García-Perales, R., Rocha, A., Albendea-García, M. J., & González-Sánchez, M. (2025). Examining gifted students preferred learning styles in Spain. Revista de Estudios e Investigación en Psicología y Educación, 12(1), Article e11091. https://doi.org/10.17979/reipe.2025.12.1.11091
Ramón García-Perales, University of Castilla-La Mancha
Department of Pedagogy, Faculty of Education of Albacete, University of Castilla-La Mancha (UCLM): https://www.uclm.es/Albacete/EducacionAB Albacete, Castilla-La Mancha – España
Alberto Rocha, Superior Institute of Educational Sciences of Douro (ISCE DOURO)
Department of Education, Superior Institute of Educational Sciences of Douro (ISCE DOURO): https://www.iscedouro.pt/en Penafiel – Portugal
María Jesús Albendea-García, University of Castilla-La Mancha
Department of Pedagogy, Faculty of Education of Albacete, University of Castilla-La Mancha (UCLM): https://www.uclm.es/Albacete/EducacionAB Albacete, Castilla-La Mancha – España
María González-Sánchez, University of Castilla-La Mancha
Department of Pedagogy, Faculty of Education of Albacete, University of Castilla-La Mancha (UCLM): https://www.uclm.es/Albacete/EducacionAB Albacete, Castilla-La Mancha – España
García-Perales, Rocha, Albendea-García, and González-Sánchez: Examining gifted students preferred learning styles in Spain
Abstract
This study analyzed how intellectually gifted students learn by examining the different learning styles they use when facing academic tasks. For this purpose, a sample of 206 students with high intellectual abilities from Spanish schools responded to an adapted version of the Honey-Alonso Learning Styles Questionnaire. Results indicated a stronger inclination toward theoretical learning, though students did not exclusively identify with a single style. Additionally, statistically significant differences emerged when examining their fields of interest in relation to their learning styles: students interested in sports had lower mean scores in scientific-technical and sociolinguistic areas than those who preferred reflective learning. For other variables, mean differences were not statistically significant. These findings highlight the need to continue researching the specific educational needs of these students and how they navigate day-to-day teaching and learning processes, with the goal of promoting a balanced academic progression through the educational stages.
Gifted students are unique protagonists in their educational journeys, and understanding
how they process and assimilate information is essential for developing teaching approaches
that meet their needs. Educational professionals must recognize and appreciate these
differences to tailor instruction effectively, which makes the study of learning styles
critical to enhancing educational quality and equity (; ). However, responses in education often lack tailored support for intellectually
gifted students, resulting in educational inequalities. Reasons often cited for this
include factors such as the low prevalence of giftedness (; ; ), persistent myths and stereotypes about the nature of giftedness, and limited understanding
of how to foster gifted students’ potential (). Additionally, insufficient teacher training (; ) and inadequate guidance for families () contribute to these ongoing disparities.
Addressing these challenges requires in-depth research to uncover the distinct characteristics
and needs of gifted students (; ; ). Responding to the question of whether we know how gifted students learn, this study
focuses on learning styles among gifted students. Understanding how these students
prefer to learn is a complex issue, as learning involves continuous changes shaped
by both individual traits and environmental influences. Learning can be defined as
the transformative process driven by knowledge and strategies acquired through experience
or practice, where context and individual characteristics play essential roles.
Intelligence has a notable impact on learning, and different types of intelligence
may influence how students approach and process information, thus affecting their
learning style (). As intelligence and learning capacity are closely connected, examining predominant
learning styles in gifted students can provide insights into their distinct educational
needs.
Learning styles refer to the cognitive, affective, and physiological traits that characterize
how learners engage with, perceive, and respond to their learning environments (Keefe,
1988, in ). They determine how students focus on, retain, and process information within the
learning environment. The model by , based on experiential learning theory, identifies four key learning styles: active, theoretical,
reflective, and pragmatic. These learning styles describe distinct ways of interacting
with information: learning through concrete experiences (active learning), abstract
conceptualization (theoretical learning), reflective observation (reflective learning),
or practical application (pragmatic learning). Honey and Mumford further developed
these concepts by creating a questionnaire to help educators identify learning styles,
enabling them to better support their students’ educational processes.
Teachers play a crucial role in adapting their methods to match students’ learning
styles, which is a fundamental aspect of inclusive education (). When students encounter new material, they naturally adopt certain strategies that
align with their dominant learning style. Recognizing the predominant learning styles
of gifted students is especially important to provide them with appropriately challenging
tasks and activities. This approach not only enhances engagement but also supports
students in processing information in ways that align with their cognitive preferences.
Gifted students exhibit several defining characteristics in their approach to learning.
Academically, they often seek new knowledge enthusiastically and can easily concentrate
on topics that interest them. They display strong abilities in redefinition, can automate
mechanical processes such as reading and arithmetic, and frequently take on leadership
roles. Their expanded vocabulary, effective communication, and critical thinking abilities
are also distinctive (). Although they respect authority, they may challenge it, preferring to follow their
own criteria. Gifted students often show intense interest in one or more academic
fields and a level of autonomy in seeking information. They may sometimes feel isolated
if their interests differ significantly from those of their peers (). These traits can result in lower-than-expected academic performance if they find
schoolwork repetitive or unchallenging ().
Neuroscience provides additional insights into the learning processes of gifted students.
Their brain development differs markedly from that of their peers, with regions such
as the cerebral cortex continuing to develop until around age 12—much later than the
average, which peaks at around age 7 (). Enhanced myelination and synaptic connectivity in gifted students enable more efficient
working memory and flexible information processing. Increased density of white matter
correlates with faster information processing and more robust connections between
ideas, which are essential for abstract reasoning and problem-solving (). The thicker corpus callosum in gifted students facilitates advanced logical reasoning,
creativity, and hemisphere connectivity, further underscoring the need for differentiated
instructional practices (; ).
A common misconception is that gifted students can thrive without external support,
as if their abilities alone suffice. However, like all children, they benefit from
adult guidance in organizing and processing information. Without such support, they
may struggle with poor study habits, which can hinder academic progress (). Studies by and show that many gifted students perform below their potential due to a lack of intrinsic
or extrinsic motivation, especially if their educational environment does not cater
to their interests.
Various personal and contextual factors also influence gifted students’ academic performance.
These include sex—often leading to underdiagnosis in gifted women compared to men
(; ; )—age, grade level, and the school environment (; ). Such factors are crucial considerations for future research, as they affect the
identification, diagnosis, and educational response provided to gifted students ().
It is useful to contextualize the reality of giftedness in Spain, looking at the 2022/23
academic year, the most recent non-university data available on the . The total number of gifted students was 51,396, or 0.62% of the students in non-university
education. Almost two-thirds (33,307; 64.81%) were men, 18,089 (35.19%) were women,
similar proportions to the present study. Finally, by educational stage, 325 (0.63%)
were in Infant Education, 20,178 (39.26%) were in Primary Education, 22,387 (43.56%)
were in Compulsory Secondary Education, 7,490 (14.57%) were in Baccalaureate, and
1,016 (1.98%) were in Vocational Training.
The aim of the present study was to assess how gifted students learn by analyzing
their predominant learning styles. Additionally, the study examined the potential
relation of personal and sociodemographic variables in the application of these learning
styles, contributing to a more nuanced understanding of the educational approaches
needed to support this unique group of learners.
Method
Participants
The sample of participants was selected through simple random probabilistic sampling
to ensure representativeness within the intellectually gifted population. A total
of 206 Spanish students participated from 11 of the 17 autonomous communities: Andalucía,
Aragón, The Balearic Islands, Cantabria, Castilla-La Mancha, Castilla & León, Catalonia,
Valencia, Madrid, Murcia, and the Basque Country. All participants had been formally
identified and diagnosed as intellectually gifted within their school settings. The
sample was predominantly male, with almost two-thirds (131; 63.59%) of the participants
being boys, while girls comprised 36.41% (75) of the sample.
The participants ranged from 8 to 18 years old, covering a broad spectrum of developmental
stages. The educational distribution included 111 students (53.88%) in Primary Education
and 95 students (46.12%) in Secondary Education (82 students in Compulsory Secondary
Education and 13 students in Baccalaureate).
In terms of special educational interventions, 33 students (16.02%) reported receiving
flexible curricular measures, such as acceleration or an enriched curriculum, at some
point during their schooling to better meet their specific needs. The remaining 173
students (83.98%) had not received extraordinary curricular interventions, reflecting
the variability in educational responses to giftedness within the school system.
Most students resided in urban areas, with 170 students (82.52%) coming from urban
settings and 36 students (17.48%) from rural areas. This distribution highlights an
urban concentration of identified gifted students, which may reflect disparities in
identification and available resources between rural and urban settings. Students
were also asked to identify their primary academic or extracurricular areas of interest.
A significant proportion, 133 students (64.56%), indicated a preference for Science
and Technology subjects, including mathematics, biology, physics, chemistry, and technology.
Another 43 students (20.87%) expressed interest in the Socio-Linguistic area, encompassing
subjects such as geography, history, Spanish language, psychology, French, and English.
Meanwhile, 20 students (9.71%) reported a preference for the Arts, covering areas
such as music, visual arts, and fine arts, and 10 students (4.85%) indicated Sports,
primarily focused on physical education. This distribution underscores a predominant
interest in Science and Technology among gifted students in this sample, which aligns
with literature findings on academic inclinations within gifted populations.
Instrument
The study used an adapted version of the Honey-Alonso Learning Styles Questionnaire
(CHAEA), originally developed to assess different learning styles based on Kolb’s
experiential learning theory. The adapted questionnaire has 80 items that evaluate
four distinct learning styles—active, reflective, theoretical, and pragmatic. Each
style is covered by 20 items, randomly distributed throughout the questionnaire, allowing
for a maximum score of 20 points per style. Respondents indicate their level of agreement
or disagreement with each item, enabling comprehensive assessment of their predominant
learning preferences and tendencies.
The adaptation was designed to suit the specific needs of the study’s gifted student
sample, ensuring both reliability and relevance (). The adapted format maintains the theoretical integrity of the original CHAEA while
optimizing item clarity and applicability for a younger, academically diverse population.
Furthermore, the adaptation allows determination of students' overall learning profiles,
categorizing them into one or more dominant learning styles. This nuanced profile
assessment supports a deeper understanding of individual differences in learning among
gifted students, which is crucial for tailored educational strategies.
Table 1 outlines the conceptualization of each learning style.
Table 1Characterization of learning styles
Learning style
Characteristics
Learns best
Challenges
Active
General: learn by doing, involve themselves in activities and in new experiences,
act first and then think about consequences, reject long term activities, like being
the focus of activities, have open minds and enjoy group work. Principally: entertainers,
risk-takers, discoverers, and spontaneous. Others: adventurers, protagonists, participants,
competitive, willing, creative…
If there is a challenge to solve, if there is excitement and when activities are short
term.
Adopting a passive role, dealing with details, analysing a lot of data, and working
on their own.
Reflexive
General: cautious, enjoy watching others, analyse data to reach conclusions, study
implications before taking action and try to remain in the background. Principally:
analytical, thorough, conscientious. Others: observant, prudent, collectors, detail-oriented,
patient…
If they can be an observer and when they can stop and think before taking action.
Being the centre of attention, explaining ideas off the cuff and without a lot of
data to draw conclusions from.
Theoretical
General: enjoy analysing and summarizing information, seek rationality and reject
the subjective, focus on problems sequentially (step by step) and incorporate observations
into consistent theories. Principally: logical, structured, and methodical. Others:
perfectionists, planners, systematic, disciplined, rationalists.
If they can investigate, examine, and ask questions, when they work on concepts from
data and theories, and if they work in structured situations.
Participating in ambiguous activities, acting without a conceptual basis, and participating
in situations where emotions are more important.
Pragmatic
General: enjoy putting ideas into practice, motivated by trying new ideas, enjoy acting
quickly in projects that appeal, problems are a challenge, and they reject people
who theorize. Principally: practical, effective, and experimenters. Others: planners,
decisive, technical, objective, positive…
If they gain techniques to apply immediately to their work, if there is a connection
between the subject they are working on and putting it into practice, if they see
real problems, and if they are given many examples.
Learning things which are unrelated to their immediate needs, learning something not
closely connected to reality, learning theoretical principles, and not having clear
instructions.
[i]Note: Adapted from .
The tool created for this study is a reduced version of the questionnaire. It is made
up of 20 randomly distributed items with the students giving yes/no responses depending
on whether they identify with the statement or not. Each learning style is covered
by 5 items: active (items 4, 8, 9, 12, and 17), reflexive (items 1, 3, 10, 13, and
16), theoretical (items 2, 6, 11, 15, and 19), and pragmatic (items 5, 7, 14, 18,
and 20). The entire instrument was administered to participants using a Microsoft
Forms questionnaire. A final section was also included with space for participants
to write what they considered appropriate to complete the research.
The weighting of the adapted instrument was based on the total positive answers. A
student response of “yes” was given a score of 1 point, “no” was given 0 points. This
gave a total of all positive responses for each learning style which were then compared.
As noted above, each learning style had five statements, so the maximum score for
each style was 5 points and the maximum total score was 20 points.
Procedure
The study was conducted nationwide in Spain between February and June 2023, involving
giftedness associations in 11 of the 17 autonomous communities, specifically: Andalucía,
Aragón, The Balearic Islands, Cantabria, Castilla-La Mancha, Castilla & León, Catalonia,
Valencia, Madrid, Murcia, and the Basque Country. These associations were integral
to facilitating participant recruitment and ensuring diverse regional representation.
Initial contact was made by email to each association, with a detailed presentation
of the study objectives, methodology, and ethical considerations, requesting their
collaboration to disseminate information about the study to their member families.
The email included a link to the questionnaire hosted on Microsoft Forms, allowing
students to participate remotely and securely, the questionnaires were completed,
and the process was monitored in the association premises attended by the participants.
Data collection adhered to strict ethical protocols, ensuring that responses were
both anonymous and confidential, the participants were identified with the initials
of their first and last names together with their date of birth. Each participant’s
family and association administrators received an informed consent form detailing
the study’s purpose, the voluntary nature of participation, and assurances of data
privacy, in compliance with ethical standards and data protection laws and following
the model of the Social Research Ethics Committee (CEIS) of the University of Castilla-La
Mancha. Obtaining informed consent from both association administrators and families
upheld the ethical obligation to respect participant autonomy and privacy throughout
the study.
Data analysis
The quantitative data were analyzed using IBM SPSS v. 28.0, with a confidence level
set at 95%. Descriptive analyses were conducted for each learning style and for the
questionnaire overall, including frequency (f), percentage (%), mean (M), and standard
deviation (SD). To explore potential relationships between learning styles and participants'
demographic variables—specifically sex, age, flexible schooling, geographic location,
and areas of interest—both descriptive statistics and non-parametric tests were used.
The choice of non-parametric tests was guided by preliminary tests for normality (Kolmogorov-Smirnov)
and homoscedasticity (Levene’s test), which indicated that the data did not meet the
assumptions required for parametric testing. As a result, the Mann-Whitney U test
and the Kruskal-Wallis test were applied to compare groups across these categorical
variables.
To further examine the influence of multiple variables, Quade’s non-parametric ANCOVA
was used to control for potential covariates, allowing a more robust analysis of differences
between learning styles and participant characteristics. This combination of tests
ensured that the analysis remained rigorous and statistically appropriate for the
data distribution characteristics, supporting reliable conclusions.
Results
This section gives the results for the learning styles and the results for the personal
and sociodemographic variables considered in the study. Prior to that, the following
Cronbach's alpha reliability indices were obtained for each learning style: Activist
.70, Reflector .68, Theorist .72 and Pragmatist .67. The frequencies and percentages
for each learning style based on the number of affirmative response (“yes”) from each
student were as follows (Table 2):
Table 2Frequencies and percentages for each learning style
Learning styles
Items with affirmative response
0f (%)
1f (%)
2f (%)
3f (%)
4f (%)
5f (%)
Activist
3 (1.46)
16 (7.77)
52 (25.24)
57 (27.67)
49 (23.79)
29 (14.08)
Reflector
1 (0.49)
16 (7.77)
28 (13.59)
44 (21.36)
77 (37.38)
40 (19.42)
Theorist
1 (0.49)
5 (2.43)
10 (4.85)
35 (16.99)
63 (30.58)
92 (44.66)
Pragmatist
3 (1.46)
17 (8.25)
28 (13.59)
78 (37.86)
48 (23.30)
32 (15.53)
For example, 92 students (44.66%) indicated 5 items from the theoretical learning
style, showing a preference for the logical and methodical and a preference to leave
ambiguous or subjective activities to one side. Only a single participant (0.49%)
selected none of the items from the theoretical or reflexive styles. The reflexive
style was also selected by a large number of participants, as 77 students (37.38%)
identified with 4 of the 5 items in this style and 40 (19.42%) identified with all
5. In contrast, in the pragmatic and active styles, most students selected 3 of the
5 items (57 students (27.67%) in active, and 78 (37.86%) in pragmatic). Lastly, the
activist style had the fewest students identifying with all 5 items (29; 14.08%).
The means and standard deviations for each learning style were as follows: Activist
M = 3.07 (SD = 1.22), Reflector M = 3.46 (SD = 1.20), Theorist M = 4.09 (SD = 1.05) and Pragmatist M = 3.20 (SD = 1.19). The means for the four styles were above 3 on a 5-point scale. The theoretical
learning style had the highest mean of 4.09 (SD = 1.05), while the active learning style had the lowest, at 3.07 (SD = 1.22).
The personal and sociodemographic variables considered were: participants’ sex, educational
stage, flexible schooling, location, and areas of interest. For the first four dichotomous
variables, the results were as follows (Table 3):
Table 3Descriptive (M and SD) and inferential statistics (Mann-Whitney U) for the dichotomous
variables
Dichotomous variables
Activist
Reflector
Theorist
Pragmatist
Sex
Boy (n = 131)
3.07 ± 1.22
3.38 ± 1.27
4.06 ± 1.04
3.15 ± 1.17
Girl (n = 75)
3.07 ± 1.23
3.59 ± 1.07
4.13 ± 1.08
3.28 ± 1.22
U (p)
4973.50 (.88)
4587.00 (.41)
4624.00 (.45)
4551.50 (.36)
Educational stage
Primary Education (n = 111)
3.11 ± 1.22
3.43 ± 1.17
4.14 ± 1.05
3.29 ± 1.13
Secondary Education (n = 95)
3.02 ± 1.24
3.48 ± 1.24
4.03 ± 1.06
3.09 ± 1.26
U (p)
5071.00 (.63)
5438.00 (.69)
4948.50 (.42)
4992.00 (.49)
Flexible schooling
Yes (n = 33)
3.06 ± 1.41
3.27 ± 1.28
4.09 ± .98
3.48 ± 1.00
No (n = 173)
3.07 ± 1.19
3.49 ± 1.18
4.09 ± 1.07
3.14 ± 1.22
U (p)
2869.00 (.96)
2584.00 (.37)
2805.50 (.87)
3223.50 (.22)
Location
Rural (n = 36)
3.31 ± 1.45
3.36 ± 1.25
3.86 ± 1.22
3.44 ± 1.11
Urban (n = 170)
3.02 ± 1.17
3.48 ± 1.19
4.14 ± 1.01
3.15 ± 1.20
U (p)
3500.50 (.16)
2897.00 (.60)
2698.00 (.23)
3385.50 (.30)
The results indicate that there were no statistically significant differences in each
style of learning for the dichotomous variables. The mean scores were similar for
boys and girls, except in the reflexive and pragmatist styles, where girls scored
higher, although the difference was not statistically significant (p = .41 and p = .36, respectively). In the educational stage variable, there were higher mean scores
in primary education in three of the four styles: activist, theorist and pragmatist;
in secondary education, there were higher scores in the reflector style. In the flexible
schooling variable, it is worth noting the higher scores for reflexive learning in
students who had not had flexible schooling, M = 3.49 (SD = 1.18), and the higher scores for pragmatic learning in students who had, M = 3.48 (SD = 1.00), with the latter approaching statistical significance p = .22. Finally, students in rural environments scored higher in active and pragmatic
learning, with the former approaching statistical significance at p = .16; in contrast, reflexive and theoretical learning had higher scores in urban
students.
In addition to these dichotomous variables, the last variable analyzed was the students’
areas of interest, the results were as follows (Table 4):
Table 4Questionnaire results by participants’ areas of interest
There was a statistically significant difference in the scores for the reflexive learning
style, at p = .04. This was due to differences in scores for this style from students who were
interested in scientific-technological and socio-linguistic areas —means of 3.56 (SD = 1.16) and 3.49 (SD = 1.30)— and students who were interested in sport, who had lower mean scores in
this learning style of 2.50 (SD = 1.27). These results are shown graphically in Figure 1.
Figure 1Results by participants’ areas of interest
To examine the significance more thoroughly, ANCOVA tests between variables were performed,
specifically, the reflexive learning style according to areas of interest with the
covariable sex [F(3,202)=2.90; p = .04], environment [F(3,202)=2.95; p = .03], flexible schooling [F(3,202)=3.13; p = .03], and educational stage [F(3,202)=2.84; p = .04].
Finally, some of the comments made by the participants are worth highlighting, such
as “At school I sometimes get bored. They go over the same things again,” and “When
I’m learning, I don’t like it that they repeat everything a hundred times,” indicating
a perception of school as repetitive and insufficiently stimulating.
Discussion
Knowing how students learn is one element to keep in mind in order to develop quality
inclusive educational processes (). The personalization of teaching and learning processes requires identifying the
styles that students use to learn. This could result in better adjustment and individualization
of education, with the consequent improvement of academic performance, increased motivation,
engagement and participation, and increased self-esteem and self-confidence. Better
understanding and retention of information allows for more effective learning, so
knowledge and application of learning styles in the classroom is a key strategy for
ensuring that all students have the same opportunities for success, thus promoting
inclusive and equitable education ().
Understanding how intellectually gifted students learn is essential for tailoring
educational approaches to support their unique needs effectively. These students display
a range of specific characteristics that challenge efforts to outline clear profiles
(). Our findings underscore this complexity: no single learning style was universally
adopted among participants. Nevertheless, 44.66% of participants identified with all
items in the theoretical learning style, which aligns with a preference for logical
analysis, step-by-step problem-solving, and well-structured theories. Students with
this style tend to excel when given opportunities to investigate questions in structured
environments. They may, however, struggle with ambiguous tasks or settings that emphasize
emotional rather than conceptual engagement. The active style was the least selected,
with only 14.08% of participants choosing all five items, suggesting that hands-on
or spontaneous activities may appeal less to this population.
In terms of personal and sociodemographic variables, no statistically significant
differences emerged by sex, educational stage, flexible schooling, or geographic location.
This aligns with findings from other studies (; ) that also reported a lack of significant impact of sex or environment on learning
styles. However, some research indicates that sex and educational stage can influence
cognitive attitudes and learning behaviors, such as perfectionism and cognitive mindset
(), or even intelligence domains (), suggesting these areas may merit further investigation.
One significant finding in the study pertains to students’ areas of interest, with
statistically significant differences (p = .04) in the reflective learning style. Students interested in sports had lower
scores in the reflective style (M = 2.50, SD = 1.27) than those inclined toward scientific-technological (M = 3.56, SD = 1.16) and socio-linguistic fields (M = 3.49, SD = 1.30). ANCOVA analyses, examining reflexive learning style according to areas of
interest with sex, environment, flexible schooling, and educational stage, confirmed
these relationships, suggesting that students' areas of interest may significantly
shape their learning style preferences. This insight is critical, as it suggests that
individualized approaches based on students’ interests could enhance engagement and
learning outcomes.
Feedback from students in the final section of the questionnaire highlights an important
disparity between learning styles and their needs and their educational experiences.
These reflections align with findings from and that gifted students often feel misunderstood in educational settings. Their expressed
lack of motivation and desire for learning outside the classroom suggest that educators
must consider more flexible and stimulating curricula to match these students’ intellectual
curiosity and pace of learning. These statements serve as a reminder that we must
ensure educators are equipped with the necessary training and resources to support
an inclusive and quality education for gifted students.
Despite the study’s contributions, it does have limitations. Although we have had
a sample of interest considering the existing under-diagnosis of these students in
Spain (), it could have benefited from broader representation in the educational stages included
in the study, especially Baccalaureate students, to achieve greater balance in relation to the participating students in
Compulsory Secondary Education (the two educational stages make up Secondary Education).
Future research should aim to replicate these findings with larger and more diverse
samples. Further studies might also consider additional variables, such as academic
performance, self-concept, self-esteem, academic engagement, physical activity, motivation
for learning, perfectionism, critical thinking, and study habits, to build a more
comprehensive understanding of gifted students’ learning styles and needs.
Education professionals must improve their understanding of the characteristics of
intellectually gifted students to provide appropriate, tailored educational experiences
that foster their potential (; ). Recognizing that each gifted individual is unique, educational systems should prioritize
inclusivity and quality, ensuring that all students receive support that respects
their distinct needs (; ). The diversity within this group is especially pronounced, characterized by a wide
range of traits and learning preferences that make generalized interventions challenging
(; ). Therefore, identification and intervention processes for gifted students must be
multidimensional to capture the complexity of traits that shape their personalities,
cognitive styles, and academic engagement (; ).
This study highlights learning style as one key aspect of gifted students’ academic
needs, especially as they transition between educational stages. The findings underscore
the importance of recognizing individual learning preferences—such as theoretical,
reflective, or pragmatic styles—as these can influence how gifted students engage
with content, retain information, and perceive their educational environment. Personalized
approaches in teaching, tailored to these learning styles, can significantly enhance
academic experiences and outcomes for gifted students, facilitating smoother transitions
between levels and fostering sustained engagement.
In summary, personalized teaching and learning processes are fundamental to achieving
an inclusive educational system. By understanding and addressing the unique ways in
which gifted students learn, educators and institutions can progress toward a more
responsive and adaptive educational environment—one that not only values but actively
supports each student’s learning journey. This commitment to personalized education
underscores the broader objective of fostering an educational landscape where all
students can realize their full potential in a supportive, inclusive setting.
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