DICIEMBRE, 2025 (176-196)Número 27
THE IMPACT OF CLASS TIME ON
ACADEMIC PERFORMANCE: MORE
HOURS, BETTER RESULTS?
EL IMPACTO DEL TIEMPO DE CLASES EN
EL RENDIMIENTO ESCOLAR: ¿MÁS HORAS,
MEJORES RESULTADOS?
DOI: https://doi.org/10.37135/chk.002.27.09
Research article
Received: (22/01/2025)
Accepted: (22/04/2025)
1Universidad Nacional de Chimborazo, Ciencias de la Educación, Humanas y
Tecnologías, Riobamba, Ecuador, email: alejandro.guato@unach.edu.ec
2Universidad Nacional de Chimborazo, Ciencias de la Educación, Humanas y
Tecnologías, Riobamba, Ecuador, email: yajaira.valdiviezo@unach.edu.ec
3Universidad Nacional de Chimborazo, Ciencias de la Educación, Humanas y
Tecnologías, Riobamba, Ecuador, email: cvarguillas@unach.edu.ec
Alejandro David Guato Valarezo1,
Yajaira Lizbeth Valdiviezo Valdiviezo2,
Carmen Siavil Varguillas Carmona3
Alejandro David Guato Valarezo, Yajaira Lizbeth Valdiviezo Valdiviezo, Carmen Siavil Varguillas Carmona
CHAKIÑAN. Revista de Ciencias Sociales y Humanidades / ISSN 2550 - 6722
177
The present article analyzes the relationship between class time dedicated to Physics and
school performance in students of 1st Unied General High School (1BGU) in Ecuadorian
institutions, the objective was to determine the signicant correlation between class time
and grade point average, as well as the dispersion of these grades. A quantitative approach
was adopted, with a non-experimental and cross-sectional design. Data were obtained from
educational institutions with dierent types of support and time load in Physics, having a
sample composed of ve institutions selected by a non-probabilistic sample by convenience.
The data obtained were analyzed by means of a parametric statistical test using Pearson’s
bivariate correlation to determine the relationship between class time and performance
variables. The results indicate a strong and signicant negative correlation between time and
dispersion, but a positive correlation with reduced signicance between time and averages,
which leads to the conclusion that class time contributes to school performance, although it
is not the only determining factor.
KEYWORDS: Education, performance, society
El presente artículo analiza la relación entre tiempo de clase dedicado a la materia de Física
y el rendimiento escolar en estudiantes de 1ro Bachillerato General Unicado (1BGU)
en instituciones ecuatorianas, el objetivo fue determinar la correlación signicativa entre
tiempo de clase y el promedio de calicaciones, así como su dispersión. Se adoptó un
enfoque cuantitativo, con un diseño no experimental y transversal. Se obtuvieron datos de
instituciones educativas con diferencias tipos de sostenimiento y carga horaria en la materia
de Física, teniendo una muestra compuesta por cinco instituciones seleccionadas por un
muestro no probabilístico por conveniencia. Los datos obtenidos se analizaron mediante
una prueba estadística paramétrica mediante la correlación bivariada de Pearson para
determinar la relación entre tiempo de clase y las variables de rendimiento. Los resultados
indican una correlación negativa fuerte y signicativa entre tiempo y dispersión, pero una
correlación positiva con signicancia reducida entre tiempo y promedios, lo que permite
concluir que el tiempo de clase aporta al rendimiento escolar, aunque no es el único factor
determinante.
PALABRAS CLAVE: Educación, rendimiento, sociedad
ABSTRACT
RESUMEN
THE IMPACT OF CLASS TIME ON ACADEMIC
PERFORMANCE: MORE HOURS, BETTER
RESULTS?
EL IMPACTO DEL TIEMPO DE CLASES EN
EL RENDIMIENTO ESCOLAR: ¿MÁS HORAS,
MEJORES RESULTADOS?
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INTRODUCTION
In developed countries, especially in Europe and Asia, the time load in
their educational systems is slightly less than in our country. However,
their academic performance is superior to ours, even though they dedicate
less time to teaching in direct contact between teacher and student. In
Ecuador, the teaching load of physics in high school has been reduced.
This reduction in the weekly time devoted to the subject generates
uncertainty as to its impact on students’ academic performance, which
could prevent the implementation of optimal educational practices
that ensure an adequate balance between academic load and student
performance.
One of the theoretical bases of the topic of study is school performance.
In the words of Gil and Monroy (2019), school performance is dened
as “a system of achievements, which builds knowledge through
educational didactic interventions and that these are evaluated through
qualitative and quantitative methods in a subject, whose objectivity
is based on grade evaluation” (p. 68). However, Lamas (2015) notes
that a dierentiation of terms for performance should be created, being
academic performance an exclusive term for higher education and
school performance for when it is handled within basic education.
As is well known, education is one of the most important aspects in the
world, which is why it is one of the main focuses of economic investment
by dierent countries. However, in its human nature, education is a
process of constant change and evolution. “The educational landscape
in the world has achieved progress with respect to educational quality in
recent years, but there is still a strong lag that prevents its achievement”
(Rubiano & Martínez, 2024, p. 5249), due to this, it is necessary to
understand the relationship that could exist between the time allocated
to the teaching of a subject and the performance reected in students.
In this sense, Colomo et al. (2016) presents the fact that more hours of
instruction do not guarantee better academic performance, mentioning
the cases of Finland and Austria that have better results compared to
those countries that dedicate more time than them to classes in direct
contact.
In addition, Gaeta and Cavazos (2016) examine the relationship between
study time, self-regulation of learning and academic performance of
university students, nding that students with better performance
dedicate more time to study through self-regulation strategies.
Alejandro David Guato Valarezo, Yajaira Lizbeth Valdiviezo Valdiviezo, Carmen Siavil Varguillas Carmona
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At the Ecuadorian level, it is essential to understand what students’
school performance depends on, since, based on this knowledge,
improvements can be made to the education system. Villaruel et al.
(2020) identies the factors that aect the school performance of high
school students in Ecuador taking as a source of study the results of
the Ser Bachiller exam in the 2016-2017 period, which allowed him to
determine some key factors to explain academic performance.
Asencios et al. (2024) mention the following: “In recent years, the
prediction and analysis of student performance has become an area of
growing interest to researchers and educators, with the goal of better
understanding the factors that contribute to academic success or failure”
(p. 118).
Therefore, when considering this perspective, it is essential to
understand whether there is a relationship between class time and
school performance, and if not, to nd the factors that could have a
greater impact on student performance.
Based on this, the following questions are posed:
Is there a signicant correlation between class time per week and
students’ partial evaluation average?
Is there a signicant correlation between class time per week and the
dispersion in students’ partial evaluation?
METHODOLOGY
The methodological framework was based on the positivist paradigm,
with a quantitative approach and a non-experimental design, the latter
understood as a typology in which variables are not manipulated in
any way (Chacma-Lara & Laura-Chávez, 2021). The selection of this
approach is based on what was established by Hernández Sampieri et
al. (2014), who emphasize that this type of study allows the observation
and analysis of variables without the need to intervene directly on
them. The study was a cross-sectional documentary study, in addition
to the descriptive analytical intention due to the fact that a multivariate
analysis was performed throughout the statistical process.
To structure the research process, the methodological model proposed
by Creswell and Creswell (2018) was adopted, who state that all
quantitative research must follow a structured sequence to ensure the
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validity and reliability of the results. In this sense, the following was
complied with: analysis of academic sources and previous studies that
address the relationship between class time and school performance,
in order to delimit the problem and formulate the research objectives;
identication of the study variables; selection of the institutions, which
was given for convenience, in attention to the willingness to support
by providing relevant data for the study, considering educational
centers with dierent hourly loads in the administration of the subject
of Physics, with class hours between 2 and 4, with each hour being
40 or 45 minutes depending on the institution; creation of a broader
study scenario by examining public, scomisional (public-private)
and private institutions; determination of the units of analysis, which
was composed of all subject grades of students enrolled in 1BGU in
the selected educational institutions, during the school year analyzed
(Creswell and Creswell, 2018).
The selection of the data was by criterion, based on a set of conditions
for their inclusion: belonging to the rst year of high school, taking
the subject of interest and having the corresponding grade record. The
selected data corresponds to all the available grades of the students in the
rst year of high school in the subject of Physics during the rst partial
of the 2024-2025 school year. This approach ensures that the selection is
representative of all accessible data, according to the available records
(Martínez-Corona et al., 2023). Due to ethical principles, the names of
the institutions and the identity of the students are kept anonymous.
Data analysis: a statistical analysis was performed using a normality
test with the Shapiro-Wilk test and the application of Pearson’s
bivariate correlation to examine the relationship between class time
and performance variables, for which the SPSS 30.0.0.0.0 program was
used. The studies of Villaruel et al. (2020) and Asencios et al. (2024),
who used similar designs to analyze the impact of dierent variables
on academic achievement, were used as a reference for this type of
analysis. Finally, the ndings were interpreted and compared with
previous studies on the inuence of instructional time on academic
achievement, highlighting similarities and dierences with other
educational contexts.
RESULTS AND DISCUSSION
Once the ratings for each of the institutions were obtained, key statistical
data were obtained for the respective analysis through the average of the
partial evaluation, the standard deviation of each group and the time of
dedication; the results obtained from these units of analysis are shown
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in Table 1.
Table 1: Units of analysis by educational institution
Using the data obtained, we sought to determine the relationship between
class time (independent variable) and school performance, measured
by the average evaluation and the deviation of partial evaluations
(dependent variables).
Using the SPSS 30.0.0.0.0 program, the normality test of the variables
was calculated to determine the method to be used to determine the
relationship between class time and school performance. The results of
the application of the normality test for the partial evaluation average
variable are presented in Table 2, and the results for the partial evaluation
deviation variable in Table 3.
Table 2: Normality test with the average of the partial evaluation.
Table 3: Normality test with the deviation of the partial evaluation.
Being a sample with ve data, the signicance considered was obtained
within the Shapiro-Wilk test, since this test is used for samples with fty
or less data. Analyzing what Luzuriaga et al. (2023) mentioned, since
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the signicance values are greater than 0.05, then there is not enough
evidence to arm that the data of both variables deviate signicantly
from a normal distribution.
In this case, a parametric statistical method should be used, being
Pearson’s bivariate correlation the indicated one due to the small sample
size. Fiallos (2021) denes this method as “Pearson’s coecient (also
called the product-moment correlation coecient), is represented by the
symbol r and provides a numerical measure of the correlation between
two quantitative variables” (p. 2495).
RELATIONSHIP BETWEEN CLASS TIME AND
PARTIAL EVALUATION AVERAGES
When analyzing the variables class time and partial evaluation averages,
the results shown in Table 4 are obtained.
Table 4: Pearson’s correlation between class time and partial
evaluation performance
When analyzing the relationship between class time and partial
evaluation averages, the Pearson correlation model yields a result of
0.700, indicating a moderate positive relationship. This value indicates
the possibility that, as class time increases, the results of the partial
evaluation should have an increasing trend. However, since the value
obtained is far from the maximum that determines a strong positive
relationship (1), it means that this parameter is not sucient to determine
a signicant relationship between the variables.
The signicance value is 0.188, which is far from the generally accepted
typical value (α = 0.05), implying that there is not enough evidence to
arm the correlation mentioned above. However, the main cause of
this value is the sample size (N = 3), which was small in scope due to
the private and sensitive nature of the information obtained for data
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analysis, in addition to the fact that priority was given to obtaining data
with educational institutions that do not occupy the same amount of
time dedicated to the subject, so that all possible dierent options were
covered.
RELATIONSHIP BETWEEN CLASS TIME AND
DISPERSION IN PARTIAL ASSESSMENT
Table 5 shows the results of the Pearson correlation analysis of the
variables class time and dispersion in the partial evaluation.
Table 5: Pearson correlation between class time and dispersion of
partial evaluation
The analysis between class time and the dispersion of partial evaluation
yields a Pearson correlation coecient of -0.991. This value reveals a
very strong negative relationship by largely approaching the lower limit
of the range of values that can be taken by the coecient used (-1).
This indicates that as the time devoted to teaching the subject increases,
the dispersion in the results of the partial evaluation tends to decrease
almost to perfection.
As for the signicance value, the value obtained was less than 0.001,
which is not only within the generally accepted margin, but has a value
incredibly close to 0, which shows that this result has extreme and
precise validity, favoring the idea that there is a relationship between
the two variables considered at this point.
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OVERALL COMPARISON OF CASES AND
SIGNIFICANCE OF CORRELATION
Comparing the time dedicated to classes and the evaluation averages,
the descriptive results of the institutions reect interesting patterns. In
the public institution, students have a low performance average (7.10),
considering that this group also presents the shortest class time, with
only 80 minutes. On the other hand, another institution also of a public
nature shows the best average performance (9.00) with a slightly longer
class time (120 minutes). Finally, in the private institution, students
have an average of 8.20, slightly higher than the group with the least
time spent, despite having the longest class time, with 160 minutes, and
still having a distance on average from the one with the best.
The results obtained in the Pearson correlation analysis revealed a
strong negative relationship between class time and the dispersion of
partial evaluations (r = -0.991). This nding suggests that, as the time
devoted to teaching increases, student grades tend to be more uniform,
which can be interpreted as a greater degree of equity in learning. The
statistically signicant relationship (p < 0.001) incorporates
the idea that this homogeneity is not random but is directly associated
with the duration of class sessions, allowing students a more uniform
understanding of the content addressed.
On the other hand, the moderate positive correlation between class
time and average performance on evaluations (r = 0.700) did not reach
statistical signicance (p = 0.188). This indicates that, although there is
a tendency for students to perform better on assessments when classes
are longer, this relationship is not consistent enough to be considered
signicant within this analysis. This result could be attributed to
the inuence of other uncontrolled variables, such as the quality of
instruction, student motivation, or even the design of the assessments.
From these ndings we infer that there is a relationship between class
time and school performance. However, it is not strong or consistent
enough to be statistically signicant in the context studied. Furthermore,
it is interpreted that, although class time is an important factor, it is not
suciently predicted of school performance. This highlights the need
to explore other variables that could inuence the results, such as the
pedagogical strategies employed by teachers and the conditions of the
dierent educational institutions.
Given the above, the combination of the results allows us to infer that
class time has a stronger eect on the contraction of learning inequalities
than the direct increase in average achievement. Previous reasoning and
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evidence have pointed out how prolonged instruction can create more
space for weaker students to reinforce concepts and explore doubts.
The correlation analysis between class time and the dispersion of partial
assessment scores shows that extending the time dedicated to teaching a
subject benets individual learning and promotes greater homogeneity
in students’ school results. This is interpreted as a better distribution
of performance, where students, regardless of their initial levels of
understanding, seem to benet from longer teaching times. This nding
is relevant, as it reinforces the importance of designing school schedules
that allow adequate time for the deepening of the topics addressed.
EDUCATIONAL IMPLICATIONS
The study provides signicant elements for the design and planning of
school timetables. The correlation between class time and performance
in partial evaluations implies that increasing class time could increase
academic performance, at least in those subjects where it is necessary
to go more deeply into the explanation of concepts or problem solving.
“Time spent in dierent time slots does tend to intervene directly
in academic performance” (Amo et al., 2023, p. 44). This nding
underscores the need to reevaluate traditional time blocks and formats
that facilitate slower, more reective learning should be adjusted.
The negative relationship identied between class time and grade
dispersion suggests that longer classes favor greater homogeneity in
learning, closing the gaps between students with dierent abilities. This
fact could be interpreted as a benecial eect of extended classes, as it
gives teachers the opportunity to provide more personalized, step-by-
step attention and reinforce tutoring.
In this sense, implementing longer sessions can be a decisive strategy to
address educational equity and ensure that the most backward students
are not left behind. “The results found highlight how attendance to face-
to-face classes, both theoretical and practical, play a relevant role in
passing the subject under study” (Rodríguez & Herrera, 2009, p. 9).
The ndings also have practical implications for curriculum design.
Schools could consider the reorganization of teaching according to
the needs of less or more interaction in the subject. Santillán (2021)
mentions that the lack of didactic activities that stimulate students’
active participation may also aect student performance. In general,
a more ecient distribution of class time could maximize student
performance and enrich the interactive experience for all students.
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STATISTICAL SIGNIFICANCE AND LIMITATIONS OF
THE STUDY
The statistical results, even with all sample limits, indicate key
relationships, specically, a strong negative correlation between
class time and standard deviation in partial evaluations (r = -0.991)
with an extremely high signicance (p < 0.001), suggesting that such
dependence is not random. It is possible, therefore, to validate the
statistical model and demonstrate that the time allocated to classes is
a relevant educational planning factor to achieve more homogeneous
grades among students.
On the other hand, although the positive correlation between class time
and average nal performance in partial evaluations is moderate (r =
0.700), it was not extremely signicant (p = 0.188), which represents
a limitation with respect to being able to arm that the relationship
between these two variables is consistent.
In this case, the reduced value of the reliability is due to the nature of
the Pearson correlation with the presence of repeated data in one of the
analysis variables, and increasing the sample of cases with hourly loads
equal to those already presented does not ensure that the signicance is
improved.
The statistical signicance in this study highlights the importance of
modifying statistical designs according to the needs of the analysis. The
(p) values and correlation coecients are useful for identifying patterns,
however, they should not be isolated. Signicant ndings, such as the
relationship between class time and dispersion, open the door to further
exploration, while less conclusive results, such as the relationship with
overall average, highlight the need for more detailed and contextualized
future analysis.
As for the limitations of the study, sample size is the main limitation of
this article, since we have worked with data from only ve university
institutions. Although the heterogeneity of the class schedules taught
was taken into consideration to ensure the representativeness of the
analysis, the number of observations is small and, therefore, it is not
possible to generalize the results to other institutional contexts.
A larger sample would have made it possible to obtain statistically
more solid relationships, with less sensitivity to individual variations
and, consequently, a reduction in the probability that the correlations
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reported are random.
Another important limitation is related to the nature of the variables
analyzed, in view of the dependence of reported data and institutions on
class times and partial evaluations. There could be uncontrolled factors
inuencing the results, including the quality of teaching, the pedagogical
strategies used by teachers, or the level of student motivation, allowing
for potential biases. The lack of direct control over such variables
may have restricted the ability to isolate the eects of class time on
performance outcomes.
Additionally, another shortcoming of the study is the absence of a
qualitative analysis of the use of time during classes and the pedagogical
approach of teachers. Based on the quantitative data collected, it is
impossible to determine whether extended time in the classroom allows
for a more participatory and student-centered educational process,
making it impossible to conrm whether time is used in a meaningful
way or simply constitutes a traditional practice of little benet to the
student.
The study also does not evaluate the levels of depth of learning achieved
by the students, which makes it impossible to create a generalization. As
mentioned above, the variables make it possible to create performance
quantication indicators but make it impossible to know whether
learning is subject to traditionalist teaching based on rote learning or to
adequate contemporary teaching based on understanding, application
and criticality. This is a considerable limitation for evaluating the real
quality of learning in the central subject of this study.
The selection of educational institutions for the development of the
study may also have generated small conicts in obtaining results.
Dierences in resources, educational approaches, and socioeconomic
characteristics of the participating institutions may have caused an
impact on the results, creating diculties in the overall interpretation
of the ndings. “Nevertheless, the results obtained in said contingency
analysis alone do not provide sucient arguments to denote whether
or not the predictive variables contemplated are independent of subject
overcoming” (Rodríguez & Herrera, 2009, p. 5).
RELATIONSHIP WITH THEORETICAL MODELS
The results of this study can be interpreted through Carroll (1963)
learning model, which establishes that academic achievement is a
direct function of the time dedicated to learning and an inverse function
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of the time required to master a content. In this sense, Cervini (2001)
mentions that the opportunity to learn is located precisely in this space
of inuence, reecting not only the initial conditions of the students,
but also the pedagogical practices and school resources available.
According to Carroll model, students who have more time available
for instruction tend to have better opportunities to achieve learning
objectives, which is consistent with the observed relationship between
class time and decreased dispersion in midterm assessment scores. This
reinforces the idea that time is a critical factor in equalizing learning
opportunities within a heterogeneous group of students.
From the point of view of constructivism, the meaningful learning
proposed by Ausubel (1963) also supports the ndings obtained.
This approach emphasizes that learning occurs most eectively when
students can connect new knowledge with their pre-existing cognitive
structure, a process that requires time and reection.
Zamora et al. (2023) mentions “meaningful learning diers from rote
learning, as it focuses on deep and critical understanding of concepts
and their application in real situations” (p. 224). Increasing class time,
in this context, could not only facilitate the acquisition of new concepts,
but could also allow students to consolidate and relate information in
a deeper way, thus reducing dierences in their understanding and
performance.
Furthermore, the relationship between class time and homogeneity in
results can be associated with Bronfenbrenner’s (1979) ecological model,
which highlights how contextual factors, such as time organization and
educational resources, inuence student development. Romero (2023)
mentions the following:
School space and school time are not independent factors but
are interconnected. For example, the arrangement of furniture in
the classroom can aect the amount of time the teacher spends
explaining and the amount of time the student has to work in
groups or alone (p. 122).
In this framework, longer classes can provide a more favorable
environment for learning, where students have the necessary time to
interact with teachers, participate in meaningful activities and clarify
doubts. Razo (2016) mentions, “School time is important, but taking
advantage of it is essential” (p. 635). This underscores the importance
of considering time as a key resource in the design of pedagogical
strategies that promote both equity and educational quality.
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SUGGESTIONS FOR EDUCATIONAL POLICIES
To optimize the impact of class time on academic performance, it is
suggested that educational policies encourage a comprehensive review
of school schedules. This involves not only extending the length of
classes in key subjects but also ensuring that this additional time is
used eectively. “The extension and better use of school time is one
of the most important changes aecting the pedagogical culture and
management of schools” (Martinic, 2015, p. 482).
Strategies could include the design of more exible curricula that
prioritize depth over quantity of content, allowing teachers to devote
more time to activities that promote meaningful learning, such
as critical analysis, problem solving and practical application of
knowledge. Regarding this, Mello & Hernández (2019) mention that
“it is recommended to evaluate the national curriculum design for the
Mathematics area from its capacity to intervene in dierent facets, from
cognitive competencies to attitudes, well-being and inclination towards
student learning” (p. 9).
An important point to implement eective policies is the investment in
resources and the improvement of school conditions. Ensuring adequate
infrastructure, access to quality teaching materials, and inclusive and
well-equipped learning environments is essential for optimal use of
class time.
In addition, an optimal space plays an important role in the student’s
perception of their learning process, as Quesada (2018) mentions, “a
comfortable and positive environment must then be created where the
student wants to spend almost a third of the day to learn and share
with all the agents involved in the educational environment” (p. 6).
These improvements should also include strengthening communication
and collaboration between teachers, students, and families, fostering
a community approach that supports learning inside and outside the
classroom.
Along the same lines, it is recommended that educational policies
consider the continuous evaluation of the reforms implemented, using
clear indicators such as academic performance, student participation
and equity in results. These evaluations should include feedback from
teachers and students to adjust strategies according to emerging needs.
Villamizar et al. (2020) mentions that evaluations should not be massive
or decontextualized, but should be formative, continuous and varied
with the purpose of evaluating the student and not the educational
system.
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In this way, policies will not only ensure the eectiveness of class
time but also contribute to the development of more adaptive and
resilient education systems in the face of changing societal challenges.
Homework also plays a key role, as Liu et al. (2023) found that spending
extra time on homework in a subject can improve school performance,
especially for low-achieving students.
IMPACT OF OTHER FACTORS ON SCHOOL
PERFORMANCE
Although the parametric method of Pearson’s correlation showed a
moderate positive correlation (r = 0.7) between class time and evaluation
average, the lack of statistical signicance (p = 0.188) suggests that
other factors may play a more decisive role in school achievement. As
Razo (2016) mentions, “more time in school will not imply increased
achievement in students if it is not used in meaningful learning
experiences and quality interactions between students and teachers” (p.
626).
From the very nature of the concept of achievement, Gonzales (1988)
mentions that school achievement is directly related to the concept of
education and its foundation in broader psycho-pedagogical, ideological
and social models. These elements can amplify or reduce the impact of
teaching time on average student achievement.
The role of the teacher is a critical factor in improving performance.
Teachers with active and student-centered strategies tend to maximize
class time, providing opportunities for meaningful learning and the
development of applicable skills. Gabalán and Vásquez (2017) mention
“perhaps we teachers must guarantee learning environments that make
each academic encounter a unique and unrepeatable experience” (p.
23).
However, when classes focus solely on the transmission of information,
the positive impact of the additional time is diluted. This fact could
explain why, although a positive trend in the correlation was observed,
a statistically signicant relationship was not reached. Another point of
view may be that of Liu (2022), which mentions “academic performance
does not need to impose more requirements on the amount of study
time, and the main point is to improve learning skills” (p. 414).
Under the above perception, the focus for the improvement of the
educational system would not be the increase of hours in direct contact
Alejandro David Guato Valarezo, Yajaira Lizbeth Valdiviezo Valdiviezo, Carmen Siavil Varguillas Carmona
CHAKIÑAN. Revista de Ciencias Sociales y Humanidades / ISSN 2550 - 6722
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with the teacher, but the adequate teaching of skills that allow the
student to learn independently of class time. Even Wagner et al. (2021)
initially proposed the idea that the time of day has more impact than
class time itself but found that there is no such impact and that it is the
teacher who really aects performance.
Another key element is the design of assessments. While additional
teaching time may provide more opportunities to practice and deepen
content, the type of assessment used has an important weight on school
averages. Carriazo et al. (2020) considers that “the educational planning
process has to encompass all levels of the organization, to carry out
the teaching and learning process in an ecient and eective way that
allows achieving quality education” (p. 91).
This underscores the importance of a comprehensive educational
strategy that encompasses both the content and context of assessments.
Assessments that prioritize memorization rather than critical analysis
or practical application of knowledge may limit the true reection of
student learning, regardless of the time spent on instruction.
The personal factor also occupies an important pillar in student
performance. Borja et al. (2021) denes personal factors as “fundamental
elements in academic performance, as students’ aptitudes, attitudes,
motivation and expectations can signicantly inuence their academic
results” (p. 56).
CONCLUSIONS
The study of how class length impacts academic performance within
the Ecuadorian educational environment has uncovered two main
ndings. Initially, there is a robust and statistically signicant inverse
relationship between class length and variance in outcomes, indicating
that longer instruction generally produces more consistent results. This
suggests an advantage for educational equity, as low-achieving students
may gain more opportunities to reinforce learning in extended class
periods.
However, the moderate link between class hours and habitual
performance was not statistically notable. Consequently, it cannot be
inferred that extended periods are associated with superior outcomes.
This underscores the complex nature of academic achievement, shaped
by numerous interconnected elements beyond the length of class hours.
The study did not address the teaching methodologies implemented
during classroom sessions. Subsequently, it is not specied whether
THE IMPACT OF CLASS TIME ON ACADEMIC PERFORMANCE: MORE HOURS, BETTER RESULTS?
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supplemental time is allocated for contemporary learning or traditional
education. The study did not incorporate measures to assess depth
of learning, such as critical thinking skills, problem-solving skills,
or understanding of conceptual frameworks. Therefore, no denitive
statements can be made about the quality or signicance of the learning
that took place.
The results indicate the need for educational planning that focuses not
only on the length of instruction but also on the pedagogical approaches
adopted by teachers. To improve productivity in education and ensure
that the time allotted is used eectively, it is essential to implement
teaching strategies that promote deep, meaningful, and equitable
learning experiences.
Finally, the data infers that teaching time does not allow for an increase
in the maximum score but rather allows for a smaller dierence in the
score between students. This reinforces the idea that time is necessary
but not sucient for equity in learning. The obstacle is to ensure that
the additional time is complemented by adequate and non-traditional
teaching, properly structured feedback and strategies to respond to the
whole group of students.
DECLARATION OF CONFLICTS OF INTEREST: The authors
declare that they have no conicts of interest.
AUTHORS’ CONTRIBUTION STATEMENT AND
ACKNOWLEDGMENTS: The contribution of each author is
mentioned below, in correspondence with their participation, using the
CRediT Taxonomy.
- Alejandro David Guato Valarezo: Principal author,
Conceptualization, Formal analysis, Research, Methodology,
Resources, Writing - original draft, Drafting.
- Yajaira Lizbeth Valdiviezo Valdiviezo: Formal analysis, Research,
Methodology, Resources.
- Carmen Siavil Varguillas Carmona: Methodology, Validation,
Visualization, Writing and Academic Writing.
The authors are grateful for the support provided by the dierent
educational institutions that provided the information required for the
development of research.
STATEMENT OF DATA AVAILABILITY: The authors declare that
the data used in the study were provided by educational institutions
Alejandro David Guato Valarezo, Yajaira Lizbeth Valdiviezo Valdiviezo, Carmen Siavil Varguillas Carmona
CHAKIÑAN. Revista de Ciencias Sociales y Humanidades / ISSN 2550 - 6722
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under conditions of anonymity, guaranteeing the condentiality of the
information. Due to this restriction, the data is not publicly available.
However, for any further verication or consultation, please contact the
authors of the study, who will be able to provide guidance on access to
the information within the relevant ethical and legal guidelines.
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