Students’ cross-domain mindset profiles and academic achievement in Finnish lower-secondary education

Abstract

Introduction
This study uses a person-centered approach to explore Finnish lower-secondary school students’ (N = 1106) mindsets across intelligence, giftedness, and creativity. It further investigates the relationship between mindsets profiles, school achievement in various subjects, and gender differences, aiming to address the domain-specificity of the three ability domains.

Methods
A self-reported questionnaire was used to measure students’ mindsets, with latent profile analysis (LPA) identifying distinct profiles. School achievement was assessed through academic grades in core and arts subjects, while gender differences in profile membership were examined via logistic regression.

Results
Four mindset profiles emerged: Growth, Fixed, Mixed, and Opposing. Most students exhibited consistent “general” mindsets across domains, except those in the Opposing profile, who combined a growth mindset for intelligence and creativity with a fixed mindset for giftedness. Students in the Opposing profile outperformed others in mathematics and foreign languages, while those in the Growth profile excelled across other subjects. The Fixed profile was linked to the lowest achievement, except in reading, foreign languages, and music, where Mixed and Fixed profiles performed similarly. Girls were more likely to belong to the Growth profile, while boys dominated the Fixed and Opposing profiles.

Discussion
The findings highlight the cross-domain nature of mindsets but reveal unique domain-specific variations, particularly for giftedness. These differences influenced academic outcomes, underscoring the nuanced role of mindsets in student achievement. Gender disparities in mindset profiles align with observed differences in school performance.

Conclusion
By identifying distinct mindset profiles, this study emphasizes the complexity of students’ beliefs and possible educational implications. Future research should explore qualitative aspects of mindset formation across ability-related constructs, its broader motivational frameworks, and their relation to students’ academic outcomes.

Full text

Frontiers in Psychology 01 frontiersin.org
Students’ cross-domain mindset
profiles and academic
achievement in Finnish
lower-secondary education
JenniLaurell *, ItaPuusepp , KaiHakkarainen and KirsiTirri
Faculty of Educational Sciences, University of Helsinki, Helsinki, Finland
Introduction: This study uses a person-centered approach to explore Finnish lower-
secondary school students’ (N = 1106) mindsets across intelligence, giftedness,
and creativity. It further investigates the relationship between mindsets profiles,
school achievement in various subjects, and gender dierences, aiming to address
the domain-specificity of the three ability domains.
Methods: A self-reported questionnaire was used to measure students’ mindsets,
with latent profile analysis (LPA) identifying distinct profiles. School achievement
was assessed through academic grades in core and arts subjects, while gender
dierences in profile membership were examined via logistic regression.
Results: Four mindset profiles emerged: Growth, Fixed, Mixed, and Opposing.
Most students exhibited consistent “general” mindsets across domains, except
those in the Opposing profile, who combined a growth mindset for intelligence
and creativity with a fixed mindset for giftedness. Students in the Opposing profile
outperformed others in mathematics and foreign languages, while those in the
Growth profile excelled across other subjects. The Fixed profile was linked to
the lowest achievement, except in reading, foreign languages, and music, where
Mixed and Fixed profiles performed similarly. Girls were more likely to belong
to the Growth profile, while boys dominated the Fixed and Opposing profiles.
Discussion: The findings highlight the cross-domain nature of mindsets but reveal unique
domain-specific variations, particularly for giftedness. These dierences influenced academic
outcomes, underscoring the nuanced role of mindsets in student achievement. Gender
disparities in mindset profiles align with observed dierences in school performance.
Conclusion: By identifying distinct mindset profiles, this study emphasizes the complexity
of students’ beliefs and possible educational implications. Future research should explore
qualitative aspects of mindset formation across ability-related constructs, its broader
motivational frameworks, and their relation to students’ academic outcomes.
KEYWORDS
mindsets, domain-specificity, latent profile analysis, creativity, lower-secondary education
Introduction
People’s beliefs about the malleability of human qualities are referred to as mindsets. Mindsets
reect how individuals view the nature of human attributes, such as intelligence and personality, as
either malleable and incremental or xed and static (Dweck, 2017, p.6). ese mindsets are also
termed implicit theories or beliefs. Mindsets exist along a spectrum ranging from growth to xed. A
growth mindset (an incremental view of human qualities) refers to the belief that human characteristics
can bedeveloped through eort and persistence. In contrast, a xed mindset (an entity view of human
qualities) reects the belief that these characteristics are stable and unchangeable. A substantial body
of research has explored how students’ mindsets about intelligence explain dierences in students’
goals and behavior in education. Many studies have results suggesting that holding an incremental
OPEN ACCESS
EDITED BY
Keiichi Kobayashi,
Shizuoka University, Japan
REVIEWED BY
Sylvia Sastre Riba,
University of La Rioja, Spain
Michael D. Broda,
Virginia Commonwealth University,
UnitedStates
*CORRESPONDENCE
Jenni Laurell
jenni.laurell@helsinki.fi
RECEIVED 21 October 2024
ACCEPTED 06 January 2025
PUBLISHED 23 January 2025
CITATION
Laurell J, Puusepp I, Hakkarainen K and
Tirri K (2025) Students’ cross-domain mindset
profiles and academic achievement in Finnish
lower-secondary education.
Front. Psychol. 16:1514879.
doi: 10.3389/fpsyg.2025.1514879
COPYRIGHT
© 2025 Laurell, Puusepp, Hakkarainen and
Tirri. This is an open-access article distributed
under the terms of the Creative Commons
Attribution License (CC BY). The use,
distribution or reproduction in other forums is
permitted, provided the original author(s) and
the copyright owner(s) are credited and that
the original publication in this journal is cited,
in accordance with accepted academic
practice. No use, distribution or reproduction
is permitted which does not comply with
these terms.
TYPE Original Research
PUBLISHED 23 January 2025
DOI 10.3389/fpsyg.2025.1514879

Laurell et al. 10.3389/fpsyg.2025.1514879
Frontiers in Psychology 02 frontiersin.org
(growth) view of intelligence supports students’ learning motivation (e.g.,
Burnette etal., 2013; Dweck and Yeager, 2019; Rhew etal., 2018), leads to
higher grades (Blackwell etal., 2007; OECD, 2018; Paunesku etal., 2015),
and fosters greater academic aspirations (Yeager etal., 2019). Nevertheless,
investigating students’ implicit beliefs beyond intelligence is essential
because those may vary across attributes. In other words, individuals can
hold diering implicit beliefs about various characteristics, such as
intelligence, giedness, creativity, or personality traits. Additionally,
mindsets are found to bedomain-specic (Dweck and Molden, 2017,
p.136), which adds to the need to investigate mindsets across domains.
Psychological constructs such as intelligence, giedness, and creativity
are complex, and no single theoretical conception exists. Researchers have,
for example, debated the conceptualization of giedness for a century
without attaining a unanimous result on its denition. e construct still
heavily carries its historical roots and is easily associated with high
intellectual ability—especially in laypeople’s’ everyday conversations.
However, looking at just students’ high intellectual ability or academic skills,
in general, is an exceptionally narrow way to view giedness, as scholars
today agree that giedness can emerge in an extensive range of skills
(Sternberg and Ambrose, 2021, pp.513–515). Regarding mindsets about
giedness, Dweck (2000, p. 122) suggested that due to the word’s
connotation, giedness is likely viewed as a xed entity as the word “gi”
implies that no eort is required, and that giedness bestows upon rare or
fortunate individuals. A few studies have compared among varying-aged
students, how their mindsets about intelligence and giedness dier and
how students’ mindset aects their achievement at school (Makel etal.,
2015; Kuusisto etal., 2017; Laurell etal., 2022). As Dweck suggested, the
ndings of all three studies indicate that students perceive intelligence as a
more malleable human quality than giedness.
Creativity is increasingly recognized as a crucial characteristic of
21st-century learners (Binkley etal., 2011; OECD, 2019). Notwithstanding,
to our knowledge, no studies have investigated mindsets about creativity,
though weare aware of studies, e.g., Karwowski (2014) and Karwowski
etal. (2017) that explored implicit beliefs about creativity, mainly in the
creative elds and primarily focused on capturing the multidimensional
nature of creativity by developing a new scale to measure its
multidimensionality. Instead, weemployed a commonly used scale to
investigate implicit beliefs about creativity’s developmental or innate nature
alongside intelligence and giedness (Dweck, 2000). In this study,
we simultaneously examine mindsets in intelligence, giedness, and
creativity, intending to understand the domain-specicity of these
intertwined and overlapping constructs (see Kaufman and Sternberg, 2008,
p.71–83). Moreover, weaim to contribute to prior mindset research by
adopting a person-centered approach to investigate students’ mindsets
about intelligence, giedness, and creativity. Additionally, weassess how
students’ prole group membership relates to academic achievement in
various subjects and gender. Wechose the person-centered method as it
provides a better understanding of mindsets’ context specicity and
replicability. Acknowledging this is relevant as mindsets might becontext-
dependable constructs and more diverse and complex than initially
theorized (Altikulaç etal., 2024). A person-centered method also identies
individuals who share similar features and classies them into more
homogeneous subgroups. e method enables the investigation of the
characteristics and percentages of learners who respond inconsistently with
theoretical expectations (Muthén and Muthén, 2000). Research about
mindsets has mainly focused on analyzing whole-sample averages, and
only a minority of mindset studies have thus far used a person-oriented
approach, which does not assume homogeneity across the entire sample.
Domain-specificity of mindset beliefs
In the early years of mindset theory development, Dweck
etal. (1995) suggested that individuals can hold different mindsets
about various attributes at once. For example, individuals might
believe they can develop their intelligence but not their
personality. In this case, a growth mindset provides a framework
for organizing thoughts and guiding actions related to intelligence.
In contrast, a fixed mindset shapes individuals’ thoughts and
actions within the personality domain, reflecting the belief that
personal traits, such as temperament, are static and unchangeable.
Dweck etal. (1995) also proposed that some individuals might
possess more generalized mindset beliefs across multiple
attributes. Even if this is the case, investigating the domain-
specificity or generality of implicit theories remains relevant, as
perceptions about one attribute’s developmental or static nature
do not necessarily imply that this perception extends to all
attributes (O’Keefe etal., 2018).
Lewis etal. (2021) recently investigated adults’ global and domain-
specic mindsets (e.g., personality, intelligence, math, writing) using a
bifactor model. ey explored the strength of generalized beliefs across
domains and discovered that mindsets remained consistent across
domains throughout the sample. e researchers emphasized that
when multiple domains are not assessed simultaneously, correlations
between separate domains may beoverlooked, leading to missed
insights. Furthermore, they suggested that simultaneous examination
of multiple domains may help validate the assumption that mindsets
specic to a particular domain are most relevant to outcomes related
to that domain. ey also propose that the signicance of general
mindset beliefs may vary depending on the context.
In another study implementing the bifactor model, Petscher etal.
(2017) evaluated the dimensionality of general and reading-specic
mindsets among fourth-grade students. ey found a general growth
mindset factor and specic aspects of general and reading-specic
mindsets. ese ndings suggest that while individuals’ mindsets across
multiple domains are likely to berelated, mindsets remain distinct in
dierent areas. Also, Schroder etal. (2016) found evidence that among
university students, mental-health-related mindsets were simultaneously
domain-specic (e.g., students’ depression mindsets predicted symptoms
of depression) and general (e.g., anxiety mindset and general mindset
factors predicted most symptoms). Yu and McLellan (2020) adopted a
person-centered method to investigate the coherence of mindsets about
intelligence and associated motivational constructs and how they
functioned together and inuenced adolescent student achievement in
math and reading. In addition to the four student proles discovered, they
found evidence supporting the domain specicity of the motivational
frameworks, as only 64% of students remained in the same prole across
the two academic subjects. As these studies have demonstrated, individuals’
implicit beliefs are not straightforward, and those should beinvestigated in
terms of the generality and specicity of mindsets and various contexts
and circumstances.
The relationship between mindsets in
learning and academic achievement
Mindsets about intelligence have been widely studied to
understand their inuence on academic achievement (e.g., Yeager and

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Frontiers in Psychology 03 frontiersin.org
Dweck, 2020). Studies included in a review article by Zhang etal.
(2017) that investigated students’ mindsets and academic achievement
demonstrated that growth mindsets about intelligence positively
inuenced academic achievement. However, some studies have failed
to nd an association between a growth mindset about intelligence
and higher academic grades (e.g., Leondari and Gialamas, 2002).
When mindsets are studied to understand their eect on achievement
at school, mathematics is commonly included in the measures; Math
is a focal academic subject widely regarded as more dependent on
inherent cognitive abilities (Costa and Faria, 2018). Additionally, the
relationship between a growth mindset and higher academic
achievement is particularly evident in subjects like math because math
oen presents cumulative challenges that require sustained eort and
adaptive motivational frameworks to overcome (Gunderson etal.,
2018). Blackwell etal. (2007) revealed an upward trajectory in math
grades over 2 years among students with a growth mindset about
intelligence, while a belief that intelligence is xed predicted a at
trajectory in students’ math grades. Moreover, in a study by Romero
et al. (2014), students who endorsed a growth mindset about
intelligence earned higher grades and were likelier to participate in
advanced math courses over time. Kuusisto etal. (2017) found that
comprehensive school students’ growth mindset about intelligence
and xed mindset about giedness indicated higher math grades.
Recent research has focused on students’ subject-specic mindsets
(e.g., mathematics: Puusepp etal., 2023; reading: Petscher etal., 2017;
language learning: Lou and Noels, 2019) and their inuence on grades
in specic subjects. e results of these studies demonstrate that a
general mindset about intelligence does not predict subject-specic
achievement as consistently as subject-specic mindsets (e.g., math-
ability mindset, reading-ability mindset, and language-learning
mindset).
Due to the somewhat conicting ndings and critique of the
mindset theory, Yeager and Dweck (2020) have tempered expectations
about the direct eects of mindsets on academic achievement, noting
that an individual’s mindset does not aect academic achievement per
se. Indeed, Rattan etal. (2015) argue that growth-minded students
tend to earn better academic grades because the mindset is embodied
in responses to setbacks in challenging learning situations. According
to Barger etal. (2022), a growth mindset is not only about working
hard but eciently, acquiring, and using help and dierent resources.
More specically, it is not enough to believe that improvement is
generally possible; it is vital to understand that eort is necessary and
to have eective strategies. If these aspects are not internalized,
continuing challenges might undermine an individual’s motivation
just as much as believing their ability is xed.
When investigating gender and mindsets, a meta-analysis by
Butler (2014) found gender dierences to beexpected in the results of
motivational studies. Regarding mindsets about intelligence, the
ndings are somewhat contradictory. While some studies (Spinath
etal., 2003) have suggested that females are more likely than males to
exhibit a growth mindset, Diseth etal. (2014) found that girls held a
weaker growth mindset than boys. Using latent-prole analysis, Yu
and McLellan (2020) revealed variations in the number and types of
gendered mindset proles (including a mindset with associated
motivational constructs), with boys more oen in proles with a xed
mindset, which facilitated mastery goal pursuit (Ability-Focused and
Disengaged). ey suggested that the mindset itself, as a single
variable, does not cause gender dierences; instead, gender dierences
commonly arise when academic subject domains (e.g., math) are
investigated alongside mindsets.
The present study
As presented in the theoretical section, several studies have
demonstrated that mindsets are not straightforward. It has been stated
that the developmental or static nature of mindsets about abilities
should be investigated in various contexts and circumstances to
understand their generality, specicity, and relationship to students’
achievement in formal education. Our interest was in examining more
than one mindset domain at a time (see Lewis etal., 2021) and an aim
to enable the comparison of the ndings of this study with previous
international and domestic studies about intelligence and giedness-
related mindsets in formal schooling (Makel etal., 2015; Kuusisto
et al., 2017; Laurell et al., 2022). us, using a person-centered
approach, this study simultaneously examines students’ implicit
beliefs, i.e., their mindsets across concepts of intelligence, giedness,
and creativity—Additionally, it investigates the relationship between
prole group membership and academic achievement in various
school subjects, as well as emerging gender dierences asking the
following questions:
1) What kinds of student proles can be identied based on
mindsets in the three domains?
2) How do the prole groups dier in (a) academic achievement
and (b) gender?
Context
Comprehensive education in Finland comprises primary school
(grades 1–6, 7–12-year-old) and lower secondary school (grades 7–9,
13–16-year-old), followed by general upper secondary school
(academic track) or vocational upper secondary school (vocational
track), with the application process based on students’ cumulative
GPA at the end lower secondary school.
e Finnish school system is considered as egalitarian, and
inclusive, and students are supported individually based on their
needs. Mandatory formal education is free of charge and the same for
all students, without ability grouping. Nevertheless, schools today are
increasingly segregated by socioeconomic status, especially in the
Helsinki metropolitan area (Bernelius and Vaattovaara, 2016). e
Finnish National Core Curriculum (NCC) (Finnish National Agency
for Education, 2014) denes the educational goals for compulsory
education. e highest-level aim is to encourage students’ academic
performance by creating an inclusive learning environment that
supports holistic psychosocial development alongside traditional
cognitive abilities.
e current NCC places a strong emphasis on teaching future skills,
which include an open-minded attitude and a growth mindset toward
learning, acquiring knowledge across various academic domains, and
being able to challenge oneself while studying, not to forget creative
thinking that is highlighted as a teaching and learning objective in the
NCC (Finnish National Agency for Education, 2014). e Finnish
educational system employs a dierentiation approach to identify gaps
between students’ knowledge and the curriculum content (Laine and

Laurell et al. 10.3389/fpsyg.2025.1514879
Frontiers in Psychology 04 frontiersin.org
Tirri, 2021). In some cases, the lack of recognition at school can prevent
students who exceed the objectives of NCC or are in some other way from
fullling their educational potential. Mindset research conducted in
Finland has reported gender dierences in students’ mindsets, with
Finnish boys displaying a stronger tendency toward a xed giedness
mindset than girls but sharing similar mindsets about intelligence to their
female counterparts (Kuusisto et al., 2017). Investigating gender
dierences is relevant because educational achievement in Finland is
increasingly polarized by gender (Hautamäki etal., 2015; OECD, 2019).
Materials and methods
Procedure
e current study was part of a longitudinal research project:
Growing Mind—Educational Transformations for Facilitating
Sustainable Personal, Social, and Institutional Renewal in the Digital
Age. e project arranged a data collection in Helsinki, Finland. e
present study was included in the project’s ethical review, which was
accepted by e University of Helsinki’s Research Ethics Committee
and the municipality. Participation to the data collection was voluntary
for the students, and for the schools. In total, 32 schools participated
in the project’s data collection, with 3,262 ninth-grade students. As the
participants were underage, consent was requested from their
guardians in advance, and in total, 1,971 guardians gave consent to use
their wards’ answers for research purposes.
e data used in this study was collected during regular school
lessons in the fall semester of 2021. Teachers collaborated with
researchers to initiate the data collection through an electronic survey
using Qualtrics soware. e questionnaire was completed on laptops
or tablets provided by the school. At the beginning of the data
collection, a short instructional video created by researchers from the
project was shown to the participants to inform them about the
research in general and its aims. e participants were informed about
their right to withdraw from the process at any time, and permission
to use their responses for research purposes was requested in writing
before the commencement of the actual survey. e data collection
procedure lasted an average of 35 min, and the extensive research
survey (190 variables) took 20–25 min to complete.
e original raw data included 1,443 study participants. However,
this dataset was cleaned from unreliable answers that would distort
the results. e raw data included many questionable cases (empty,
fake, untraceable names). For reliability, data was deleted if the
participant (1) had answered jokingly, (2) had not answered more
than 6% of the questionnaire, (3) had answered twice, (4) took part in
the questionnaire without the permission of the guardian, or (5) did
not permit to use their answer for research purposes. At the beginning
of the analysis for the present study, the dataset included 1,260
participants. However, some participants (n = 154) quit the survey
before reaching the section where the mindsets were evaluated. us,
before the main analysis for this study, 154 cases were eliminated.
Participants
A total of 1,106 participants (15–16 years old) were included in
the main analysis for this study. e respondents were required to
identify their gender at the beginning of the questionnaire, and 51.3%
identied themselves as girls (n = 567) and 43.4% as boys (n = 480).
In turn, 5.3% identied themselves as “other” or did not report their
gender (n = 59).
Mindset measures
Intelligence, giedness, and creativity mindsets were assessed
using the Implicit eories of Intelligence Scale (ITI; Dweck, 2000).
Within the framework of Dweck’s theory, weemployed an instrument
that intentionally refrains from providing respondents with predened
denitions of the constructs under investigation, meaning no explicit
denitions of intelligence, giedness, and creativity were given to
participants in the questionnaire. e ITI scale originally consists of
four entity statements and four incremental statements, but it was
suggested by Dweck (2008) that the growth mindset items beomitted
and only the xed mindset items beused, as the growth mindset items
can lead to a social desirability bias. In our survey, the scale consisted
of Dweck’s three entity statements: “People have a certain amount of
intelligence, and not much can bedone to change it,” “To behonest,
youcannot really change how intelligent youare,” and “People can
learn new things, but cannot really change their basic intelligence,.”
Scale was adapted to other domains by replacing “intelligence” with
“giedness,” and “creativity” which is a common manner in mindset-
domain research (Burnette etal., 2013; Chiu etal., 1997). Each item
was assessed with a 6-point scale from 1 (strongly agree) to 6 (strongly
disagree), with higher scores indicating a greater endorsement of a
growth mindset. e internal consistencies of the mindset scales were
found to begood: Cronbach’s alpha for the intelligence scale was
α= 0.89; for giedness, it was α= 0.93, and for creativity, it was
α= 0.94. ree mean scores were used.
Academic achievement
Data regarding the grades was obtained from school year reports
requested from the National Agency for Education at the end of the
2022 academic year. Academic grades in Finland range from 4
(lowest) to 10 (highest) and are based on teachers’ evaluations of tests,
homework, classroom participation, and student eort (Finnish
National Agency for Education, 2014). Instead of using the GPA of the
school year reports, we evaluated grades in specically chosen
academic subjects: mathematics, reading, 1st compulsory foreign
language (e.g., English, French, German), music, visual arts, and cras.
Data analysis
Conrmatory factor analysis (CFA) in R (Version 4.3.3) with the
RStudio interface (Version 2024.04.1) and lavaan package (Version
0.6–17; Rosseel, 2012) was rst conducted to determine the factor
structure of the mindset measures. Subsequently, latent prole analysis
(LPA) with the mean scores of the three mindset domains as indicator
variables was performed in Mplus version 8.9 to explore the prole
groups. e specication “TYPE = COMPLEX” with “school” as the
cluster was applied to account for the nesting of students within
schools (Muthen and Muthen, 2024). Solutions with 2–10 proles

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Frontiers in Psychology 05 frontiersin.org
were explored. e best solution was determined by considering
theoretical interpretability, prole sample sizes, and the following t
indices: AIC, sample-size adjusted BIC (SABIC), entropy, and values
of VLMR test. Smaller AIC and SABIC values indicate a better t,
higher entropy indicates greater classication certainty (with values
larger than 0.80 indicating a “good” classication), while a
non-signicant VLMR test suggests that a model with one less class
has a better t (Collins and Lanza, 2009; Nylund etal., 2007; Nylund-
Gibson and Choi, 2018). In addition, to avoid local solution
convergence, werequired the best log-likelihood value to bereplicated
for the solution selected for further analysis. e BCH approach in
Mplus was used to inspect prole dierences in academic achievement
(Asparouhov and Muthén, 2014). Wedid not add gender to the LPA
as a predictor to inspect gender dierences in prole membership
because of the considerable number of participants identifying
themselves as “other” (n =57, 4.8%) whom weopted to include in the
analysis. us, gender dierences were analyzed separately using
logistic regression analyses with gender as the independent variable
predicting the odds of belonging to one prole compared to others.
Logistic regression analyses were conducted in SPSS 29.0.2.0.
Results
Descriptives and bivariate correlations between all study variables
are presented in Table1. Based on CFA, a model with three correlated
factors of intelligence, creativity mindset, and intelligence mindsets t
the data well, χ2(24) = 124.24 (p < 0.001);f CFI = 0.989, TLI = 0.983,
RMSEA = 0.061, 90% C.I. (0.051, 0.072), SRMR = 0.022. Subsequently,
LPA with the three mindset variables was conducted. Based on the t
indices of the LPA solutions (Table2), the solution with four latent
proles was chosen for further analysis. Although the AIC and SABIC
values decreased with additional proles, solutions with more proles
resulted in lower entropy and extremely small prole groups. As for
solutions with eight and nine proles, the entropy increased and the
SABIC values decreased notably from the seven-to the eight-prole
solution (see also Supplementary Figure S1). However, for these
solutions, multiple very small prole groups emerged (2–3% of cases)
and, importantly, the best log-likelihood value was not replicated
(Table 2). erefore, the eight-and nine-prole solutions were
discounted. e four-prole solution exhibited a high entropy and,
compared to the three-prole solution, included an additional prole
that clearly diered from other prole groups. e proles were
labeled as the following: Fixed, Growth, Mixed, and Opposing Mindsets
(see Figure1 and Table3). e majority of students belonged to the
Growth Mindset prole (44.4%), characterized by a high growth
mindset on all mindset measures. e second largest prole group
(37.07%) was the Mixed Mindsets prole, which was characterized by
moderate levels of growth mindset on all measures. Slightly more than
a 10th of the participants belonged to the Fixed Mindsets prole
(11.85%), with a relatively xed mindset regarding intelligence,
creativity, and giedness. e smallest prole group, which welabeled
Opposing Mindsets (6.7%), was characterized by a relatively strong
growth mindset about intelligence and creativity but a xed mindset
about giedness.
Between-profile dierences in
achievement
Based on omnibus Chi-square tests, the grades of students from
the four mindset proles diered in all the subjects weinvestigated
(Table4). Post-hoc pairwise comparisons indicated that students in
the Fixed-Mindsets prole tended to have lower grades than students
in the other proles in all subjects (Table 4) apart from reading,
foreign languages, and music, where Mixed-Mindset students achieved
TABLE1 Descriptive statistics and correlations between all the measures.
Variable Range M (SD) 1 2 3 4 5 6 7 8 9
1. Intelligence
Mindset 1–6 4.36
(1.23) —
2. Giedness
Mindset 1–6 4.35
(1.30) 0.570** —
3. Creativity
Mindset 1–6 4.20
(1.43) 0.591** 552** —
4. Mathematics 4–10 8.51
(1.32) 0.126** 0.040 0.102** —
5. Reading 4–10 8.55
(1.12) 0.128** 0.084** 0.118** 0.703** —
6. Foreign
languages 4–10 8.94
(1.06) 0.071*0.021 0.081*0.603** 0.611** —
7. Music 4–10 8.91
(0.87) 0.091*0.131** 0.114** 0.421** 0.428** 0.304** —
8. Visual arts 4–10 8.64
(0.98) 0.139** 0.160** 0.111** 0.445** 0.525** 0.361** 0.388** —
9. Cra 4–10 8.50
(0.97) 0.145** 0.146** 0.147*0.471** 0.507** 0.296** 0.423** 0.552** —
*p < 0.05; **p < 0.01.

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Frontiers in Psychology 06 frontiersin.org
equally low grades. Additionally, compared to the Mixed Mindsets
prole, the Growth-Mindset students achieved better grades in all
subjects except math and foreign languages. Interestingly, the
Opposing-Mindsets prole exhibited better grades than the other
proles in math and foreign languages. Regardless, students in this
prole did not dier from students in the Growth-Mindsets prole in
terms of their grades in the other subjects.
Gender composition
Logistic regression indicated that when using boys as the reference
group, the Fixed-Mindsets (41% girls; OR = 0.39, SE = 0.08), Opposing-
Mindsets (28% girls; OR = 0.23, SE = 0.07), and Mixed-Mindsets (47%
girls; OR = 0.54, SE = 0.08) proles contained signicantly fewer girls
than the Growth-Mindsets prole (61% girls; ps < 0.001). Additionally,
compared to the Mixed-Mindsets prole, there were signicantly fewer
girls in the Opposing-Mindsets prole (OR = 0.43, SE = 0.12,
p = 0.002). No other signicant dierences in gender distribution were
found (ps > 0.10).
Discussion
Our study aimed to understand lower-secondary school
students views about the malleable or static nature of intelligence,
giftedness, and creativity, and what kinds of mindsets profiles
groups can be identified across the domains. Research on
mindsets has predominantly focused on fixed and growth
mindsets within individual domains. However, to understand
TABLE2 Fit indices of the LPA solutions.
Nr. of profiles Log-likelihood
(LL)
Best LL
replicated
Entropy AIC SABIC VLMR
2−5,175.25 Yes 0.731 10,370.504 10,388.827 <0.001
3−5,043.847 Yes 0.739 10,115.694 10,141.346 0.002
4−4,947.758 Yes 0.821 9,931.517 9,964.497 0.236
5−4,903.579 Yes 0.791 9,851.158 9,891.468 0.198
6−4,858.078 Yes 0.808 9,768.157 9,815.80 0.049
7−4,828.145 Yes 0.773 9,716.290 9,771.257 0.374
8−4,635.373 No 0.967 9,338.746 9,401.042 0.042
9−4,602.520 No 0.952 9,281.039 9,350.665 0.148
10 −4,575.368 Yes 0.942 9,234.737 9,311.692 0.073
Solutions may not betrustworthy, when the best log-likelihood is not replicated.
FIGURE1
Standardized scores of the three mindset measures in the four latent mindset profiles.

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Frontiers in Psychology 07 frontiersin.org
both the general and domain-specificity of mindsets, it is crucial
to investigate multiple mindsets across domains, as beliefs about
the malleability of one attribute do not automatically apply across
all domains (O’Keefe etal., 2018). Examining multiple domains
at once can also help clarify the validity of the assumption that
mindsets specific to a certain domain are most relevant to the
outcomes associated with that domain (Lewis etal., 2021). In this
study, our goal was to examine cross-domain mindset profiles.
Weemployed a person-centered approach to identify mindset
profiles with latent profile analysis and to examine how profile-
group membership related to academic achievement as well as
whether this membership differed by gender. Growth, Fixed,
Mixed, and Opposing profiles were revealed, and these profiles
were associated with differences in academic achievement. The
results suggest that adolescent students’ learning-related mindsets
were largely consistent across the three domains under
investigation, although some students showed notable differences
in their mindsets between the domains. In addition, membership
of the profiles differed by gender, as girls were more likely to
belong to the Growth-Mindsets profile across domains. Our
discussion focuses on the profiles identified in this study and the
relationship between profile-group membership, academic
achievement, and gender.
Mindsets profiles
We identied four mindset proles: Growth, Fixed, Mixed, and
Opposing Mindsets. ree of these proles (Growth, Fixed, and
Mixed) were consistent across the domains of intelligence,
giedness, and creativity. By contrast, one prole (Opposing
Mindsets) was characterized by a growth mindset about
intelligence and creativity but a xed mindset about giedness.
e largest prole group (44.4%) consisted of students with a
strong growth mindset in all three domains; thus, it was labeled
Growth Mindsets. Identifying a clear growth-mindset prole was
unsurprising, as previous studies conducted in the Finnish context
have shown that many students tend to hold a growth mindset,
particularly regarding intelligence (Kuusisto etal., 2017; Laurell
etal., 2022).
In the second largest prole group (37.1%), students demonstrated
moderate growth mindsets across domains. Dweck and Molden
(2017) note that approximately 20% of students can exhibit an
undecided mindset while other estimates suggest that the amount can
beanywhere between 15 and 37% of the population (Kaijanaho and
Tirronen, 2018).
e third prole group, with 11.9% of students, was characterized
by a relatively xed mindset in all domains; thus, the prole was
named Fixed Mindsets. e smallest (6.7%), atypical prole—Opposing
Mindsets—consisted of students who held a growth mindset in the
domains of intelligence and creativity but a xed mindset in the
domain of giedness. In this prole, students also performed
exceptionally well in mathematics and languages. is prole aligns
with the ndings of Makel etal. (2015), Kuusisto etal. (2017), and
Laurell etal. (2022), which have demonstrated that when comparing
mindsets about intelligence and giedness among school students, the
domain of giedness is oen perceived as more xed in nature, even
in dierent cultural contexts (USA vs. Finland). However, as
previously highlighted, it is suggested that a connotation in the word
‘gi’ implies that giedness is obtained at birth. In sum, giedness is
perceived as more xed in nature (Dweck, 2008). is is accurate,
especially in languages (e.g., English and Finnish) where the word
giedness implies something given to a person without eort on the
part of the recipient. More specically, in the same way as in English,
the Finnish words lahjakas and lahjakkuus, which can betranslated
directly as gied and giedness, are derived from the word lahja,
meaning gi or talent in Finnish. Moreover, in everyday speech, and
TABLE4 Means and between-group dierences in grades in all inspected subjects.
Variable Latent profile
Fixed mindsets
(n = 131)
Growth mindsets
(n = 491)
Mixed mindsets
(n = 410)
Opposing
mindsets (n = 74)
χ2
M (SE) M (SE) M (SE) M (SE)
Math grade 8.00a (0.19) 8.59b (0.10) 8.47b (0.11) 9.20c (0.12) 47.77***
Reading grade 8.24a (0.18) 8.69b (0.10) 8.42a (0.14) 8.92b (0.16) 21.19***
Foreign languages grade 8.82a (0.12) 9.04b (0.08) 8.91a,b (0.12) 9.52c (0.09) 46.97***
Arts grade 8.29a (0.15) 8.78b (0.06) 8.61c (0.12) 8.60b,c (0.12) 15.74**
Music grade 8.63a (0.11) 9.03b (0.07) 8.84a,c (0.07) 9.00b,c (0.12) 13.66**
Cras grade 8.12a (0.15) 8.66b (0.07) 8.40c (0.11) 8.73b (0.13) 27.48***
Chi-square omnibus tests with 3 degrees of freedom. ***p < 0.001; **p < 0.01; *p < 0.05. Means with the same superscripts do not dier between prole groups.
TABLE3 Descriptives of the mindset profiles.
Variable Latent profile
Fixed
mindsets
(n =131)
Growth
mindsets
(n =491)
Mixed
mindsets
(n =410)
Opposing
mindsets
(n =74)
M (SD)
95% CI
[LL, UL]
M (SD)
95% CI
[LL, UL]
M (SD)
95% CI
[LL, UL]
M (SD)
95% CI
[LL, UL]
Intelligence
mindset
2.50 (0.99)
[2.34, 2.68]
5.16 (0.78)
[5.10, 5.24]
3.95 (0.89)
[3.87, 4.04]
4.64 (1.12)
[4.36, 4.88]
Creativity
mindset
2.44 (1.02)
[2.27, 2.63]
5.27 (0.72)
[5.21, 5.33]
3.70 (0.81)
[3.62, 3.78]
5.18 (0.80)
[5.01, 5.35]
Giedness
mindset
2.02 (0.65)
[1.90, 2.13]
5.44 (0.57)
[5.39, 5.49]
3.82 (0.70)
[3.75, 3.89]
1.96 (0.69)
[1.82, 2.13]

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Frontiers in Psychology 08 frontiersin.org
in the school context, the Finnish words describing giedness/talent
are likely oen associated with high-achieving students. Further
research, for example, using qualitative methods, is needed to
understand what could explain the domain-specic variance in the
implicit beliefs about intelligence, giedness, and creativity within this
student group.
When simultaneously measuring multiple domains, wefound
moderate correlations between the mindsets. is suggests that
mindsets about intelligence, giedness, and creativity exhibit a degree
of consistency, reinforcing the notion of generalized beliefs regarding
growth or xed ideas about human attributes, as was noted by Lewis
etal. (2021). Notwithstanding, the results also suggest an Opposing-
Mindsets prole, including both domain-general and domain-specic
views. ese ndings align with research conducted by Petscher etal.
(2017), Schroder etal. (2016), and Puusepp etal. (2023). Furthermore,
these results mirror those of Lewis etal. (2021), who found evidence
that beliefs across domains consist of a common global (or general)
mindset belief plus, in some circumstances, domain-specic mindsets.
ey also demonstrated at least some domain-specic aspects of
mindsets across multiple domains. In sum, these results suggest that
students’ perceptions of intelligence and creativity are more similar
than their perceptions of the malleability of giedness.
Mindsets profiles and academic
achievement among the groups
When wecompared the academic achievement of the Growth,
Mixed, Fixed, and Opposing-Mindsets prole groups in mathematics,
reading, 1st compulsory foreign language, music, visual arts, and
cras, wefound that students’ academic grades diered according to
their prole While the Growth-Mindsets prole appeared to bethe
group with the highest overall academic grades, surprisingly, the best
grades in math and languages were found among the prole with
Opposing-Mindsets. Our results partially align with previous variable-
oriented studies in the sense that growth-mindset students
outperformed those with a xed mindset (e.g., Claro etal., 2016).
However, in our ndings, students from the Growth Mindsets and
Mixed Mindsets proles did not dier in their math grades, although
it has been shown that dierences in achievement according to
mindset are most prominent in mathematics (Gunderson etal., 2018).
Nevertheless, similar results about students’ mindsets in the
domains of intelligence and giedness were obtained in a variable-
oriented study by Kuusisto etal. (2017), which was also conducted in
the context of a Finnish school. ey found that students’ growth-
oriented views about intelligence but xed ideas about giedness were
associated with higher grades in mathematics. Interestingly, the
Opposing-Mindsets group also outperformed the other prole groups
in their foreign language grades but not, for example, in reading,
which has been commonly a subject related to prociency in
mathematics (Koponen etal., 2020). Nevertheless, in the context of
Finnish education, it seems that the domain of giedness is a
somewhat loaded construct, and, for a minority of students, xed
mindset beliefs are related to high performance in mathematics. In
Finland, in lay speech, it remains rather common to describe someone
as a “math person,” which refers to the idea that some individuals
possess an innate ability in math while others simply do not. Such
expressions are likely to reinforce the belief that high performance in
math is related to individuals’ giedness or natural talent above
anything else. ese thoughts might (unconsciously) aect, in
particular, students who show natural interest and high ability in
mathematics from an early age.
Such students probably receive praise from parents, peers, and
teachers for their apparent talent in math, and they easily gain high
grades in the subject at school. Nonetheless, such praise can
beharmful and may prevent these students from reaching their full
potential: Dweck (2007) has noted in relation to intelligence that
students with a xed mindset tend to emphasize “looking smart.”
Consequently, they may beunwilling to show vulnerability when
facing challenges or failures, which may lead to avoidance of
challenging learning opportunities. e same may betrue of xed
ideas of giedness, and students with an Opposing-Mindsets prole
might hold such notions especially in relation to math (Gunderson
etal., 2018). Consequently, in the long run, these students might not
beable to exploit their full capability in specic areas despite their
talent (Burnette etal., 2022; Dweck, 2007).
However, it is important to note that Finnish education legislation
does not explicitly address gied students or recognize them as a
subgroup with special needs (Laine and Tirri, 2021). is lack of
recognition can prevent high-performing students from fullling their
potential or receiving the necessary support, as the Finnish educational
system employs a dierentiation approach aimed at identifying gaps
between students’ knowledge and the curriculum content (Laine and
Tirri, 2021). Additionally, high-performing students may not
besuciently challenged, as this depends on the individual eorts of
teachers. While these (Opposing Mindset) students perform well in
mathematics in lower secondary school (as seen in this study), it is
possible that if they proceed to study STEM-related subjects in higher
education, they might encounter challenges as the materials become
more complex and demanding. is possible threat should
beacknowledged. ere is an elevated risk of dropping out from the
studies if these individuals are not able to change their implicit beliefs
about giedness. Nevertheless, this is dependent on the development
of students’ mindsets, as some people might retain their xed mindsets
throughout their life course while others might abandon such views
as they grow older.
On the other hand, for Opposing-Mindsets students, a xed
mindset about giedness might also reect their self-assurance about
their skills. A previous study found that primary and upper secondary
school students’ implicit beliefs about intelligence did not induce
higher grades in math or languages; instead, students’ previous school
achievements aected their mindset beliefs, and this was mediated by
perceptions of their academic competence (Leondari and Gialamas,
2002). However, it is notable that although the number of students in
the Opposing-Mindsets group was small compared to the whole sample
in our study, it is possible that one or two students in each class hold
such a mindset. However, most students weinvestigated held a growth
mindset about giedness, which underlines that not all individuals
automatically develop xed beliefs about giedness. Furthermore, it
is possible that those students who rated giedness dierently to
intelligence and creativity held dierent conceptions of giedness than
students in the other proles. is could berevealed by future studies
through qualitative research using interviews to grasp underlying
factors such as family background, and other relevant factors.
When wefurther compared the proles and focused on mixed
mindsets and growth mindsets, we discovered that the

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Growth-Mindsets prole outperformed the Mixed-Mindsets prole in
all other subjects than math and foreign languages. Moreover, the
Growth Mindsets prole outperformed the other prole groups in
most of the subjects in addition to reading. As already mentioned in
reference to a study by Leondari and Gialamas (2002), could it bethat
previous school achievements aect the mindsets of these students
rather than vice versa?
In terms of Fixed Mindsets, wediscovered that students in this
prole achieved lower grades than students within the Growth-
Mindsets prole in all other subjects than reading and music. Based
on mindset theory and the ndings of multiple variable-centered
studies (e.g., Blackwell etal., 2007; Burnette etal., 2023), this result is
unsurprising, but it also indicates that growth-mindset beliefs are not
always associated with higher grades or performance in all subjects.
Academic achievement also diered between the proles of Fixed and
Mixed Mindsets as the grades of students with a Fixed Mindsets prole
were lower than those of students in the Mixed Mindsets prole in
every other subject than reading, foreign languages, and music.
Nevertheless, this nding also underscores the importance of
investigating both the general and subject-specic aspects of mindsets
as even if individuals exhibit a general mindset, they might also hold
subject-specic mindsets in areas such as math (Puusepp etal., 2023)
and language learning (Petscher etal., 2017).
Mindsets profiles and dierences between
genders
Gender dierences have been found to berather common in
motivational studies (Butler, 2014); however, mindset research is more
ambiguous in its ndings on gender dierences, as such dierences
may only become apparent when studies include subject-domain-
specic mindsets (e.g., math) alongside more general mindsets (Yu
and McLellan, 2020). We decided to investigate girls’ and boys’
membership of the dierent mindset proles because there are clear
gender dierences in academic achievement in compulsory education
in Finland (Hautamäki etal., 2013, 2015; Finnish National Agency for
Education, 2014). Moreover, previous Finnish mindsets studies have
observed gender dierences, with boys more likely to hold xed ideas
about intelligence and giedness (Kuusisto et al., 2017; Laurell
etal., 2022).
We used boys as the reference group and discovered that in the
Fixed, Mixed, and Opposing proles, there were noticeably fewer girls
than in the Growth-Mindsets prole. Additionally, when the Mixed-
Mindsets and Opposing-Mindsets proles were investigated, the
Opposing-Mindsets prole included signicantly fewer girls. As there
were more boys in this prole, which included xed mindsets about
giedness, the ndings align with previous Finnish studies (Kuusisto
etal., 2017; Laurell etal., 2022), which also found that adolescent boys
were more likely than their female counterparts to hold xed mindsets
about giedness while no gender dierences were observed in the
domain of intelligence.
We found that girls were overrepresented in the Growth and
Mixed-Mindsets proles. is result aligns with a previous study which
found that boys tended to prioritize validating their competences or
avoiding displays of incompetence (i.e., a performance approach and
avoidance goals; Yu and McLellan, 2020) while girls were
overrepresented in proles with dominant mastery goals. In other
words, girls are more likely than boys to exhibit a willingness to
develop their skills; thus, they are more likely to develop a growth
mindset. One explanation for girls’ superior grades at school in
general is the greater eort that they put into their studies (Butler and
Hasenfratz, 2017), which is a core behavior linked to holding a growth
mindset. Relatedly, the overrepresentation of girls in the Growth or
Mixed-Mindsets proles in our study might help explain boys’ poorer-
than-average performance in the school system in Finland (OECD,
2019). is suggestion aligns with the results from a global meta-
analysis performed by Lindberg etal. (2010) and a national analysis
in Finland conducted by Metsämuuronen and Nousiainen (2021),
which both suggested that while average mathematics performance
between genders is quite similar, boys are more likely to berepresented
at both the high and low ends of the performance spectrum.
Limitations and future research
Our study contains several limitations that should beconsidered
and addressed in future research. Our study explored students in
Finnish lower-secondary school, which limits the generalizability of
the ndings to other cultural or educational contexts. Furthermore,
our study relied on self-reported questionnaires to measure students’
mindsets—their views about the malleability of characteristics—
which may have introduced biases, such as misinterpretation of
questions, failure to take the questions seriously, or deliberately
choosing not to answer. Additionally, participants’ preconceptions
about the nature of intelligence, giedness, and creativity may have
inuenced their responses. However, the mindset research is interested
on people’s conceptions of attributes as developmental of trait-like, not
on understanding how individuals themselves dene the constructs.
Still, this issue relates to the context present as dierent cultural
norms, or prior exposure to discussions about giedness does
inuence on the ideas and perceptions students have. Future research
could, thus, include qualitative methods, such as interviews or open-
ended survey items, to explore how students conceptualize giedness.
is would provide additional context for understanding mindset
proles, particularly the xed giedness mindset seen in the Opposing
Mindsets group.
It is also important to note that the mindset scale used for data
collection only included entity items (Dweck, 2008); thus, it does not
necessarily capture the nature of the students’ mindsets as thoroughly,
as the recommendation to omit the incremental items assumes that
entity and incremental views represent two polar theories (Combette
and Kelemen, 2024). Moreover, it should also benoted that some
more recent studies (Dupeyrat and Mariné, 2005; Scherer and
Campos, 2022) have questioned whether the implicit intelligence
theory construct is unidimensional (see, for example, Combette and
Kelemen, 2024; Lüenegger and Chen, 2017). Moreover, wedid not
account for broader motivational constructs such as eort beliefs or
achievement goals, which could have provided a more thorough
understanding of this complex phenomenon. Proling students based
on a broader set of motivational variables, rather than an implicit
theory of intelligence scale alone, could have revealed more in-depth
information about the students’ mindsets and how other motivational
constructs were related to them in the creation of “meaning systems.”
Furthermore, it is highly relevant to consider how mindsets are
measured in future studies and what can beclaimed based on data

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Frontiers in Psychology 10 frontiersin.org
gathered with mindset items alone. Moreover, while our latent prole
analysis identied four proles (Fixed, Growth, Mixed, and Opposing
Mindsets), the smallest prole (Opposing Mindsets) comprised only
6.7% of the sample, which may reduce the reliability of conclusions
drawn about this specic prole. e present study relied solely on
academic grades, which may not fully capture student performance
and skill complexities. Grades are subjective and reliant on teachers’
evaluations; thus, they may vary from student to student for several
reasons. erefore, academic grades may not entirely reect students’
potential across all areas of learning.
Finally, weused a cross-sectional design, which limited our ability to
infer causality between mindsets and academic achievement. In future
studies, it is crucial to use longitudinal data to assess how mindsets evolve
over time and whether students remain in the same prole groups or how
stable the proles are during the lower-secondary school years. In
addition, it is important to examine how prole group membership
inuences academic outcomes among students. Future studies should
also investigate broader motivational constructs such as eort beliefs and
achievement goals. Additionally, it would bebenecial to include scales
with global mindset beliefs and domain-specic mindsets (e.g., Lewis
etal., 2021). To beable to observe the domain-specicity and generality
of students’ mindsets more reliably, it seems necessary to investigate
mindsets further from this perspective.
Conclusion
In conclusion, the results of the current study suggest that mindsets
in the domains of intelligence, giedness, and creativity form distinct
proles among adolescent students in lower secondary schools, with
prole membership linked to academic achievement and gender. e
study also highlights the value of a person-centered approach when
examining mindsets across multiple general domains. Latent prole
analysis provided an opportunity to identify hidden patterns in
individual students’ general mindsets and specically illustrated how
the prole groups diered between subjects and gender. Weidentied
four mindset proles across the three mindset domains using this
method—Growth, Fixed, Mixed, and Opposing Mindsets—and
dierences were found in achievement in various subjects related to
each prole group. Our results align with previous studies highlighting
the intricacy of students’ mindset beliefs. Our ndings show that
mindset beliefs are highly relevant in the school context, as they can
aect achievement in specic subjects. However, our results emphasize
that even generalized mindsets do not uniformly aect academic
achievement across all subjects. Rather, the ndings were more
nuanced, with notable dierences between subjects with dierent
orientations and goals. Although students with growth mindsets
generally performed extremely well across a range of academic
subjects, interestingly they were outperformed in math by students
with a xed mindset about giedness—a unique combination of
growth and xed beliefs that warrants further investigation, as do
gender dierences within and across mindset domains. Moreover, our
study emphasizes the importance of simultaneously examining
mindset beliefs across multiple domains. Educators should not assume
that adolescent learners neatly t into growth or xed mindset
categories, as some may hold more complex beliefs. By contrast, others
may hold generalized views on their attributes and abilities. us, it is
necessary to explicitly identify students’ proles to support students
with varying mindsets and beliefs instead of simply assuming that
academic achievement provides the necessary motivation for them to
continue their ability development or fulll their potential. Although
our ndings suggest that domain specicity matters, it remains unclear
how mindsets about intelligence, giedness, and creativity manifest in
the everyday life of schools. Consequently, further research in the
Finnish context is necessary on domain-specicity and the generality
of mindsets, particularly intelligence, giedness, and creativity.
Data availability statement
e authors will make the raw data supporting this article’s
conclusions available to any qualied researcher without
undue reservation.
Ethics statement
e studies involving humans were approved by the Research
Ethics Committee in the Humanities and Social and Behavioural
Sciences at the University of Helsinki. e studies were conducted in
accordance with the local legislation and institutional requirements.
Written informed consent for participation in this study was provided
by the participants’ legal guardians/next of kin.
Author contributions
JL: Conceptualization, Data curation, Funding acquisition,
Investigation, Project administration, Writing – original dra,
Writing – review & editing. IP: Data curation, Formal analysis,
Methodology, Soware, Validation, Writing– review & editing. KH:
Project administration, Resources, Supervision, Validation, Writing–
review & editing. KT: Supervision, Validation, Writing– review &
editing.
Funding
e author(s) declare that nancial support was received for the
research, authorship, and/or publication of this article. A personal
working grant (230174) from the Alfred Kordelin foundation enabled
the corresponding author to work with the study full time. Helsinki
University Library covered the publication fee.
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.

Laurell et al. 10.3389/fpsyg.2025.1514879
Frontiers in Psychology 11 frontiersin.org
Generative AI statement
e authors declare that Gen AI was used in the creation of this
manuscript. e rst author occasionally used ChatGPT to revise the
text and improve grammar and uency in the manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their aliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may beevaluated in this article, or
claim that may bemade by its manufacturer, is not guaranteed or
endorsed by the publisher.
Supplementary material
e Supplementary material for this article can befound online
at: https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1514879/
full#supplementary-material
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Appendix
TABLE A1 Post hoc pairwise comparison significance levels and eect sizes for grades.
1 2 3
Math grade
1. Fixed Mindsets
2. Growth Mindsets 0.39***
3. Mixed Mindsets 0.29*ns
4. Opposing Mindsets 0.80*** 0.41*** 0.45***
Reading (Finnish/Swedish) grade
1. Fixed Mindsets
2. Growth Mindsets 0.36**
3. Mixed Mindsets ns 0.20*
4. Opposing Mindsets 0.51*** ns 0.35**
Foreign languages grade
1. Fixed Mindsets
2. Growth Mindsets *
3. Mixed Mindsets ns ns
4. Opposing Mindsets *** *** ***
Arts grade
1. Fixed Mindsets
2. Growth Mindsets ***
3. Mixed Mindsets * *
4. Opposing Mindsets *ns ns
Music grade
1. Fixed Mindsets
2. Growth Mindsets ***
3. Mixed Mindsets ns *ns
4. Opposing Mindsets *ns ns
Crafts grade
1. Fixed Mindsets
2. Growth Mindsets ***
3. Mixed Mindsets * **
4. Opposing Mindsets *** ns *
p < 0.001; **p < 0.01; *p < 0.05; ns, non-signicant.