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Article |
Uso del aprendizaje móvil para la enseñanza y análisis
de medidas de tendencia central en datos agrupados
Axel Jefferson Córdova López[*]
Nelly Maricela Crespata
Barriga*
Pedro Enrique Zambrano Murillo*
Tannia Gabriela Acosta Chávez*
Abstract
This article presents a quasi-experimental study on
the integration of mobile technologies in teaching measures of central tendency
for grouped data to third-year high school students at a public educational
institution in Guayaquil, Ecuador. The objective was to evaluate the impact of
m-learning (mobile learning) as a pedagogical tool in the understanding and
analysis of statistical concepts. Two groups were involved: an experimental
group, which used mobile devices to access content and interactive exercises,
and a control group, which did not use this technology. The results show a
significant improvement in the academic performance of the experimental group,
with a notable increase in their ability to interpret and calculate measures of
central tendency. These findings suggest that incorporating mobile learning not
only facilitates access to educational resources but also contributes to the
development of analytical and mathematical skills in a more dynamic and
accessible environment. It is concluded that m-learning can be an effective
strategy for modernizing the teaching of statistics in the current educational
context.
Keywords: M-learning, Measures of central tendency, Teaching
statistics, Grouped data, Educational technology.
Resumen
Este
artículo presenta un estudio cuasi-experimental sobre la integración de
tecnologías móviles en la enseñanza de las medidas de tendencia central para
datos agrupados en estudiantes de tercer año de bachillerato en una unidad
educativa pública de Guayaquil, Ecuador. El objetivo fue evaluar el impacto del
m-learning (aprendizaje móvil) como herramienta
pedagógica en la comprensión y análisis de conceptos estadísticos. Se trabajó
con dos grupos: uno experimental, que utilizó dispositivos móviles para acceder
a contenidos y ejercicios interactivos, y un grupo de control, que no empleó
esta tecnología. Los resultados muestran una mejora significativa en el
rendimiento académico del grupo experimental, con un incremento notable en la
capacidad de interpretar y calcular las medidas de tendencia central. Estos
hallazgos sugieren que la incorporación del aprendizaje móvil no solo facilita
el acceso a recursos educativos, sino que también contribuye al desarrollo de
habilidades analíticas y matemáticas en un entorno más dinámico y accesible. Se
concluye que el m-learning puede ser una estrategia
efectiva para modernizar la enseñanza de la estadística en el contexto
educativo actual.
Palabras
Clave: M-learning, Medidas de tendencia central, Enseñanza de la
estadística, Datos agrupados, Tecnología educativa.
Introduction
The advance of technology has transformed various
aspects of society, including education. Among the most recent innovations is
m-learning (mobile learning), a methodology that uses mobile devices such as smartphones
and tablets to facilitate the teaching-learning process. This approach has
proven to be particularly effective in teaching complex concepts, such as
measures of central tendency for grouped data in the area of statistics.
M-learning has positioned itself as an important
tool that provides flexibility and accessibility to educational resources.
According to Crompton and Burke (2018), mobile learning allows students to
access educational content anytime and anywhere, which favors the
personalization of the learning process. In addition, recent studies have shown
that the use of mobile devices can improve academic performance in various
disciplines, including mathematics (Sung, Chang & Liu, 2016).
In Ecuador, the use of mobile technologies in the
classroom is still limited, but presents enormous potential to improve the
teaching of mathematics and other sciences. In this context, the present
research focuses on evaluating the effectiveness of m-learning in the
calculation and interpretation of measures of central tendency, with the
objective of determining whether the integration of this technology can improve
students' academic performance and foster a greater understanding of
statistical concepts.
This study was carried out with third year high
school students of the Vicente Rocafuerte Fiscal Educational Unit, using a
quasi-experimental design that included a control group and an experimental
group. Through the implementation of interactive content and activities
accessible from mobile devices, the experimental group had the opportunity to
explore the concepts in a more dynamic way, while the control group received
traditional teaching.
Several studies have supported the effectiveness of
m-learning in improving academic performance and concept retention. For
example, Sung, Chang, and Liu (2016) found that mobile devices promote more
active and engaged learning, especially in complex areas such as mathematics
and statistics. Similarly, Barreno and Guevara (2022) conclude that the use of
mobile applications in mathematics teaching not only improves the understanding
of topics, but also increases students' motivation.
In summary, this study seeks to contribute to the
debate on the feasibility and effectiveness of m-learning in secondary
education, with a particular focus on the teaching of statistics. The results
not only provide empirical evidence on the impact of mobile learning on
academic achievement, but also provide a basis for future research and the
implementation of educational policies that promote technological integration
in the classroom.
Materials and methods
This study adopted a quasi-experimental approach to
evaluate the impact of m-learning on the learning of measures of central
tendency for grouped data in third year high school students of the Unidad Educativa Fiscal Vicente Rocafuerte. An experiment was
designed with two groups of students: an experimental group, which used mobile
devices as a learning tool, and a control group, which received traditional
instruction without the use of mobile technology.
Study design: The quasi-experimental design
allowed comparing the results between the two groups. The experimental group,
composed of 40 students, used mobile devices (mainly smartphones) to access a
series of educational resources, including interactive simulations, hands-on
exercises, and tutorials related to measures of central tendency for grouped
data. The control group, also composed of 40 students, followed traditional
instruction with textbooks and paper assignments.
Participants: The study participants were 80
third-year high school students from Unidad Educativa
Vicente Rocafuerte in Guayaquil, Ecuador. The students were selected
intentionally, considering those with regular access to mobile devices and
Internet connection. The inclusion criterion was that students had previous
experience in the use of mobile devices and were familiar with the basic
management of educational applications.
Instruments: To measure the impact of
m-learning on learning measures of central tendency, the following instruments
were used:
·
Prior
knowledge questionnaire: a test administered before the intervention to assess
the initial level of understanding of measures of central tendency in both
groups.
·
Mobile
applications: The experimental group used educational applications that
provided interactive simulations, statistical calculators and exercises on
measures of central tendency. Applications such as GeoGebra and Khan Academy
were used as part of the m-learning.
·
Post-intervention
evaluation questionnaire: The same questionnaire applied at the beginning was
used at the end of the intervention to assess the level of learning achieved by
both groups.
·
Perception
survey: Students in the experimental group answered a survey to measure their
satisfaction and perception of the use of m-learning as an educational tool.
Procedure: The study was conducted in three phases:
· Phase 1: Initial assessment. A diagnostic
questionnaire was administered to both groups to measure prior knowledge about
measures of central tendency for grouped data.
· Phase 2: Intervention. The experimental group
used mobile devices for a period of four weeks, performing activities that
included simulations, interactive exercises and self-assessments. On the other
hand, the control group followed traditional classes without the use of mobile
technology.
· Phase
3: Final evaluation. At the end of the intervention, the evaluation
questionnaire was reapplied to both groups to compare the results.
Additionally, the experimental group completed a perception survey about their
experience with m-learning.
Data analysis: Data were analyzed using descriptive and inferential
statistics. Means and standard deviations were calculated for both groups'
scores on the pre- and post-intervention assessments. To determine if
significant differences existed between the groups, a t-test for independent
samples was performed. Cronbach's alpha was also applied to measure the
reliability of the questionnaire used.
Results
The results of this study show a significant
difference in academic performance between the experimental group, which used
m-learning, and the control group, which followed a traditional approach. The
following are the findings obtained after the intervention.
Comparison of performance between the experimental
group and the control group: Before the intervention, both groups showed
similar academic performance in the baseline assessment on measures of central
tendency for pooled data. The mean score on the diagnostic questionnaire was
5.4 out of 10 for the experimental group and 5.3 for the control group, with no
statistically significant differences (p > 0.05).
After the intervention, the experimental group
showed a considerable improvement in their academic performance, with an
average score of 8.2 out of 10, while the control group obtained an average of
6.1. The difference between both groups was significant (p < 0.01),
suggesting that the use of m-learning contributed significantly to the learning
of the concepts of measures of central tendency.
Statistical analysis: A t-test for independent
samples was performed to compare the results between the experimental group and
the control group in the post-intervention assessment. The results indicated
that the experimental group significantly outperformed the control group (t =
3.45, p < 0.01), supporting the hypothesis that the use of mobile devices
improves the understanding of statistical concepts.
Additionally, Cronbach's Alpha applied to the
questionnaire responses showed a reliability of 0.78, indicating that the
assessments used were consistent and reliable in measuring student learning.
Experimental group's perception of
m-learning: The experimental group also responded to a perception survey
on the use of mobile applications as an educational tool. Eighty-five percent
of the students indicated that the interactive activities improved their
understanding of measures of central tendency. In addition, 90% of the
participants indicated that the use of m-learning made classes more dynamic and
participatory, while 80% expressed interest in continuing to use these
technologies in other subjects.
Summary of results: Significant improvement in the experimental group: Students
who used m-learning significantly improved their performance compared to the
control group, with an average difference of 2.1 points in the final
evaluation.
·
High
satisfaction with the use of m-learning: The majority of students in the
experimental group expressed a positive perception of the use of mobile
applications, highlighting the flexibility and easy access to interactive
content.
· Consistency in evaluations: The questionnaire
used to measure knowledge showed high internal consistency, with a Cronbach's
Alpha coefficient of 0.78, which reinforces the validity of the results
obtained.
The findings of this study suggest that the
integration of m-learning in the teaching of measures of central tendency for
grouped data can significantly improve the academic performance of high school
students. Comparison between the experimental group, which used mobile devices
to access interactive content, and the control group, which followed a
traditional approach, revealed a statistically significant difference in
academic outcomes, with a clear benefit for those who used m-learning. Improved
academic performance: the use of mobile applications and interactive resources
resulted in better understanding and higher retention of statistical concepts,
which was reflected in the better performance of the experimental group in the
post-intervention assessment. This improvement suggests that m-learning is an
effective tool for teaching complex topics in mathematics and statistics.
Increased motivation and participation: Students in
the experimental group reported a higher level of motivation and participation
in learning activities, suggesting that the use of mobile devices makes the
teaching process more dynamic and engaging. Interaction with digital resources
allowed students to be actively involved in their own learning process.
Flexibility and accessibility: m-learning provided
students with the possibility of accessing educational materials at any time
and from anywhere, which favored more autonomous and personalized learning.
This flexibility is a key factor in promoting a more modern approach adapted to
the needs of learners in the digital age.
Feasibility of m-learning in educational contexts:
This study demonstrates that m-learning is a viable methodology in the
Ecuadorian educational context, where access to mobile devices is widespread.
Its implementation can be an effective strategy to modernize the educational
system and promote the integration of emerging technologies in the classroom. In
conclusion, the integration of mobile technologies in education can transform
the way students learn, especially in disciplines such as statistics. The results
of this study support the implementation of m-learning programs in educational
institutions as a key tool to improve learning and prepare students for the
challenges of the digital world.
Barreno, M., & Guevara, C. (2022). Objetos de aprendizaje móvil para
la enseñanza de las matemáticas. Revista
Latinoamericana de Tecnología Educativa, 15(3), 35-48.
Crompton, H., & Burke, D. (2018). The use of
mobile learning in higher education: A systematic review. Computers &
Education, 123, 53-64.
Manning, R. (2016). Mobile broadband in Latin
America: A path to digital inclusion. World Bank Group Report. Retrieved from https://www.worldbank.org.
Salica, P., & Almirón, S. (2021). Analítica del aprendizaje del móvil
learning (m-learning) en la educación secundaria. Journal of Educational Technology, 13(2), 78-89.
Sung, Y., Chang, K. E., & Liu, T. C. (2016). The
effects of integrating mobile devices with teaching and learning on students'
learning performance: A meta-analysis and research synthesis. Computers & Education, 94, 252-275.
Licenciado en Ciencias de la Educación
Mención Físico Matemático Unidad Educativa Montepiedra
acordova@montepiedra.edu.ec
https://orcid.org/0009-0009-2722-8244
Magíster en Informática Educativa Universidad
Técnica de Ambato nm.crespata@uta.edu.ec
https://orcid.org/0009-0005-3138-3889
Licenciado en Pedagogía de las Matemáticas
y la Física
Universidad de Guayaquil pedro.zambranomu@ug.edu.ec
https://orcid.org/0009-0002-6107-695X
Magíster en Docencia Matemática Universidad
Agraria del Ecuador-Universidad de Guayaquil tacosta@uagraria.edu.ec