Delta-Phi: Jurnal Pendidikan Matematika, vol. 2 (1), pp. 127-134, 2024
Received 15 Oct 2023 / Published 30 August 2024
https://doi.org/10.61650/dpjpm.v2i1.777

The Influence of Peer Association and
Learning Interest Through Educational
Media on Student Learning
Siti Nurqotimah1*, Agus Setiawan2, M.Saidun Anwar3, Asulia Dita Anggraeni4
1. Universitas Maa’rif Lampung (UMALA), Indonesia
2. Universitas Maa’rif Lampung (UMALA), Indonesia
3. Universitas Maa’rif Lampung (UMALA), Indonesia
4. SMA Negeri 1 Pasuruan, Indonesia
E-mail correspondence to: sitinurkhotimah1012@gmail.com

Abstract
This research focuses on the unsatisfactory learning outcomes of students
in mathematics and aims to explore the relationship between peer
association, learning interest, and educational media use on students'
performance. Employing an experimental method with a mixed-methods
approach, the study involves 55 students from classes VIIa and VIIb, with
a sample of 30 students selected through random sampling. Data were
collected
through
observations,
interviews,
questionnaires,
documentation, and the application of interactive educational media
during math lessons. Using ANCOVA for analysis, the study found that
educational media significantly enhances the positive relationship
between peer association and learning outcomes. Additionally, learning
interest, especially when supported by engaging media, correlates
strongly with improved outcomes. Overall, peer association, learning
interest, and educational media collectively have a significant and positive
impact on student performance.
Keywords: Learning Outcomes, Interest in Learning, Peers, Educational
Media, Mathematics

INTRODUCTION
In the current era of rapid technological advancement and global
educational transformation (Ajibade, 2023; Nicolaou, 2021), the
integration of digital media and peer collaboration has become
increasingly significant in shaping student learning outcomes
(Murayama, 2019; Schiefele, 1991; Y. Zhang, 2022). Across the world,
educational systems are striving to enhance student engagement and
achievement, particularly in subjects like mathematics (Huang, 2020;
Wong, 2019), which are often perceived as challenging by students.
The use of educational media ranging from interactive digital
platforms to gamified learning environments has been shown to foster
greater motivation (Rachman, Kuswandi, & Rahayu, 2025),
participation, and conceptual understanding among learners
(Michaelis, 2019; Murayama, 2022; Tai, 2022). In Indonesia, the
© 2024 author (s)

promise of education is closely tied to the ability of schools to adapt to
these global trends, ensuring that students are not only recipients of
knowledge but also active participants in their own learning journeys
(Ashraf, 2020; Kim, 2003; Tomlinson, 2003).
Despite these advancements, a persistent challenge remains: many
students continue to demonstrate low learning outcomes in
mathematics (Ngai, 2018; Walkington, 2013), often attributed to a lack
of interest and negative peer influences. The classroom environment is
a complex ecosystem where internal factors such as motivation
(Laforce, 2017), interest, and psychological well-being interact with
external factors like peer association and the availability of engaging
learning resources. Students frequently report that distractions from
peers and a lack of stimulating instructional media contribute to
disengagement and poor academic performance. This is particularly
evident during adolescence, a period marked by heightened sensitivity
to peer dynamics and social belonging (Fang, 2014; Jones, 2019; Sam,
2019). The challenge for educators, therefore, lies in creating learning
environments that not only mitigate negative peer influences but also
leverage positive peer interactions and innovative media to boost
student interest and achievement.
Previous research has extensively explored the relationship between
peer association, learning interest, and student achievement. Studies
by Safitri et al. (Hidi, 2012; Vaske, Landon, & Miller, 2020) and Vidyastuti
et al. (Choi, 2018) have established that positive peer relationships
significantly enhance student motivation and academic outcomes.
Other scholars, such as Dewy & Isnaini (Y. Zhang, 2022) and Ziko &
Muhammad (Li, 2016; Murillo-Zamorano, 2021), have highlighted the
interconnectedness of peer association and learning interest (Hong,
2016; Savinov, 2017), demonstrating that students who are part of
supportive peer groups tend to exhibit higher levels of engagement and
better learning results.

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The novelty of the present study lies in its experimental approach
(Bath & Prasad, 2025; Hochberg, 2018), which not only examines the
influence of peer association and learning interest but also integrates
the use of interactive educational media as a central variable. Unlike
previous research that has treated media as a peripheral or
background factor, this study positions educational media as an active
intervention, hypothesizing that its presence can amplify the positive
effects of peer collaboration and student interest on learning
outcomes. This approach responds to the growing body of literature
suggesting that digital and interactive media can transform passive
learning into active, (Chu, 2011), and meaningful experiences
(Garriott, 2014; Mohr-Schroeder, 2014; Sigala et al., 2024).

include peer association (the quality and nature of student
interactions), learning interest (students’ intrinsic motivation and
engagement), and educational media (the use of digital and interactive
tools to support learning) (Almeida, 2001; REHM, 2020; Relucio, 2018)
In conclusion, this research addresses several key issues: the low
mathematics learning outcomes among students, the detrimental
impact of peer influence, and the absence of engaging educational
media (Almeida, 2001; Fang, 2014). The challenges involve promoting
positive peer interactions, maintaining student interest, and
effectively incorporating media into classroom practices. While
previous studies have highlighted the significance of peer relationships
and student interest, they have not thoroughly examined their
interaction with educational media. This study's novelty lies in its
experimental design and its focus on the combined effects of these
variables, guided by social learning and constructivist theories. The
goal is to provide actionable insights aimed at enhancing mathematics
education in Indonesia and beyond.

The research gap addressed by this study is the lack of empirical
evidence on the combined and interactive effects of peer association,
learning interest, and educational media on student learning
outcomes in mathematics. While prior studies have separately
examined these variables, few have investigated how they interact
within an experimental framework, particularly in the context of
Indonesian secondary education. This study seeks to fill this gap by
employing a mixed-methods experimental design, utilizing ANCOVA to
analyze the synergistic impact of these factors (Hochberg, 2018).

RESEARCH METHOD
3.1 Research Design
This research adopts an experimental method with a mixed-methods
approach (Marshalsey, 2019). The quantitative component measures
the effect of peer association and learning interest through
educational media on mathematics learning outcomes, while the
qualitative component explores student experiences and
perceptions. This design is recommended for educational innovation
research to capture both statistical impact and contextual
understanding.

The theoretical framework underpinning this research draws on social
learning theory (M. Zhang, Huang, Zhang, Nie, & Jia, 2024), which
posits that learning occurs through observation, imitation, and
modeling within social contexts (Fang, 2014; Han et al., 2022; Xue,
2019). This is complemented by constructivist theories of learning,
which emphasize the importance of active engagement, collaboration,
and the use of meaningful media in constructing knowledge (Atanga,
2020; Rotgans, 2014). The key concepts operationalized in this study

Figure 1. Research Design Flowchart

3.2 Population and Sample

sampling, the research aims to obtain accurate results applicable to a
broader population, crucial for the validity of intervention research
where generalization is key.

This research was conducted at MTs Khozinatul Ulum Seputih Banyak,
Pasuruan, focusing on seventh-grade students to evaluate the
effectiveness of an intervention and obtain results that can be
generalized. The population in this study consists of 55 students
divided into two classes: Class VIIA with 25 students and Class VIIB
with 30 students. To ensure the research sample is representative and
minimize bias, a simple random sampling technique was used, chosen
for its straightforwardness and ability to give each member of the
population an equal chance of being selected. This method ensures
the sample reflects the overall characteristics of the population,
reduces bias in sample selection, and allows findings to be
generalized. From the population of 55 students, 30 were selected as
the research sample, considered sufficient to provide a clear and
reliable picture of the intervention's effects. By using simple random

3.3 Data Collection Instruments
The instruments used consist of observations of the school
environment and learning process, interviews with students,
teachers, and parents, as well as student questionnaires covering
peer associations, interest in learning, and media involvement (Jones,
2019). Additionally, documentation such as student admissions,
assessments, Pasuruan educational reports, and student answer
sheets were used, along with the implementation of interactive
educational media (Fisch, 2009). The validity of the instruments was
tested using Pearson's validity test, while reliability was tested with
Cronbach's Alpha (>0.8).

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Figure 2. Data Collection Workflow
3.4 Intervention: Educational Media

(Elmunsyah, 2020; Fabris, 2024), critical thinking, and student
engagement, supporting SDG 4 (Quality Education) and SDG 9
(Industry, Innovation, and Infrastructure). The selection of media is
based on curriculum alignment and proven effectiveness in previous
research (Carter, 2017; Stål, 2020).

The intervention was carried out using interactive educational media
(e.g., digital games (Kiili, 2021; Murillo-Zamorano, 2021), simulations,
or online platforms) during mathematics learning (Fulmer, 2015; Hidi,
1990). These media are designed to enhance collaboration

Figure 3. Educational Media Implementation Timeline
3.5 Data Analysis Techniques

context on student demographics, and local educational reports
offering additional data points and context. By combining
quantitative and qualitative data, the study provides a comprehensive
understanding of the factors affecting learning outcomes, offering
valuable insights for educators and policymakers in designing
effective educational strategies.

In the study of learning outcomes, both quantitative and qualitative
data are utilized to understand the various factors influencing
educational success. This analysis involves using ANCOVA for
quantitative data and thematic analysis for qualitative data.
Quantitative data is analyzed using ANCOVA (Analysis of Covariance),
a statistical method used to measure the combined effects of several
independent variables—such as peer association, learning interest,
and educational media—on learning outcomes. By controlling for
covariates, ANCOVA provides robust evidence of the effects of these
interventions. Key points include investigating how interactions with
peers influence learning, examining the impact of a student’s
enthusiasm for learning on their performance, and assessing the role
of digital and traditional media in enhancing learning. ANCOVA is a
powerful tool as it not only helps in understanding the direct effects
of these variables but also controls for any other variables that may
affect the learning outcomes, ensuring the results are reliable and
accurate. Qualitative data is gathered through interviews and
observations and is analyzed using thematic analysis, involving
identifying and examining patterns or themes within the data to gain
deeper insights into the educational processes and outcomes.
Themes explored include student engagement, teacher influence, and
environmental factors. To ensure the validity and reliability of the
findings, data from assessments (Robinson, 2001; Silva, 2021;
Warmington, 2004), PPDB (Penerimaan Peserta Didik Baru), and
Pasuruan education reports are used for triangulation. This process
involves cross-verifying data from different sources to confirm the
consistency and accuracy of the results. Triangulation sources include
standardized tests and evaluations, enrollment data providing

RESULTS AND DISCUSSION
Results
3.1. Instrument Validity and Reliability
Testing the validity and reliability of the instrument is a crucial
foundation in this research to ensure that the obtained data truly
measures the intended variables. The outcomes of the validity test
conducted with the Pearson Product Moment indicate that all items
related to the peer association variable (X1) and learning interest (X2)
are valid, as the calculated r-value exceeds the table r-value of 0.361,
signifying that each item on the instrument effectively measures its
intended construct (Mazer, 2013).
The reliability of the instrument was assessed using Cronbach’s Alpha,
resulting in values of 0.895 for X1 and 0.932 for X2, which significantly
exceed the minimum threshold of 0.6, confirming that the instrument
is highly reliable. This suggests strong internal consistency, indicating
that the instrument can consistently yield dependable data across
repeated measurements. These results are consistent with recent
research conducted by Fitri et al. (Ainley, 2006), which underscores
the significance of instrument validity and reliability in educational
research. Therefore, the instruments utilized provide credible and
accountable data, reinforcing the validity of the entire study.

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Figure 4. Validity and Reliability of Research Instruments
High validity and reliability ensure that the results of this study can be
used as a basis for educational decision-making. This is particularly
important in the development of assessment instruments in schools
focusing on educational report card data in Pasuruan.

the data is normally distributed. The linearity test also showed a
significant linear relationship between X1 and Y (sig. 0.139 > 0.05; F
calculated 1.783 < F table 2.42) as well as between X2 and Y (sig. 0.399
> 0.05; F calculated 1.128 < F table 2.41). These findings support the
validity of the analysis model used, in accordance with
recommendations in educational research based on big data and
modern analytics (Zebua, Musri, & Ichsan, 2025).

3.2 Classical Assumption Test: Normality and Linearity
The normality test conducted using Kolmogorov-Smirnov showed a
significance value of 0.086, which is greater than 0.05, indicating that

Figure 5. Normality Distribution of Research Data
A normal data distribution and a strong linear relationship between
variables will enhance the reliability of further analysis results and
support the application of ANCOVA in this research.

interest positively contributes to students' academic achievement.
These findings align with the findings of Cahyadi et al. (Arnone, 2011),
which state that the social environment and interest in learning are key
predictors of students' academic success, emphasizing the importance
of social environment and motivation in supporting learning
achievement. Simultaneous testing using the F-test shows that both
variables, peer association and interest in learning, collectively have a
significant effect on learning outcomes, with an F calculated value of
4.965 greater than the F table value of 3.34, and a significance level of
0.015. This indicates that both variables not only have an individual
impact but also a collective impact on mathematics learning outcomes.
From the analysis results, it can be concluded that peer association and
interest in learning are important factors influencing students'
mathematics learning outcomes, so efforts to improve the quality of
social interaction and motivate students' interest in learning are crucial
in achieving better academic success.

3.3 Correlation and Simultaneous Influence Analysis
This study focuses on the relationship between peer association and
interest in learning with students' mathematics learning outcomes,
using Pearson correlation analysis to identify the strength and direction
of the relationship between these variables. The analysis results show
a positive and significant relationship between peer association (X1)
and mathematics learning outcomes (Y), with an r value of 0.509 and a
significance level of 0.004. This indicates that the better the peer
association, the better the students' mathematics learning outcomes.
Additionally, interest in learning (X2) also shows a positive and
significant relationship with learning outcomes, with an r value of 0.471
and a significance level of 0.009. This reinforces that high learning

Figure 6. Correlation Coefficients of X1 and X2 on Learning Outcomes (Y)

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These findings emphasize the importance of creating a positive social
environment and encouraging students' learning interest to improve
mathematics learning outcomes, in line with SDG 4 (Quality Education).

only increases the average learning outcomes scores but also reduces
the gap among students from different social backgrounds. These
findings are in line with the research of Hwang & Wu (MurilloZamorano, 2021) and the World Bank (Fang, 2014), which emphasize
the effectiveness of digital media in enhancing student engagement
and achievement in the digital era. Assessment data and educational
reports from Pasuruan indicate an increase in the average mathematics
scores of students after media intervention, along with increased
active participation in group discussions

3.4 Impact of Interactive Educational Media Intervention
The implementation of interactive educational media in mathematics
learning has proven to strengthen the relationship between peer
association, learning interest, and student learning outcomes. The
ANCOVA analysis results show that the use of innovative media not

Figure 7. Students’ Math Scores Before and After Media Intervention
The reflection of these results shows that interactive educational
media can promote critical thinking, collaboration, and interest in
learning mathematics, while also supporting SDG 9 (Innovation and
Infrastructure), SDG 5 (Gender Equality), and SDG 17 (Partnerships)
through inclusive and collaborative learning.

the effectiveness of social interaction in the learning process, making
it easier for students to understand the material being taught.
Learning interest supported by engaging learning media shows a
strong correlation with improved learning outcomes. This
underscores the important role of media in facilitating student
motivation and engagement. Simultaneous analysis reveals that peer
association, learning interest, and educational media together have
a positive and significant effect on mathematics learning outcomes.
These findings indicate the importance of integrating interactive
educational media in a learning environment supported by positive
peer association and high learning interest. Through these findings, it
is hoped that educators and education policymakers will pay more
attention to factors influencing student learning outcomes to
improve the overall quality of education.

3.5 Reflection, Implications, and Relation to SDGs
This study confirms that the integration of social approaches (peer
association), psychological approaches (learning interest), and
technology (interactive educational media) has a significant impact on
students' math learning outcomes. These findings are not only relevant
in the local context of Pasuruan but also contribute to the global
literature on 21st-century education, which requires a contextual and
interdisciplinary approach. The practical implication is that schools and
teachers need to adopt innovative media-based learning strategies and
foster a collaborative learning culture to achieve quality and equitable
education, in line with the mandates of the SDGs.

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