Vol. 13/ Núm. 2 2026 pág. 1648
https://doi.org/10.69639/arandu.v13i2.2291
The Effectiveness of Using the Web Tool Vocaroo on
Vocabulary Learning in A1 English Learners
La eficacia del uso de la herramienta web Vocaroo en el aprendizaje de vocabulario en
estudiantes de inglés de nivel A1
Christian Giovanny Tupiza Villamar
cgtupizanv@ube.edu.ec
https://orcid.org/0009-0008-9899-6470
Universidad Bolivariana del Ecuador
Ecuador
Josué Reinaldo Bonilla Tenesaca
jrbonillat@ube.edu.ec
https://orcid.org/0000-0002-6748-2345
Universidad Bolivariana del Ecuador
Ecuador
Johnny Segundo Campoverde López
jscampoverdel@ube.edu.ec
https://orcid.org/0000-0003-0108-4755
Universidad Bolivariana del Ecuador
Ecuador
Artículo recibido: 10 abril 2026- Aceptado para publicación:16 mayo 2026
Conflictos de intereses: Ninguno que declarar.
ABSTRACT
This study investigated the effectiveness of the web tool Vocaroo on vocabulary learning in A1
English learners. An action research design with a mixed-methods explanatory sequential
approach was employed, conducted at a public educational institution in Quito, Ecuador. Thirty
A1-level students participated over 4 weeks (8 sessions). Instruments included a vocabulary pre-
test and post-test, a Likert scale survey based on Self-Determination Theory, and a researcher's
learning log. Results showed a significant improvement in vocabulary scores from 11.8 to 24.6
out of 30 (108.5% increase, p < 0.001), with a very large effect size (Cohen's d = 2.8). The survey
revealed high motivation and engagement (overall mean = 4.6/5), and 100% of students expressed
desire to continue using Vocaroo. A strong positive correlation (r = 0.72, p < 0.01) was found
between motivation and vocabulary gains. Thematic analysis of the learning log identified five
themes: progressive increase in engagement, reduction of speaking anxiety, development of
autonomy, overcoming technical barriers, and positive transformation of classroom dynamics.
Keywords:, vocabulary learning, A1 learners, EFL teaching, web tools, audio recording
Vol. 13/ Núm. 2 2026 pág. 1649
RESUMEN
Este estudio investigó la efectividad de la herramienta web Vocaroo en el aprendizaje de
vocabulario en estudiantes de inglés nivel A1. Se empleó un diseño de investigación-acción
con enfoque de métodos mixtos de tipo secuencial explicativo, realizado en una institución
educativa pública de Quito, Ecuador. Participaron 30 estudiantes de nivel A1 durante 4
semanas (8 sesiones). Los instrumentos incluyeron un pre-test y post-test de vocabulario, una
encuesta de escala Likert basada en la Teoría de la Autodeterminación, y un diario de
aprendizaje del investigador. Los resultados mostraron una mejora significativa en las
puntuaciones de vocabulario (11.8 a 24.6, 108.5%, p < 0.001), con un tamaño del efecto muy
grande (d de Cohen = 2.8). La encuesta reveló una alta motivación y compromiso (media total =
4.6/5), y el 100% de los estudiantes desea continuar usando Vocaroo. Se encontró una
correlación positiva fuerte (r = 0.72, p < 0.01) entre motivación y ganancias de vocabulario. El
análisis temático del diario de aprendizaje identificó cinco temas: aumento progresivo del
compromiso, reducción de la ansiedad al hablar, desarrollo de autonomía, superación de
barreras técnicas y transformación positiva de la dinámica del aula.
Palabras clave: vocaroo, aprendizaje de vocabulario, estudiantes A1, enseñanza del
inglés como lengua extranjera, herramientas web, grabación de audio
Todo el contenido de la Revista Científica Internacional Arandu UTIC publicado en este sitio está disponible bajo
licencia Creative Commons Atribution 4.0 International.
RESUMEN
Este estudio investigó la efectividad de la herramienta web Vocaroo en el aprendizaje de
vocabulario en estudiantes de inglés nivel A1. Se empleó un diseño de investigación-acción
con enfoque de métodos mixtos de tipo secuencial explicativo, realizado en una institución
educativa pública de Quito, Ecuador. Participaron 30 estudiantes de nivel A1 durante 4
semanas (8 sesiones). Los instrumentos incluyeron un pre-test y post-test de vocabulario, una
encuesta de escala Likert basada en la Teoría de la Autodeterminación, y un diario de
aprendizaje del investigador. Los resultados mostraron una mejora significativa en las
puntuaciones de vocabulario (11.8 a 24.6, 108.5%, p < 0.001), con un tamaño del efecto muy
grande (d de Cohen = 2.8). La encuesta reveló una alta motivación y compromiso (media total =
4.6/5), y el 100% de los estudiantes desea continuar usando Vocaroo. Se encontró una
correlación positiva fuerte (r = 0.72, p < 0.01) entre motivación y ganancias de vocabulario. El
análisis temático del diario de aprendizaje identificó cinco temas: aumento progresivo del
compromiso, reducción de la ansiedad al hablar, desarrollo de autonomía, superación de
barreras técnicas y transformación positiva de la dinámica del aula.
Palabras clave: vocaroo, aprendizaje de vocabulario, estudiantes A1, enseñanza del
inglés como lengua extranjera, herramientas web, grabación de audio
Todo el contenido de la Revista Científica Internacional Arandu UTIC publicado en este sitio está disponible bajo
licencia Creative Commons Atribution 4.0 International.
Vol. 13/ Núm. 2 2026 pág. 1650
INTRODUCTION
Vocabulary is a fundamental component of second language acquisition, as it facilitates
effective communication between speakers. For A1 English learners according to the Common
European Framework of Reference (CEFR, 2018), acquiring basic vocabulary is essential for
developing the four macro skills: listening, speaking, reading, and writing. As Webb and Nation
(2017) explain, vocabulary knowledge is not merely about knowing a word's meaning but
involves multiple dimensions including form, meaning, and use.
Schmitt (2019) emphasizes that vocabulary acquisition is the foundation upon which all
other language skills are built, arguing that without sufficient vocabulary, learners cannot fully
engage in meaningful communication.
In the Latin American context, and particularly in Ecuador, A1 English learners face
multiple challenges. Recent research has documented that "lack of vocabulary" remains one of the
primary obstacles to oral communication (Vargas Saritama & Guerra Vinueza, 2023).
Furthermore, studies by Ortega Auquilla and Vázquez Barros (2020) found that Ecuadorian
public school classrooms are often overcrowded, technological resources are limited, and
traditional teaching methods relying on written repetition and translation persist, which fail to
develop accurate pronunciation or active oral production. Affective barriers such as "fear of
making mistakes" continue to inhibit students' oral participation (Jaramillo Pontón & Veloz
Armas, 2023).
Technology has emerged as an ally in vocabulary instruction. Among available tools,
Vocaroo stands out for being free, requiring no registration or installation, and allowing audio
recordings that can be shared via links. Recent systematic reviews by Zhang and Zou (2022)
confirm that simple, low-threshold technological tools are particularly effective in low-resource
educational contexts. However, there remains a gap in the literature regarding the effectiveness
of simple audio recording tools like Vocaroo specifically for vocabulary learning in A1 learners
in such contexts.
Self-Determination Theory (Ryan & Deci, 2017) provides the theoretical framework for
this study, positing that the satisfaction of three basic psychological needs (autonomy,
competence, and relatedness) sustains learners' intrinsic motivation. Research by Li (2021)
applying SDT to technology-enhanced language learning has demonstrated that tools allowing
learner control and self-pacing significantly enhance motivation and learning outcomes.
Technological tools like Vocaroo can satisfy these needs by allowing students to work at their
own pace (autonomy), receive immediate feedback on their pronunciation (competence), and
share recordings with peers and teacher (relatedness).
The general objective of this study was to determine the effectiveness of using the web
tool Vocaroo on vocabulary acquisition in A1 English learners. Specifically, it sought to: (1)
INTRODUCTION
Vocabulary is a fundamental component of second language acquisition, as it facilitates
effective communication between speakers. For A1 English learners according to the Common
European Framework of Reference (CEFR, 2018), acquiring basic vocabulary is essential for
developing the four macro skills: listening, speaking, reading, and writing. As Webb and Nation
(2017) explain, vocabulary knowledge is not merely about knowing a word's meaning but
involves multiple dimensions including form, meaning, and use.
Schmitt (2019) emphasizes that vocabulary acquisition is the foundation upon which all
other language skills are built, arguing that without sufficient vocabulary, learners cannot fully
engage in meaningful communication.
In the Latin American context, and particularly in Ecuador, A1 English learners face
multiple challenges. Recent research has documented that "lack of vocabulary" remains one of the
primary obstacles to oral communication (Vargas Saritama & Guerra Vinueza, 2023).
Furthermore, studies by Ortega Auquilla and Vázquez Barros (2020) found that Ecuadorian
public school classrooms are often overcrowded, technological resources are limited, and
traditional teaching methods relying on written repetition and translation persist, which fail to
develop accurate pronunciation or active oral production. Affective barriers such as "fear of
making mistakes" continue to inhibit students' oral participation (Jaramillo Pontón & Veloz
Armas, 2023).
Technology has emerged as an ally in vocabulary instruction. Among available tools,
Vocaroo stands out for being free, requiring no registration or installation, and allowing audio
recordings that can be shared via links. Recent systematic reviews by Zhang and Zou (2022)
confirm that simple, low-threshold technological tools are particularly effective in low-resource
educational contexts. However, there remains a gap in the literature regarding the effectiveness
of simple audio recording tools like Vocaroo specifically for vocabulary learning in A1 learners
in such contexts.
Self-Determination Theory (Ryan & Deci, 2017) provides the theoretical framework for
this study, positing that the satisfaction of three basic psychological needs (autonomy,
competence, and relatedness) sustains learners' intrinsic motivation. Research by Li (2021)
applying SDT to technology-enhanced language learning has demonstrated that tools allowing
learner control and self-pacing significantly enhance motivation and learning outcomes.
Technological tools like Vocaroo can satisfy these needs by allowing students to work at their
own pace (autonomy), receive immediate feedback on their pronunciation (competence), and
share recordings with peers and teacher (relatedness).
The general objective of this study was to determine the effectiveness of using the web
tool Vocaroo on vocabulary acquisition in A1 English learners. Specifically, it sought to: (1)
Vol. 13/ Núm. 2 2026 pág. 1651
diagnose and compare vocabulary acquisition levels before and after the intervention, (2)
implement and document a set of Vocaroo-based activities, (3) evaluate the correlation between
student engagement with Vocaroo and vocabulary gains, and (4) integrate quantitative and
qualitative findings. The hypothesis was that using Vocaroo produces significant improvement in
vocabulary acquisition in A1 students, with a large effect size.
MATERIALS AND METHODS
Research Approach and Design
This study employed an action research approach within a mixed-methods framework,
specifically an explanatory sequential design (Creswell & Plano Clark, 2018). Action research
was selected as the overarching methodology because the researcher is also a teacher-practitioner
seeking to solve a concrete pedagogical problem in their own classroom: low vocabulary
retention, poor pronunciation accuracy, and high speaking anxiety among A1 English learners in
a public school context. Unlike purely experimental research conducted in controlled laboratory
settings, action research is situated within the naturalistic classroom environment and emphasizes
iterative cycles of planning, action, observation, and reflection (Kemmis, McTaggart, & Nixon,
2014). This approach was appropriate because the goal was not merely to measure learning
outcomes but to implement a practical intervention (Vocaroo), evaluate its effectiveness in real
time, and generate actionable knowledge that could directly improve teaching practice.
The action research design followed four cyclical phases over the 4-week intervention
period. In the planning phase, the researcher identified the specific vocabulary learning problems
through initial observation and a diagnostic pre-test, then designed eight Vocaroo-based activities
aligned with the curriculum and the Self-Determination Theory framework. In the action phase,
the researcher implemented the intervention over eight sessions, maintaining a structured learning
log after each session to document immediate observations. In the observation phase, the
researcher collected quantitative data (post-test and survey) and continued qualitative
observations, noting changes in student behavior, engagement levels, and technical challenges. In
the reflection phase, conducted after the intervention, the researcher integrated the quantitative
and qualitative findings to evaluate the overall effectiveness of Vocaroo and to identify lessons
for future implementation. This cyclical structure allowed for ongoing adjustments; for example,
after observing technical difficulties in Sessions 1 and 2, the researcher incorporated peer
troubleshooting and backup paper-based activities in Session 3.
The mixed-methods framework was specifically operationalized as an explanatory
sequential design. In this design, quantitative data collection and analysis occur first, followed by
qualitative data collection and analysis, with the qualitative data serving to explain, elaborate on,
or contextualize the quantitative results (Creswell & Plano Clark, 2018). The rationale for
selecting this design over a concurrent design (where both types of data are collected
diagnose and compare vocabulary acquisition levels before and after the intervention, (2)
implement and document a set of Vocaroo-based activities, (3) evaluate the correlation between
student engagement with Vocaroo and vocabulary gains, and (4) integrate quantitative and
qualitative findings. The hypothesis was that using Vocaroo produces significant improvement in
vocabulary acquisition in A1 students, with a large effect size.
MATERIALS AND METHODS
Research Approach and Design
This study employed an action research approach within a mixed-methods framework,
specifically an explanatory sequential design (Creswell & Plano Clark, 2018). Action research
was selected as the overarching methodology because the researcher is also a teacher-practitioner
seeking to solve a concrete pedagogical problem in their own classroom: low vocabulary
retention, poor pronunciation accuracy, and high speaking anxiety among A1 English learners in
a public school context. Unlike purely experimental research conducted in controlled laboratory
settings, action research is situated within the naturalistic classroom environment and emphasizes
iterative cycles of planning, action, observation, and reflection (Kemmis, McTaggart, & Nixon,
2014). This approach was appropriate because the goal was not merely to measure learning
outcomes but to implement a practical intervention (Vocaroo), evaluate its effectiveness in real
time, and generate actionable knowledge that could directly improve teaching practice.
The action research design followed four cyclical phases over the 4-week intervention
period. In the planning phase, the researcher identified the specific vocabulary learning problems
through initial observation and a diagnostic pre-test, then designed eight Vocaroo-based activities
aligned with the curriculum and the Self-Determination Theory framework. In the action phase,
the researcher implemented the intervention over eight sessions, maintaining a structured learning
log after each session to document immediate observations. In the observation phase, the
researcher collected quantitative data (post-test and survey) and continued qualitative
observations, noting changes in student behavior, engagement levels, and technical challenges. In
the reflection phase, conducted after the intervention, the researcher integrated the quantitative
and qualitative findings to evaluate the overall effectiveness of Vocaroo and to identify lessons
for future implementation. This cyclical structure allowed for ongoing adjustments; for example,
after observing technical difficulties in Sessions 1 and 2, the researcher incorporated peer
troubleshooting and backup paper-based activities in Session 3.
The mixed-methods framework was specifically operationalized as an explanatory
sequential design. In this design, quantitative data collection and analysis occur first, followed by
qualitative data collection and analysis, with the qualitative data serving to explain, elaborate on,
or contextualize the quantitative results (Creswell & Plano Clark, 2018). The rationale for
selecting this design over a concurrent design (where both types of data are collected
Vol. 13/ Núm. 2 2026 pág. 1652
simultaneously) or an exploratory design (qualitative first) was threefold. First, the primary
research question was fundamentally quantitative: "Does Vocaroo significantly improve
vocabulary acquisition?" Therefore, the study required robust statistical evidence of learning
gains (pre-test/post-test comparison) and correlation (motivation and vocabulary gains). Second,
the qualitative component (the researcher's learning log) was designed not as an independent
source of discovery but as a complementary explanatory mechanism; to answer the "why" and
"how" behind the statistical results. For instance, if the quantitative data showed a large effect
size, the learning log could explain that this was due to progressive anxiety reduction and
autonomy development. Third, collecting qualitative data after the intervention (rather than
during a separate phase) allowed the researcher to return to the quantitative findings with specific
explanatory questions already in mind, increasing the interpretative power of the qualitative
analysis.
The design was also quasi-experimental with a single group assessed before and after the
intervention (one-group pre-test/post-test design). This design is common in action research and
educational interventions where random assignment is not feasible due to intact classroom
structures and ethical constraints (Cohen, Manion, & Morrison, 2018). The absence of a control
group is a recognized limitation, which is addressed explicitly in the limitations section. However,
the use of a pre-test/post-test design within an action research framework is justified because the
primary purpose was to measure change within the same group over time, using each student as
their own control, rather than to compare against an untreated group. This design is particularly
sensitive to detecting individual differences in learning gains and allows for correlational analysis
between motivation and improvement.
To strengthen the validity of the quasi-experimental design, several procedures were
implemented. First, the pre-test and post-test were identical in content and format, administered
under the same conditions (same time of day, same classroom, same instructions) to ensure
comparability. Second, the intervention was delivered by the same researcher-teacher across all
sessions to maintain consistency. Third, a 2-week period separated the pre-test from the beginning
of the intervention to minimize testing effects, and no vocabulary instruction occurred during that
interval. Fourth, the statistical analysis included effect size calculation (Cohen's d) to quantify the
magnitude of the improvement beyond mere statistical significance, as recommended by Plonsky
and Oswald (2014) for second language acquisition research.
The integration of quantitative and qualitative strands occurred at two levels. First, during
the analysis phase, the quantitative results were tabulated and interpreted, and then the qualitative
learning log was thematically analyzed to identify patterns that could explain the quantitative
findings. Second, during the interpretation phase (presented in the Discussion section), the
qualitative themes were explicitly linked to the statistical results, for example, by showing how
the theme "reduction of speaking anxiety" explained the large gains in pronunciation accuracy
simultaneously) or an exploratory design (qualitative first) was threefold. First, the primary
research question was fundamentally quantitative: "Does Vocaroo significantly improve
vocabulary acquisition?" Therefore, the study required robust statistical evidence of learning
gains (pre-test/post-test comparison) and correlation (motivation and vocabulary gains). Second,
the qualitative component (the researcher's learning log) was designed not as an independent
source of discovery but as a complementary explanatory mechanism; to answer the "why" and
"how" behind the statistical results. For instance, if the quantitative data showed a large effect
size, the learning log could explain that this was due to progressive anxiety reduction and
autonomy development. Third, collecting qualitative data after the intervention (rather than
during a separate phase) allowed the researcher to return to the quantitative findings with specific
explanatory questions already in mind, increasing the interpretative power of the qualitative
analysis.
The design was also quasi-experimental with a single group assessed before and after the
intervention (one-group pre-test/post-test design). This design is common in action research and
educational interventions where random assignment is not feasible due to intact classroom
structures and ethical constraints (Cohen, Manion, & Morrison, 2018). The absence of a control
group is a recognized limitation, which is addressed explicitly in the limitations section. However,
the use of a pre-test/post-test design within an action research framework is justified because the
primary purpose was to measure change within the same group over time, using each student as
their own control, rather than to compare against an untreated group. This design is particularly
sensitive to detecting individual differences in learning gains and allows for correlational analysis
between motivation and improvement.
To strengthen the validity of the quasi-experimental design, several procedures were
implemented. First, the pre-test and post-test were identical in content and format, administered
under the same conditions (same time of day, same classroom, same instructions) to ensure
comparability. Second, the intervention was delivered by the same researcher-teacher across all
sessions to maintain consistency. Third, a 2-week period separated the pre-test from the beginning
of the intervention to minimize testing effects, and no vocabulary instruction occurred during that
interval. Fourth, the statistical analysis included effect size calculation (Cohen's d) to quantify the
magnitude of the improvement beyond mere statistical significance, as recommended by Plonsky
and Oswald (2014) for second language acquisition research.
The integration of quantitative and qualitative strands occurred at two levels. First, during
the analysis phase, the quantitative results were tabulated and interpreted, and then the qualitative
learning log was thematically analyzed to identify patterns that could explain the quantitative
findings. Second, during the interpretation phase (presented in the Discussion section), the
qualitative themes were explicitly linked to the statistical results, for example, by showing how
the theme "reduction of speaking anxiety" explained the large gains in pronunciation accuracy
Vol. 13/ Núm. 2 2026 pág. 1653
(Section 3 of the test). This integration is visually represented in the results and discussion
sections through joint display of quantitative tables and qualitative excerpts.
Finally, the research design was documented using the good reporting practices for
mixed-methods research in applied linguistics (Plonsky, 2017), including explicit specification of
the priority (quantitative priority with qualitative support), the timing (sequential: quantitative →
qualitative), and the point of integration (analysis and interpretation phases).
Context and Participants
The study was conducted at a public educational institution in Quito, Ecuador. Thirty
first-year secondary school students participated. Table 1 provides the exact demographic
breakdown of the participant sample.
Table 1
Demographic Characteristics of Participants (n=30)
Characteristic Category Number of Students Percentage (%)
Age 14 years 18 60%
15 years 12 40%
Sex Female 16 53.3%
Male 14 46.7%
English Level (CEFR) A1 (beginner) 30 100%
Smartphone access at home Yes 26 86.7%
No 4 13.3%
All students were officially classified as A1 beginners according to institutional placement
tests aligned with the CEFR (2018). The institution had limited technological resources: one
computer lab with 15 functioning computers and intermittent internet connectivity. However,
approximately 85% of students possessed basic smartphones with internet access at home. This
socioeconomic profile aligns with the contextual challenges described by Mosquera Endara et al.
(2020) in Ecuadorian public education.
Intervention
The intervention lasted 4 weeks with two 45-minute sessions per week (8 sessions total).
Each session focused on specific vocabulary themes (family members, food and drinks, daily
routines) and progressively built students' skills from basic recording to self-assessment and peer
feedback. Activities included: basic recording and playback, comparing with model recordings,
word of the day recording, peer listening and feedback, audio vocabulary journal, minimal pairs
pronunciation practice, vocabulary quiz recording, and final showcase.
Instruments
Three instruments were used for triangulation:
1. Vocabulary Pre-Test and Post-Test (Quantitative): Adapted from Schmitt (2010), the
(Section 3 of the test). This integration is visually represented in the results and discussion
sections through joint display of quantitative tables and qualitative excerpts.
Finally, the research design was documented using the good reporting practices for
mixed-methods research in applied linguistics (Plonsky, 2017), including explicit specification of
the priority (quantitative priority with qualitative support), the timing (sequential: quantitative →
qualitative), and the point of integration (analysis and interpretation phases).
Context and Participants
The study was conducted at a public educational institution in Quito, Ecuador. Thirty
first-year secondary school students participated. Table 1 provides the exact demographic
breakdown of the participant sample.
Table 1
Demographic Characteristics of Participants (n=30)
Characteristic Category Number of Students Percentage (%)
Age 14 years 18 60%
15 years 12 40%
Sex Female 16 53.3%
Male 14 46.7%
English Level (CEFR) A1 (beginner) 30 100%
Smartphone access at home Yes 26 86.7%
No 4 13.3%
All students were officially classified as A1 beginners according to institutional placement
tests aligned with the CEFR (2018). The institution had limited technological resources: one
computer lab with 15 functioning computers and intermittent internet connectivity. However,
approximately 85% of students possessed basic smartphones with internet access at home. This
socioeconomic profile aligns with the contextual challenges described by Mosquera Endara et al.
(2020) in Ecuadorian public education.
Intervention
The intervention lasted 4 weeks with two 45-minute sessions per week (8 sessions total).
Each session focused on specific vocabulary themes (family members, food and drinks, daily
routines) and progressively built students' skills from basic recording to self-assessment and peer
feedback. Activities included: basic recording and playback, comparing with model recordings,
word of the day recording, peer listening and feedback, audio vocabulary journal, minimal pairs
pronunciation practice, vocabulary quiz recording, and final showcase.
Instruments
Three instruments were used for triangulation:
1. Vocabulary Pre-Test and Post-Test (Quantitative): Adapted from Schmitt (2010), the
Vol. 13/ Núm. 2 2026 pág. 1654
test consisted of 30 total points: 15 points for vocabulary breadth (recognition), 10 points
for vocabulary depth (production), and 5 points for pronunciation accuracy using a 4-point
rubric adapted from Yorulmaz and Altay (2025). The same test was administered before
and after the intervention.
2. Likert Scale Survey (Quantitative): A 10-item, 5-point Likert scale survey (1=strongly
disagree, 5=strongly agree) measured students' perceived motivation, engagement, and
satisfaction of the three psychological needs (autonomy, competence, relatedness) based
on Self-Determination Theory (Ryan & Deci, 2017). It was administered after the post-
test.
3. Researcher's Learning Log (Qualitative): A structured log maintained after each of the 8
sessions documented student engagement, technical difficulties, behavioral changes, and
researcher reflections. Data were analyzed using thematic analysis (Braun & Clarke,
2013).
Ethical Considerations
Ethical considerations followed the guidelines of the American Educational Research
Association (AERA, 2011). Prior to data collection, informed consent was obtained from the
parents or legal guardians of all participating students through a formal letter explaining the
study's purpose, procedures, risks, and benefits. Additionally, written assent was obtained from
the students themselves after the study was explained in age-appropriate language. Participation
was entirely voluntary, and students could withdraw at any time without academic penalty.
Anonymity was guaranteed by assigning each participant a code number; names were never
recorded on tests or survey instruments. Data were stored on a password-protected computer
accessible only to the researcher.
Data Analysis
Quantitative data were analyzed using paired-sample t-tests, descriptive statistics, and
Pearson correlation coefficients using SPSS version 26. Qualitative data from the learning log
were analyzed using reflexive thematic analysis following Braun and Clarke's (2013) six-phase
process.
RESULTS AND DISCUSSION
Quantitative Results
Pre-Test and Post-Test Results
The vocabulary test consisted of 30 total points: 15 for vocabulary breadth (recognition),
10 for vocabulary depth (production), and 5 for pronunciation accuracy. Table 2 presents a
comparison of the pre-test and post-test vocabulary scores for the 30 participants.
test consisted of 30 total points: 15 points for vocabulary breadth (recognition), 10 points
for vocabulary depth (production), and 5 points for pronunciation accuracy using a 4-point
rubric adapted from Yorulmaz and Altay (2025). The same test was administered before
and after the intervention.
2. Likert Scale Survey (Quantitative): A 10-item, 5-point Likert scale survey (1=strongly
disagree, 5=strongly agree) measured students' perceived motivation, engagement, and
satisfaction of the three psychological needs (autonomy, competence, relatedness) based
on Self-Determination Theory (Ryan & Deci, 2017). It was administered after the post-
test.
3. Researcher's Learning Log (Qualitative): A structured log maintained after each of the 8
sessions documented student engagement, technical difficulties, behavioral changes, and
researcher reflections. Data were analyzed using thematic analysis (Braun & Clarke,
2013).
Ethical Considerations
Ethical considerations followed the guidelines of the American Educational Research
Association (AERA, 2011). Prior to data collection, informed consent was obtained from the
parents or legal guardians of all participating students through a formal letter explaining the
study's purpose, procedures, risks, and benefits. Additionally, written assent was obtained from
the students themselves after the study was explained in age-appropriate language. Participation
was entirely voluntary, and students could withdraw at any time without academic penalty.
Anonymity was guaranteed by assigning each participant a code number; names were never
recorded on tests or survey instruments. Data were stored on a password-protected computer
accessible only to the researcher.
Data Analysis
Quantitative data were analyzed using paired-sample t-tests, descriptive statistics, and
Pearson correlation coefficients using SPSS version 26. Qualitative data from the learning log
were analyzed using reflexive thematic analysis following Braun and Clarke's (2013) six-phase
process.
RESULTS AND DISCUSSION
Quantitative Results
Pre-Test and Post-Test Results
The vocabulary test consisted of 30 total points: 15 for vocabulary breadth (recognition),
10 for vocabulary depth (production), and 5 for pronunciation accuracy. Table 2 presents a
comparison of the pre-test and post-test vocabulary scores for the 30 participants.
Vol. 13/ Núm. 2 2026 pág. 1655
Table 2
Comparison of Pre-Test and Post-Test Vocabulary Scores
Measure Pre-Test Post-Test Gain Percentage Improvement
Class Mean Score (out of 30) 11.8 24.6 +
12.8
108.5%
Median Score 12.0 25.0 13.0 108.3%
Highest Score 18.0 29.0 +11.0 61.1%
Lowest Score 6.0 19.0 +13.0 216.7%
Standard Deviation 3.2 2.8 -0.4 -
The results show a dramatic shift in score distribution. Before the intervention, the class
mean was 11.8 out of 30, indicating that students knew less than 40% of the target vocabulary.
After the intervention, the mean increased to 24.6, representing a gain of 12.8 points and a
percentage improvement of 108.5%. This more-than-doubling of scores suggests that the Vocaroo
intervention had a substantial positive impact on vocabulary learning. The standard deviation
decreased slightly from 3.2 to 2.8, indicating that the intervention not only raised scores overall
but also reduced the performance gap between higher- and lower-achieving students.
To better visualize the transformation in student performance, the distribution of scores
across three proficiency ranges (low, intermediate, and high) was analyzed. Figure 1 illustrates
the distribution of students across these score ranges before and after the intervention. The figure
allows for a visual comparison of how many students moved from low and intermediate
performance levels to high performance levels following the four-week Vocaroo intervention.
This type of distribution analysis is important because it reveals not only average improvements
but also whether the intervention benefited all students or only certain subgroups.
Figure 1
Distribution of Students by Score Range Before and After Intervention
Description of Figure 1: The figure consists of two side-by-side bar charts. The left bar
chart represents the pre-test distribution, and the right bar chart represents the post-test
distribution. The vertical axis shows the number of students (0 to 30), and the horizontal axis
Table 2
Comparison of Pre-Test and Post-Test Vocabulary Scores
Measure Pre-Test Post-Test Gain Percentage Improvement
Class Mean Score (out of 30) 11.8 24.6 +
12.8
108.5%
Median Score 12.0 25.0 13.0 108.3%
Highest Score 18.0 29.0 +11.0 61.1%
Lowest Score 6.0 19.0 +13.0 216.7%
Standard Deviation 3.2 2.8 -0.4 -
The results show a dramatic shift in score distribution. Before the intervention, the class
mean was 11.8 out of 30, indicating that students knew less than 40% of the target vocabulary.
After the intervention, the mean increased to 24.6, representing a gain of 12.8 points and a
percentage improvement of 108.5%. This more-than-doubling of scores suggests that the Vocaroo
intervention had a substantial positive impact on vocabulary learning. The standard deviation
decreased slightly from 3.2 to 2.8, indicating that the intervention not only raised scores overall
but also reduced the performance gap between higher- and lower-achieving students.
To better visualize the transformation in student performance, the distribution of scores
across three proficiency ranges (low, intermediate, and high) was analyzed. Figure 1 illustrates
the distribution of students across these score ranges before and after the intervention. The figure
allows for a visual comparison of how many students moved from low and intermediate
performance levels to high performance levels following the four-week Vocaroo intervention.
This type of distribution analysis is important because it reveals not only average improvements
but also whether the intervention benefited all students or only certain subgroups.
Figure 1
Distribution of Students by Score Range Before and After Intervention
Description of Figure 1: The figure consists of two side-by-side bar charts. The left bar
chart represents the pre-test distribution, and the right bar chart represents the post-test
distribution. The vertical axis shows the number of students (0 to 30), and the horizontal axis
Vol. 13/ Núm. 2 2026 pág. 1656
shows three score ranges: Low (0-10 points), Intermediate (11-20 points), and High (21-30
points). In the pre-test, the bars show: 9 students in the Low range, 19 students in the Intermediate
range, and 2 students in the High range. In the post-test, the bars show: 0 students in the Low
range, 4 students in the Intermediate range, and 26 students in the High range.
The results in Figure 1 show a dramatic shift in score distribution. Before the intervention,
only 2 students (6%) scored in the high range (21-30 points). After the intervention, 26 students
(87%) scored in the high range, representing an increase of 81 percentage points. Notably, no
students remained in the low range (0-10) after the intervention, whereas 9 students (30%) had
been in that range before the intervention. The intermediate range (11-20 points) also decreased
from 19 students (63%) before the intervention to 4 students (13%) after the intervention,
indicating that most students moved from intermediate to high performance. This distributional
shift suggests that the Vocaroo intervention was effective across the entire ability spectrum, from
the lowest-performing to the highest-performing students.
Table 3 presents the results disaggregated by the three test sections: vocabulary breadth
(recognition), vocabulary depth (production), and pronunciation accuracy. This disaggregation is
important because it reveals which aspects of vocabulary knowledge were most affected by the
Vocaroo intervention.
Table 3
Results by Test Section
Section Maximum
Points
Pre-Test
Mean
Post-Test
Mean
Gain Improvement
Section 1: Vocabulary
Breadth (Recognition)
15 6.9 12.8 +
5.9
85.5%
Section 2: Vocabulary
Depth (Production)
10 3.2 8.1 +
4.9
153.1%
Section 3: Pronunciation
Accuracy
5 1.7 3.7 +
2.0
117.6%
As shown in Table 3, the highest percentage improvement was in Vocabulary Depth
(Production) with 153.1%, followed by Pronunciation Accuracy with 117.6%. This indicates that
Vocaroo was particularly effective in helping students not only recognize words but also produce
them correctly in sentences and pronounce them accurately. The relatively lower but still
substantial improvement in Vocabulary Breadth (85.5%) suggests that recognition skills also
improved considerably, though they started from a slightly higher baseline relative to the
maximum possible score.
Paired-Sample T-Test Results
Table 4 displays the statistical significance tests comparing pre-test and post-test scores.
This table includes the t-statistic, degrees of freedom, p-value, and effect size, which together
indicate whether the observed improvement was statistically significant and practically
shows three score ranges: Low (0-10 points), Intermediate (11-20 points), and High (21-30
points). In the pre-test, the bars show: 9 students in the Low range, 19 students in the Intermediate
range, and 2 students in the High range. In the post-test, the bars show: 0 students in the Low
range, 4 students in the Intermediate range, and 26 students in the High range.
The results in Figure 1 show a dramatic shift in score distribution. Before the intervention,
only 2 students (6%) scored in the high range (21-30 points). After the intervention, 26 students
(87%) scored in the high range, representing an increase of 81 percentage points. Notably, no
students remained in the low range (0-10) after the intervention, whereas 9 students (30%) had
been in that range before the intervention. The intermediate range (11-20 points) also decreased
from 19 students (63%) before the intervention to 4 students (13%) after the intervention,
indicating that most students moved from intermediate to high performance. This distributional
shift suggests that the Vocaroo intervention was effective across the entire ability spectrum, from
the lowest-performing to the highest-performing students.
Table 3 presents the results disaggregated by the three test sections: vocabulary breadth
(recognition), vocabulary depth (production), and pronunciation accuracy. This disaggregation is
important because it reveals which aspects of vocabulary knowledge were most affected by the
Vocaroo intervention.
Table 3
Results by Test Section
Section Maximum
Points
Pre-Test
Mean
Post-Test
Mean
Gain Improvement
Section 1: Vocabulary
Breadth (Recognition)
15 6.9 12.8 +
5.9
85.5%
Section 2: Vocabulary
Depth (Production)
10 3.2 8.1 +
4.9
153.1%
Section 3: Pronunciation
Accuracy
5 1.7 3.7 +
2.0
117.6%
As shown in Table 3, the highest percentage improvement was in Vocabulary Depth
(Production) with 153.1%, followed by Pronunciation Accuracy with 117.6%. This indicates that
Vocaroo was particularly effective in helping students not only recognize words but also produce
them correctly in sentences and pronounce them accurately. The relatively lower but still
substantial improvement in Vocabulary Breadth (85.5%) suggests that recognition skills also
improved considerably, though they started from a slightly higher baseline relative to the
maximum possible score.
Paired-Sample T-Test Results
Table 4 displays the statistical significance tests comparing pre-test and post-test scores.
This table includes the t-statistic, degrees of freedom, p-value, and effect size, which together
indicate whether the observed improvement was statistically significant and practically
Vol. 13/ Núm. 2 2026 pág. 1657
meaningful.
Table 4
Statistical Significance of Vocabulary Gains
Statistical Measure Value
Mean Difference (Post-test - Pre-test) 12.8
Standard Deviation of Difference 3.1
t-statistic 22.6
Degrees of Freedom (df) 29
p-value p < 0.001
Effect Size (Cohen's d) 2.8 (very large)
The paired-sample t-test revealed a statistically significant improvement from pre-test to
post-test (t(29) = 22.6, p < 0.001). The effect size (Cohen's d = 2.8) is considered very large,
indicating that the Vocaroo intervention had a substantial positive impact on vocabulary
acquisition. This effect size is substantially larger than the average educational intervention effect
size of 0.4 reported by Hattie (2023) in his updated synthesis of meta-analyses.
Likert Scale Survey Results
Table 5 presents the survey results organized by the theoretical constructs of Self-
Determination Theory: autonomy, competence, relatedness, and overall engagement. These
constructs were measured to understand students' motivational responses to the Vocaroo
intervention.
Table 5
Survey Results by Construct (n=30)
Construct Mean Score (out of 5)Standard
Deviation
Interpretation
Autonomy (Items 1-3) 4.7 0.4 Very High
Competence (Items 4-6) 4.6 0.5 Very High
Relatedness (Items 7-8) 4.4 0.6 High
Overall Engagement (Items 9-10) 4.8 0.3 Very High
TOTAL SURVEY (10 items) 4.6 0.5 Very High
Table 6 provides the mean score and percentage of agreement for each individual survey
item. Examining individual items allows for a more nuanced understanding of which specific
aspects of the intervention students valued most.
meaningful.
Table 4
Statistical Significance of Vocabulary Gains
Statistical Measure Value
Mean Difference (Post-test - Pre-test) 12.8
Standard Deviation of Difference 3.1
t-statistic 22.6
Degrees of Freedom (df) 29
p-value p < 0.001
Effect Size (Cohen's d) 2.8 (very large)
The paired-sample t-test revealed a statistically significant improvement from pre-test to
post-test (t(29) = 22.6, p < 0.001). The effect size (Cohen's d = 2.8) is considered very large,
indicating that the Vocaroo intervention had a substantial positive impact on vocabulary
acquisition. This effect size is substantially larger than the average educational intervention effect
size of 0.4 reported by Hattie (2023) in his updated synthesis of meta-analyses.
Likert Scale Survey Results
Table 5 presents the survey results organized by the theoretical constructs of Self-
Determination Theory: autonomy, competence, relatedness, and overall engagement. These
constructs were measured to understand students' motivational responses to the Vocaroo
intervention.
Table 5
Survey Results by Construct (n=30)
Construct Mean Score (out of 5)Standard
Deviation
Interpretation
Autonomy (Items 1-3) 4.7 0.4 Very High
Competence (Items 4-6) 4.6 0.5 Very High
Relatedness (Items 7-8) 4.4 0.6 High
Overall Engagement (Items 9-10) 4.8 0.3 Very High
TOTAL SURVEY (10 items) 4.6 0.5 Very High
Table 6 provides the mean score and percentage of agreement for each individual survey
item. Examining individual items allows for a more nuanced understanding of which specific
aspects of the intervention students valued most.
Vol. 13/ Núm. 2 2026 pág. 1658
Table 6
Individual Survey Item Results
Item Statement M
ean
Score
%
Agree/Strongly
Agree
Autonomy
1 I could practice the words at my own pace using
Vocaroo.
4
.8
97%
2 I decided how many times to record each word. 4
.7
93%
3 I felt in control of my own learning when using
Vocaroo.
4
.6
90%
Competence
4 I could hear my pronunciation improve after using
nVocaroo.
4.7 93%
5 I felt capable of saying the new words correctly. 4.5 87%
6 Vocaroo helped me remember the meaning of the
words.
4.6 90%
Relatedness
7 I liked sharing my Vocaroo recordings with my
teacher.
4.3 83%
8 I felt connected to my classmates through our
recording activities.
4.5 87%
Overall
Engagement
9 I enjoyed using Vocaroo for vocabulary practice. 4.8 97%
10 I would like to continue using Vocaroo in future
English classes.
4.9 100%
The survey results indicate exceptionally high student satisfaction. Critically, 100% of
students agreed or strongly agreed that they would like to continue using Vocaroo in future
English classes (Item 10). Item 9 ("I enjoyed using Vocaroo") received 97% agreement. The
lowest mean (4.3 for Item 7) still represents a high level of agreement.
Correlation Between Motivation and Vocabulary Gains
Table 7 presents the Pearson correlation results between students'
motivation/engagement survey scores and their vocabulary gains. This correlation addresses the
theoretical claim that higher motivation leads to greater learning outcomes.
Table 6
Individual Survey Item Results
Item Statement M
ean
Score
%
Agree/Strongly
Agree
Autonomy
1 I could practice the words at my own pace using
Vocaroo.
4
.8
97%
2 I decided how many times to record each word. 4
.7
93%
3 I felt in control of my own learning when using
Vocaroo.
4
.6
90%
Competence
4 I could hear my pronunciation improve after using
nVocaroo.
4.7 93%
5 I felt capable of saying the new words correctly. 4.5 87%
6 Vocaroo helped me remember the meaning of the
words.
4.6 90%
Relatedness
7 I liked sharing my Vocaroo recordings with my
teacher.
4.3 83%
8 I felt connected to my classmates through our
recording activities.
4.5 87%
Overall
Engagement
9 I enjoyed using Vocaroo for vocabulary practice. 4.8 97%
10 I would like to continue using Vocaroo in future
English classes.
4.9 100%
The survey results indicate exceptionally high student satisfaction. Critically, 100% of
students agreed or strongly agreed that they would like to continue using Vocaroo in future
English classes (Item 10). Item 9 ("I enjoyed using Vocaroo") received 97% agreement. The
lowest mean (4.3 for Item 7) still represents a high level of agreement.
Correlation Between Motivation and Vocabulary Gains
Table 7 presents the Pearson correlation results between students'
motivation/engagement survey scores and their vocabulary gains. This correlation addresses the
theoretical claim that higher motivation leads to greater learning outcomes.
Vol. 13/ Núm. 2 2026 pág. 1659
Table 7
Pearson Correlation Results
Correlation Value Interpretation
Pearson Correlation Coefficient (r) 0.72 Strong positive correlation
p-value p < 0.01 Statistically significant
There was a strong, statistically significant positive correlation (r = 0.72, p < 0.01)
between students' survey scores (perceived motivation and engagement) and their vocabulary
gains (post-test minus pre-test). This indicates that students who reported higher motivation and
engagement tended to achieve greater vocabulary improvement.
Qualitative Results
The researcher's learning log (8 sessions) was analyzed using reflexive thematic analysis
(Braun & Clarke, 2013). Five main themes emerged from the data.
Theme 1: Progressive Increase in Student Engagement
Table 8 documents the researcher's rating of engagement levels across the eight sessions.
These ratings were based on observable behaviors such as voluntary participation, focus on tasks,
and positive affective responses.
Table 8
Engagement Levels Across Sessions
Session Engagement Level (1-5) Key Observation
Session 1 4 Initial laughter, curiosity, some hesitation
Session 2 4 Reduced laughter, increased focus
Session 3 5 High engagement, voluntary repetition
Session 4 5 Active peer collaboration
Session 5 5 Independent work, autonomy observed
Session 6 5 High focus on difficult sounds
Session 7 5 Serious, self-directed practice
Session 8 5 Celebration, pride in work
The learning log documented a clear progression from initial hesitation and laughter (a
normal reaction to hearing one's own voice for the first time) to focused, autonomous practice by
Session 3. By Session 8, students were asking to record again because "this one is better" and
expressing pride in their work.
Theme 2: Reduction of Speaking Anxiety
• The learning log provided evidence of significant anxiety reduction:
• Students who initially refused to record (2 students) were recording comfortably by
Session 5
• Voluntary re-recording without teacher prompting increased from 10 students in Session 1
to 25 students in Session 8
Table 7
Pearson Correlation Results
Correlation Value Interpretation
Pearson Correlation Coefficient (r) 0.72 Strong positive correlation
p-value p < 0.01 Statistically significant
There was a strong, statistically significant positive correlation (r = 0.72, p < 0.01)
between students' survey scores (perceived motivation and engagement) and their vocabulary
gains (post-test minus pre-test). This indicates that students who reported higher motivation and
engagement tended to achieve greater vocabulary improvement.
Qualitative Results
The researcher's learning log (8 sessions) was analyzed using reflexive thematic analysis
(Braun & Clarke, 2013). Five main themes emerged from the data.
Theme 1: Progressive Increase in Student Engagement
Table 8 documents the researcher's rating of engagement levels across the eight sessions.
These ratings were based on observable behaviors such as voluntary participation, focus on tasks,
and positive affective responses.
Table 8
Engagement Levels Across Sessions
Session Engagement Level (1-5) Key Observation
Session 1 4 Initial laughter, curiosity, some hesitation
Session 2 4 Reduced laughter, increased focus
Session 3 5 High engagement, voluntary repetition
Session 4 5 Active peer collaboration
Session 5 5 Independent work, autonomy observed
Session 6 5 High focus on difficult sounds
Session 7 5 Serious, self-directed practice
Session 8 5 Celebration, pride in work
The learning log documented a clear progression from initial hesitation and laughter (a
normal reaction to hearing one's own voice for the first time) to focused, autonomous practice by
Session 3. By Session 8, students were asking to record again because "this one is better" and
expressing pride in their work.
Theme 2: Reduction of Speaking Anxiety
• The learning log provided evidence of significant anxiety reduction:
• Students who initially refused to record (2 students) were recording comfortably by
Session 5
• Voluntary re-recording without teacher prompting increased from 10 students in Session 1
to 25 students in Session 8
Vol. 13/ Núm. 2 2026 pág. 1660
• Students smiling when hearing their own voice (instead of laughing nervously) increased
from 20% to 80%
• Students asking to share recordings with the class increased from 0 to 12 students
A representative observation from the learning log (Session 5): "Student H, who refused
to record in Session 1 saying 'no me gusta mi voz' (I don't like my voice), today recorded 5
words without being asked and said 'escuché mi grabación y sonó mejor' (I listened to my
recording and it sounded better). This is a remarkable transformation."
Theme 3: Development of Autonomy and Self-Assessment Skills
Table 9 shows the development of autonomy indicators across three selected sessions.
These indicators reflect students' growing ability to manage their own learning without direct
teacher prompting.
Table 9
Development of Autonomy Indicators Across Sessions
Indicator Session 1 Session 4 Session 8
Students re-recording without prompting 10 students 18 students 25 students
Students self-assessing before sharing 2 students 12 students 22 students
Students asking to record extra words 3 students 8 students 15 students
By the end of the intervention, students had developed the ability to evaluate their own
pronunciation and identify areas for improvement without teacher prompting; a key
metacognitive skill for lifelong language learning, consistent with findings by Teng (2022) on
self-regulated vocabulary learning.
Theme 4: Overcoming Technical Barriers
Technical challenges (internet connectivity issues, incompatible devices, microphone
problems) were present in Sessions 1-2 but were successfully resolved by Session 3. By the final
sessions, students had learned to troubleshoot basic problems independently. The learning log
noted that "students are now proficient in using Vocaroo independently." This finding aligns with
the work of Kohnke and Moorhouse (2022), who found that simple, low-bandwidth tools are most
sustainable in low-resource contexts.
Theme 5: Positive Transformation of Classroom Dynamics
The learning log documented a transformation from passive, teacher-centered instruction
to active, collaborative learning. One entry noted: "In traditional speaking activities, many
students would remain silent. Now, students are actively recording, sharing, and giving feedback.
Students who never raised their hand before are now asking to share their recordings with the
class."
CONCLUSION
The results of this study provide strong evidence that Vocaroo is highly effective for
vocabulary learning in A1 English learners in public school contexts. The improvement from a
• Students smiling when hearing their own voice (instead of laughing nervously) increased
from 20% to 80%
• Students asking to share recordings with the class increased from 0 to 12 students
A representative observation from the learning log (Session 5): "Student H, who refused
to record in Session 1 saying 'no me gusta mi voz' (I don't like my voice), today recorded 5
words without being asked and said 'escuché mi grabación y sonó mejor' (I listened to my
recording and it sounded better). This is a remarkable transformation."
Theme 3: Development of Autonomy and Self-Assessment Skills
Table 9 shows the development of autonomy indicators across three selected sessions.
These indicators reflect students' growing ability to manage their own learning without direct
teacher prompting.
Table 9
Development of Autonomy Indicators Across Sessions
Indicator Session 1 Session 4 Session 8
Students re-recording without prompting 10 students 18 students 25 students
Students self-assessing before sharing 2 students 12 students 22 students
Students asking to record extra words 3 students 8 students 15 students
By the end of the intervention, students had developed the ability to evaluate their own
pronunciation and identify areas for improvement without teacher prompting; a key
metacognitive skill for lifelong language learning, consistent with findings by Teng (2022) on
self-regulated vocabulary learning.
Theme 4: Overcoming Technical Barriers
Technical challenges (internet connectivity issues, incompatible devices, microphone
problems) were present in Sessions 1-2 but were successfully resolved by Session 3. By the final
sessions, students had learned to troubleshoot basic problems independently. The learning log
noted that "students are now proficient in using Vocaroo independently." This finding aligns with
the work of Kohnke and Moorhouse (2022), who found that simple, low-bandwidth tools are most
sustainable in low-resource contexts.
Theme 5: Positive Transformation of Classroom Dynamics
The learning log documented a transformation from passive, teacher-centered instruction
to active, collaborative learning. One entry noted: "In traditional speaking activities, many
students would remain silent. Now, students are actively recording, sharing, and giving feedback.
Students who never raised their hand before are now asking to share their recordings with the
class."
CONCLUSION
The results of this study provide strong evidence that Vocaroo is highly effective for
vocabulary learning in A1 English learners in public school contexts. The improvement from a
Vol. 13/ Núm. 2 2026 pág. 1661
pre-test mean of 11.8 to a post-test mean of 24.6 represents a 108.5% increase more than double
the baseline scores. This finding is consistent with Kartal and Korucu (2020), who found that
beginner EFL learners who recorded and listened to their own voices showed significant
improvement in word stress and phoneme accuracy. However, the magnitude of improvement in
this study (108.5%) exceeds typical gains reported in traditional vocabulary instruction, which
Webb and Nation (2017) suggest ranges between 20-40% over similar time periods.
The very large effect size (Cohen's d = 2.8) is particularly significant. In educational
research, an effect size of 0.8 is considered large; therefore, an effect size of 2.8 indicates a
transformative impact. To contextualize this, Hattie (2023) synthesized over 2,100 meta-analyses
and found that the average effect size of educational interventions is approximately 0.4. An effect
size of 2.8 is seven times larger than this average, suggesting that Vocaroo is not merely a helpful
supplement but could be considered a highly effective core strategy for vocabulary instruction
with A1 learners. This effect size is comparable to the most effective technology-enhanced
vocabulary interventions reported by Zhang and Zou (2022) in their meta-analysis of digital
vocabulary learning tools.
The finding that Vocabulary Depth (production) showed the highest improvement
(153.1%) is particularly noteworthy. Vocabulary production; using words correctly in sentences;
is typically more difficult for A1 learners than vocabulary recognition (Schmitt, 2019). The
learning log explains this finding: during Session 5 (Audio Vocabulary Journal), students
practiced producing full sentences, not just isolated words. This finding demonstrates that
Vocaroo can support productive vocabulary knowledge, which is essential for real-world
communication, corroborating the work of Yorulmaz and Altay (2025) on mobile-assisted
vocabulary learning.
The strong positive correlation (r = 0.72, p < 0.01) between motivation scores and
vocabulary gains provides empirical support for Self-Determination Theory (Ryan & Deci, 2017)
in the context of technology-based vocabulary learning. Students who reported higher levels of
autonomy, competence, and relatedness achieved greater vocabulary gains. This finding has
important practical implications: teachers should not merely provide access to technology but
must implement it in ways that satisfy students' psychological needs for autonomy (choice, self-
pacing), competence (opportunities to experience success), and relatedness (connection with
teacher and peers). These results align with the meta-analytic findings of Slemp et al. (2024) on
SDT in educational technology contexts.
The qualitative findings complement and explain the quantitative results. The reduction
in speaking anxiety documented in the learning log addresses a key barrier identified by Jaramillo
Pontón and Veloz Armas (2023) in the Ecuadorian context. The privacy and self-pacing afforded
by Vocaroo allowed anxious students to practice without fear of public embarrassment, gradually
building confidence until they were willing to share recordings with the class. This finding is
pre-test mean of 11.8 to a post-test mean of 24.6 represents a 108.5% increase more than double
the baseline scores. This finding is consistent with Kartal and Korucu (2020), who found that
beginner EFL learners who recorded and listened to their own voices showed significant
improvement in word stress and phoneme accuracy. However, the magnitude of improvement in
this study (108.5%) exceeds typical gains reported in traditional vocabulary instruction, which
Webb and Nation (2017) suggest ranges between 20-40% over similar time periods.
The very large effect size (Cohen's d = 2.8) is particularly significant. In educational
research, an effect size of 0.8 is considered large; therefore, an effect size of 2.8 indicates a
transformative impact. To contextualize this, Hattie (2023) synthesized over 2,100 meta-analyses
and found that the average effect size of educational interventions is approximately 0.4. An effect
size of 2.8 is seven times larger than this average, suggesting that Vocaroo is not merely a helpful
supplement but could be considered a highly effective core strategy for vocabulary instruction
with A1 learners. This effect size is comparable to the most effective technology-enhanced
vocabulary interventions reported by Zhang and Zou (2022) in their meta-analysis of digital
vocabulary learning tools.
The finding that Vocabulary Depth (production) showed the highest improvement
(153.1%) is particularly noteworthy. Vocabulary production; using words correctly in sentences;
is typically more difficult for A1 learners than vocabulary recognition (Schmitt, 2019). The
learning log explains this finding: during Session 5 (Audio Vocabulary Journal), students
practiced producing full sentences, not just isolated words. This finding demonstrates that
Vocaroo can support productive vocabulary knowledge, which is essential for real-world
communication, corroborating the work of Yorulmaz and Altay (2025) on mobile-assisted
vocabulary learning.
The strong positive correlation (r = 0.72, p < 0.01) between motivation scores and
vocabulary gains provides empirical support for Self-Determination Theory (Ryan & Deci, 2017)
in the context of technology-based vocabulary learning. Students who reported higher levels of
autonomy, competence, and relatedness achieved greater vocabulary gains. This finding has
important practical implications: teachers should not merely provide access to technology but
must implement it in ways that satisfy students' psychological needs for autonomy (choice, self-
pacing), competence (opportunities to experience success), and relatedness (connection with
teacher and peers). These results align with the meta-analytic findings of Slemp et al. (2024) on
SDT in educational technology contexts.
The qualitative findings complement and explain the quantitative results. The reduction
in speaking anxiety documented in the learning log addresses a key barrier identified by Jaramillo
Pontón and Veloz Armas (2023) in the Ecuadorian context. The privacy and self-pacing afforded
by Vocaroo allowed anxious students to practice without fear of public embarrassment, gradually
building confidence until they were willing to share recordings with the class. This finding is
Vol. 13/ Núm. 2 2026 pág. 1662
consistent with the work of Elov et al. (2025), who found that private, self-paced audio recording
reduces speaking anxiety in EFL learners.
The development of autonomy and self-assessment skills represents a metacognitive gain
that extends beyond vocabulary learning. By the end of the intervention, students could evaluate
their own pronunciation and identify areas for improvement without teacher prompting; a skill
that is essential for independent language learning. Teng (2022) has shown that self-regulated
vocabulary learning strategies are strong predictors of long-term vocabulary retention. This
finding has important implications for public school contexts where teachers cannot provide
individualized feedback due to large class sizes.
The resolution of technical challenges by Session 3 demonstrates that the digital divide,
while real, is not insurmountable. The key factors were selecting a simple, free, low-data tool
(Vocaroo) and preparing backup plans for common problems. This finding addresses concerns
raised by Checa Medina (2021) about technology integration challenges in Ecuadorian public
schools and aligns with the recommendations of Kohnke and Moorhouse (2022) for sustainable
technology integration in low-resource contexts.
The survey finding that 100% of students want to continue using Vocaroo is exceptionally
rare in educational research and indicates that the intervention was overwhelmingly well-
received. This directly contradicts the characterization of A1 learners in public schools as
"unmotivated" (Vargas Saritama & Guerra Vinueza, 2023). Rather, these results suggest that
students are highly motivated when provided with appropriate, engaging tools. This finding is
consistent with the motivational framework proposed by Al-Hoorie (2020), who argues that
motivation is not a fixed trait but is highly responsive to contextual and pedagogical factors.
Finally, the findings of this study address the four problems identified in the research
context: (1) vocabulary acquisition difficulties (addressed through repeated, self-paced practice),
(2) lack of technological resources (Vocaroo is free and works on basic smartphones),
(3) large class sizes and limited feedback (self-assessment and peer feedback replaced teacher
feedback), and (4) low motivation and speaking anxiety (private, self-paced practice reduced
anxiety and increased engagement). Based on these findings, the null hypothesis is rejected. This
study contributes to the literature by providing empirical evidence for the effectiveness of a
simple, free, accessible web tool for vocabulary learning in A1 English learners. The findings
have practical implications for English teachers in public schools throughout Latin America who
seek effective, low-cost strategies for vocabulary instruction. It is recommended that Vocaroo be
integrated into regular English instruction for A1 learners, particularly for vocabulary production
and pronunciation practice.
Limitations
This study has several limitations. First, the single-group pre-test/post-test design without
a control group means that causal claims must be made cautiously. Second, the intervention
consistent with the work of Elov et al. (2025), who found that private, self-paced audio recording
reduces speaking anxiety in EFL learners.
The development of autonomy and self-assessment skills represents a metacognitive gain
that extends beyond vocabulary learning. By the end of the intervention, students could evaluate
their own pronunciation and identify areas for improvement without teacher prompting; a skill
that is essential for independent language learning. Teng (2022) has shown that self-regulated
vocabulary learning strategies are strong predictors of long-term vocabulary retention. This
finding has important implications for public school contexts where teachers cannot provide
individualized feedback due to large class sizes.
The resolution of technical challenges by Session 3 demonstrates that the digital divide,
while real, is not insurmountable. The key factors were selecting a simple, free, low-data tool
(Vocaroo) and preparing backup plans for common problems. This finding addresses concerns
raised by Checa Medina (2021) about technology integration challenges in Ecuadorian public
schools and aligns with the recommendations of Kohnke and Moorhouse (2022) for sustainable
technology integration in low-resource contexts.
The survey finding that 100% of students want to continue using Vocaroo is exceptionally
rare in educational research and indicates that the intervention was overwhelmingly well-
received. This directly contradicts the characterization of A1 learners in public schools as
"unmotivated" (Vargas Saritama & Guerra Vinueza, 2023). Rather, these results suggest that
students are highly motivated when provided with appropriate, engaging tools. This finding is
consistent with the motivational framework proposed by Al-Hoorie (2020), who argues that
motivation is not a fixed trait but is highly responsive to contextual and pedagogical factors.
Finally, the findings of this study address the four problems identified in the research
context: (1) vocabulary acquisition difficulties (addressed through repeated, self-paced practice),
(2) lack of technological resources (Vocaroo is free and works on basic smartphones),
(3) large class sizes and limited feedback (self-assessment and peer feedback replaced teacher
feedback), and (4) low motivation and speaking anxiety (private, self-paced practice reduced
anxiety and increased engagement). Based on these findings, the null hypothesis is rejected. This
study contributes to the literature by providing empirical evidence for the effectiveness of a
simple, free, accessible web tool for vocabulary learning in A1 English learners. The findings
have practical implications for English teachers in public schools throughout Latin America who
seek effective, low-cost strategies for vocabulary instruction. It is recommended that Vocaroo be
integrated into regular English instruction for A1 learners, particularly for vocabulary production
and pronunciation practice.
Limitations
This study has several limitations. First, the single-group pre-test/post-test design without
a control group means that causal claims must be made cautiously. Second, the intervention
Vol. 13/ Núm. 2 2026 pág. 1663
duration was only 4 weeks; long-term retention of vocabulary gains was not measured. Third, the
researcher also delivered the intervention, which may have introduced bias. Fourth, the study was
conducted in a single institution, limiting generalizability. Future research should include control
groups, delayed post-tests, independent teachers, and multiple institutions, as recommended by
Plonsky and Oswald (2014) for second language acquisition intervention research.
duration was only 4 weeks; long-term retention of vocabulary gains was not measured. Third, the
researcher also delivered the intervention, which may have introduced bias. Fourth, the study was
conducted in a single institution, limiting generalizability. Future research should include control
groups, delayed post-tests, independent teachers, and multiple institutions, as recommended by
Plonsky and Oswald (2014) for second language acquisition intervention research.
Vol. 13/ Núm. 2 2026 pág. 1664
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AERA. https://www.aera.net/Portals/38/docs/About_AERA/CodeOfEthics.pdf
Braun, V., & Clarke, V. (2013). Successful qualitative research: A practical guide for beginners.
Sage Publications.
CEFR. (2018). Common European Framework of Reference for Languages: Learning, teaching,
assessment (Companion volume with new descriptors). Council of Europe.
https://rm.coe.int/cefr-companion-volume-with-new-descriptors-2018/1680787989
Checa Medina, J. (2021). The integration of ICTs in EFL teaching in Ecuadorian high schools:
One country, two realities. Journal of English Language Teaching and Applied
Linguistics, 3(8), 1-13. https://doi.org/10.32996/jeltal.2021.3.8.1
Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education (8th ed.).
Routledge.
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods
research (3rd ed.). Sage Publications.
Elov, B., Khamraeva, S., & Ismailova, N. (2025). AI speaking tests and EFL student confidence:
A quantitative study. International Journal of Educational Technology, 18(1), 45-59.
Hattie, J. (2023). Visible learning: The sequel. Routledge. https://doi.org/10.4324/9781003380542
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communication skills in Ecuadorian face-to-face learning environments [Bachelor's
thesis, Universidad Técnica Particular de Loja].
Kartal, G., & Korucu, E. (2020). The effect of voice recording on pronunciation of young EFL
learners. Computer Assisted Language Learning, 33(4), 512-535.
https://doi.org/10.1080/09588221.2019.1704430
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participatory action research. Springer. https://doi.org/10.1007/978-981-4560-67-2
Kohnke, L., & Moorhouse, B. L. (2022). Facilitating synchronous online language learning
through Zoom. RELC Journal, 53(1),222-227.
https://doi.org/10.1177/00336882211013441
Li, M. (2021). The effects of technology on language learners' motivation: A self-determination
theory perspective. Computer Assisted Language Learning, 34(3), 299-322.
https://doi.org/10.1080/09588221.2019.1610046
Mosquera Endara, M. R., Cárdenas Medina, J. P., & Prado Yépez, J. L. (2020). ICT in
Ecuadorian public schools: A systematic review of challenges and opportunities. RISTI
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students' English oral communication skills in Ecuadorian face-to-face learning
environments [Bachelor's thesis, Universidad Técnica Particular de Loja].
Webb, S., & Nation, P. (2017). How vocabulary is learned. Oxford University Press.
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digital age: "Memrise" and learner motivation through the lens of SLA theories. Akukeg,
12(1), 45-67.
Zhang, R., & Zou, D. (2022). A meta-analysis of the effects of digital vocabulary learning tools on
EFL/ESL learners' vocabulary acquisition. Computer Assisted Language Learning,
35(4), 899-935. https://doi.org/10.1080/09588221.2020.1793371
- Revista Ibérica de Sistemas e Tecnologias de Informação, E32, 123-138.
Ortega Auquilla, D. P., & Vázquez Barros, C. E. (2020). Ecuadorian EFL teachers' perceptions
on the use of technological resources during the COVID-19 pandemic. Maskana, 11(2),
45-53. https://doi.org/10.18537/mskn.11.02.06
Plonsky, L. (2017). Quantitative research methods. In S. Loewen & M. Sato (Eds.), The
Routledge handbook of instructed second language acquisition (pp. 505-521).
Routledge.
Plonsky, L., & Oswald, F. L. (2014). How big is "big"? Interpreting effect sizes in L2 research.
Language Learning, 64(4), 878-912. https://doi.org/10.1111/lang.12079
Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in
motivation, development, and wellness. Guilford Press.
https://doi.org/10.1521/9781462528806
Schmitt, N. (2010). Researching vocabulary: A vocabulary research manual. Palgrave
Macmillan.
Schmitt, N. (2019). Understanding vocabulary acquisition, instruction, and assessment: A
research agenda. Language Teaching, 52(2), 261-274.
https://doi.org/10.1017/S0261444819000053
Slemp, G. R., Kern, M. L., Patrick, K. J., & Ryan, R. M. (2024). A meta-analysis of self-
determination theory in educational technology contexts. Educational Psychology
Review, 36(1), 15-42. https://doi.org/10.1007/s10648-024-09845-6
Teng, M. F. (2022). Self-regulated vocabulary learning: A review of the literature and future
research directions. TESOL Quarterly, 56(2), 783-801. https://doi.org/10.1002/tesq.3073
Vargas Saritama, A. B., & Guerra Vinueza, F. J. (2023). Factors that influence high school
students' English oral communication skills in Ecuadorian face-to-face learning
environments [Bachelor's thesis, Universidad Técnica Particular de Loja].
Webb, S., & Nation, P. (2017). How vocabulary is learned. Oxford University Press.
Yorulmaz, M., & Altay, I. F. (2025). App-solutely motivated! EFL vocabulary learning in the
digital age: "Memrise" and learner motivation through the lens of SLA theories. Akukeg,
12(1), 45-67.
Zhang, R., & Zou, D. (2022). A meta-analysis of the effects of digital vocabulary learning tools on
EFL/ESL learners' vocabulary acquisition. Computer Assisted Language Learning,
35(4), 899-935. https://doi.org/10.1080/09588221.2020.1793371