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ISSN: 2454-6186 | DOI: 10.47772/IJRISS
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Assessing the Effectiveness of Text-to-Speech Applications on
Enhancing Listening Comprehension and Student Engagement: A
Quasi-Experimental Studys
*1
Neneng Avrianti,
2
Yohanes Gatot Sutapa Yuliana,
3
Endang Susilawati,
1,2,3
Tanjungpura University, Pontianak, Indonesia
*Corresponding Author
DOI: https://dx.doi.org/10.47772/IJRISS.2025.925ILEIID000081
Received: 23 September 2025; Accepted: 30 September 2025; Published: 07 November 2025
ABSTRACT
This study investigates the effectiveness of Text-to-Speech (TTS) applications in enhancing listening
comprehension and student engagement among Indonesian senior high school students learning English as a
foreign language (EFL). Recognizing the persistent challenge of limited authentic audio materials and low
learner motivation in EFL contexts, this quasi-experimental research employed a non-equivalent control group
design involving 40 tenth-grade students divided into experimental and control groups. Over a three-week
intervention, the experimental group utilized the TTSMaker application, while the control group received
conventional instruction. Data were collected through pre- and post-tests for listening comprehension and
time-on-task observations to assess engagement, analyzed using Multivariate Analysis of Covariance
(MANCOVA) and Analysis of Covariance (ANCOVA). The results demonstrated substantial improvements in
both listening comprehension (Partial Eta² = 0.937) and student engagement (Partial Eta² = 0.929), with the
TTS intervention explaining 96.8% of the variance in post-test outcomes. These findings provide robust
evidence that TTS technology effectively supports EFL learners by offering clear, consistent, and engaging
auditory input that reduces cognitive load and promotes active participation. The study underscores the
pedagogical potential of AI-based applications as accessible, cost-effective, and inclusive tools for improving
English language instruction, particularly in resource-limited educational settings, and calls for further
exploration of their long-term impacts and integration strategies in modern classrooms.
Keywords: Text-to-Speech; listening comprehension; student engagement; educational technology; AI in
education
INTRODUCTION
In recent years, the integration of Artificial Intelligence (AI) in education has transformed traditional teaching
methods, particularly in English as a Foreign Language (EFL) contexts. The growing use of digital tools has
created new opportunities to enhance language learning effectiveness, learner engagement, and accessibility
(Ahmadi, 2018; Masitho Istiqomah et al., 2021) and also to build the students’ motivation (Woo & Choi,
2021). Engagement refers to the active and direct involvement of students in academic activities throughout
the learning process. It can be seen as “energy in action,” emphasizing its dynamic character and showing that
genuine engagement extends beyond passive participation to include active involvement in behavioral,
cognitive, and emotional aspects (Anderman et al., 2024; Cirocki et al., 2024). In educational contexts, Text-to-
Speech (TTS) technology has shown significant value in supporting learning (Widyana et al., 2022). Among
these innovations, Text-to-Speech (TTS) technology has emerged as a promising tool that converts written text
into natural-sounding spoken language, allowing learners to develop listening comprehension through
exposure to authentic pronunciation, intonation, and rhythm (Chen et al., 2021; Dida et al., 2023). TTS
enhances listening skills (Karakaş, 2017; Manu & Masan, 2020; Matsuda, 2017) and promote good
engagement (Al-Jarf, 2022; Amin, 2024; Chiang, 2019; Huang & Liao, 2024). In highlighted, it can improve
language skills like reading fluency, vocabulary, decoding, and pronunciation accuracy, as well as enhance
listening and comprehension of oral instructions. Recent studies show that the software’s support for various
ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
Page 486
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accents helps students understand information better, while their positive attitudes toward TTS promote
flexible learning anytime and anywhere. In Indonesia, teaching listening comprehension remains a persistent
challenge due to the limited availability of native-like audio materials, the high cost of commercial resources,
and low learner motivation (Fitria, 2022; Yudhistiro & Silalahi, 2021). Traditional instruction often relies on
outdated recordings or teacher narration, which may not reflect real-world speech patterns or provide sufficient
linguistic variety (Sherina & Hasnawati, 2023). As a result, students struggle to comprehend authentic spoken
English, limiting their overall language proficiency.
Problem Statement
Despite the increasing availability of AI-based educational technologies, there remains a significant gap in
empirical research examining the effectiveness of Text-to-Speech (TTS) applications for improving both
listening comprehension and student engagement among Indonesian EFL learners. Most prior studies have
focused on pronunciation or reading assistance (Manu & Masan, 2020; Widyana et al., 2022), leaving unclear
whether TTS can meaningfully enhance comprehension and participation in authentic listening contexts. This
gap highlights the urgent need to explore TTS as an innovative, low-cost, and pedagogically sound alternative
to conventional listening instruction. Given these challenges, integrating AI-based TTS applications into
English instruction presents an innovative, cost-effective, and inclusive alternative. This research specifically
explores the effectiveness of the TTSMaker application in enhancing listening comprehension and promoting
student engagement among senior high school learners in Indonesia. The issue is significant because listening
ability forms the foundation for other language skills, and engagement determines long-term language success
(Brown & Lee, 2015; Wang et al., 2024).
Objectives
This study aimed to investigate the pedagogical impact of using Text-to-Speech (TTS) applications in English
language learning for Indonesian EFL students. The specific objectives were to:
1. Evaluate whether the use of the TTSMaker application significantly improves students’ listening
comprehension compared with conventional teaching methods.
2. Determine the extent to which TTS technology enhances student engagement during listening
activities.
3. Assess the overall effectiveness of TTS applications as an accessible educational innovation for
resource-limited learning environments.
These objectives were directly aligned with the problem of inadequate listening instruction in Indonesian
classrooms and aimed to provide empirical evidence supporting the use of AI-driven learning tools for
sustainable English education.
PRODUCT DESCRIPTION & METHODOLOGY
The innovation in this study centers on the Text-to-Speech application, particularly the TTSMaker application,
a free, web-based Text-to-Speech platform that converts English text into natural audio using AI-generated
voices. The software allows teachers to create customizable listening materials that mirror native
pronunciation, adjust speech speed, and accommodate different learner proficiency levels. Unlike conventional
listening activities that rely on static recordings or textbook CDs, TTSMaker offers dynamic, updatable, and
authentic audio content that is accessible anytime and anywhere. Appendix 2.
To evaluate its educational effectiveness, the study employed a quasi-experimental non-equivalent control
group. The participants consisted of 52 tenth-grade students from two existing classes. This study used an
intact group design; each group consisted of 26 students were divided into an experimental group (using
TTSMaker) and a control group (receiving conventional instruction). The planned sample size was 26 students
in each group. However, due to the absence of some students during the treatment, the actual sample analyzed
consisted of 20 students. The analysis was conducted only with students who fully participated in the
treatment/test. This condition is referred to as attrition or subject loss in the study. The intervention lasted three
ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
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weeks (see Appendix 3), focusing on listening comprehension lessons aligned with the national English
curriculum. Listening comprehension was measured using a pre-validated pre- and post-test, with ten multiple-
choice, ten true and false statements, and one inferential question (see Appendix 4).
While student engagement was assessed through Time-on-Task observation employing a 2-minute momentary
time sampling technique that was conducted over 30 minutes pre- and post-test (Fisher et al., 2015; Spanjers et
al., 2008), see Appendix 5. Especially in ToT observation, based on Fisher et al. (2014), divide “time-on-task”
into two categories: on-task and off-task. On-task behavior involves active participation in learning activities
like reading, writing, listening, discussing, or presenting. Off-task behavior includes actions unrelated to the
lesson, classified into four types: irrelevant peer interactions, attention to the environment, self-directed
actions, and other behaviors such as wandering or sleeping (Godwin et al., 2021). A pilot study was conducted
to ensure the reliability and validity of the instruments, so that we could test the effectiveness of data collection
methods and make adjustments before using them with actual participants (Cohen et al., 2018; Mackey &
Gass, 2016). Data collection proceeded in three stages: pre-testing, treatment implementation (integration of
Text-to-Speech applications for the experimental group), and post-testing. Both control and experimental
groups must receive identical initial assessments and identical post-tests, though the initial evaluation may
differ in form from the post-test as long as they assess the same content at the same difficulty level. When
developing these tests, it's crucial to ensure that neither group has an unfair advantage in completing the post-
test, while maintaining consistent content coverage and difficulty across both assessments (Cohen et al., 2018).
The topics for pre-, post-test, and treatment were similar; it was about sport and athletes (see Appendices).
Before data collection, ethical clearance and school permission were obtained. Statistical analyses included
descriptive statistics, assumption testing (using the Shapiro–Wilk test for normality and Levene’s test for
homogeneity), and inferential analysis. To address the first research question, Multivariate Analysis of
Covariance (MANCOVA) was employed to compare posttest outcomes between the experimental and control
groups while controlling for pretest scores. To address the second research question, Analysis of Covariance
(ANCOVA) was applied within the experimental group to examine posttest scores while controlling for
corresponding pretest scores. A significance level of p < 0.05 was used throughout.
POTENTIAL FINDINGS AND COMMERCIALIZATION
This section presents the results of a quasi-experimental study investigating the effect of Text-to-Speech (TTS)
applications on students’ listening comprehension and engagement. Data analysis followed a systematic
process, including assumption testing, descriptive statistics, and inferential analysis. Based on the results of
the descriptive analysis in Table 1, the experimental group’s mean pre-listening score was 59.70 (SD = 1.92,
95% CI [58.80, 60.60]), while the control group obtained a mean score of 60.05 (SD = 1.47, 95% CI [59.36,
60.74]). After the treatment, the experimental group’s mean post-listening score increased to 77.20 (SD =
2.57), which was considerably higher than that of the control group, which reached only 62.20 (SD = 2.46). A
similar trend was observed in engagement scores, where the experimental group showed an improvement from
60.00 to 82.85, while the control group increased slightly from 59.55 to 60.75.
Table 1. Statistics Descriptive.
Variable
Group
Mean
SD
Pre-Listening
Experiment
59.70
1.92
Control
60.05
1.47
Post Listening
Experiment
77.20
2.57
Control
62.20
2.46
Pre Engagement
Experiment
60.00
2.41
Control
59.55
3.28
Post Engagement
Experiment
82.85
3.83
Control
60.75
3.85
ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
Page 488
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In Table 2, the Shapiro-Wilk test confirmed normal data distribution (p > 0.05), and Levene’s test confirmed
the assumption of homogeneity of variances for all variables (p > .05), indicating equal variances between
groups. Independent Samples T-Test results revealed no significant differences between the experimental and
control groups on the Pre-Listening Score (t(38) = -0.647, p = .521) and Pre-Engagement Score (t(38) =
0.494, p = .624), confirming that both groups were equivalent before the treatment. However, the Post-
Listening Score (t(38) = 18.859, p < .001) and Post-Engagement Score (t(38) = 18.200, p < .001) showed
highly significant differences in favor of the experimental group. These results indicate that the
implementation of Text-to-Speech (TTS) applications had a substantial positive effect on students’ listening
comprehension and engagement levels. See Appendix 1.
Table 2. Normality Test
Group
Shapiro-Wilk
Statistic
df
Sig.
Pre Listening
Score
Experime
nt
.966
20
.679
Control
.957
20
.489
Post Listening
Score
Experime
nt
.970
20
.748
Control
.968
20
.714
Pre
Engagement
Score
Experime
nt
.934
20
.181
Control
.932
20
.169
Post
Engagement
Score
Experime
nt
.972
20
.793
Control
.973
20
.821
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The results demonstrated that the integration of TTSMaker significantly improved students’ listening
comprehension and engagement levels compared with conventional instruction. The MANCOVA analysis
revealed highly significant between-group differences (p < 0.001) with very large effect sizes: listening
comprehension (Partial Eta² = 0.937) in Table 3 and engagement (Partial Eta² = 0.929) in Table 4. The
intervention in Table 5 explained 96.8% of the variance in combined post-test outcomes, confirming the robust
impact of TTS-based learning.
Table 3. The Between-Subjects Analysis of Post-test Listening Comprehension
Factor
Significance
Partial Eta²
Effect Size
Pre-test Listening
0.000
0.351
Large
Pre-test Engagement
0.000
0.326
Large
Group
0.000
0.937
Very Large
Table 4. The Between-Subjects Analysis of Post-Test Engagement
Factor
Significance
Partial Eta²
Effect Size
Pre-test Listening
0.434
0.017
Not significant
Pre-test Engagement
0.374
0.022
Not significant
Group
0.000
0.929
Very Large
Table 5. A Multivariate Analysis of Covariance (MANCOVA)
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Effect
Significance
Partial Eta Squared
Interpretation
Pre-test Listening
0.000
-
Significant covariate effect
Pre-test Engagement
0.001
-
Significant covariate effect
Group
0.000
0.968
Very large treatment effect
Within-group analyses also indicated substantial improvement in listening comprehension (p = 0.002; Partial
Eta² = 0.412) in Table 6 and engagement (p = 0.028; Partial Eta² = 0.241) in Table 7,
Table 6. The Within-Group Analysis of Post-Test Engagement
Table 7. The Within-Group Analysis of Post-Test Engagement
This study provides robust empirical evidence for the effectiveness of Text-to-Speech applications in
enhancing listening comprehension and student engagement among Indonesian senior high school students
learning English as a foreign language. The exceptionally large effect sizes observed across all analyses
demonstrate that TTS technology represents a powerful educational tool with significant potential for
transforming English language instruction. The findings address both research questions conclusively. First,
the use of TTS applications significantly and substantially affects students' listening comprehension skills and
engagement compared to traditional methods, with effect sizes that exceed typical educational interventions.
Second, within the experimental group, significant improvements in both listening comprehension and
engagement were observed following the TTS intervention, confirming the technology's direct positive impact.
Based on the time-on-task observations, students in the experimental group using the TTSMaker application
showed noticeably higher engagement throughout the learning sessions. They remained focused on assigned
tasks, actively listened, and interacted meaningfully with the material. Instances of off-task behavior were
minimal, indicating that TTS use sustained students’ attention and encouraged consistent participation in
learning activities.
ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
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Figure 1. MANCOVA and ANCOVA Analyses
Besides that, the students were asked to give their perspective on using Text-to-Speech (TTS) applications that
made learning English more enjoyable and less stressful. They felt that listening to clear, natural-sounding
voices helped them understand pronunciation and meaning more easily than with the technique that is usually
used by the teacher or traditional listening materials. Many students mentioned that the TTS activities
increased their motivation to practice listening outside the classroom and made lessons feel more interactive.
Some also appreciated that they could replay the audio anytime, which helped them learn at their own pace.
Overall, learners perceived TTS as a useful and modern tool that improved both their comprehension and
confidence in learning English.
From a practical perspective, these results suggest that TTS applications like TTSMaker offer a viable and
highly effective solution to the persistent challenges faced by English language educators in Indonesia. The
technology's accessibility, cost-effectiveness, and ease of implementation make it particularly suitable for
resource-limited educational contexts. The ability to create customized, high-quality audio materials addresses
the specific needs of Indonesian EFL learners while providing the flexibility to adapt to rapidly evolving
curriculum requirements. The theoretical implications of this study extend beyond the immediate context,
providing empirical support for the integration of AI-powered educational technologies within established
pedagogical frameworks. The results demonstrate that when properly implemented, TTS technology can
enhance rather than replace traditional instruction, creating synergistic effects that benefit both academic
outcomes and student motivation. However, successful implementation of TTS technology requires careful
consideration of contextual factors, teacher training, and ongoing support. Educational institutions and
policymakers should view these findings as an opportunity to invest in digital infrastructure and professional
development that enables educators to effectively integrate such technologies into their teaching practices.
The implications of this research extend beyond the Indonesian context, offering insights relevant to EFL
instruction globally, particularly in developing countries facing similar resource constraints and technological
integration challenges. The study contributes to the growing body of evidence supporting the transformative
potential of AI-powered educational technologies while providing a model for rigorous evaluation of such
interventions. As we move further into the digital age, the integration of technologies like TTS applications
represents not merely an enhancement to traditional teaching methods but a necessary evolution in educational
practice. The exceptional results observed in this study suggest that embracing such innovations can lead to
substantial improvements in both learning outcomes and student engagement, ultimately contributing to more
effective and inclusive English language education. The success demonstrated in this research should
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encourage educators, administrators, and policymakers to seriously consider TTS technology integration as
part of comprehensive strategies for improving English language instruction. With proper implementation,
support, and continued research, TTS applications have the potential to significantly enhance the quality and
accessibility of English language education, thereby preparing students more effectively for success in our
increasingly interconnected and digitally driven world.
NOVELTY AND RECOMMENDATIONS
This research contributes novelty in two key areas. First, it provides empirical evidence on the pedagogical
benefits of TTS applications in improving listening comprehension and engagement within an Indonesian EFL
context, an area where prior studies were mostly theoretical or limited to small-scale pilot implementations
(Manu & Masan, 2020; Widyana et al., 2022). Second, it demonstrates how AI-powered TTS technology can
serve as a sustainable alternative to traditional listening materials, enabling teachers to create authentic,
adaptive, and cost-free audio resources that cater to diverse learner needs. The study validates Cognitive Load
Theory (Sweller, 1988) by showing that TTS reduces learners’ mental effort during listening, allowing more
focus on comprehension. It also aligns with Social Constructivist Theory (Vygotsky), emphasizing that
engaging in technological tools fosters interactive and collaborative learning experiences.
Future research should examine the long-term effects of TTS integration on language retention, explore learner
and teacher perceptions qualitatively, and compare various TTS platforms to determine the most effective
features for classroom application. Additionally, government and institutional stakeholders are encouraged to
support digital literacy programs and professional development initiatives to facilitate the widespread and
pedagogically sound adoption of AI-driven educational tools.
ACKNOWLEDGEMENTS
The authors would like to express their sincere gratitude to the Department of English Education, Faculty of
Teacher Training and Education, Tanjungpura University, for the continuous academic and administrative
support provided throughout this research. Special appreciation is extended to the participating students and
English teachers at the senior high school in Sui Kunyit, whose cooperation made this study possible. The
authors are also thankful to their colleagues for their constructive feedback and valuable insights during the
research process. This study was conducted independently as part of the authors’ commitment to advancing
English language education and technology-enhanced learning in Indonesia.
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APPENDIX 2
Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F
Sig.
t
df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
Pre-Listening
Score
Equal
variances
assumed
1.390
.246
-.647
38
.521
-.350
.541
-1.445
.745
Equal
variances
not
assumed
-.647
35.539
.522
-.350
.541
-1.447
.747
Post Listening
Score
Equal
variances
assumed
.028
.868
18.859
38
.000
15.000
.795
13.390
16.610
Equal
variances
not
assumed
18.859
37.934
.000
15.000
.795
13.390
16.610
Pre Engagement
Score
Equal
variances
assumed
2.131
.153
.494
38
.624
.450
.910
-1.393
2.293
Equal
variances
not
assumed
.494
34.834
.624
.450
.910
-1.399
2.299
Post
Engagement
Score
Equal
variances
assumed
.022
.884
18.200
38
.000
22.100
1.214
19.642
24.558
Equal
variances
not
assumed
18.200
37.999
.000
22.100
1.214
19.642
24.558
TTS Maker Application
ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
Page 494
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TTSMaker Configuration Parameters
Parameter
Description
Setting Used
Voice Type
Speaker gender
Female
Language
Voice language
English US
Speed
Speech rate
0.85x (slightly slower)
Pitch
Voice tone
Neutral
Output Format
Audio file type
MP3
APPENDIX 3
INTERVENTION PLAN (3 MEETINGS)
Descriptive Text (Monologue & Conversation)
General Theme: Great Athletes
Meeting 1
Monologue: Lionel Messi (Soccer)
Focus: Identifying main ideas and details
Pre-Listening
The teacher shows a photo of Messi.
Q&A: “What do you know about Lionel Messi?”
Vocabulary brainstorming: goal, champion, World Cup, Barcelona, Argentina.
While-Listening
Audio (TTS Monologue about Messi):
“Lionel Messi is one of the most famous football players in the world. He was born in Argentina in 1987.
Messi is known for his dribbling skills, creativity, and teamwork. He played for Barcelona for more than
15 years and scored over 600 goals. In 2022, he helped Argentina win the FIFA World Cup. Messi is
admired for his humility and dedication.”
Task 1 (Main Idea): Students choose the main idea, “Messi’s achievements and qualities as a football
player.”
Task 2 (Details): Students answer multiple choice questions about his birth year, country, number of goals,
and latest achievement.
1. When was Lionel Messi born?
A. In 1985
B. In 1986
C. In 1987
D. In 1988
E. In 1989
2. Where was Lionel Messi born?
A. Brazil
ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
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www.rsisinternational.org
B. Spain
C. Portugal
D. Argentina
E. France
3. How many goals did Messi score for Barcelona?
A. Over 400 goals
B. Over 500 goals
C. Over 600 goals
D. Over 700 goals
E. Over 800 goals
4. What was Messi’s latest achievement mentioned in the text?
A. Winning the UEFA Champions League
B. Becoming Barcelona’s captain
C. Winning the FIFA World Cup
D. Moving to Paris Saint-Germain
E. Retiring from football
5. What is the main idea of the text?
A. Lionel Messi’s journey to becoming a football coach
B. Lionel Messi’s early life and education
C. Lionel Messi’s achievements and qualities as a football player
D. Lionel Messi’s problems during his career
E. Lionel Messi’s life after retirement
Post-Listening
Short discussion: “What qualities of Messi can inspire students?”
Students write three adjectives to describe Messi (example: talented, humble, hardworking).
Meeting 2
Conversation: LeBron James (Basketball)
Focus: Inference (implied meaning)
Pre-Listening
The teacher shows a picture of LeBron James.
Questions: “Do you know LeBron James? What sport does he play?”
Prediction activity: “What achievements might the speakers talk about?”
While-Listening
Audio (TTS Conversation about LeBron):
A: “Have you heard about LeBron James?”
B: “Of course, he is one of the greatest basketball players ever.”
A: “What makes him so famous?”
B: “He has won NBA championships, played in many All-Star games, and is known as a leader on and off
the court.”
A: “Wow, so he inspires people not only by his skills, but also by his personality.”
B: “Exactly, he is also very active in charity and education projects.”
Task 1 (Inference – True/False):
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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
LeBron is respected only for his basketball skills. (F)
His influence outside the court makes him a role model. (T)
LeBron James is known as one of the greatest basketball players ever. (T)
He has never played in any All-Star games. (F)
The conversation shows that LeBron inspires people both by his talent and his character. (T)
Task 2 (Pair Discussion): Students discuss: “What values does LeBron promote beyond sports?”
Post-Listening
Students create a short conversation about another athlete (example: badminton player).
Role-play: one student asks, the other answers.
Meeting 3
Mixed: Novak Djokovic (Tennis) & Michael Phelps (Swimming)
Focus: Evaluating content and communicative purpose
1. Pre-Listening
The teacher shows photos of Djokovic and Phelps.
Questions: “Which sports do they play? What do you know about them?”
2. While-Listening
Audio 1 (Djokovic Monologue):
“Novak Djokovic is a Serbian tennis player. He has won more than 20 Grand Slam titles and is known for
his strong mental focus. Djokovic is also famous for his fitness and consistent performance. He often
speaks about discipline and resilience in sports.”
Audio 2 (Phelps Conversation):
A: “Michael Phelps is amazing, right?”
B: “Yes, he is the most decorated Olympian of all time with 23 gold medals in swimming.”
A: “Unbelievable! What makes him so successful?”
B: “Hard work, daily practice, and determination.”
Task 1 (Evaluation – True/False):
The text about Djokovic aims to describe his hobbies. (F)
The conversation about Phelps expresses admiration for his discipline. (T)
Both texts emphasize the importance of mental and physical preparation. (T)
Novak Djokovic comes from Serbia. (T)
Djokovic is known for being lazy and inconsistent in his performance. (T)
He often talks about discipline and resilience in sports. (T)
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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
Michael Phelps has won 23 gold medals in swimming. (T)
Phelps is described as an ordinary swimmer with few achievements. (F)
According to the conversation, Phelps’s success comes from hard work and daily practice. (T)
Both athletes are known only for their natural talent, not for their discipline or effort. (F)
3. Post-Listening
• Small group discussion: “Which athlete inspires you the most and why?”
• 2–3 minute presentation – students present their discussion results.
APPENDIX 4
Instrument: Listening Comprehension Pre-Test
AUDIO TEXT: Cristiano Ronaldo
"Cristiano Ronaldo is one of the most famous football players in the world. He was born in Madeira, Portugal,
in 1985. Ronaldo is known for his speed, strong shots, and amazing goals. He has played for big clubs like
Manchester United, Real Madrid, and Juventus. With these teams, he won many trophies, including league
titles and the Champions League. Ronaldo also played for the Portugal national team and helped them win the
European Championship in 2016. Many people admire him for his discipline and hard work, both on and off
the field."
Multiple Choice
Listen carefully to the audio. You will hear some questions followed by four possible answers. Choose the
correct answer based on what you hear for numbers 1-5.
1. What is the main idea of the monologue about Cristiano Ronaldo?
A. His personal life
B. His career in different clubs
C. His reputation as a great football player
D. His family background
E. His retirement plan
2. What does the speaker mainly describe about Ronaldo?
A. His trophies only
B. His personality only
C. His birthplace only
D. His overall achievements and qualities
E. His future plans
3. Where was Cristiano Ronaldo born?
A. Madrid
B. Manchester
C. Madeira
D. Lisbon
E. Turin
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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
4. In what year was Cristiano Ronaldo born?
A. 1982
B. 1983
C. 1984
D. 1985
E. 1986
5. Which team did Ronaldo help win the European Championship?
A. Real Madrid
B. Juventus
C. Portugal national team
D. Manchester United
E. Sporting Lisbon
True/False
After listening, decide whether each statement is true or false based on the information in the recording for
numbers 6-10.
No.
Statement
True
False
6.
Ronaldo became successful only because of his natural talent. (T/F)
7.
Ronaldo never played for the Portugal national team. (T/F)
8.
Ronaldo is admired for his dedication. (T/F)
9.
The purpose of the monologue about Ronaldo is to entertain the
audience with a funny story. (T/F)
10.
The text encourages listeners to learn discipline and hard work from an
athlete. (T/F)
AUDIO TEXT: Michael Jordan
A: “Hey, do you know about Michael Jordan?”
B: “Of course! He is considered the greatest basketball player of all time.”
A: “What made him so special?”
B: “He played for the Chicago Bulls and won six NBA championships. His skills, leadership, and competitive
spirit made him different from others.”
A: “Wow, did he only play basketball?”
B: “No, he also tried baseball for a short time, but basketball was always his passion. Even after retiring, he
inspired millions of athletes around the world.”
Multiple Choice
Listen carefully to the audio. You will hear some questions followed by four possible answers. Choose the
correct answer based on what you hear for numbers 11-15.
11. What is the main topic of the conversation?
A. Michael Jordan’s family life
B. Michael Jordan’s career in basketball
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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
C. Michael Jordan’s short baseball career
D. Michael Jordan’s early childhood
E. Michael Jordan’s coaching experience
12. What is the conversation mainly discussing about Jordan?
A. His failures in sports
B. His hobbies outside basketball
C. His role as a coach
D. His greatness as a basketball player
E. His retirement life
13. What makes these two athletes similar according to the texts?
A. Both played tennis
B. Both retired in 2016
C. Both are admired for their achievements and influence
D. Both were born in Portugal
E. Both never played in international competitions
14. How many NBA championships did Michael Jordan win with the Chicago Bulls?
A. Four
B. Five
C. Six
D. Seven
E. Eight
15. What other sport did Michael Jordan try?
A. Tennis
B. Golf
C. Baseball
D. Soccer
E. Swimming
True/False
After listening, decide whether each statement is true or false based on the information in the recording for
numbers 16-20.
No.
Statement
True
False
16.
Jordan’s influence on athletes continues even after his retirement. (T/F)
17.
Jordan’s baseball career was longer than his basketball career. (T/F)
18.
The conversation about Jordan aims to describe why he is considered
the greatest. (T/F)
19.
The text highlights the personal hobbies of the athlete more than their
achievements. (T/F)
20.
The speakers show respect and admiration for Jordan. (T/F)
21. What can you infer about the qualities that make great athletes like Michael Jordan and Ronaldo
successful?
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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
Instrument: Listening Comprehension Post-Test
AUDIO TEXT: Serena Williams
"Serena Williams is one of the greatest tennis players of all time. She was born in Michigan, United States, in
1981. Serena is famous for her powerful serve, strong groundstrokes, and fighting spirit. She won 23 Grand
Slam singles titles, the most in the Open Era. Serena also won Olympic gold medals and became a role model
for many young athletes. In 2022, she retired from professional tennis, but her legacy continues to inspire
people around the world."
Multiple Choice
Listen carefully to the audio. You will hear some questions followed by four possible answers. Choose the
correct answer based on what you hear for numbers 1-5.
1. What is the main idea of the monologue about Serena Williams?
A. Her personal hobbies
B. Her powerful tennis skills and achievements
C. Her childhood memories
D. Her favorite tournaments
E. Her life after retirement
2. What does the speaker mainly describe about Serena Williams?
A. Her injuries during matches
B. Her career as a coach
C. Her Grand Slam victories and influence
D. Her life in Michigan
E. Her retirement hobbies
3. Where was Serena Williams born?
A. New York
B. Los Angeles
C. Michigan
D. Florida
E. Texas
4. In what year was Serena Williams born?
A. 1979
B. 1980
C. 1981
D. 1982
E. 1983
5. How many Grand Slam singles titles did Serena Williams win?
A. 21
B. 22
C. 23
D. 24
E. 25
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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
True/False
After listening, decide whether each statement is true or false based on the information in the recording for
numbers 6-10.
No.
Statement
True
False
6.
Serena Williams is admired only for her physical strength. (T/F)
7.
Serena Williams’ retirement means she is no longer an inspiration. (T/F)
8.
The purpose of the monologue about Serena is to describe her life as a
coach. (T/F)
9.
The text focuses more on the personal hobby of the athlete than his
career. (T/F)
10.
The tone of the text shows admiration for the athlete’s achievements.
(T/F)
AUDIO TEXT: Usain Bolt
A: “Have you ever heard of Usain Bolt?”
B: “Yes, he is the fastest sprinter in history.”
A: “What did he achieve?”
B: “He won eight Olympic gold medals and set world records in the 100 meters and 200 meters.”
A: “That’s incredible! Did he retire already?”
B: “Yes, he retired in 2017, but people still call him the ‘Lightning Bolt’ because of his amazing speed.”
Multiple Choice
Listen carefully to the audio. You will hear some questions followed by four possible answers. Choose the
correct answer based on what you hear for numbers 11-15.
11. What is the main topic of the conversation?
A. Usain Bolt’s life in Jamaica
B. Usain Bolt’s records and achievements in sprinting
C. Usain Bolt’s family background
D. Usain Bolt’s coaching career
E. Usain Bolt’s business after retirement
12. What is the conversation mainly discussing about Usain Bolt?
A. His failures in running
B. His training routine
C. His titles and nickname as the fastest man
D. His personal lifestyle
E. His post-retirement business
13. What does Usain Bolt have in common, according to the texts?
A. Are American athletes
B. Are known as the greatest in their sports
C. Are still competing today
D. Played tennis
E. Were born in the 1990s
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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
14. How many Olympic gold medals did Usain Bolt win?
A. Six
B. Seven
C. Eight
D. Nine
E. Ten
15. When did Usain Bolt retire?
A. 2015
B. 2016
C. 2017
D. 2018
E. 2019
True/False
After listening, decide whether each statement is true or false based on the information in the recording for
numbers 16-20.
No.
Statement
True
False
16.
Usain Bolt’s nickname “Lightning Bolt” shows his incredible speed.
(T/F)
17.
Bolt’s records in sprinting prove his dominance in athletics. (T/F)
18.
The conversation about Bolt highlights his achievements and why he is
respected. (T/F)
19.
Bolt left strong legacies in sports. (T/F)
20.
The text suggests that discipline and determination are key to success.
(T/F)
21. What can you infer about the qualities that make great athletes like Serena Williams and Usain Bolt
successful?
APPENDIX 5
TIME-ON-TASK OBSERVATION SHEET
Date : __________________________________
Class : __________________________________
Observer : __________________________________
Learning Topic : __________________________________
Observation Duration : ______ minutes (Interval: every ___ minutes)
Instructions for Completion:
1. Write On-Task if students are actively engaged in learning according to the criteria.
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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)
ISSN: 2454-6186 | DOI: 10.47772/IJRISS
Special Issue | Volume IX Issue XXV October 2025
2. Write Off-Task column if students show disengaged behavior.
3. Record a brief description of the behavior in the column for each student.
No.
Interval
Timing
(minutes)
Student 1
Student 2
Student 3
Student 4
Student 5
1
0 – 2
2
2 – 4
3
4 – 6
4
6 – 8
5
8 – 10
6
10 – 12
7
12 – 14
8
14 – 16
9
16 – 18
10
18 – 20
11
20 – 22
12
22 – 24
13
24 – 26
14
26 – 28
15
28 – 30