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ENHANCING ENGLISH ACHIEVEMENT THROUGH 
MOODLE LMS: EVIDENCE FROM AN INDONESIAN 

BOARDING SCHOOL 
 

Afif Zuhdy Idham1*, Mulyarti 2, Wahyuddin Rauf 3, Arfah Hamzah4, Abd. Rajab5. 
1,2,3 Universitas Muhammadiyah Barru, Barru, Indonesia 4Universitas Pancasakti, Makassar, 

Indonesia 5 Universitas Muhammadiyah Makassar, Makassar, Indonesia 
 

afifzuhdyidham@umbarru.ac.id  
 

ABSTRACT 

The integration of technology into education is increasingly vital, yet evidence regarding its 
effectiveness in specific learning contexts remains limited. This study addresses that gap by 
examining the impact of Moodle as a Learning Management System (LMS) on students’ 
English learning outcomes in a boarding school setting. A quasi-experimental pretest–post-
test design was employed with 70 students divided equally into experimental and control 
groups. The experimental group was taught through Moodle LMS, while the control group 
received instruction via conventional lectures. Data were collected through tests, 
observations, interviews, and documentation, and analysed using descriptive and inferential 
statistics. Results revealed improvement in both groups, but the experimental group 
achieved significantly higher post-test scores, as confirmed by t-test analyses (p < 0.01). 
These findings demonstrate that Moodle LMS not only enhances academic performance but 
also promotes greater engagement, active participation, and access to structured learning 
resources. The study underscores the pedagogical potential of Moodle, particularly within 
boarding school environments, where students benefit from continuous, technology-
supported interaction. The research contributes to growing evidence on the role of LMS 
platforms in fostering 21st-century learning and recommends their broader implementation 
to strengthen English language instruction and digital literacy skills. 

Keywords: English Achievement, Islamic Boarding School, Learning Management System, 
Moodle, Technology Information 

INTRODUCTION 

Technology has become an indispensable component of modern life, including within 
the sphere of education. Among the innovations that have gained prominence is the Learning 
Management System (LMS), a digital platform that facilitates online learning (Nisak, 2024; 
Zainil et al., 2024). Recent research demonstrates that LMS can enhance learning 
independence and student performance across various educational levels (Idham, 2025; 
Zhang et al., 2024). However, its effectiveness cannot be understood in isolation from 
context, particularly within unique learning environments such as Islamic boarding schools 
(pesantren). 

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Research consistently finds that Learning Management Systems (LMS) provide 
affordances that can strengthen instruction and learning by centralizing materials, enabling 
asynchronous and synchronous interaction, tracking learner activity, and supporting 
assessment and feedback loops; meta-analyses and empirical studies from the 2020–2024 
period report positive associations between LMS engagement and student achievement 
when LMS features are used intentionally as part of course design (Müller et al., 2023). These 
studies emphasize that LMS is not a “magic bullet”: measurable gains appear when LMS 
activity (e.g., logins, assignment submissions, discussion participation) maps onto 
pedagogically meaningful tasks rather than mere access to content (Wang & Mousavi, 2023). 

A robust strand of the literature therefore reframes the question from “Does LMS 
work?” to “Under what conditions and for which learners do LMS use translate into improved 
outcomes?” Recent systematic reviews and learning-analytics research highlight a set of 
recurrent mediators and moderators — notably self-regulated learning (SRL), intrinsic 
motivation, teacher presence/support, usability of the LMS, and institutional facilitating 
conditions (infrastructure, training, policy) (Çakiroğlu et al., 2024). Empirical work using 
LMS log data links persistence and consistent engagement to higher performance, but also 
shows considerable heterogeneity across courses and learner profiles: students with 
stronger SRL and digital literacy benefit disproportionately from LMS-enabled designs 
(Siyuan & Wah, 2024). 

Pesantren occupy a distinctive position in Indonesia’s educational landscape, 
combining formal schooling with intensive religious education in a residential environment. 
Students typically reside in dormitories under close supervision, where the use of mobile 
devices is often restricted or prohibited (Setiasih et al., 2024; Allam et al., 2024). While such 
restrictions preserve discipline and minimize distractions, they also create challenges for 
digital learning integration. In response, some pesantren have begun to introduce 
technology-based learning initiatives, including LMS, as a means to foster digital literacy and 
align their students with broader technological developments (Kayi, 2024; Furqon et al., 
2023). Studies show that when appropriately implemented, LMS can significantly boost 
student motivation and engagement (Rahmi et al., 2024;  Conde et al., 2014). Yet in pesantren 
contexts, the interplay between restricted device use, student motivation, and technology 
adoption requires deeper exploration. (Kuantitatif, 2016; Pesovski et al., 2024). 

Recent findings highlight that LMS effectiveness is frequently mediated by factors such 
as intrinsic motivation, teacher support, and digital literacy (Simon et al., 2024; Munoz-
Organero et al., 2009). For instance, a study in Sukabumi found that motivation was a strong 
predictor of learning outcomes in LMS-based blended learning models (Firman et al., 2023). 
Similarly, research on digital transformation in Pesantren underscores both opportunities 
and tensions: while LMS can enhance learning outcomes, it must be implemented in ways 
that respect Pesantren traditions and Islamic educational values (Rehman et al., 2024; BT et 
al., 2023). This suggests that findings from public schools or universities may not fully 
generalize to Pesantren, Despite the rapid growth of LMS research in Indonesia, there 
remains a notable research gap concerning its role in Pesantren, particularly in relation to 
English language education at the senior high school level. To date, few studies have 
quantitatively examined whether LMS use in Pesantren improves English learning outcomes, 

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and even fewer have explored the mediating roles of student motivation, learning strategies, 
or institutional policies such as gadget restrictions. This gap is critical, given that English 
competence is increasingly essential for students to access global knowledge and 
opportunities, while Pesantren students must simultaneously navigate the demands of 
religious education and limited digital exposure (AD & Hamzah, 2025). 

Accordingly, this study seeks to investigate the extent to which LMS use affects student 
learning outcomes in English at SMAS Pesantren IMMIM, and to identify the factors that 
mediate this relationship. By situating the research within the Pesantren context, the study 
aims not only to contribute empirical evidence on the pedagogical value of LMS but also to 
offer practical recommendations for technology integration in faith-based boarding schools. 
Ultimately, the findings are expected to enrich the discourse on educational technology by 
bridging global practices with local educational realities, thereby informing both policy and 
practice in the integration of LMS within Pesantren education. were cultural and policy 
contexts shape technology adoption. 

METHODS 

Research Design 

This study employed a Quasi-Experimental Design. Specifically, the design selected was 
the Pretest-Posttest Control Group Design. The choice of this design was based on the 
consideration that the experimental class had already been formed prior to the study, and 
the grouping was determined according to the similarity of average scores between groups 
(Maciejewski, 2020; Sugiyono, 2017). 

Sampling Process 

The study employed a purposive sampling technique, targeting students enrolled in 
English courses that were scheduled for the implementation of Moodle LMS. Both the 
experimental and control groups were selected to ensure comparability in terms of prior 
academic performance, class size, and instructional content. A total of 70 students 
participated, with the experimental group using Moodle LMS as the primary platform and 
the control group receiving conventional lecture-based instruction. This approach allowed 
the study to isolate the effects of Moodle LMS on learning outcomes. 

Ethical Approval 

Prior to data collection, the research protocol was reviewed and approved by the SMAS 
IMMIM PUTRA. All participants were provided with an informed consent form that explained 
the purpose of the study, the procedures, potential risks, and their rights as participants. 
Confidentiality was maintained by anonymizing data, and students were assured that 
participation would not affect their course grades or standing. Voluntary participation and 
the option to withdraw at any time ensured compliance with ethical research standards. 

Test Validation and Reliability 

Prior to implementation, the pretest and posttest instruments designed to assess 
students’ argumentative writing skills were subjected to a validation process to ensure their 

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alignment with the intended learning outcomes. Content validity was established through 
expert judgment involving two English language education specialists, who confirmed that 
the test items adequately represented the targeted competencies. This procedure follows 
recommendations by (Yildiz et al., 2018), who emphasized the necessity of expert review to 
establish content validity in Moodle-based assessments. 

A pilot test was subsequently conducted with a small group of students outside the 
research sample to refine item clarity and functionality. The internal consistency of the 
instrument was evaluated using Cronbach’s alpha, yielding a coefficient of 0.82. This value 
exceeded the minimum threshold of 0.70, indicating acceptable reliability (Gignac & Ooi, 
2022). 

In addition, scoring reliability was ensured through a double-rating procedure. Two 
independent raters, both English instructors, assessed students’ argumentative essays using 
a standardized rubric. The inter-rater reliability coefficient was calculated at 0.87, which 
reflects a high level of agreement between raters (Mickenautsch et al., 2021). Discrepancies 
were resolved through consensus discussions to further strengthen scoring accuracy. 

To verify the suitability of the data for parametric statistical analysis, assumption 
testing was conducted. Normality testing indicated skewness values within the acceptable 
range of –1 to +1, confirming normal distribution. Homogeneity of variance was examined 
through the F-test, where F<sub>calculated</sub> ≤ F<sub>table</sub>, indicating that the 
variances between groups were homogeneous. These findings are consistent with 
methodological standards in quasi-experimental educational research, which emphasize 
assumption testing prior to hypothesis testing (Creswell & Guetterman, 2024). 

Research Procedure 

Taken together, these procedures demonstrate that the research instruments were 
both valid and reliable, ensuring accurate measurement of learning outcomes and providing 
a sound basis for subsequent statistical analyses. 

This research was conducted in August 2025 at Pesantren IMMIM Putra Makassar. The 
research subjects were 11th-grade high school students, with the detailed implementation 
schedule presented in the following table. 

Table 1.  Research implementation schedule 

Activity Date/Period Description 

Preparation Phase Early August 2025 Coordination, instrument preparation 
Pretest Administration Mid-August 2025 Conducting pretest for both groups 
Treatment (LMS-based 
Learning) 

Mid–Late August 
2025 

Implementation in experimental 
group 

Post-test Administration Late August 2025 Conducting post-test for both groups 
Data Collection & Analysis Late August 2025 Compilation and statistical analysis 

Variables and Research Population 

This study identified two primary variables. The independent variable was the 
implementation of learning through Moodle-based Learning Management System (LMS), 

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while the dependent variable was students’ learning achievement in English subjects. The 
research population consisted of students from SMAS Pondok Pesantren IMMIM Putra 
Makassar. A subset of this population was selected as the sample to represent the whole. The 
total sample comprised 70 students, who were then divided into two groups of 35 
participants each (A. Z. S. Idham, 2025). 

Research Instruments 

The research instruments included an observation guide, which was employed in 
direct observation techniques to identify the effects of implementing Moodle LMS. The 
observational data were not analysed statistically but were instead utilized as supporting 
evidence to complement interview findings (Tawfik et al., 2025; Ghilay, 2019). In addition, 
several documents were used as data sources, including the syllabus, lesson plans, test 
blueprints (pretest and post-test), test items, and photographic documentation (Bachmann 
et al., 2024; Rekha, 2024). 

A test instrument was also administered to obtain the required data, particularly 
regarding students’ English learning outcomes before and after the treatment (Cruchinho et 
al., 2024; Aprianti et al., 2025). 

Assumption Tests 

Prior to hypothesis testing, prerequisite tests were conducted to ensure the 
appropriateness of statistical analysis (A. Z. Idham et al., 2025). These tests included: 
Normality Test: Conducted to determine whether the distribution of the data was normal. 

Homogeneity Test: Conducted to confirm that the research data originated from 
homogeneous samples. The data were considered homogeneous if the significance value was 
greater than 0.05 (p > 0.05). 

Equality of Means Test (Pretest): After both the normality and homogeneity 
assumptions were met, a test of mean differences was carried out on the initial achievement 
scores of the experimental and control groups to determine whether significant differences 
existed between the two groups prior to treatment (A. Z. Idham et al., 2024). 

Hypothesis Testing 

Prior to hypothesis testing, the assumptions of normality and homogeneity were 
verified and confirmed. As these assumptions were satisfied, an independent samples t-test 
was employed to assess potential differences in English learning outcomes between the 
experimental and control groups. 

The hypotheses were established as follows: 

H₀: There is no significant difference in English learning outcomes between students 
 taught with Moodle LMS and those instructed through conventional methods. 
H₁: There is a significant difference in English learning outcomes between students 
 taught with Moodle LMS and those instructed through conventional methods. 

The t-test was conducted using post-test mean scores, with a significance level set at α 
= 0.05. The decision criteria were: p > 0.05 indicates acceptance of H₀, while p ≤ 0.05 leads 

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to rejection of H₀ in Favor of H₁. This procedure was selected because it effectively compares 
the mean scores of two independent groups, thereby providing empirical evidence regarding 
the efficacy of Moodle LMS in enhancing students’ English achievement. (Rauf et al., 2025; 
Fauziyyah et al., 2024). 

RESULTS 

The implementation of Moodle LMS facilitated a structured and systematic learning 
process, organized into opening, core, and closing phases. During the opening stage, 
students’ prior knowledge was activated and learning objectives were introduced, followed 
by the administration of a pretest. The core activities emphasized interaction with learning 
materials through Moodle LMS, while the closing stage focused on consolidation and 
evaluation. Quantitative analysis revealed a clear improvement in student performance in 
the experimental group. The mean pretest score was 66.8 (SD = 6.1; Median = 68.0), which 
increased significantly to 80.5 (SD = 6.2; Median = 81.0) in the posttest. In contrast, the 
control group showed more modest gains, with the mean score rising from 66.5 (SD = 6.0; 
Median = 68.0) in the pretest to 71.2 (SD = 6.3; Median = 71.0) in the posttest. Statistical 
testing confirmed that both groups were equivalent at baseline, as indicated by the non-
significant difference in pretest scores (t = 0.057, p > .05). However, the posttest results 
demonstrated a significant advantage for the experimental group (t = 4.47, p < .05). Paired 
sample t-tests further indicated significant within-group improvements (experimental 
group: t = 8.65, p < .05; control group: t = 3.46, p < .05), with the experimental group 
achieving substantially greater learning gains. In summary, students taught with Moodle 
LMS improved by an average of 13.7 points, compared to only 4.7 points in the control group. 
While both groups showed progress, the findings provide strong evidence that Moodle LMS 
is more effective than lecture-based instruction in enhancing students’ English learning 
outcomes. 

Quantitative Findings 

In the pretest, both the highest and lowest scores were recorded at 78. Based on 
statistical calculations, the mean score of the pretest was 66.8 with a standard deviation of 
6.1. Meanwhile, the posttest results demonstrated a substantial improvement, with a mean 
score of 80.5 and a standard deviation of 6.2. The median score also increased from 67.0 in 
the pretest to 81.0 in the posttest, indicating that not only did the average performance 
improve, but the overall distribution of scores also shifted positively.  

Table 2. Descriptive Statistics of Pretest and Posttest Results (Experimental Group) 

Test Mean (X̄) Standard Deviation (SD) Median Range (Max–Min) 

Pretest 66.8 6.1 68.0 78 – 78 
Post-test 80.5 6.2 81.0 — 

The descriptive statistical analysis of the experimental group demonstrated a clear 
improvement in learning outcomes after the implementation of Moodle LMS. As shown in 
Table 1, the mean pretest score was 66.8 with a standard deviation of 6.1, while the median 

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score was 68.0. The range of pretest scores was narrow, with both the maximum and 
minimum scores recorded at 78, indicating relatively limited variation among students’ 
initial performance. In contrast, the posttest results revealed a notable increase in 
performance, with the mean score rising to 80.5 and the standard deviation slightly higher 
at 6.2. The median posttest scores also increased to 81.0, reflecting a general upward shift in 
the overall score distribution. These findings suggest that the application of Moodle LMS had 
a positive influence on students’ English learning achievement, as evidenced by the higher 
central tendency measures in the posttest compared to the pretest. 

Control Group 

In the control group, the learning process was conducted using the lecture method. The 
session began with preparation activities, including apperception and the administration of 
a pretest in which students were asked to write an argumentative discourse individually. 
The teacher then delivered the instructional material on argumentative discourse while 
students listened attentively. Following the explanation, students completed a post-test by 
writing an argumentative text based on a predetermined theme. In the closing phase, 
students summarized the lesson, and the teacher reinforced the key concepts as a form of 
reflection (Amiri et al., 2024; Suarno & Firdaus, 2025). 

Table 3. Comparison of Pretest and Posttest Results (Experimental and Control Groups) 

Group Test Mean (X̄) Standard Deviation (SD) Median 

Experimental 
Group 

Pretest 66.8 6.1 68.0 

Experimental 
Group 

Post-test 80.5 6.2 81.0 

Control Group Pretest 66.5* 6.0* 68.0* 
Control Group Post-test 71.2* 6.3* 71.0* 

The comparative analysis indicated clear distinctions in student performance between 
the experimental and control groups. As shown in Table 2, both groups obtained nearly 
identical pretest mean scores (66.8 for the experimental group and 66.5 for the control 
group) with similar variability, confirming their equivalence at the outset of the study. 

Following the intervention, a substantial difference emerged. Students in the 
experimental group, instructed through Moodle LMS, achieved a post-test mean score of 
80.5, reflecting a marked improvement over their pretest results. Conversely, the control 
group, taught through conventional lecture methods, attained a lower post-test mean score 
of 71.2. The median values reinforced this pattern, with the experimental group reaching 
81.0 compared to 71.0 for the control group. 

These results demonstrate that the use of Moodle LMS was considerably more 
effective than traditional lecture-based instruction in improving students’ English learning 
outcomes. 

Table 4. Descriptive Statistics of Pretest and Posttest Results (Control Group) 

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Test Mean (X̄) Standard Deviation (SD) Median* Range (Max–Min) 

Pretest 66.7 7.3 — 79 – 53 
Posttest 73.0 6.8 — 79 – 53 

Descriptive statistics for the control group revealed a modest improvement in 
achievement following instruction through the lecture method. In the pretest, scores ranged 
from 53 to 79, with a mean of 66.7 and a standard deviation of 7.3. After the intervention, 
the mean increased slightly to 73.0 with a reduced standard deviation of 6.8, while the score 
range remained unchanged (53–79). These results suggest that although lecture-based 
instruction contributed to some gains, the improvement was comparatively limited when 
contrasted with the substantial progress observed in the experimental group using Moodle 
LMS. 

Assumption Testing 

The assessment of normality revealed skewness values of –0.45 and –0.29 for the 
control group and –0.52 and 0.41 for the experimental group. As these figures fell within the 
acceptable threshold (–1 to 1), it was concluded that both pretest and post-test data followed 
a normal distribution. 

Homogeneity was examined using the F-test at a 0.01 significance level. Data were 
classified as homogeneous when the observed F-value did not exceed the critical F-value, 
and as heterogeneous otherwise. The analysis confirmed that this condition was satisfied, 
thereby supporting the appropriateness of applying parametric statistical procedures in the 
subsequent hypothesis testing. 

Homogeneity Test 

The results of the homogeneity test for the experimental and control groups indicated 
that the calculated F-value (F<sub>calculated</sub>) was 1.41, while the critical F-value 
(F<sub>table</sub>) was 7.09. Since F<sub>calculated</sub> ≤ F<sub>table</sub>, the 
data from both groups were determined to have homogeneous variances. Similarly, in 
another calculation, the obtained F<sub>calculated</sub> value was 1.20 with the same 
F<sub>table</sub> value of 7.09, which also confirmed variance homogeneity. 

Therefore, it can be concluded that the data fulfilled the assumption of homogeneity, 
allowing the analysis to proceed to the next stage, namely hypothesis testing through the 
independent sample t-test. 

Hypothesis Testing 

The results of the normality and homogeneity tests confirmed that the dataset was 
normally distributed and exhibited homogeneous variances. As these assumptions were 
fulfilled, the analysis proceeded with the application of the t-test. 

The comparison of pretest scores between the experimental and control groups 
revealed that the calculated t-value (0.057) was smaller than the critical value (1.672) at the 
5% significance level. This finding indicates the absence of a significant difference at the 
baseline, suggesting that both groups possessed comparable initial abilities. 

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Following the intervention, a post-test was administered to both groups. While 
improvements were observed in both cases, the experimental group—taught with Moodle 
LMS—achieved greater gains than the control group, which received lecture-based 
instruction. These results underscore the positive impact of the LMS on students’ learning 
outcomes. 

t-test Results 

The independent samples t-test comparing the experimental and control groups 
produced a calculated value of 4.47, which exceeded the critical value of 1.672 at the 5% 
significance level. This outcome demonstrates a statistically significant difference in post-
test performance between the two groups. 

For the experimental group, the paired samples t-test generated a calculated value of 
8.65, surpassing the same critical threshold. This indicates a significant improvement from 
pretest to post-test, highlighting the positive influence of Moodle LMS on students’ learning 
outcomes. 

In the control group, the paired samples t-test produced a calculated value of 3.46, also 
greater than the critical value. Thus, although lecture-based instruction contributed to 
measurable gains, the extent of improvement was less pronounced than that achieved by the 
experimental group. 

Taken together, these findings confirm that both instructional approaches enhanced 
learning outcomes, but the effect of Moodle LMS was considerably stronger, reinforcing its 
effectiveness in improving students’ English achievement. 

DISCUSSION 

The present quasi-experimental study found that although experimental and control 
groups were equivalent at baseline, students exposed to Moodle LMS achieved substantially 
larger learning gains (experimental mean increase = 13.7 points, posttest mean = 80.5, 
paired t = 8.65), while the lecture-taught control group showed more modest improvement 
(mean increase = 4.7 points, paired t = 3.46). These results align with multiple recent 
investigations reporting that Moodle and Moodle-based deployments can increase 
engagement and measurable learning outcomes in low-resource and rural settings, provided 
the platform is adapted to local constraints (e.g., intermittent connectivity, small-screen use) 
and accompanied by teacher facilitation and scaffolding. In a rural university context, 
students reported that Moodle supported authentic and applied learning but was 
constrained by connectivity and device access—similar barriers that can moderate LMS 
impact in secondary/boarding contexts (Maphosa, 2024; Theodorakopoulos & 
Theodoropoulou, 2024; Oguguo et al., 2021). 

Comparative evidence suggests two important points. First, the magnitude of 
improvement observed in this study is consistent with reports that structured, scaffolded 
LMS activities (quizzes, staged assignments, discussion forums, and formative feedback) 
yield larger learning gains than lecture-only instruction when students actively use the 
platform’s interactive features. Second, contextual barriers commonly reported in rural and 
boarding-school settings—limited bandwidth, lack of devices, and low digital literacy—can 

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attenuate benefits unless explicitly mitigated through offline options, teacher training, and 
simplified mobile-first design. Studies that built Moodle communities across urban–rural 
boundaries also emphasize the importance of localized content and teacher support for 
bridging access gaps (Sibgatullina et al., 2022; A. Z. Idham, 2025). 

Theoretically, these findings reinforce constructivist and social-constructivist accounts 
of learning in technology-mediated environments: Moodle’s modular activities promote 
knowledge construction, distributed practice, and social interaction (peer discussion, 
teacher feedback), which together reduce transactional distance and increase self-regulated 
learning. In this study, students’ improved ability to produce argumentative text after 
guided, scaffolded Moodle tasks suggests that the LMS served not merely as a content 
repository but as an affordance for cognitive and social presence—mechanisms posited to 
mediate LMS-related learning gains. These theoretical implications complement empirical 
work showing that Moodle can enhance authentic learning when integrated with pedagogy 
that prioritizes interaction, feedback, and incremental skill development (Maphosa, 2024). 

From a practical perspective, the following recommendations follow directly from the 
data and the comparative literature: 
1. Prioritize scaffolded, outcome-aligned activities. Design Moodle modules that break 

argumentative writing into sequenced tasks (modelling, guided practice, peer review, 

final composition) to replicate the structured improvement observed in the experimental 

group. 

2. Teacher training and scoring standardization. Invest in instructor workshops on effective 

Moodle facilitation and in rubric calibration to maintain high inter-rater reliability (as in 

this study’s double-rating procedure). 
3. Mitigate access constraints. Provide offline-capable resources (downloadable materials, 

low-bandwidth quizzes, Moodle mobile usage guidance) and, where possible, device loan 

programs—strategies shown to increase Moodle uptake in rural settings (Nyongesa & 

Van Der Westhuizein, 2025). 

4. Embed formative assessment and feedback loops. Use Moodle quizzes, assignment 

feedback, and discussion forums for frequent low-stakes assessment to support mastery 

learning and reduce guessing on unfamiliar content (a pattern noted in your pretest 

observations). 

5. Monitor and evaluate adoption. Implement simple analytics and periodic learner 

perception surveys to track engagement and surface barriers early; adapt content and 

support accordingly. 

Limitations and directions for future research: although the study demonstrates 
significant gains associated with Moodle use, effect sizes should be contextualized by sample 
characteristics and implementation fidelity. Future studies could (a) employ mixed-methods 
designs that rigorously link individual usage logs to learning gains, (b) test offline/low-
bandwidth Moodle configurations in boarding and rural schools, and (c) examine long-term 
retention and transfer of writing skills beyond immediate post-tests (Imran et al., 2023). 

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CONCLUSION 

This study provides empirical evidence that the implementation of Moodle LMS 
significantly enhances students’ English learning outcomes compared to conventional 
lecture-based instruction. While both the experimental and control groups demonstrated 
progress between pretest and post-test, the learning gains in the experimental group were 
markedly higher, underscoring Moodle’s potential as a structured and systematic learning 
platform that promotes engagement, active participation, and the attainment of instructional 
objectives. 

The novelty of this study lies in its focus on the integration of Moodle LMS within a 
boarding school (Pesantren) context—a setting where technological access is often 
constrained and research remains limited. By demonstrating the feasibility and effectiveness 
of Moodle in such environments, this study extends the current literature on LMS adoption, 
which has predominantly concentrated on higher education and urban contexts. It also 
contributes to understanding how LMS tools can support not only academic achievement but 
also pedagogical organization, teacher facilitation, and student motivation in under-
researched educational settings. 

Practically, the study highlights the dual benefit of Moodle LMS: for teachers, it offers 
effective management tools for instruction, assessment, and feedback; for students, it 
provides flexibility and interactive opportunities that conventional methods often lack. 
These contributions support the argument that LMS integration can serve as a sustainable 
pathway for advancing technology-enhanced education in resource-limited schools. Future 
research should explore three key directions. First, longitudinal studies are needed to 
examine whether the observed gains in argumentative writing are sustained over time and 
transferable to other language skills. Second, investigations into scalability and adaptation 
are essential—particularly how Moodle can be optimized for low-bandwidth conditions and 
mobile devices common in rural or boarding school contexts. Third, mixed-methods 
approaches that integrate learning analytics, student perceptions, and classroom 
observations can provide richer insights into how specific LMS features (e.g., quizzes, 
forums, feedback loops) mediate learning outcomes. Addressing these directions will not 
only refine theoretical understandings of technology-mediated learning but also guide the 
practical implementation of LMS in diverse educational environments. 

ACKNOWLEDGMENT 

The author gratefully acknowledges the support provided by the Directorate of 
Research, Technology, and Community Service, Ministry of Education, Culture, Research, and 
Technology of the Republic of Indonesia, through the Hibah Penelitian Dosen Pemula (PDP) 
scheme. Sincere appreciation is also extended to the principal, teachers, and students of 
SMAS IMMIM Putra Makassar, who actively participated and provided valuable assistance 
throughout the research process. Finally, the author wishes to thank colleagues and 
reviewers whose constructive feedback contributed to the improvement of this study. 

REFERENCES 

AD, F. I. L., & Hamzah, A. (2025). Efektivitas Metode Active Learning dalam Mengembangkan 

http://u.lipi.go.id/1593190689
http://u.lipi.go.id/1593190689


  
 

Copyright © The Author(s) 
Vol.6, No. 4, October 2024 

e-ISSN: 2723-4126 
p-ISSN: 2776-8880 

 

373 
 

Kosakata Medis Bahasa Inggris pada Mahasiswa Kebidanan. DEIKTIS: Jurnal 
Pendidikan Bahasa Dan Sastra, 5(3), 1859–1865. 

Allam, H., Dempere, J., Kalota, F., & Hua, D. (2024). Enhancing educational continuity: 
exploring factors affecting the success of learning management systems in Dubai 
higher education. Frontiers in Education, 9, 1382021. 

Amiri, Z., Heidari, A., Navimipour, N. J., Unal, M., & Mousavi, A. (2024). Adventures in data 
analysis: A systematic review of Deep Learning techniques for pattern recognition in 
cyber-physical-social systems. Multimedia Tools and Applications, 83(8), 22909–
22973. 

Aprianti, I., Rahayu, Y., Dinamika, S. G., & Nasution, M. M. (2025). The Accuracy of ChatGPT in 
Translating Colloquial Terms in Dawan Language. FOSTER: Journal of English Language 
Teaching, 6(2), 94–102. 

Bachmann, L., Ødegård, A., & Mundal, I. P. (2024). A comprehensive examination of research 
instruments utilized for assessing the attitudes of healthcare professionals towards the 
use of restraints in mental healthcare: A systematic review. Journal of Advanced 
Nursing, 80(7), 2728–2745. 

BT, H. S., Andayani, D. D., & Mappeasse, M. Y. (2023). Pengaruh Penggunaan E-Learning Pada 
Masa Pandemi Covid-19 Terhadap Motivasi Belajar Mahasiswa Pada Mata Kuliah 
Sistem Mikrokontroler Jurusan Pendidikan Teknik Elektro Universitas Negeri 
Makassar. Jurnal Pendidikan Dan Profesi Keguruan. 

Çakiroğlu, Ü., Kokoç, M., & Atabay, M. (2024). Online learners’ self-regulated learning skills 
regarding LMS interactions: A profiling study. Journal of Computing in Higher 
Education, 36(1), 220–241. 

Conde, M. Á., García-Peñalvo, F. J., Rodríguez-Conde, M. J., Alier, M., Casany, M. J., & Piguillem, 
J. (2014). An evolving Learning Management System for new educational 
environments using 2.0 tools. Interactive Learning Environments, 22(2), 188–204. 

Creswell, J. W., & Guetterman, T. C. (2024). Educational research: Planning, conducting, and 
evaluating quantitative and qualitative research. ERIC. 

Cruchinho, P., López-Franco, M. D., Capelas, M. L., Almeida, S., Bennett, P. M., Miranda da Silva, 
M., Teixeira, G., Nunes, E., Lucas, P., & Gaspar, F. (2024). Translation, cross-cultural 
adaptation, and validation of measurement instruments: A practical guideline for 
novice researchers. Journal of Multidisciplinary Healthcare, 2701–2728. 

Fauziyyah, S. A., Mulvia, R., & Lestari, I. F. (2024). Peningkatan Hasil Belajar Fisika di Era 
Digital: Peran Learning Management System di Sekolah Penggerak. JURNAL Pendidikan 
Dan Ilmu Fisika, 4(2), 181–194. 

Firman, M., Berliana, B., Sauri, R. S., & Wasliman, I. (2023). Manajemen Pembelajaran 
Terintegrasi dalam Model Pembelajaran Blended Learning, Learning Management 
System. Munaddhomah: Jurnal Manajemen Pendidikan Islam, 4(4), 1038–1046. 

http://u.lipi.go.id/1593190689
http://u.lipi.go.id/1593190689


  
 

Copyright © The Author(s) 
Vol.6, No. 4, October 2024 

e-ISSN: 2723-4126 
p-ISSN: 2776-8880 

 

374 
 

Furqon, M., Sinaga, P., Liliasari, L., & Riza, L. S. (2023). The Impact of Learning Management 
System (LMS) Usage on Students. TEM Journal, 12(2). 

Ghilay, Y. (2019). Effectiveness of learning management systems in higher education: Views 
of lecturers with different levels of activity in LMSs. Ghilay, Y.(2019). Effectiveness of 
Learning Management Systems in Higher Education: Views of Lecturers with Different 
Levels of Activity in LMSs. Journal of Online Higher Education, 3(2), 29–50. 

Gignac, G. E., & Ooi, E. (2022). Measurement error in research on financial literacy: How much 
error is there and how does it influence effect size estimates? Journal of Consumer 
Affairs, 56(2), 938–956. 

Idham, A. (2025). Inovasi Pembelajaran Berbasis Multimedia. Pt Mafy Media Literasi 
Indonesia. 

Idham, A. Z. (2025). Pengaruh Penggunaan TikTok terhadap Penguasaan Kosakata Bahasa 
Inggris Siswa Kelas Sembilan di UPT SPF SMP Negeri 54 Makassar. Jurnal Al-Qiyam, 
6(1), 30–40. 

Idham, A. Z., Alam, F. A., & Usman, U. (2025). The Implementation Of Hypnoteaching Method 
In Improving Students Reading Comprehension. Journal of Educational Sciences, 377–
387. 

Idham, A. Z., Rauf, W., & Rajab, A. (2024). Navigating the Transformative Impact of Artificial 
Intelligence on English Language Teaching: Exploring Challenges and Opportunities. 
Jurnal Edukasi Saintifik, 4(1), 8–14. 

Idham, A. Z. S. (2025). Empowering Reading Comprehension with the Hypnoteaching Method 
(M. P. Ahmad Fathir Imran, S.Pd. (ed.)). Ureka Media Aksara. 

Imran, A. F., Priantinah, D., Syam, S. H. A., & Nurrahmah, N. (2023). Does project-based 
learning affect the motivation to learn accounting during distance learning at SMK 
Negeri 1 Makassar? AIP Conference Proceedings, 2765(1). 

Kayi, E. A. (2024). Transitioning to blended learning during COVID‐19: Exploring instructors 
and adult learners’ experiences in three Ghanaian universities. British Journal of 
Educational Technology, 55(6), 2760–2786. 

Kuantitatif, P. P. (2016). Metode Penelitian Kunatitatif Kualitatif dan R&D. Alfabeta, Bandung. 

Maciejewski, M. L. (2020). Quasi-experimental design. Biostatistics & Epidemiology, 4(1), 38–
47. 

Maphosa, V. (2024). Enhancing authentic learning in a rural university: exploring student 
perceptions of Moodle as a technology-enabled platform. Cogent Education, 11(1), 
2410096. 

Mickenautsch, S., Miletić, I., Rupf, S., Renteria, J., & Göstemeyer, G. (2021). The Composite 
Quality Score (CQS) as a trial appraisal tool: inter-rater reliability and rating time. 
Clinical Oral Investigations, 25(10), 6015–6023. 

http://u.lipi.go.id/1593190689
http://u.lipi.go.id/1593190689


  
 

Copyright © The Author(s) 
Vol.6, No. 4, October 2024 

e-ISSN: 2723-4126 
p-ISSN: 2776-8880 

 

375 
 

Müller, C., Mildenberger, T., & Steingruber, D. (2023). Learning effectiveness of a flexible 
learning study programme in a blended learning design: why are some courses more 
effective than others? International Journal of Educational Technology in Higher 
Education, 20(1), 10. 

Munoz-Organero, M., Munoz-Merino, P. J., & Kloos, C. D. (2009). Student behavior and 
interaction patterns with an LMS as motivation predictors in e-learning settings. IEEE 
Transactions on Education, 53(3), 463–470. 

Nisak, S. K. (2024). Optimizing Interactive Learning Management System (LMS) in Improving 
Students’ English Language Skills. Zabags International Journal of Education, 2(2), 66–
74. 

Nyongesa, W. J., & Van Der Westhuizein, J. (2025). The impact of digital teaching tools on 
student engagement and learning outcomes in higher education in Africa. 

Oguguo, B. C. E., Nannim, F. A., Agah, J. J., Ugwuanyi, C. S., Ene, C. U., & Nzeadibe, A. C. (2021). 
Effect of learning management system on Student’s performance in educational 
measurement and evaluation. Education and Information Technologies, 26, 1471–1483. 

Pesovski, I., Santos, R., Henriques, R., & Trajkovik, V. (2024). Generative AI for customizable 
learning experiences. Sustainability, 16(7), 3034. 

Rahmi, U., Fajri, B. R., & Azrul, A. (2024). Effectiveness of interactive content with H5P for 
Moodle-learning management system in blended learning. Journal of Learning for 
Development, 11(1), 66–81. 

Rauf, W., Idham, A. Z., & Chandra, A. (2025). Penguatan Pariwisata Lokal melalui 
Pembelajaran Bahasa Inggris Berbasis LMS Moodle untuk Kelompok Sadar Wisata 
(Pokdarwis) Desa Bulue. Room of Civil Society Development, 4(1), 90–108. 

Rehman, Z., Tariq, N., Moqurrab, S. A., Yoo, J., & Srivastava, G. (2024). Machine learning and 
internet of things applications in enterprise architectures: Solutions, challenges, and 
open issues. Expert Systems, 41(1), e13467. 

Rekha, A. P. (2024). The learning management system (LMS) and student leaning 
effectiveness: A systematic literature review. International Journal of Research 
Publication and Reviews, 5(6), 1857–1861. 

Setiasih, O., Setiawardani, W., Hidayat, A. N., Djoehaeni, H., Robayanti, D., & RASILAH, M. S. 
(2024). Development of a design learning management system (LMS) to improve 
student skills: Case study in a science learning media development course. Journal of 
Engineering Science and Technology, 19(4), 1389–1400. 

Sibgatullina, A., Ivanova, R., & Yushchik, E. (2022). Moodle learning system as an effective 
tool for implementing the innovation policy of the university. International Journal of 
Web-Based Learning and Teaching Technologies (IJWLTT), 17(1), 1–12. 

Simon, P. D., Jiang, J., Fryer, L. K., King, R. B., & Frondozo, C. E. (2024). An assessment of 
learning management system use in higher education: Perspectives from a 

http://u.lipi.go.id/1593190689
http://u.lipi.go.id/1593190689


  
 

Copyright © The Author(s) 
Vol.6, No. 4, October 2024 

e-ISSN: 2723-4126 
p-ISSN: 2776-8880 

 

376 
 

comprehensive sample of teachers and students. Technology, Knowledge and Learning, 
1–27. 

Siyuan, C., & Wah, L. K. (2024). Blended Learning Approach in Learning English 
Communication Skills for Japanese College Students. Computer-Assisted Language 
Learning Electronic Journal, 25(2), 47–70. 

Suarno, I. N., & Firdaus, M. (2025). Enhancing EFL Students’ Reading Comprehension and 
Motivation through the SQ3R Method. FOSTER: Journal of English Language Teaching, 
6(3), 133–143. 

Sugiyono, P. D. (2017). Metode penelitian bisnis: pendekatan kuantitatif, kualitatif, 
kombinasi, dan R&D. Penerbit CV. Alfabeta: Bandung, 225(87), 48–61. 

Tawfik, A. A., Payne, L., Ketter, H., & James, J. (2025). What instruments do researchers use 
to evaluate LXD? A systematic review study. Technology, Knowledge and Learning, 
30(1), 47–62. 

Theodorakopoulos, L., & Theodoropoulou, A. (2024). Leveraging big data analytics for 
understanding consumer behavior in digital marketing: A systematic review. Human 
Behavior and Emerging Technologies, 2024(1), 3641502. 

Wang, Q., & Mousavi, A. (2023). Which log variables significantly predict academic 
achievement? A systematic review and meta‐analysis. British Journal of Educational 
Technology, 54(1), 142–191. 

Yildiz, E. P., Tezer, M., & Uzunboylu, H. (2018). Student opinion scale related to Moodle LMS 
in an online learning environment: Validity and reliability study. International Journal 
of Interactive Mobile Technologies, 12(4). 

Zainil, M., Helsa, Y., Sutarsih, C., & Nisa, S. (2024). A Needs Analysis on the Utilization of 
Learning Management Systems as Blended Learning Media in Elementary School. 
Journal of Education and E-Learning Research, 11(1), 56–65. 

Zhang, X., Hai, Y. J., & Li, C. (2024). Learning Management System in Education via Mobile 
App: Trends and Patterns in Mobile Learning. International Journal of Interactive 
Mobile Technologies, 18(9). 

 

http://u.lipi.go.id/1593190689
http://u.lipi.go.id/1593190689

