The role of critical thinking, creative thinking, and digital readiness
in promoting academic achievement
El papel del pensamiento crítico,
el pensamiento creativo y la preparación digital en la promoción del desempeño
académico
Universitas Islam
Negeri Raden Intan Lampung. Indonesia.
University of Szeged. Hungary.
Universitas Islam
Negeri Raden Intan Lampung. Indonesia.
Universitas Islam
Negeri Raden Intan Lampung. Indonesia.
Universitas Muhammadiyah Pringsewu. Indonesia.
Universitas PGRI
Madiun. Indonesia.
Received: 2025-06-04 Revised: 2026-02-24 Accepted: 2026-03-04 Published: 2026-09-01
How to cite:
Anggoro, B.S., Suherman, S., Muhammad, R.R., Hidayatullah,
H., & Andari, T. (2026). The role of critical thinking, creative thinking, and digital readiness
in promoting academic achievement [El papel del pensamiento crítico, el
pensamiento creativo y la preparación digital en la promoción del desempeño
académico]. Pixel-Bit, Revista de Medios y
Educación, 77, Art. 10. https://doi.org/10.12795/pixelbit.116601
ABSTRACT
Critical and creative mathematical thinking are widely
regarded as vital competencies for the 21st century, playing a significant role
in shaping academic success. Despite their importance, limited research has
explored how these skills relate to students’ digital readiness. Addressing
this gap, the present study investigated the interconnections between critical
thinking, creative thinking, and digital readiness in the context of
mathematics education. The research involved 312 preservice students who
responded to an online questionnaire. Data were analysed using structural
equation modelling, which confirmed the validity and reliability of the
measurement instruments. The results showed that critical and creative thinking
significantly predicted digital readiness, which, in turn, significantly
predicted academic achievement. Although the direct effects of critical and
creative thinking on academic achievement were positive, they were not
statistically significant. These findings indicate that digital readiness fully
mediates the relationship between higher-order thinking skills and academic
achievement. The study underscores the importance of integrating digital
readiness with critical and creative thinking in educational settings to better
equip students for the demands of the digital age. Educational institutions are
therefore encouraged to incorporate these competencies into their curricula.
RESUMEN
El pensamiento matemático crítico y creativo es ampliamente considerado como
una competencia vital para el siglo XXI, desempeñando un papel significativo en
la consecución del éxito académico. A pesar de su importancia, son pocos los
estudios que han explorado cómo estas habilidades se relacionan con la
preparación digital de los estudiantes. Con el fin de cerrar esta brecha, el
presente estudio investigó las interconexiones entre el pensamiento crítico, el
pensamiento creativo y la preparación digital en el contexto de la educación
matemática. En la investigación participaron 312 estudiantes en formación que
respondieron a un cuestionario en línea. Los datos se analizaron mediante
modelos de ecuaciones estructurales, lo que confirmó la validez y fiabilidad de
los instrumentos de medición. Los resultados mostraron que el pensamiento
crítico y creativo predecía significativamente la preparación digital, lo que,
a su vez, predecía significativamente el desempeño académico. Aunque los
efectos directos del pensamiento crítico y creativo sobre el desempeño
académico fueron positivos, no fueron estadísticamente significativos. Estos
hallazgos indican que la preparación digital interviene plenamente en la
relación entre las habilidades de pensamiento de orden superior y el desempeño
académico. El estudio subraya la importancia de integrar la preparación digital
con el pensamiento crítico y creativo en los entornos educativos, a fin de
preparar mejor a los estudiantes para las exigencias de la era digital. Por lo
tanto, se alienta a las instituciones educativas a incorporar estas
competencias en sus planes de estudio.
KEYWORDS · PALABRAS CLAVES
Academic achievement, Critical thinking,
Creative thinking, Digital readiness, Pre-cervice students · Desempeño académico, pensamiento crítico, pensamiento
creativo, preparación digital, estudiantes en formación.
1.
Introduction
Critical
and creative mathematical thinking skills are recognised as essential
21st-century competencies, particularly for preservice teachers who must be
prepared to educate students in an increasingly complex world. Critical
thinking helps students analyse and evaluate problems logically and make evidence-based decisions (Anggraeni
et al., 2023),
while creative thinking supports the generation of novel ideas, solutions, and
approaches (Suherman
& Vidákovich, 2022).
Recognising this, the present study aims to investigate how these cognitive
abilities contribute to the development of academic achievemet among preservice
teachers, who are expected to facilitate such skills in their future students.
In an era shaped by rapid technological change and
global challenges, preservice teachers are expected to master more than content
knowledge; they must also develop high levels of thinking and decision-making
skills. Research has consistently shown that critical and creative thinking can
enhance academic achievement (Akpur,
2020),
foster unique problem-solving abilities (Wu
et al., 2024),
and increase competitiveness of graduates in the workforce (Thornhill-Miller
et al., 2023).
However, many preservice teachers still face difficulties in technological
readiness (Kim
et al., 2019) and
struggle to maintain a sense of academic achievement (García-Martínez et al., 2021; Ocal et al., 2025).
Based on constructivist learning theory, this study
also emphasises the importance of active student involvement in building
personal and academic agency. According to this theory, students actively construct knowledge through
meaningful learning experiences and reflective practices (Bada
& Olusegun, 2015; Le & Nguyen, 2024; S. Pan et al., 2024).
This engagement is essential to develop a strong sense of technological
readiness and academic motivation. By investigating how these experiences relate
to academic achievement, the current study aims to better understand how
cognitive and motivational factors interact to shape the readiness of
preservice teachers for modern classrooms.
Furthermore, the research is informed by
self-determination theory by Ryan
& Deci (2017),
which highlights how autonomy-supportive teaching fosters motivation,
responsibility, and cognitive growth. Prior studies have shown that digital
readiness supports academic success (Kim
et al., 2019),
critical thinking increases academic competence (Karaer
et al., 2024),
and creative thinking enhances high-order thinking and academic achievement (Anggoro
et al., 2024; Israel-Fishelson & Hershkovitz, 2024).
Despite this, few studies have investigated the combined influence of these
variables within a single comprehensive model. Therefore, the aim of this study is to
holistically examine the influence of critical thinking, creative thinking, and
digital readiness on the development of academic achievement, offering insights
into how preservice teachers can be better supported in cultivating the skills
necessary for 21st century education.
2. Theoretical framework
2.1. Critical thinking and academic achievement
Critical thinking skills play a crucial role in
improving academic achievement in the 21st century, especially for preservice
teachers, who are expected to deeply understand concepts and evaluate multiple
solutions to solve academic problems. This ability enables individuals to
distinguish valid information from misinformation, an essential competency in
the digital era (Almulla,
2023). With these skills, students are not only able to identify weaknesses in
their learning approaches but also to develop more effective strategies to achieve educational goals.
Research by Wang et al. (2019) shows that students with
higher levels of critical thinking tend to exhibit stronger self-regulation in
responding to academic demands. Dispositions also play a vital role in critical
thinking assessments and are closely linked to academic achievement (Liu
et al., 2023).
Students with strong affective dispositions, as noted by Sk
& Halder (2024),
are more likely to apply their critical thinking skills in various situations
compared to those who have the skills but do not actively use them. This
highlights the importance of fostering not only the cognitive aspects of
critical thinking but also the motivation and willingness to apply these skills
in real academic contexts. In addition, critical thinking skills help
preservice teachers develop confidence in decision making and maintain
consistency in analysing information thoroughly, evaluating arguments, and
making rational decisions based on strong evidence (Dunne,
2015). This
aligns with metacognitive theory, which plays an important role in the learning
process by assessing the level of active control that influences academic
achievement (Y.
Pan et al., 2024).
Long-term, students who are capable of critical thinking are better prepared to
face both academic and professional challenges, leading to a positive impact on
their performance and academic success.
H1: Critical thinking positive impact on academic
achievement
2.2. Creative thinking and academic achievement
Creative thinking and academic achievement share a
mutually strengthening relationship that contributes significantly to learning
outcomes. Students who demonstrate creative thinking skills tend to approach
academic tasks with greater flexibility and innovation, enabling them to plan
and complete assignments more effectively. Research by Alwhaibi et al. (2024) indicates that creative thinking accounts for a substantial 47.5% of variance
in academic performance, highlighting its critical role in educational success.
Both convergent and divergent thinking, where the latter includes creative
thinking, have been shown to positively correlate with academic skills of
students’ (Fung
& Chung, 2024).
Empirical evidence supports this relationship across age groups, from primary
school children (Zhang
et al., 2020) to
university students (Alabbasi
et al., 2023),
confirming that convergent and divergent cognitive processes contribute to
academic achievement (Akpur,
2020; Gajda, 2016; Gajda et al., 2017).
Creative thinking has also been recognised as a
significant factor influencing academic performance (Aktas
& Tabak, 2018).
However, the strength of the relationship between creativity and academic success
varies depending on the age of the students, the educational stage, and even
between schools at the same level of education (Gralewski
& Karwowski, 2012).
These variations may be attributed to differences in how open teachers and institutions
are to creativity, as well as the extent of student participation in the
learning process (Gajda,
2016).
When these factors align positively, creative thinking not only enhances
student engagement, but also improves academic performance (Karunarathne
& Calma, 2024).
Therefore, the integration of creative thinking into academic development
provides a strong foundation for achieving optimal learning outcomes.
H2: Creative thinking meaningful impact on academic achievement.
2.3. Digital readiness and academic achievement
Research consistently highlights that students who
possess a high level of digital literacy—which include skills related to
information analysis, online collaboration, and technological navigation—tend
to demonstrate better academic performance and engagement in their studies (Fernandez
et al., 2022; Kim et al., 2019).
For instance, Kim
et al. (2019) emphasize
that students exhibiting confidence in their digital capabilities open
themselves to enhanced academic success, suggesting that positive experiences
with digital tools alone are insufficient without a committed approach to
learning. Moreover, findings from Nikou
and Aavakare (2021)
reveal that the effects of digital literacy on students' willingness to use
technology are intricately mediated by their expectations regarding performance
and the effort required, underscoring the necessity for realistic pedagogical
approaches in fostering digital literacy. Furthermore, Çalışkan
(2023)
shows that students struggling with internet access, a crucial aspect of digital
literacy, often display lower motivation and academic outcomes, while
initiatives aimed at enhancing digital skills correlate with increased
achievement levels and self-efficacy among learners. Sari
(2024) supports
this notion, indicating that students with strong digital competencies in
science courses improve their engagement and, subsequently, their performance.
This aligns with the findings of Buzzetto-Hollywood
et al. (2018),
who assert that many students enter higher education without adequate digital
training, suggesting a need for targeted educational interventions designed to
instill necessary digital competencies for academic success. This cumulative
evidence establishes a compelling connection between digital readiness and
enhanced academic achievement, advocating for educational systems to prioritize
digital literacy initiatives as integral to preparing students for contemporary
academic challenges.
H3: Digital readiness impact on academic achievement.
2.4. Mediation role of digital readiness
Previous studies underscore that critical thinking and
creative thinking skills are positively associated with academic success (Akpur,
2020; Liu et al., 2023; Nasution et al., 2023).
For example, Liu
et al. (2023)
demonstrated that high school students with a strong critical thinking disposition
are more adept at problem analysis and problem-solving, which contributes to
improved academic performance. Similarly, research by Saeed
and Ramdane (2022)
highlights the interconnections between critical thinking, creative thinking,
and reflective thinking, suggesting that these cognitive skills collectively
enhance academic achievement through their interaction. Moreover, research by Althubaiti
et al. (2022)
emphasises that students
proficient in digital skills can effectively leverage their critical and creative
capacities to navigate educational challenges. This mediation occurs because
digital readiness enables students to access diverse resources, collaborate more
effectively, and employ innovative problem-solving techniques, transformational
skills necessary for academic achievement in the modern educational landscape (Fernandez
et al., 2022).
Consequently, this framework underscores the necessity of fostering both
digital readiness and higher-order thinking skills within educational structures
to create an environment conducive to enhanced academic performance (Figure 1).
H4: Digital readiness as a mediator between critical
thinking, creative thinking, and academic achievement.
Figure
1
The
hypothesized model of critical thinking, creative thinking, digital readiness,
and academic achievement.
Note: own elaboration.
3. Methodology
3.1. Participant
This research included 312 preservice teachers from
Lampung Province, Indonesia, selected using proportionate stratified random sampling.
The total population consisted of approximately 1,650 preservice teachers
enrolled in public and private teacher education institutions during the
2024/2025 academic year. The sample size was determined using the Slovin
formula with a 5% margin of error, which indicated a minimum required sample of
312 participants. Stratification was conducted based on semester level (2nd,
4th, and 6th semester) and institution type (public and private) to ensure proportional
representation of each subgroup within the population. This method was employed
to enhance representativeness and reduce sampling bias across academic levels
and institutional categories. The cross-sectional study comprised 158 male
(49.4%) and 154 female (50.6%) participants. Respondents were recruited from
both public and private institutions across urban and rural districts. The mean
age of participants was 19.83 years (SD = 1.04). Ethical approval was obtained
from the Institutional Review Board of Universitas Islam Negeri Raden Intan
Lampung, Indonesia, in accordance with institutional research ethics
guidelines. Informed consent was secured from all participants prior to data
collection. A detailed summary of participant demographics is presented in
Table 1.
Table
1
Demographics
of the sample
|
Demographics |
Frequency |
Percentage (%) |
||||
|
Gender |
Male |
158 |
49.4 |
|
||
|
|
Female |
154 |
50.6 |
|
||
|
Grade semester |
2 |
130 |
41.7 |
|
||
|
|
4 |
104 |
33.3 |
|
||
|
|
6 |
78 |
25.0 |
|
||
|
Residence |
City |
164 |
52.6 |
|
||
|
|
Urban |
148 |
47.4 |
|
||
Note: n = 312; mean age =
19.83; SD = 1.04
3.2. Instruments
Critical thinking.
This instrument was adopted from Sosu
(2013) and
consists of 5 items. Examples
of the items include “I usually try to think about the bigger picture during a discussion,” “I
often use new ideas to shape (modify) the way I do things,” “I usually think
about the wider implications of a decision before taking action,” and “I often
think about my actions to see whether I could improve them.” The original
instrument was developed in English and demonstrated a good model fit with
X²(97) = 158.82, TLI = .91, CFI = .92, RMSEA = .059 with a 90% CI of .042–.075,
SRMR = .064, and Cronbach’s alpha = .79. Responses are measured using a 5-point
Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Since
the original instrument was in English, it was translated into the local
language using a standard forward–backward translation procedure. Two
independent translators produced a forward translation into the target
language, which was then reviewed and reconciled. A back-translation into
English was conducted by a third independent translator to check for
consistency. The psychometric evaluation was conducted in this study.
Creative thinking.
This instrument was adapted from Rogaten
& Moneta (2015) and
includes four items. Sample statements are: “I find effective solutions by
combining multiple ideas', 'While working on something, I try to generate as
many ideas as possible,” “I try to act out potential solutions to explore their
effectiveness,” and “Incorporating previous solutions in new ways leads to good
ideas.” The original version is in English and demonstrated high psychometric properties,
with a Kaiser–Meyer–Olkin (KMO) statistic of 0.937 and factor loadings ranging
from 0.62 to 0.83. The model fit indices were χ² = 48.47, df = 5, p <
.001, CFI = 0.97, NNFI = 0.95, SRMR = 0.038, and RMSEA = 0.78. The instrument
uses a 5-point Likert scale, where 1 represents “strongly disagree” and 5
represents “strongly agree.” The psychometric properties of the instrument were
evaluated in this study.
Digital readiness.
The concept of digital readiness in this study was adapted from the work of Hong
and Kim (2018),
which assesses the self-perceived digital competencies of college students in
relation to their academic involvement. Digital readiness is considered a critical
factor in supporting students' academic achievement at the university level.
The instrument consists of five scales divided by 17 items, each rated on a
5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
An example of the instruments are “I can critically interpret digital media
content” and “I can share my files with classmates using online software.” The
previous instruments were the goodness of fit indices: χ2 = 241.329,
df = 103, p < .001, RMSEA = .056 [.047, .065], TLI = .933, CFI = .949,
and SRMR = .041. Cronbach's alpha of 5 scales between .776 and
.859, while the Cronbach’s alpha for the entire measure was .874. In the current study, the validity of the scale was
assessed.
Academic achievement,
commonly indicated by the grade point average (GPA), reflects the overall
academic performance of students and is often used to evaluate the impact of
educational practices. GPA is widely recognised as a strong indicator of student
success in higher education settings (Kim
et al., 2019). To
collect information on academic achievement, students were asked to self-report
their most recent GPA.
3.3. Data Analysis
This study began with a preliminary analysis of the
data, including descriptive statistics and intervariable correlations,
conducted using SPSS version 29. To test the proposed hypotheses, structural equation modelling (SEM) was employed to test the
proposed hypotheses. Before proceeding with SEM, it was essential to evaluate the validity and
reliability of the measurement instruments. Therefore, confirmatory factor
analysis (CFA) was used to assess the construct validity of the questionnaire.
In the SEM analysis, performed with SmartPLS version 4, several key model fit
indices were used to evaluate model adequacy. These included the Comparative
Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of
Approximation (RMSEA) and Standardised Root Mean Square Residual (SRMR). As recommended
in the literature, the acceptable fit is indicated by CFI and TLI values
greater than 0.90, RMSEA values below 0.05, and SRMR values ranging from 0 to
0.10 (Hu
& Bentler, 1999).
4. Analysis and results
4.1. Internal Consistency and Convergent Validity
The evaluation of the instrument's construct validity
in this study was conducted through a confirmatory factor analysis. Table 2
presents the results of the evaluation of the measurement model for the three
latent variables. Critical thinking
items showed loadings ranging from 0.755 to 0.861, with a Cronbach’s alpha of
0.785, indicating acceptable reliability and convergent validity. Creative thinking also
performs well, with loads between 0.646 and 0.815, a Cronbach’s alpha of 0.803,
suggesting that the construct is reliable and valid. Digital readiness
demonstrates excellent internal consistency, as reflected by a Cronbach alpha
of 0.835. The outer loadings range from 0.710 to 0.840, confirming good convergent validity. Average variance extracted (AVE)
reflects the proportion of variance that a latent variable captures relative to
variance due to measurement error, where higher values (above 0.5) signify
stronger convergent validity. In this study, the AVE values ranged from 0.536
to 0.630.
Table
2
Loading
Factors and Convergence Validity of the Variables
|
Latent Variables |
Outer loadings |
Cronbach's alpha |
Composite Reliability |
AVE |
|||
|
Critical
Thinking |
|
0.785 |
0.852 |
0.536 |
|||
|
|
Cri1 |
0.755 |
|
|
|
||
|
|
Cri2 |
0.785 |
|
|
|
||
|
|
Cri3 |
0.769 |
|
|
|
||
|
|
Cri4 |
0.861 |
|
|
|
||
|
|
Cri5 |
0.755 |
|
|
|
||
|
Creative
Thinking |
|
0.803 |
0.872 |
0.630 |
|||
|
|
Cre1 |
0.709 |
|
|
|
||
|
|
Cre2 |
0.773 |
|
|
|
||
|
|
Cre3 |
0.646 |
|
|
|
||
|
|
Cre4 |
0.815 |
|
|
|
||
|
Digital
Readiness |
|
0.835 |
0.884 |
0.604 |
|||
|
|
Dig1 |
0.710 |
|
|
|
||
|
|
Dig2 |
0.781 |
|
|
|
||
|
|
Dig3 |
0.840 |
|
|
|
||
|
|
Dig4 |
0.806 |
|
|
|
||
|
|
Dig5 |
0.741 |
|
|
|
||
4.2. Discriminant Validity
A discriminant validity test was performed to determine
whether latent factors are empirically distinct from each other. The
Heterotrait-Monotrait ratio (HTMT) method was used for this assessment,
following the recommendation by Henseler
et al. (2015). The
results, summarised in Table 3, showed values ranging from 0.521 to 0.864,
confirming discriminant validity since all values were below the 0.90
threshold.
Table
3
Discriminant
validity – Heterotrait Monotrait Ratio (HTMT)
|
AAC |
CRI |
CRE |
DIG |
|
|
Academic Achievement |
- |
|||
|
Creative Thinking |
0.521 |
- |
||
|
Critical Thinking |
0.544 |
0.864 |
- |
|
|
Digital Readiness |
0.752 |
0.757 |
0.764 |
- |
Note: AAC = Academic achievement;
CRI = Critical thinking; CRE = Creative thinking; DIG = Digital readiness
4.3. Descriptive statistics
Table 4 presents a statistical overview of the
variables examined in the study. Most of the students demonstrated moderate
academic achievement, with an average score of 3.29 (SD = 0.99). Critical
thinking scores averaged 3.22 (SD = 0.68) on a 5-point Likert scale. Similarly,
creative thinking and digital readiness showed mean scores of 3.18 (SD = 0.75)
and 3.27 (SD = 0.75), respectively. Regarding the data distribution, the skewness
values ranged between -0.07 and 0.17, and the kurtosis values ranged between
-0.37 and 0.58, both within acceptable limits of normality as suggested by Kline
(2015).
Table
4
Descriptive
statistics and normality of the variables.
|
Variables |
M |
SD |
Skewness |
Kurtosis |
|
Academic
achievement |
3.29 |
.99 |
-.03 |
-.37 |
|
Critical
thinking |
3.22 |
.68 |
.17 |
.58 |
|
Creative
thinking |
3.18 |
.75 |
.14 |
-.03 |
|
Digital
readiness |
3.27 |
.75 |
-.07 |
.25 |
4.4. SEM analysis
Structural equation modelling was used to test the
hypotheses of this study (see Fig. 2). The model fit indices were as follows:
Chi-square = 200.472, df = 56, p < .001, CFI = 0.936, TLI = 0.914, RMSEA =
0.08, and SRMR = 0.05. The
results indicate that the model fit meets the criteria, confirming its
suitability (Hu
& Bentler, 1999).
The determination coefficient indicated that academic
achievement was explained by critical thinking, creative thinking, and digital
readiness, explaining 47.5% of the variance
(R² = .475). Likewise, digital readiness was explained by critical and creative
thinking, accounting for 48.4% of its variance (R² = .484).
Regarding the structural paths, digital readiness
significantly predicted academic achievement (β = .623, p < .001).
However, critical thinking (β = .074, p > .05) and creative thinking
(β = .024, p > .05) did not significantly predict academic achievement
directly. Although the
coefficients were positive, they were small and not statistically significant, indicating
that critical thinking and creative thinking do not exert a direct effect on
academic achievement.
Table 5 presents the specific indirect effects based on
bootstrapping with 5,000 resamples. The results indicated that digital readiness significantly mediated the effects
of critical and creative thinking on academic achievement (β = .254, p
< .001), as well as between creative thinking and academic achievement
(β = .216, p < .001).
Table
5
The direct and indirect effect of the
variables.
|
Path |
Original sample (O) |
Sample mean (M) |
Standard deviation (STDEV) |
T statistics (|O/STDEV|) |
p |
|
CRE
-> AAC |
0.024 |
0.027 |
0.076 |
0.318 |
>.05 |
|
CRE
-> DIG |
0.347 |
0.347 |
0.063 |
5.537 |
<.001 |
|
CRI
-> AAC |
0.074 |
0.074 |
0.080 |
0.920 |
>.05 |
|
CRI
-> DIG |
0.408 |
0.411 |
0.058 |
7.041 |
<.001 |
|
DIG
-> AAC |
0.623 |
0.620 |
0.056 |
11.154 |
<.001 |
|
CRE
-> DIG -> AAC |
0.216 |
0.215 |
0.040 |
5.376 |
<.001 |
|
CRI
-> DIG -> AAC |
0.254 |
0.256 |
0.046 |
5.541 |
<.001 |
Figure
2
PLS-SEM model of digital readiness as
mediator.
Note: own elaboration.
5. Discussion
The structural model demonstrated an acceptable fit to
the data. However, RMSEA was 0.08, which is at the upper bound of commonly
accepted thresholds for reasonable fit (Browne,
1993; Hu & Bentler, 1999).
This suggests that while the model adequately represents the observed data, some minor misfit may exist; therefore, caution is
warranted when interpreting the structural relationships.
The results indicate a notable positive relationship
between digital readiness, critical thinking, and creative thinking, reinforcing the hypothesis that digital readiness,
critical thinking, and creative thinking collectively contribute to academic
achievement.
Although the direct effects of critical and creative thinking on academic performance
were positive, they were not statistically significant, suggesting that
these thinking skills influence academic outcomes indirectly, primarily through
digital readiness. This aligns with previous research showing no direct relationship
between critical and creative thinking and academic achievement (Shirazi
& Heidari, 2019; Syamiya et al., 2025).
According to Y.
Huang (2022),
digital readiness equips students with essential technology-related skills and
fosters an environment conducive to critical engagement and creative
problem-solving. Similarly, Kim
et al. (2019)
emphasise that students who are digitally competent engage more fully in their
learning, which can contribute to improved academic performance. Therefore,
fostering digital readiness is crucial to developing necessary technical skills
alongside critical and creative thinking abilities essential for success in an
increasingly digital world (Suherman
& Vidákovich, 2024b).
Furthermore, the interdependencies among critical
thinking, creative thinking, and digital readiness underscore the importance of
an educational curriculum that integrates technology with cognitive skill
development. Studies indicate that integrating digital tools can enhance
students' critical and creative thinking capacities, ultimately contributing to
improved academic outcomes (Bergdahl
et al., 2020).
This convergence of skills is particularly relevant in the educational
landscape of today and to
prepare students for the digital era, particularly in STEM education (Mujib
& Mardiyah, 2025), where
the demand for innovative problem-solving abilities is paramount. Although Wen
et al. focus on the impact of organisational digital readiness in the business
context (Jun
et al., 2022),
the analogy to educational institutions suggests that integrating digital readiness into teaching frameworks
may strengthen students’ academic performance (Komarudin
& Suherman, 2024).
Lastly, creating a supportive environment that
encourages digital readiness alongside critical and creative thinking is vital
to improving educational outcomes. Academic self-concept, as indicated by Marsh
(1992), plays
a significant role in academic achievement, suggesting that fostering students’ digital
self-efficacy may enhance their performance in critical and creative tasks (Farida
et al., 2024). By
integrating targeted training programs aimed at improving digital proficiency
and promoting critical and creative competencies, educators can empower
students to meet their academic expectations more effectively. Yang
et al. (2024)
indicate that the promotion of digital readiness is positively correlated with
higher levels of academic engagement, which may lead to elevated achievement
levels. Therefore, prioritizing the
enhancement of digital readiness alongside critical and creative thinking is
essential to prepare
students for the complexities of the modern educational and professional
landscape.
6. Conclusions
The findings of this study highlight the critical role
of digital readiness as a mediator between critical and creative thinking and
academic achievement, highlighting
the importance of educational frameworks that integrate technology and
cognitive skill development. As preservice students demonstrate increased digital
proficiency, their ability to engage in critical analysis and innovative problem
solving enhances their overall academic performance, aligning with previous
research that emphasises the interconnectedness of these skills. The
implications of these findings suggest that educational institutions should
prioritise the cultivation of digital readiness within curricula, thereby
equipping students with the competencies needed to excel in digital learning
environments. This
involves not only providing access to technology, but also implementing
instructional strategies that foster students’
critical and creative thinking skills. Emphasising these interconnected skills can
significantly contribute to preparing students for the demands of the modern
workforce, ultimately promoting their academic success and lifelong learning
capabilities.
7. Limitations and future research
The limitations of this study stem primarily from its
reliance on self-reported measures of digital readiness, critical thinking,
creative thinking, and academic achievement which may be subject to response bias and thus may not
fully reflect students’ actual abilities or experiences. Additionally, the
scope of the investigation was limited to a specific educational setting,
limiting the generalizability of the findings in diverse contexts and
educational environments. Future research should aim to expand the sample size
to include multiple institutions and employ a mixed method approach, integrating
qualitative data to complement quantitative findings, providing more nuanced
insights (da
Silva et al., 2021). Furthermore,
longitudinal studies could be beneficial to examine how digital readiness
evolves over time and impacts academic achievement, particularly in rapidly evolving educational
landscapes driven by technological advancements (Grijalva Salazar et al., 2023). Exploring
other factors, such as socioeconomic status (Suherman
& Vidákovich, 2024a) and
the specific elements of digital readiness that most significantly influence critical
and creative thinking would also aid in refining educational practices, enabling targeted interventions to strengthen these
competencies in students (Abd-Alrazaq et al., 2024).
Contributions
S.S.:
Conceptualization, Writing - Original Draft, Formal analysis, Methodology,
Editing, and Visualization. B.S.S.: Supervision, Funding acquisition, Writing –
review & editing. R.R.M.: Visualization, Review, and Editing. T.A.: Formal analysis,
Editing, and Visualization. I.P.A.: Editing and Visualization. V.H.K.:
Methodology and Editing.
Funding
This
work has not received any specific grants from funding agencies in the public,
commercial, or non-profit sectors.
Data
Availability Statement
Data
will be made available on request.
Ethics
approval
The institutional review board of Universitas Islam
Negeri Raden Intan Lampung granted the ethical clearance for the study,
according to the institutional ethics guidelines
Conflicts
of interest
There
are no conflicts of interest to declare.
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