants considerable
stability in achievement goal orientations was detected preceding educational transitions, we were here able to specifically address the
possible moderating role of an educational transition to the stability
of goal orientations. Moreover, in line with prior research (Bråten &
Olaussen, 2005; Ratelle et al., 2004; Roeser et al., 1999), we assumed
that while most students would display a relatively stable motivational profile, some students would demonstrate either adaptive or
maladaptive change in motivation across the transition. Third, regarding well-being, our predictions were mainly based on the results
from Roeser et al. (2002), Sideridis (2005), Daniels et al. (2008), and
Tuominen-Soini et al. (2008). We hypothesized that students who
dominantly display mastery tendencies would express most adaptive
academic well-being, students pursuing more performance-related
goals and outcomes would show some signs of distress at school,
and students emphasizing avoidance tendencies would show the
most maladaptive pattern of academic well-being. Finally, we presumed that possible changes toward more favorable motivational
profiles would promote academic well-being, while changes toward
less favorable motivational profiles would undermine academic
well-being.
3. Method
3.1. Context
In Finland, the comprehensive school is a nine-year compulsory
general schooling for all children aged 7–16. After completing compulsory schooling, young Finns face an important choice: whether
to continue in general education, that is, general upper secondary
school or to apply for vocational upper secondary education. In the
year 2004, 54% of completers of comprehensive school opted for the
general upper secondary school and 38.5% for the vocational school,
while 2.5% remained in the comprehensive school to attend the optional 10th grade and 5% did not continue studying in formal education immediately (Statistics Finland, 2009). Student selection to
general upper secondary schools is mainly based on previous academic achievement, whereas selection criteria used by vocational
schools may also include work experience and aptitude tests. After
completing either general upper secondary or vocational education
(the studies are usually accomplished in three years), students are eligible to move into higher education. In case completers of
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comprehensive school feel that their skills are not quite up to the
standard required by further education, they can enroll in additional,
optional education in the so-called 10th grade. Some of the students,
who do not continue in formal education after comprehensive school,
may study at folk high schools, which offer a broad range of education
that is mainly non-formal.
In Finland, the transition to upper secondary education is a key educational transition in adolescence. Students' academic achievement
during the ninth grade has important ramifications as high academic
achievement is required to be able to enter general upper secondary
school and also some vocational schools. For students opting for vocational schools, the forthcoming transition entails also a selection of occupational field. After the transition, especially general upper
secondary school studies are very different in structure from comprehensive school studies; students choose courses according to their individual programs and need student counseling in planning their own
program. Therefore, the ninth grade as well as the forthcoming transition can be assumed to be stressful for students and a challenge for
school adjustment (see Salmela-Aro et al., 2008). Studies suggest that
although the Finnish youth have proved to be rather competent
learners in many international comparisons (e.g., PISA, 2006), this
does not necessarily mean that they are thriving in school. According
to the WHO's study, less than 15% of 11-year-olds, less than 10% of
13-year-olds and less than 5% of 15-year-olds in Finland reported liking
school a lot (Currie et al., 2004). Moreover, general upper secondary
school students' burnout is of concern, since it has been found that
they experience more exhaustion than vocational school students
(Salmela-Aro et al., 2008).
3.2. Participants
This study is part of the ongoing Finnish Educational Transitions
(FinEdu) Studies. The data were collected from all the lower secondary
schools in one city in Eastern Finland. At the beginning of the study the
participants were about 15-year-old students (M = 15.01, SD= 0.20)
facing the transition from comprehensive school to upper secondary
education. At the first measurement point, 707 students returned
their questionnaires. A total of 579 students (82% of the original sample,
288 girls and 291 boys) participated in the study at both measurement
points and had complete achievement goal orientation information and
were included in the final sample. Independent samples t-tests were
performed in order to examine whether the students in the final sample
and the students with incomplete data differed in their achievement
goal orientations in Time 1. The only significant difference was found
on mastery-extrinsic orientation (t(143.14)=4.51, pb .001, d=0.52)
favoring the participants with full data (M=5.45, SD=1.17) over the
ones with incomplete data (M=4.83, SD=1.35). No differences
were found on mastery-intrinsic (t(690)=1.87, p=.062, d=0.19),
performance-approach (t(688)=1.52, p=.130, d=0.16), performanceavoidance (t(691)=1.20, p=.230, d=0.12), and avoidance orientations
(t(150.35)=−1.30, p=.195, d=0.15).
3.3. Measures
The participants completed questionnaires tapping various types
of constructs related to motivation and academic well-being. Descriptive statistics (i.e., raw means and standard deviations) and internal
consistencies (i.e., alphas) for all variables are presented in Table 1.
3.3.1. Achievement goal orientations
Five types of achievement goal orientations were assessed using
an instrument originally developed by Niemivirta (2002b; see also
Tuominen-Soini et al., 2008, 2011). The scale for mastery-intrinsic
orientation comprised three items assessing students' focus on
learning, understanding, and gaining competence (e.g., “To acquire
new knowledge is an important goal for me in school”). The scale
Table 1
Descriptive statistics and internal consistencies for all variables.
Variable
Mastery-intrinsic orientation
Mastery-extrinsic orientation
Performance-approach orientation
Performance-avoidance orientation
Avoidance orientation
School value
Exhaustion at school
Cynicism toward the meaning of school
Sense of inadequacy as a student
Schoolwork engagement
Satisfaction with educational choice
Time 1
Time 2
M
SD
α
M
SD
α
5.03
5.45
3.78
3.83
4.38
5.32
2.69
2.20
2.41
−
−
1.18
1.17
1.26
1.48
1.30
1.14
.97
1.05
1.01
−
−
.87
.86
.68
.82
.73
.71
.60
.81
.75
−
−
5.19
5.38
3.68
3.67
4.33
5.49
2.67
2.23
2.44
3.58
4.05
1.14
1.14
1.33
1.45
1.30
1.04
1.04
1.11
1.05
1.31
.79
.86
.84
.72
.85
.77
.64
.77
.87
.79
.94
.91
Note. α = Cronbach's alpha.
for mastery-extrinsic orientation comprised three items assessing students' aspiration on getting good grades and succeeding in school (e.g.,
“My goal is to succeed in school”). The scale for performance-approach
orientation comprised three items assessing students' focus on relative
ability and judgments of competence (e.g., “An important goal for me in
school is to do better than other students”). The scale for performanceavoidance orientation comprised three items assessing the avoidance of
demonstrating normative incompetence (e.g., “I try to avoid situations
in which I might fail or make a mistake”). The scale for avoidance orientation (referring to work avoidance; Nicholls et al., 1985) comprised three
items reflecting students' desire to avoid achievement situations and to
minimize the effort and time spent on studying (e.g., “I try to get away
with as little effort as possible in my schoolwork”). Students rated all
items using a 7-point Likert-type scale ranging from 1 (Not true at all) to
7 (Very true). Only 0.7% of the item scores measuring achievement goal
orientations were missing. The missing values in achievement goal orientation measures were imputed by expectation–maximization (EM) algorithm as implemented in the SPSS statistical program. Composite scores
were computed for each scale by averaging the scale sum scores.
3.3.2. School value
The scale for school value (Niemivirta, 2004) comprised three items
assessing students' perceived importance, utility, and interestingness of
school going and studying (e.g., “I think going to school is a waste of
time”, reversed item). Items were rated using a 7-point Likert-type
scale ranging from 1 (Not true at all) to 7 (Very true).
3.3.3. School burnout
School burnout was assessed by using the School Burnout Inventory (SBI) developed by Salmela-Aro and colleagues (Salmela-Aro &
Näätänen, 2005; for validity and reliability, see Salmela-Aro et al.,
2009). The inventory consists of three subscales: exhaustion at
school (e.g., “I feel overwhelmed by my schoolwork”), cynicism toward the meaning of school (e.g., “I feel that I am losing interest in
my schoolwork”), and sense of inadequacy as a student (e.g., “I
often have feelings of inadequacy in my schoolwork”). Each subscale
comprised three items, which were assessed using a 6-point Likerttype scale ranging from 1 (Completely disagree) to 6 (Completely
agree). Composite scores were computed separately for the three
subscales.
3.3.4. Schoolwork engagement
Schoolwork engagement was assessed at the second measurement point by using the Schoolwork Engagement Inventory (EDA;
Salmela-Aro & Upadyaya, 2012; see also Schaufeli, Bakker, &
Salanova, 2006). The scale consists of nine items measuring vigor
(e.g., “When I study, I feel that I am bursting with energy”),
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
dedication (e.g., “I am enthusiastic about my studies”), and absorption (e.g., “Time flies when I'm studying”) in relation to schoolwork.
Students rated all items on a 7-point Likert-type scale ranging from
0 (Never) to 6 (Every day). For the purpose of this study, a composite
score was computed from all nine items to indicate the level of students' schoolwork engagement.
3.3.5. Satisfaction with educational choice
After the transition to upper secondary education, students were
asked how satisfied they were with their choice of education. Four
items (e.g., “Are you satisfied with your current form of education?”)
were rated on a 5-point Likert-type scale ranging from 1 (Not at all) to
5 (Very much).
3.3.6. Educational track
At the second measurement point, students were asked to report
their current educational track. Track was coded as follows: general
upper secondary school students were coded 1 (Academic track,
N = 372), vocational school students were coded 2 (Vocational track,
N = 174), and those students who attended the optional 10th grade
of comprehensive school or went on to study in a folk high school
(i.e., outside formal education) were coded 3 (Postpone track,
N = 33). In this study, no students reported discontinuing studying
entirely.
3.4. Procedure
The participants completed self-report questionnaires once during
the ninth grade (spring term 2004) and once during the first year of
upper secondary education (spring term 2005). Achievement goal
orientations, school value, and school burnout were assessed at both
measurement points, whereas schoolwork engagement and satisfaction with educational choice were assessed only at the second measurement point. Questionnaires were group-administered to
students in school during regular class sessions.
3.5. Data analyses
3.5.1. Preliminary analyses
Longitudinal confirmatory factor analysis (LCFA) was used in
order to examine structural stability (i.e., measurement invariance),
stability in mean levels, and normative stability (i.e., the degree to
which the relative ordering of the subjects on the variable remains
constant over time). LCFAs were conducted on items reflecting
achievement goal orientations in Time 1 and Time 2 using the
Mplus statistical package (Version 5.1; Muthén & Muthén,
1998–2006). The procedure for testing invariance involved testing
and comparing six models that imposed successive equality restrictions on model parameters. Invariance was tested by comparing the
goodness of fit statistics of a particular model with a model having additional constraints. The combination of the following indices was
used to evaluate overall model fit: Comparative Fit Index (CFI;
Bentler, 1990) with a cutoff value of >.95, the root mean square
error of approximation (RMSEA; Steiger, 1990) with a cutoff value
of b.06, and the standardized root mean square residual (SRMR; Hu
& Bentler, 1998) with a cutoff value of b.09. In order to take into account the slight non-normality of the sample data, maximum likelihood parameter estimates with robust standard errors and meanadjusted chi-square test statistics (S–B χ 2) were used for analyzing
mean and covariance structures (Satorra & Bentler, 1994). To calculate ΔS–B χ 2, parallel analyses with both robust estimators and ordinary maximum likelihood estimates were run. For assessing
comparative model fit, the chi-square difference tests with the
Satorra–Bentler scaled chi-square were performed using the
method described by Satorra (2000). The equality constraints
are supported if the χ 2-test produces a non-significant loss of
295
fit for the constrained model as compared to the unconstrained
model. Correlational analyses were performed in order to examine the convergent and discriminant validity of the achievement
goal orientations.
3.5.2. Latent profile analysis
A person-centered approach was utilized in order to classify students into homogenous groups with similar patterns of achievement
goal orientation (see Niemivirta, 2002a). At the level of statistical
analysis, this means that individuals are studied on the basis of their
patterns of individual characteristics rather than on the basis of separate variables (Bergman & Nurmi, 2010). Since we were interested in
studying the development of individual patterns across time (for a
similar perspective, see Janson & Mathiesen, 2008; Tuominen-Soini
et al., 2011), we used the ISOA procedure (I-States as Objects Analysis; Bergman & El-Khouri, 1999). I-state is defined as an individual's
pattern of values at a specific measurement point in the variables
that are to be used for classification. It is assumed in ISOA that approximately the same classification structure applies at all measurement points (although individuals might change the pattern they
belong to and the proportion of individuals belonging to the different
classes might vary between measurement points) (Bergman & Nurmi,
2010).
To start with, we reorganized our longitudinal data and created a
new file consisting of all I-states for all individuals. Next, we carried
out a series of latent profile analyses (LPA). LPAs were conducted
using the composite scores of the five scales assessing achievement
goal orientations. LPA is a probabilistic or model-based variant of traditional cluster analysis (Muthén & Muthén, 2000; Vermunt &
Magidson, 2002), which goal is to identify the smallest number of latent classes (groups) that adequately describe the associations among
observed continuous variables (achievement goal orientations). In
the analyses, classes are added stepwise until the model optimally
fits the data. Bayesian Information Criterion (BIC), and Vuong–Lo–
Mendell–Rubin (VLMR) and adjusted Lo–Mendell–Rubin likelihood
ratio tests were used as the statistical criteria for choosing the best fitting model. A decrease in BIC when an additional class is added indicates an improvement in model fit. Regarding VLMR and LMR, a
resulting p value less than .05 indicates that the estimated model is
preferable over the reduced model (Lo, Mendell, & Rubin, 2001).
Also, classification quality (i.e., entropy value), the usefulness and
interpretableness of the latent classes in the solutions as well as the
reasonableness of the solutions in relation to theory and previous research were considered when comparing different models. The analyses were conducted using the Mplus program (Muthén & Muthén,
1998–2006). In the LPA models, covariances were allowed to vary
across clusters. Finally, the data were reorganized in such a way
that the data for each student at both measurement points were
again handled as two successive measurements of the same
individual.
3.5.3. Configural frequency analysis
A configural frequency analysis (CFA; von Eye, 1990) was carried
out to examine the stability of and changes in group memberships
from Time 1 to Time 2. CFA compares the observed to expected frequencies in a cross-tabulation and asks whether cell frequencies are
larger or smaller than could be expected based on some chance
model. By means of first order CFA, we examined whether there are
any specific classes that individuals tend to stay in more frequently
than would be expected by chance alone (i.e., individual stability)
and whether there is movement between classes that cannot be ascribed to chance fluctuations (i.e., individual change). Types are patterns that are observed more frequently than expected by chance
and antitypes are patterns that are observed less frequently than
expected by chance.
296
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
3.5.4. Analyses of variance and covariance
One-way ANOVAs were conducted in order to examine how students with different achievement goal orientation profiles differ
with respect to academic well-being. ANOVAs were performed separately for Time 1 and Time 2. In addition, we investigated how the
changes in achievement goal orientation profiles from Time 1 to
Time 2 were related to academic well-being. For that purpose, and
to control for the influence of Time 1 well-being, we performed
two-way (Change in Goal Orientation Group × Educational Track)
ANCOVAs with Time 1 well-being measures as covariates.
4. Results
4.1. Preliminary results
4.1.1. Structural stability of achievement goal orientations
A model for the subsequent invariance analyses 1 is illustrated in
Fig. 1 and the standardized factor loadings and residual variances
for the final measurement model are presented in Appendix A. The
fit indices for the models tested are presented in Table 2. All of the
subjective fit indices met the recommended criteria, and hence, suggested a good model-data fit for all six of the models within the invariance routine. Next, we compared the fit of the models. An
acceptable fit of Model 1 indicated configurally invariant factor structure over time. Metric invariance was achieved; the model with equal
factor pattern and loadings across measurement points (M2) fit the
data better than the unconstrained model (M1) did. The model with
equal internal consistency (M3) fit the data better than the previous
model (M2). Model 4 did not fit the data better than Model 3, but
by freeing two pairs of intercepts the model fit improved significantly
(M4b) and, consequently, sufficient scalar invariance was achieved.
The test for equivalence of factor variance (M5) did appear to be viable, also. To sum up, the results of LCFAs indicated sufficient measurement invariance, meaning that equivalent achievement goal
orientation constructs were assessed at both measurement points.
4.1.2. Stability in mean levels
The results of LCFA indicated that the test for equivalence of factor
means (M6) was not supported. Although the chi-square difference
test between Model 6 and Model 5 was significant, the subjective fit
indices were acceptable for Model 6 as well. Based on modification indices, three latent factor means were freed: mastery-intrinsic (Time
1 M = 5.27, SD = 1.05; Time 2 M = 5.44, SD = 1.05; p b .01, d = 0.16),
mastery-extrinsic (Time 1 M = 5.42, SD = 1.06; Time 2 M = 5.37,
SD = 1.06; p = ns., d = 0.05), and performance-avoidance orientation
(Time 1 M = 4.08, SD = 1.44; Time 2 M = 3.90, SD = 1.44; p b .05,
d = 0.13). In other words, mastery-intrinsic orientation increased
slightly and mastery-extrinsic and performance-avoidance orientations decreased slightly over time. This modification significantly improved the model fit (M6b).
4.1.3. Normative stability of achievement goal orientations
Disattenuated correlations between the latent constructs across the
measurement points were .48 (p b .001) for mastery-intrinsic, .57
(p b .001) for mastery-extrinsic, .53 (p b .001) for performanceapproach, .54 (p b .001) for performance-avoidance, and .55 (p b .001)
1
Cross-sectional confirmatory factor analyses on achievement goal orientations
were first performed separately for the two time points to verify the acceptability of
the measurement of the constructs. The model fit the data well at Time 1, χ2 (80,
N = 579) = 239.70, p b 0.001, CFI = .96, RMSEA = .059, SRMR = .049, and at Time 2, χ2
(79, N = 579) = 247.14, p b 0.001, CFI = .96, RMSEA = .061, SRMR = .049. Error covariances between one pair of similarly worded items were freed at Time 2.
for avoidance orientation. The squared multiple correlations (R2) for
the five factors were .23, .32, .28, .29, and .30, respectively. As demonstrated by high disattenuated correlations between the latent constructs across the measurement points, the results indicated quite
substantial normative stability in achievement goal orientations.
4.1.4. Correlational results
The correlational results (see Table 3) demonstrated slightly different patterns of associations for mastery-intrinsic and masteryextrinsic orientations, mastery-extrinsic and performance-approach
orientations, and performance-avoidance and avoidance orientations
and, thus, provided support for convergent and discriminant validity.
For example, mastery-intrinsic and mastery-extrinsic orientations
were both positively related to school value, schoolwork engagement,
and satisfaction with educational choice, and negatively related to
cynicism and inadequacy, but differently related to exhaustion;
mastery-extrinsic orientation was positively related to exhaustion,
while mastery-intrinsic orientation was not related to it at Time 1
and negatively related to it at Time 2. Mastery-extrinsic and
performance-approach orientations were similarly (positively) related to exhaustion, but differently related to other indices of well-being
(mastery-extrinsic orientation being more favorably related to wellbeing). Finally, the patterns of associations were slightly different
for performance-avoidance and avoidance orientations; both were
negatively related to school value and positively related to cynicism
and inadequacy, but performance-avoidance orientation was positively related to exhaustion while avoidance orientation was not related to it, and, on the other hand, avoidance orientation had a
stronger negative correlation to engagement.
4.2. Achievement goal orientation profiles
The first main goal of this study was to examine what kinds of
achievement goal orientation profiles can be identified among students during the transition to upper secondary education. The results
from a series of LPAs (see Table 4 for fit indices) showed that the BIC
decreased when additional latent classes were added, but the VLMR
and LMR tests provided clear support for the expected four-class solution. The entropy value was 0.74, which indicates that the four-class
model provided a clear classification. The average individual posterior
probabilities for being assigned to a specific latent class are presented
in Appendix B. The four groups were labeled, according to the score
mean profiles, as indifferent, success-oriented, mastery-oriented, and
avoidance-oriented (see Fig. 2). The students in the indifferent group
(N = 421, 36%) represented a typical student in the sample with
their joint—yet weak—emphasis on mastery, performance, and avoidance, in other words, they did not display a dominant tendency towards any specific achievement goal orientation (see Table 5 for
pairwise comparisons on raw mean values and Appendix C for descriptive statistics and number of students for Time 1 and Time 2). Indifferent students had scores close to the sample mean on all
achievement goal orientations, which can be seen as a relatively
“flat” profile in Fig. 2. Success-oriented students (N = 411, 36%)
expressed high levels of mastery-extrinsic, mastery-intrinsic, and
both performance-related orientations. They seemingly strived for
both absolute and relative success, although they considered the
goal of learning important as well. Mastery-oriented students
(N = 243, 21%) emphasized both mastery-intrinsic and masteryextrinsic orientations but had relatively low scores on all other orientations. Hence, an important goal for them in school was to learn as
much as possible, yet they also stressed the importance of getting
good grades. Avoidance-oriented students (N = 83, 7%) scored high
on avoidance orientation and, in contrast, very low on masteryintrinsic and mastery-extrinsic orientations. They mainly aimed at
minimizing the effort and time spent on studying.
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
Time 1
Time 2
Mastery intrinsic
orientation
Mastery intrinsic
orientation
297
MI1
MI1
MI2
MI2
MI3
MI3
ME1
ME1
Mastery extrinsic
orientation
ME2
Mastery extrinsic
orientation
ME2
ME3
ME3
PAP1
PAP1
Performance approach
orientation
PAP2
Performance approach
orientation
PAP2
PAP3
PAP3
PAV1
PAV1
Performance avoidance
orientation
Performanceavoidance
orientation
PAV2
PAV2
PAV3
PAV3
AV1
AV1
Avoidance
orientation
AV2
Avoidance
orientation
AV2
AV3
AV3
Fig. 1. The measurement model for scales assessing achievement goal orientations. Note. For the sake of clarity, freely estimated covariances between parallel error terms are omitted from
the figure.
4.3. Stability of achievement goal orientation profiles
The second main goal of this study was to examine the stability of
and changes in achievement goal orientation profiles (i.e., group
memberships) over time. Goal orientation groups at Time 1 and
Time 2 provided sixteen possible configurations. Application of CFA
(χ 2 (9, N = 579) = 143.04, p b 0.001) revealed four types and one
antitype (see Table 6 and Fig. 3). It turned out that four out of four
cells, those corresponding to individuals belonging to the same class
at both measurement points, showed significant types, and it was
untypical for indifferent students to move to mastery-oriented
group (antitype).
Approximately half of the students displayed a stable motivational
profile over time. Most of the changes that did occur in the group
memberships were directed towards groups with fairly similar motivational profiles, and there were only few clear changes. More specifically,
46% of students moved to a neighboring group (e.g., from masteryoriented to success-oriented), only 2% of students demonstrated substantive, unfavorable change in their profile (i.e., from mastery- or
success-oriented to avoidance-oriented), and only 2% of students demonstrated considerable, favorable change in their profile (i.e., from
avoidance-oriented to mastery- or success-oriented).
4.4. Differences in academic well-being
In order to further describe the characteristics of the motivational
profiles, we examined how students with different profiles differed
with respect to academic well-being variables by means of one-way
Table 2
Goodness of fit statistics for alternative models.
Model
Hypothesis
χ2 MLM
df
CFI
RMSEA
SRMR
Hypothesis test
Δ S–B χ2
Δ df
p
M1
M2
M3
M4
M4b
M5
M6
M6b
Configural invariance
Metric invariance
Equivalence of residual variance
Scalar (item intercept) invariance
M4 + two pairs of intercepts free
Equivalence of factor variance
Equivalence of factor means
M6 + 3 factor means free
684.028
700.287
721.796
766.593
736.763
742.408
770.310
743.732
345
355
370
380
378
383
388
385
.95
.95
.95
.95
.95
.95
.95
.95
.041
.041
.041
.042
.040
.040
.041
.040
.046
.047
.047
.048
.047
.048
.049
.048
Overall fit
M2–M1
M3–M2
M4–M3
M4b–M3
M5–M4b
M6–M5
M6b–M5
16.265
23.236
48.347
14.601
3.813
30.677
0.971
10
15
10
8
5
5
2
0.092
0.079
0.000
0.067
0.577
0.000
0.615
Note. CFI = comparative fit index; RMSEA = root mean square error of approximation; SRMR = standardized root mean square residual; Δ S–B χ2 = chi-square difference test
with the Satorra–Bentler scaled chi-square.
298
Table 3
Correlations.
Measures
Time 1 Achievement goal orientations
2.
3.
4.
5.
6.
7.
8.
−
.73⁎⁎
Time 2 Achievement goal orientations
9.
10.
−.21⁎⁎
−.12⁎⁎
.10⁎
.23⁎⁎
.19⁎⁎
−.15⁎⁎
.30⁎⁎
.32⁎⁎
.38⁎⁎
−.27⁎⁎
−.24⁎⁎
−
11.
12.
13.
Time 2 Academic well-being
14.
15.
−
−.44⁎⁎
.05
.36⁎⁎
.31⁎⁎
−.43⁎⁎
−.21⁎⁎
−
−.13⁎⁎
−.51⁎⁎
−.35⁎⁎
.43⁎⁎
.37⁎⁎
16.
17
18.
19.
−
−.39⁎⁎
−.43⁎⁎
−
20.
−
.53⁎⁎
.23⁎⁎
.03
−.34⁎⁎
.43⁎⁎
.06
−.36⁎⁎
−.23⁎⁎
.43⁎⁎
.29⁎⁎
−.01
−.03
−.26⁎⁎
.21⁎⁎
−.01
−.23⁎⁎
−.16⁎⁎
.35⁎⁎
.22⁎⁎
−
.39⁎⁎
.11⁎
−.23⁎⁎
.44⁎⁎
.21⁎⁎
−.38⁎⁎
−.15⁎⁎
.27⁎⁎
.50⁎⁎
.10⁎
.09⁎
−.14⁎⁎
.15⁎⁎
.19⁎⁎
−.10⁎
−.02
.20⁎⁎
.14⁎⁎
−
.38⁎⁎
.09⁎
.01
.14⁎⁎
−.04
.07
.08
.23⁎⁎
.45⁎⁎
.23⁎⁎
.02
−.07
.07
−.04
.04
.07
.09⁎
−
.20⁎⁎
−.11⁎⁎
.24⁎⁎
.17⁎⁎
.28⁎⁎
−
−.46⁎⁎
−.05
.42⁎⁎
.32⁎⁎
.03
−.50⁎⁎
−.29⁎⁎
−
.33⁎⁎
.52⁎⁎
−.07
.00
.21⁎⁎
.47⁎⁎
−.29⁎⁎
−.21⁎⁎
.10⁎
.12⁎⁎
.45⁎⁎
−.29⁎⁎
.29⁎⁎
.29⁎⁎
−.05
−.09⁎
−.24⁎⁎
.41⁎⁎
.03
.16⁎⁎
.12⁎⁎
.24⁎⁎
.02
.27⁎⁎
.21⁎⁎
−.38⁎⁎
−.21⁎⁎
.02
−.24⁎⁎
−.17⁎⁎
.28⁎⁎
.19⁎⁎
.06
−.12⁎⁎
.22⁎⁎
.16⁎⁎
.20⁎⁎
−.06
−.11⁎
−
−.02
.06
.47⁎⁎
.16⁎⁎
.23⁎⁎
.02
−.09⁎
−.29⁎⁎
−.24⁎⁎
.11⁎
.18⁎⁎
.25⁎⁎
−.31⁎⁎
.20⁎⁎
.42⁎⁎
.35⁎⁎
−.36⁎⁎
−.30⁎⁎
.60⁎⁎
.12⁎⁎
−.07
−.33⁎⁎
.48⁎⁎
−.08⁎
−.42⁎⁎
−.30⁎⁎
.57⁎⁎
.41⁎⁎
−
.34⁎⁎
.12⁎⁎
−.23⁎⁎
.40⁎⁎
.10⁎
− 33⁎⁎
−.21⁎⁎
.49⁎⁎
.32⁎⁎
−
.46⁎⁎
.15⁎⁎
−.13⁎⁎
.18⁎⁎
.04
.14⁎⁎
.13⁎⁎
.04
−
.22⁎⁎
−.26⁎⁎
.34⁎⁎
.26⁎⁎
.33⁎⁎
−.09⁎
−.17⁎⁎
−
.44⁎⁎
.58⁎⁎
−.13⁎⁎
−.24⁎⁎
−
.79⁎⁎
−.54⁎⁎
−.56⁎⁎
.52⁎⁎
−
Note. MI = mastery-intrinsic orientation; ME = mastery-extrinsic orientation; PAP = performance-approach orientation; PAV = performance-avoidance orientation; AV = avoidance orientation; SV = school value; EXH = exhaustion at
school; CYN = cynicism toward the meaning of school; INA = sense of inadequacy as a student; ENG = schoolwork engagement; SAT = satisfaction with educational choice. Test–retest correlations are in bold.
⁎ p b .05.
⁎⁎ p b .01.
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
1.
Time 1
1. MI
2. ME
3. PAP
4. PAV
5. AV
6. SV
7. EXH
8. CYN
9. INA
Time 2
10. MI
11. ME
12. PAP
13. PAV
14. AV
15. SV
16. EXH
17. CYN
18. INA
19. ENG
20. SAT
Time 1 Academic well-being
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
4.5. Change in goal orientation group and academic well-being
Table 4
Information criteria values for different class solutions.
Number of
classes
BIC
pVLMR
pLMR
Entropy
Group sizes
1
2
3
4
5
19,263.876
18,723.548
18,455.048
18,318.837
18,310.268
–
0.0000
0.0000
0.0004
0.3934
–
0.0000
0.0000
0.0005
0.4003
–
.72
.70
.74
.72
1158
377, 781
374, 528, 256
83, 411, 421, 243
19, 171, 239, 375, 354
Note. BIC = Bayesian Information Criterion, pVLMR = Vuong–Lo–Mendell–Rubin
likelihood ratio test, pLMR = Lo–Mendell–Rubin adjusted likelihood ratio test.
ANOVAs. All effects and the mean differences are summarized in
Table 7. The results showed that goal orientation groups differed significantly on school value, school burnout, schoolwork engagement,
and satisfaction with educational choice. The pairwise comparisons
of means revealed that mastery-oriented students displayed highest
school value, followed by success-oriented students. Avoidanceoriented students had lowest scores on school value, but at Time 2
they did not differ significantly from indifferent students. With respect to exhaustion, success-oriented students scored higher than
all the other students except for indifferent students at Time 2. Interestingly, mastery-oriented and avoidance-oriented students did not
differ in exhaustion. Regarding cynicism, avoidance-oriented students expressed most cynicism at Time 1. At Time 2, avoidanceoriented and indifferent students had equally high scores on cynicism. Mastery-oriented students scored the lowest on cynicism,
followed by success-oriented students. With respect to inadequacy,
mastery-oriented students scored lower than the other students,
who had rather similar scores on inadequacy. The results showed further that mastery-oriented and success-oriented students reported
most engagement, while avoidance-oriented students reported least
engagement. After the transition, mastery-oriented students reported
the highest degree of satisfaction with their educational choice followed by success-oriented students. Indifferent and avoidanceoriented students were equally satisfied with their educational
choice.
Finally, we investigated how the changes in achievement goal orientation profiles were related to academic well-being. We created a
new variable reflecting change in goal orientation group from Time
1 to Time 2. Those students who stayed in indifferent group were
coded 1 (Stable indifferent). Since there were only ten students who
stayed in the avoidance-oriented group and since avoidanceoriented students resembled indifferent students in many respects
in earlier ANOVAs (see Table 7), these ten students were also coded
1. Those students who stayed in success-oriented group were coded
2 (Stable success-oriented) and those who stayed in masteryoriented group were coded 3 (Stable mastery-oriented). With respect
to those students who changed groups from Time 1 to Time 2, the students were coded either 4 (Adaptive change; i.e., from avoidanceoriented to indifferent, success-oriented or mastery-oriented; from
indifferent to success-oriented or mastery-oriented; from successoriented to mastery-oriented) or 5 (Maladaptive change; i.e., from
mastery-oriented to success-oriented, indifferent or avoidanceoriented; from success-oriented to indifferent or avoidanceoriented; from indifferent to avoidance-oriented).
Next, we performed two-way (5 × 2) ANCOVAs with change in
goal orientation group, educational track, and their interactions as independent variables, Time 2 well-being measures as dependent variables, and Time 1 well-being measures as covariates (see Table 8).
Consistent with the homogeneity assumption in ANCOVA, the regression coefficients of the covariates were not different across the different groups. The means for academic well-being measures by change
in goal orientation group are presented in Table 9. The results showed
that, for school value, the only significant effect was found for change
in goal orientation group. Pairwise comparisons of adjusted means
revealed that students in adaptive change, stable mastery-oriented,
and stable success-oriented groups displayed higher school value
than students in stable indifferent, and maladaptive change groups.
In relation to cynicism and inadequacy, significant main effects were
detected for change in goal orientation group. For example, students
in maladaptive change group expressed more cynicism compared to
students in stable success-oriented, adaptive change, and stable
mastery-oriented groups. Students in stable indifferent group scored
higher on inadequacy compared to students in stable mastery-
1,5
Standardized scores
1
0,5
0
Group 1: Indifferent
Group 2: Success-oriented
-0,5
Group 3: Mastery-oriented
Group 4: Avoidance-oriented
-1
-1,5
-2
-2,5
Masteryintrinsic
299
Mastery- Performance- Performance- Avoidance
extrinsic
approach
avoidance
Type of orientation
Fig. 2. Students' standardized mean scores on achievement goal orientation scales as a function of group membership.
300
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
Table 5
Mean differences in achievement goal orientations between goal orientation groups.
Variable
Mastery-intrinsic orientation
Mastery-extrinsic orientation
Performance-approach orientation1
Performance-avoidance orientation
Avoidance orientation
Sample mean
Indifferent
Successoriented
Masteryoriented
Avoidanceoriented
N = 1158
N = 421
N = 411
N = 243
N = 83
M
SD
M
SD
M
SD
M
SD
M
SD
5.11
5.42
3.73
3.75
4.36
1.16
1.15
1.30
1.46
1.30
4.46
4.72
3.53
3.90
4.77a
.87
.67
.90
1.23
1.06
5.68
6.28
4.91
4.49
4.38
.81
.57
.84
1.34
1.22
5.87
5.97
2.54a
2.56a
3.32
.80
.73
.83
1.12
1.16
3.40
3.02
2.37a
2.85a
5.18a
1.20
.58
.84
1.36
1.39
F(3,1154)
p
η2
307.20
860.54
489.26
134.93
95.42
b.001
b.001
b.001
b.001
b.001
.44
.69
.56
.26
.20
Note. Goal orientation group means within a row sharing the same subscripts are not significantly different at the p b .05 level (with Games-Howell correction,
correction).
N describes I-states rather than number of the students.
oriented and adaptive change groups. Also, students in maladaptive
change group scored higher on inadequacy than students in adaptive
change group.
Further two-way (5 × 2) ANOVAs were performed for engagement
and satisfaction with educational choice. Significant effects were
detected only for change in goal orientation group. Students in stable
mastery-oriented, adaptive change, and stable success-oriented
groups reported more engagement and satisfaction with educational
choice than students in maladaptive change and stable indifferent
groups.
5. Discussion
Our results demonstrate that students display various patterns of
achievement goal orientations at the end of comprehensive school
and during the transition to upper secondary education, that these
patterns are relatively stable across the transition, and that these patterns are associated in meaningful ways with students' academic
well-being. In identifying students' achievement goal orientation profiles, we found, as anticipated and consistent with prior research
(Niemivirta, 2002b; Tuominen-Soini et al., 2008, 2011), groups displaying a dominant tendency towards mastery (mastery-oriented
students), performance (success-oriented students), and avoidance
1
with Bonferroni
(avoidance-oriented students), and a group without a dominant tendency towards any specific goal orientation (indifferent students).
Over one third of students belonged to the indifferent group,
which can be seen as representing a “typical” student who does acknowledge the goals of learning and doing well in school, but is
somewhat reluctant to invest effort in the attainment of those goals.
A similar group has been identified also in prior work (Niemivirta,
2000; Tuominen-Soini et al., 2008, 2011), and together these studies
suggest that a typical Finnish student seeks to do what is expected
(to learn and perform well), but also tries to minimize the required
effort. This is in line with our view that competing preferences are
quite common among adolescents, especially in a school context
where students seek to both follow personal interests and respond
to external demands. It also echoes the findings of Turner et al.
(1998), who identified a group of uncommitted students, who did
not appear to be highly invested in either learning or performing
well, but who still tried to conform to typical classroom expectations
of getting answers right and using adaptive study strategies. In the
present study, indifferent students scored relatively low on school
value, engagement, and satisfaction with educational choice, and
rather high on school-related cynicism and sense of inadequacy.
Still, they were more engaged in their studies than avoidanceoriented students. Combining this with previous findings showing
that, compared to avoidance-oriented students, indifferent students
have higher academic achievement and higher fear of failure
(Tuominen-Soini et al., 2011), suggests that their motivational profile
Table 6
Configural frequency analysis on Time 1 and Time 2 goal orientation groups.
Configuration
T
T
T
A
T
T1/T2
11
12
13
14
21
22
23
24
31
32
33
34
41
42
43
44
Obs.
Exp.
χ2
p
10
5
19
8
7
113
60
43
22
49
108
27
2
21
28
57
2.97
13.64
15.60
9.79
15.79
72.41
82.81
52.00
14.59
66.89
76.49
48.03
7.65
35.07
40.10
25.18
4.07
− 2.34
.86
−.57
− 2.21
4.77
− 2.51
− 1.25
1.94
− 2.19
3.60
− 3.04
− 2.04
− 2.38
− 1.91
6.34
.0000
.0097
.1943
.2834
.0135
.0000
.0061
.1061
.0261
.0144
.0002
.0012
.0206
.0088
.0280
.0000
100 %
Note. T1 = Time 1 goal orientation group (1 = avoidance-oriented, 2 = successoriented, 3 = indifferent, 4 = mastery-oriented); T2 = Time 2 goal orientation
group (1 = avoidance-oriented, 2 = success-oriented, 3 = indifferent, 4 = masteryoriented). A = antitype; T = type.
90 %
80 %
70 %
60 %
Avoidance-oriented
50 %
Mastery-oriented
40 %
Success-oriented
30 %
Indifferent
20 %
10 %
0%
Time 1
Time 2
Fig. 3. Statistical types and antitypes. Note. Straight line indicates pathways between
time points identified as statistical types; broken line indicates pathways between
time points identified as statistical antitypes.
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
301
Table 7
Mean differences in academic well-being between goal orientation groups.
Variable
T1
T2
T1
T2
T1
T2
T1
T2
T2
T2
Indifferent
School value
School value
Exhaustion at school
Exhaustion at school1
Cynicism toward the meaning of school
Cynicism toward the meaning of school
Sense of inadequacy as a student1
Sense of inadequacy as a student
Schoolwork engagement1
Satisfaction with educational choice
Successoriented
Masteryoriented
Avoidanceoriented
M
SD
M
SD
M
SD
M
SD
4.90
5.00a
2.57a
2.72ab
2.52
2.69a
2.62a
2.83a
3.03
3.74a
1.12
.94
.93
1.02
.98
1.20
.96
1.07
1.21
.85
5.58
5.68
2.95
2.86a
2.03
2.01
2.44a
2.41b
4.09a
4.21
.93
1.00
1.02
1.06
.97
.88
1.03
.92
1.02
.61
6.00
6.21
2.56a
2.46bc
1.57
1.64
1.86
1.88
4.22a
4.44
.74
.62
.83
1.00
.68
.83
.83
.88
1.10
.58
4.22
4.78a
2.32a
2.15c
3.15
2.70a
2.67a
2.45ab
2.03
3.59a
1.41
1.10
.88
.95
1.25
1.13
1.12
1.09
1.20
.99
Note. Means within a row sharing the same subscripts are not significantly different at the p b .05 level (with Games–Howell correction,
is slightly more adaptive than that of avoidance-oriented students'.
That is, they acknowledge the importance of studying and learning
but, still, they do not necessarily thrive in school.
Mastery-oriented students emphasized learning and strived towards goals implying self-improvement and growth, although succeeding in school was also an important goal for them. These
students, characterized by high levels of school value, engagement,
and satisfaction with educational choice, also reported lowest levels
of cynicism and inadequacy. In line with previous research (e.g.,
Bråten & Olaussen, 2005; Daniels et al., 2008; Meece & Holt, 1993;
Tuominen-Soini et al., 2008, 2011; Turner et al., 1998), students emphasizing mastery goal orientation appear to display the most adaptive pattern of learning and adjustment.
Success-oriented students strived for both absolute and relative
success, yet they also emphasized the importance of learning and understanding. Success-oriented students reported relatively high
school value, engagement, and satisfaction with educational choice.
However, having a stronger concern of validating their competence,
success-oriented students were more likely than mastery-oriented
students to report exhaustion, cynicism, and inadequacy. In other
words, these students expressed mastery-focused tendencies along
with performance-related concerns. Prior research has shown that
while students who strive for success achieve well, they are somewhat preoccupied with possible failures in school and susceptible to
emotional distress (Daniels et al., 2008; Smith et al., 2002;
Tuominen-Soini et al., 2008, 2011). Our results concur with this and,
also, resemble the findings of Roeser et al. (2002), who identified a
group of students manifesting “a pattern of motivation despite emotional distress”, that is, students with positive academic motivation
1
F
p
η2
F(3,567) = 48.97
F(3,571) = 60.49
F(3,552) = 9.20
F(3,569) = 7.61
F(3,542) = 37.46
F(3,564) = 35.18
F(3,523) = 14.58
F(3,564) = 25.63
F(3,551) = 67.23
F(3,566) = 33.84
b.001
b.001
b.001
b.001
b.001
b.001
b.001
b.001
b.001
b.001
.21
.24
.05
.04
.17
.16
.08
.12
.27
.15
with Bonferroni correction).
and achievement, and at the same time, poor mental health. It is likely
that, in the long run, constant concerns about outperforming others
and succeeding in school pose a threat to success-oriented students'
well-being, which, in turn, might induce negative affect and cognition
in the face of difficulty (see Grant & Dweck, 2003). It is notable that
over one third of students belonged to success-oriented group (see
also Tuominen-Soini et al., 2011).
The small group of avoidance-oriented students deliberately
aimed at minimizing the effort and time spent on studying and, consequently, they showed the most maladaptive pattern of motivation
and academic well-being. These students were characterized by relatively low levels of school value, engagement, and satisfaction with
educational choice as well as by relatively high levels of cynicism
and inadequacy. It seems that avoidance-oriented students lack
both interest and confidence in their schoolwork, and, consequently,
they put little effort because they see no reason for doing so (see
Seifert & O'Keefe, 2001). As prior studies show that avoidanceoriented students' academic achievement is relatively low
(Tuominen-Soini et al., 2011) and that low academic achievement
and low schoolwork engagement are related to feelings of cynicism
and sense of inadequacy (Salmela-Aro et al., 2009), it is clear that
this pattern of motivation and beliefs holds a risk of inferior academic
success. However, it must be noted that avoidance-oriented students
scored as low as mastery-oriented students on exhaustion, suggesting
that despite their unfavorable motivational profile, avoidanceoriented students may not necessarily feel bad about it. Certain passivity and alienation, that is, not being concerned about succeeding
in school or outperforming others may help these students to cope
with the conflict between personal interests and external pressure.
Table 8
Summary statistics for ANCOVAs and ANOVAs.
Independent variables
Dependent variables
School value
Exhaustion at school
Cynicism toward the meaning of school
Sense of inadequacy as a student
Schoolwork engagementb
Satisfaction with educational choiceb
a
b
Covariatea
Change in goal orientation
group (G)
Track (T)
G×T
F
p
η2
F
p
η2
F
p
η2
F
p
η2
F(1,525) = 92.60
F(1,506) = 130.65
F(1,497) = 114.40
F(1,480) = 83.38
−
−
.000
.000
.000
.000
−
−
.15
.21
.19
.15
−
−
F(4,525) = 21.24
F(4,506) = .75
F(4,497) = 12.04
F(4,480) = 8.02
F(4,512) = 21.13
F(4,529) = 12.28
.000
.557
.000
.000
.000
.000
.14
.01
.09
.06
.14
.09
F(1,525) = 1.27
F(1,506) = 10.85
F(1,497) = 11.16
F(1,480) = 12.38
F(1,512) = .30
F(1,529) = 2.94
.261
.001
.001
.000
.582
.087
.00
.02
.02
.03
.00
.01
F(4,525) = 1.17
F(4,506) = .99
F(4,497) = .48
F(4,480) = .35
F(4,512) = 1.19
F(4,529) = .61
.324
.413
.752
.842
.315
.657
.01
.01
.00
.00
.01
.01
Covariate is the Time 1 score of the same variable.
Measured only at Time 2.
302
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
Table 9
Means, standard deviations, and adjusted means (with Time 1 scores as covariates) for academic well-being measures by change in goal orientation group.
Variable
School value
Adjusted (with T1 scores as covariate)
Exhaustion at school
Adjusted (with T1 scores as covariate)
Cynicism toward the meaning of school
Adjusted (with T1 scores as covariate)
Sense of inadequacy as a student
Adjusted (with T1 scores as covariate)
Schoolwork engagement
Satisfaction with educational choice
Stable indifferent
N = 118
Stable successoriented N = 113
Stable masteryoriented N = 57
Adaptive change
N = 151
Maladaptive change
N = 140
M
SD/(SE)
M
SD/(SE)
M
SD/(SE)
M
SD/(SE)
M
SD/(SE)
5.00
5.20b
2.55
2.64a
2.67
2.47ab
2.78
2.68a
2.89b
3.80b
.96
(.09)
1.00
(.09)
1.13
(.09)
.99
(.09)
1.24
.81
5.69
5.75a
2.97
2.53a
1.94
1.83c
2.43
2.30ab
4.11a
4.25a
.98
(.12)
1.08
(.13)
.81
(.14)
.95
(.13)
.98
.53
6.14
5.88a
2.47
2.35a
1.81
1.94bc
2.04
2.02bc
4.27a
4.40a
.60
(.16)
1.09
(.19)
1.08
(.19)
1.07
(.19)
.93
.61
5.91
5.98a
2.51
2.58a
1.92
1.86c
2.08
2.06b
3.94a
4.28a
.94
(.08)
.94
(.08)
.94
(.08)
.93
(.09)
1.31
.70
5.10
5.09b
2.77
2.67a
2.61
2.57a
2.68
2.59ac
3.14b
3.83b
1.04
(.09)
1.06
(.09)
1.25
(.10)
1.12
(.10)
1.24
.78
Note. Means within a row sharing the same subscripts are not significantly different at the p b .05 level (with Bonferroni adjustment). Pairwise comparisons are made for adjusted
means, except for schoolwork engagement and satisfaction with educational choice, which were measured only at Time 2.
Recent research employing similar methodology has shown that
although achievement goal orientation profiles are relatively stable,
they can also change over time; around 60% of both lower and
upper secondary school students displayed identical motivational
profiles over time, when there was no change in the educational context (Tuominen-Soini et al., 2011). In the present study, where change
in the context was included, half of the students displayed identical motivational profiles across the transition, and only 4% of students demonstrated substantive change in their profile. This suggests that
adolescent students' motivational profiles are, indeed, rather stable,
and thus lends support for the conception of achievement goal orientation as a disposition that reflects students' general motivational
tendencies in achievement and learning contexts. It nevertheless
seems natural that some students display change in their motivational profile considering that in addition to the change in educational context that itself induces growing demands and even strain,
young people are simultaneously encountering several biological,
psychological, and social changes characteristic of adolescence (see
Salmela-Aro, 2011).
According to the findings of the present study, it seems that the
upper secondary transition is not something negative as such. In
fact, it was found that, overall, mastery-intrinsic orientation increased
slightly across the transition, while in previous studies mastery goal
orientation has decreased across the middle school transition. Furthermore, some of the students went through the transition without
adjustment problems and declining motivation, while some of the
students encountered unfavorable, parallel changes in motivation
and well-being. Implying a better fit between the student and the
new educational context, students who exhibited a stable, favorable
(i.e., mastery- or success-oriented) motivational profile and students
who displayed adaptive change in their profile scored higher than the
other students on engagement and satisfaction with educational
choice after the transition. At the same time, we may speculate that
the students who continually manifest an unfavorable motivational
profile or display maladaptive change in their profile presumably experience a less successful transition (based on their lower ratings of
engagement and satisfaction after the transition) resulting in some
sort of misfit between the individual and the new context. These results imply that motivational profile can reflect either a risk or
protective factor in the context of educational transitions. According to Eccles and Roeser (2009), exposure to the developmentally appropriate environment would facilitate both motivation and continued
growth; in contrast, exposure to developmentally inappropriate environments should create a particularly poor stage-environment fit,
which should lead to declines in motivation as well as detachment
from the goals of the institution.
5.1. Practical implications
The person-centered approach enabled us to reveal students' various patterns of motivation across the transition and, consequently,
contributed to our understanding of individual development of motivation and academic well-being. With this understanding, we may
speculate how schools could best support students' motivation and
well-being during the demanding transitional period. First, since we
know that students hold quite different motivational mindsets,
schools should invest in personal student counseling services preceding the transition to upper secondary education in order to best support each student in making suitable choices for themselves (see
Vuori, Koivisto, Mutanen, Jokisaari, & Salmela-Aro, 2008). After comprehensive school, the upper secondary transition offers young Finns
a chance to select, for the first time, their educational track. For some
students, this might be the possibility to start over, in a positive way.
For example, students who are not academically-oriented might find
their niche as vocational school students in a context that emphasizes
practical skills.
Second, schools should put more effort to identifying potential
at-risk groups (students who manifest stable, unfavorable motivational profile or who display maladaptive change in their profile) and support their commitment to school and feelings of
competence so that these students would not alienate themselves
from school. On the other hand, there is a risk that students who
seemingly thrive in school are neglected and left without support
(see Daniels et al., 2008; Tuominen-Soini et al., 2008). For example, success-oriented students' vulnerability to emotional distress
and exhaustion should not be concealed by their academic
success.
Third, in our view, the endorsement of mastery goals should be
supported and encouraged to best promote all students' motivation,
school adjustment and well-being. Making performance goals and
ability differences especially salient to students in classrooms leads
to greater incidence of social comparison behaviors and competition,
which, in turn, are likely to undermine motivation and learning in the
long run. Both low- and high-performing students can suffer from the
negative consequences of this. On one hand, low-performing students
become aware of their relative low standing, which might boost their
cynical attitudes and sense of inadequacy. On the other hand, learning
environment that emphasizes performance goals and social comparison can be risky for success-oriented students, who already are
performance-focused and preoccupied with possible failures in
school. An emphasis on learning and self-improvement would be
fruitful because it might help these students to appraise the learning
situation—even in the case of failure—as an opportunity to learn and
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
303
improve. In this case, errors would not pose a threat to the students'
self-evaluations and well-being and they might even increase effort
and persistence (see Grant & Dweck, 2003). Especially in general
upper secondary schools, encouraging the endorsement of mastery
goals and reducing the emphasis on social comparison would be important means of minimizing the negative effects of the commonly
competitive environment.
of school disengagement and distress. Some students encounter declining motivation and different types of adjustment problems, while many
students navigate through the transition without notable problems and
some even seem to flourish and become increasingly motivated and engaged in studying.
5.2. Limitations and future research
The first author has a doctoral student position at the Finnish
Doctoral Programme in Education and Learning. This research was
supported by a grant from the Finnish Cultural Foundation to the
first author, by grants from the Academy of Finland (134931,
139168) and the Jacobs Foundation to the second author, and by
grants from the Academy of Finland (109193, 111799) to the third
author. It is part of the ongoing Finnish Educational Transitions
(FinEdu) Studies.
An important issue to be studied in future research is the generalizability of our findings to students in other countries where the context
of the transition might differ. Consequently, future work should include
the replication of our classification in other nationalities and, also, in
other educational contexts and among students of various ages. Also,
the possible moderating role of gender could be investigated more
closely. Future research could include multiple approaches and sources
of information (e.g., teachers, student counselors, student health care
personnel) in assessing students' well-being in order to complement
the student data with professionals' view on student well-being. In
the present study, the measurement period was one year, but it
would be useful to prolong the time span of the study design. For example, it would be important to follow success-oriented students' further
educational paths to try to understand more about this rather interesting pattern of functioning in which emotional distress is present, but it
does not seem to undermine the student's engagement and commitment in studying. Similarly, the origins of these tendencies as well
as the developmental sources of avoidance orientation should be investigated, thus extending the follow-up to the earlier years of students' educational careers. In future research, it might be of
specific value to discuss the advantages and costs of intrapersonal
versus interpersonal standards on subjective well-being and link
this to other relevant approaches to motivation, such as selfdetermination theory.
5.3. Conclusions
This study contributes to current research by filling some gaps in
our understanding of the development of achievement goal orientations and of the interplay between motivation and academic wellbeing over time. Existing studies have focused on the transition
from elementary to middle school, so this is one of the few longitudinal studies examining the development of achievement goal orientations across the transition to upper secondary education. To our
knowledge, it is also the only such study utilizing a longitudinal
person-centered approach and including an educational transition.
This approach simplified comparisons across measurement points
and allowed for more easily interpretable findings, and thus enabled
us to take a more holistic approach to the identification of both distinct
groups of students and complex patterns of motivational strivings and
indices of academic well-being. By focusing on the configurations of
five different types of achievement goal orientations, we examined
the relative emphasis of different motivational tendencies, and, thus, offered an alternative view on the issue of multiple goals and their effects
on important outcomes. In terms of those outcomes, we extended prior
research by linking achievement goal orientations with academic, that
is, context-specific well-being.
In conclusion, students endorse multiple achievement-related goals
and outcomes simultaneously, and the patterns of these strivings are
differentially associated with academic well-being, yet rather stable
across an educational transition. Students predominantly displaying
mastery tendencies express most adaptive academic well-being, while
students pursuing more performance-related goals and outcomes are
susceptible to school burnout. Students emphasizing avoidance tendencies show the most maladaptive pattern of motivation and academic
well-being. The results suggest that adolescence is not a uniform time
Acknowledgments
Appendix A. Standardized factor loadings and residual variances
for the measurement model
Factor loading
Item
MI1
MI2
MI3
ME1
ME2
ME3
PAP1
PAP2
PAP3
PAV1
PAV2
PAV3
AV1
AV2
AV3
MI
ME
PAP
PAV
AV
T1/T2
T1/T2
T1/T2
T1/T2
T1/T2
.794/.794
.827/.827
.855/.855
.806/.806
.750/.750
.865/.865
.619/.619
.579/.579
.766/.766
.822/.822
.790/.790
.768/.768
.620/.620
.831/.831
.667/.667
Residual
variances
T1/T2
.369/.369
.316/.316
.270/.270
.351/.351
.438/.438
.253/.253
.617/.617
.664/.664
.413/.413
.325/.325
.376/.376
.410/.410
.616/.616
.310/.310
.555/.555
Note. T1 = Time 1; T2 = Time 2; MI = mastery-intrinsic orientation;
ME = mastery-extrinsic orientation; PAP = performance-approach orientation; PAV = performance-avoidance orientation; AV = avoidance
orientation.
Appendix B. Average latent class probabilities for most likely latent
class membership by latent class
Most likely
latent class
membership
Latent class
1
2
3
4
1
2
3
4
0.874
0.000
0.036
0.002
0.000
0.876
0.074
0.075
0.124
0.071
0.834
0.085
0.002
0.053
0.055
0.838
Note. Values in italics represent the average posterior probability
associated with the clusters to which persons were assigned.
304
H. Tuominen-Soini et al. / Learning and Individual Differences 22 (2012) 290–305
Appendix C. Descriptive statistics for achievement goal orientations
by goal orientation group
Variable
Mastery-intrinsic orientation
Mastery-extrinsic orientation
Performance-approach orientation
Performance-avoidance orientation
Avoidance orientation
Mastery-oriented
Avoidance-oriented
T1
Indifferent
T2
T1
Success-oriented
T2
T1
T2
T1
T2
N = 206
N = 215
N = 223
N = 188
N = 108
N = 135
N = 42
N = 41
M
SD
M
SD
M
SD
M
SD
M
SD
M
SD
M
SD
M
SD
4.35
4.77
3.53
3.97
4.81
.91
.72
.91
1.29
1.08
4.57
4.67
3.54
3.82
4.73
.82
.62
.89
1.17
1.04
5.64
6.28
4.87
4.45
4.36
.80
.56
.80
1.38
1.21
5.72
6.29
4.96
4.53
4.40
.82
.57
.89
1.31
1.24
5.74
5.99
2.56
2.63
3.30
.79
.72
.73
1.18
1.09
5.97
5.96
2.52
2.50
3.34
.80
.74
.90
1.08
1.21
3.29
2.95
2.42
2.91
5.24
1.21
.57
.83
1.31
1.46
3.50
3.09
2.33
2.80
5.12
1.20
.59
.86
1.43
1.33
Note. T1 = Time 1; T2 = Time 2.
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