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The Impact of High-Frequency Vocabulary Activation Strategies in Improving Speaking Skills and Vocabulary Knowledge of Rural ESL Learners

August 2025 – Volume 29, Number 2

https://doi.org/10.55593/ej.29114a2

Raju Dhuli
Indian Institute of Technology. Bhubaneswar, India
<a21hs09003atmarkiitbbs.ac.in>

Rajakumar Guduru
Indian Institute of Technology. Bhubaneswar, India
<rajakumarguduruatmarkiitbbs.ac.in>

Abstract

This paper examines the effectiveness of vocabulary activation strategies in enhancing the speaking proficiency of English as Second Language (ESL) learners in rural areas. Recognizing the unique challenges faced by ESL learners in these regions, the study investigates how targeted vocabulary knowledge strategies can improve oral communication. A quasi-experimental pretest-posttest control group design was employed, involving 520 ESL learners from five government secondary schools in Khurdha district, Odisha, India. The participants were divided into experimental (n =290) and control (n =230) groups. The experimental group received instruction using high-frequency vocabulary strategies derived from a corpus-based word list, including the New General Service List (new-GSL), to boost speaking skills, while the control group followed traditional methods. Pre- and post-tests measured participants’ vocabulary knowledge and speaking proficiency. Two-way ANOVA with one repeated measure and descriptive statistics were run to analyze the data. Statistical analysis of the data revealed that the experimental group showed significantly greater improvement in both high-frequency vocabulary and speaking skills compared to the control group. The study’s findings offer valuable insights for educators and policymakers aiming to enhance ESL instruction in rural contexts, demonstrating the positive impact of high-frequency vocabulary activation strategies on speaking proficiency and vocabulary knowledge.

Keywords: High-frequency vocabulary, speaking skills, ESL students, and activation strategies

Vocabulary plays a pivotal role in language acquisition, serving as the foundation for all linguistic skills—reading, writing, listening, and speaking. Proficiency in these skills hinges on one’s ability to use vocabulary effectively, and thus, vocabulary knowledge becomes a key determinant of overall language proficiency. As Wilkins (1972) aptly says, “Without grammar, something can be conveyed, but without vocabulary, nothing can be conveyed (p.111).” This statement underscores the essential function of vocabulary in facilitating communication. Vocabulary not only aids in comprehension but also enhances one’s ability to express oneself clearly and accurately. As such, vocabulary knowledge is a critical benchmark for assessing a learner’s linguistic competence (Schmitt & Elaphan, 2001). The importance of vocabulary extends to cognitive development and communication, as noted by Conderman et al. (2013). They emphasize that vocabulary influences how one thinks and learns, and there is a strong correlation between vocabulary size and mastery of the four essential language skills: listening, speaking, reading, and writing. Students with an extensive vocabulary are better equipped to understand and articulate new concepts using abstract language, while those with limited vocabulary face challenges in communication.

Speaking, in particular, is regarded as one of the most important language skills. El-Sakka (2016) emphasizes its importance, describing it as a crucial means through which individuals express their personality, self-image, and understanding of the world around them (Luoma, 2004). Nevertheless, attaining spoken proficiency demands significant effort and time, particularly for learners who lack consistent exposure to English-speaking environments. Goh and Burns (2012) asserted that the development of speaking skills involves three key areas: a) language and discourse knowledge, encompassing vocabulary, grammar, and phonology, b) core speaking skills, including pronunciation, interaction management, and discourse organization, and c) communication strategies, involving cognitive and metacognitive strategies that assist leaners in managing speaking tasks effectively.

Vocabulary acquisition plays a crucial role in the development of speaking proficiency. Research consistently demonstrates a strong correlation between vocabulary size and speaking proficiency individuals possessing a broader vocabulary typically exhibiting greater fluency and accuracy in speech. In contrast, those with a limited vocabulary face challenges in expressing themselves (Uchihara & Clenton, 2020). According to Nation (2001), vocabulary knowledge and language use are complementary processes—vocabulary facilitates language use, and in turn, language use fosters vocabulary growth. This reciprocal relationship underscores the foundational role of vocabulary in both language learning and communicative competence. August et al. (2005) further contends that learners with a limited vocabulary are more likely to avoid engaging in spoken interactions, thereby impeding the development of their speaking skills. This issue is particularly pronounced among rural ESL learners, for whom limited vocabulary knowledge often translates into reduced fluency and accuracy in spoken English.

Nation (2008) categorizes vocabulary into high-frequency, mid-frequency, and low-frequency groups based on their prevalence in texts. High-frequency words are commonly used in everyday language, while low-frequency words are specific to specialized fields. For rural ESL learners, building a strong foundation in high-frequency vocabulary is crucial for improving their speaking proficiency. Many rural students have limited access to meaningful English language exposure, leading to difficulties in developing fluency and confidence in speaking. Targeting high-frequency vocabulary through effective activation strategies offers a practical pathway to address these challenges and improve their speaking proficiency. This study seeks to address the challenges faced by rural ESL learners by investigating the impact of vocabulary knowledge on their speaking skills. By focusing on teaching high-frequency words and employing strategies that encourage active use of vocabulary, the research aims to contribute to the development of more effective teaching methods that support rural students in improving their communication skills. In doing so, the study aims to provide a roadmap for teachers to create more supportive learning environments where rural ESL learners can thrive.

Literature Review

Vocabulary Learning Strategies

Several vocabulary learning strategy taxonomies have been proposed by linguists such as, Gu and Johnson (1996), Nation (2001), and Schmitt (1997). These frameworks typically categorize strategies into two broad types: discovery strategies, which aid in learning new words and consolidation strategies, which support the retention and use of vocabulary. Such strategies enabled learners to progress from passive recognition of vocabulary to active use of vocabulary, particularly enhancing their speaking skills. Despite this, learning vocabulary in a foreign language remains a significant challenge for many EFL learners. Nevertheless, when appropriate techniques are employed, students can substantially expand their lexical repertoire. Vocabulary strategies—such as learning word families, using mnemonic devices, inferring meaning from context, and applying spaced repetition—have been shown to improve both the retention and retrieval of new words (Nation, 2001). These techniques not only helped students build their vocabulary but also encouraged its active use in conversation, which has become essential for improving language skills.

Numerous studies have investigated vocabulary learning strategies employed by learners in second language acquisition. Rakchanok (2014) found that Thai EFL students utilized strategies focusing on leaning and retaining words to improve long-term memory and recall. Yang and Dai (2012) reported that Chinese university students employed vocabulary learning techniques that focused on orthographic and phonological forms and association meanings. Moreover, Saengpakdeejit (2014) discovered that Italian-Turkish simultaneous and sequential bilingual high school students frequently employed social strategies in vocabulary learning. Yamada (2018) identified several effective strategies in L2 vocabulary instruction, including input seeking, planning, selective attention, spaced learning, confident guessing, and note-taking. Manigandan (2020) demonstrated that the use of vocabulary learning strategies significantly improved learners’ speaking skills. Similarly, Smith et al. (2020) found high-frequency vocabulary activation techniques were beneficial in ESL classrooms.

Research on Vocabulary Lists for Language Development

In recent years, there has been significant development in creating word lists tailored to aid vocabulary teaching, each carefully curated based on frequency, relevance, and importance in language usage. The General Service List (GSL), established by West (1953), comprised around 2,000 high-frequency words crucial for general language proficiency. Also, the Academic Word List (AWL), introduced by Coxhead (2000) comprised 570-word families commonly employed across academic disciplines; The New General Service List (NGSL), presented by Browne et al. (2013), represented an updated version of the GSL. With 2,494 high-frequency words, the new GSL encompassed modern language usage, incorporating contemporary vocabulary. Research by Adolphs and Schmitt (2003) indicated that learners need mastery of at least 2,000 to 3,000 high-frequency words to engage in basic oral conversations in English. Similarly, Nation (1993) suggested that mastery of 3,000-word families has been essential for developing other linguistic abilities, such as reading and writing. Without this foundational vocabulary, learners encounter difficulties in understanding and producing language, which impeded their overall language development.

Various studies have investigated the use of word lists to improve language skills, particularly speaking skills. For example, Smith et al. (2020) explored the extent to which   academic vocabulary lists meet the lexical requirements of speaking assessments in academic settings. Their findings indicated that test-takers who employed more sophisticated and diverse range of academic vocabulary tended to achieve higher proficiency scores. The study supported the use of vocabulary lists as valid predictors of speaking performance, although as direct instructional tools.  It also highlighted the gaps in language use during academic presentations and emphasized the importance of developing customized word lists tailored to speaking proficiency. Similarly, Syarofi and Shobaha (2023) examined the effects of teaching the Academic Word List in foreign language speaking classes on speaking abilities. Their study aimed to enhance speaking and academic discussion skills by promoting a deeper understanding of vocabulary items and encouraging timely, purposeful, and communicative use of newly acquired vocabulary.

Speaking Skills and Vocabulary Learning

Coady (1993), Lee and Muncie (2006), and Tahir et al. (2021) found that explicit vocabulary instruction, including the use of higher-level target vocabulary, could significantly improve learners’ vocabulary knowledge and usage. Derakhshan and Janebi (2020) conducted a study examining the relationship between vocabulary and speaking skills. Their results revealed that knowledge of the 3,000-word frequency level contributed uniquely to the prediction of the second language overall speaking ability and its fluency dimension. Similarly, Alharthi (2020) emphasized the critical role of vocabulary in improving speaking skills, noting that it serves as a key factor in distinguishing proficiency levels, especially among intermediate levels and advanced learners (Suryanto et al., 2021). Muliadi (2018) also investigated the effects of vocabulary mastery on the speaking ability of engineering students, highlighting the importance of developing communicative competence. In a similar study, Lankapalli (2018) explored the development of oral communication skills of engineering students using audio-visual aids, concluding that improved vocabulary significantly contributed to students’ speaking skills. Furthermore, studies by Sukendra (2023), Alharthi (2020), Khan et al. (2018), and Koizumi (2013) collectively revealed a reciprocal relationship between vocabulary knowledge and speaking skills of college-level students, reinforcing the interdependence of these two aspects of language development.

Laufer and Nation (1995) underscored the significance of vocabulary knowledge in effective communication, particularly highlighting the importance of high-frequency words. They proposed strategies for retaining and activating vocabulary to enhance speaking proficiency. Similarly, Richards (2015) explored various vocabulary-teaching methods aimed at improving speaking skills. His work emphasized the utilization of activities and strategies to activate high-frequency vocabulary in classroom settings. Akhavan (2007) investigated the impact of explicit vocabulary instruction on ESL learners’ speaking abilities, emphasizing its role in enhancing fluency. Alavi and Taghizadeh (2017) examined the correlation between vocabulary learning strategies and speaking performance, stressing the positive influence of active engagement with vocabulary on speaking skills. In summary, the aforementioned studies highlighted the significance of vocabulary in enhancing speaking skills and were relevant to the present study. Most of these studies aimed at investigating the impact of vocabulary knowledge on the speaking skills of college-level students. Furthermore, these studies indicated positive results regarding the importance of vocabulary in enhancing the speaking skills of students. Although previous studies have found vocabulary important for speaking, it is potentially even more important for rural learners because when Ab Dollah and Shah (2016) investigated the vocabulary learning strategies of learners in rural and urban areas, they found notable disparities between the two groups. Their study indicated that teachers should place a strong emphasis on teaching VLSs to students, particularly in rural areas. Moreover, Hien and Spring (2024) examined the difficulties rural learners of L1 Burkinabè local language encounter while studying L2 French with regard to French passives, in contrast to their urban counterparts. The results showed that geographic location was the most significant factor affecting language acquisition of rural students due to lack of exposure, practice opportunities, and high-quality instruction.

In similar lines, Rahmat and Akbar (2019) examined the motivation levels of L2 learners in rural and urban areas and found a significant difference. While rural students often had lower motivation due to limited opportunities and external pressures, urban students demonstrated stronger intrinsic motivation because of greater exposure, social encouragement, and access to learning tools. The results of this study supported the idea that one of the main factors influencing L2 proficiency is motivation. Additionally, Kato (2020) used the term ‘poverty of opportunity’ to characterize students living in areas where the target language was not commonly spoken. This research focused on Japanese language learners in the United States, but it also showed how limited exposure to the language could impede the development of competency, which is particularly relevant to ESL learners in remote areas. The findings highlighted the need to expand access to real-world language input. The combined findings of these studies demonstrated how exposure, motivation, geographic location, and opportunity gaps substantially influenced L2 vocabulary development, providing a solid basis for the present study on improving the speaking skills of rural ESL learners. In light of the findings from previous studies, the following conclusions can be derived: First, past research mostly concentrated on developing the speaking skills of college-level students. Second, there has not been much research undertaken to explore the impact of vocabulary on improving the competence of rural ESL learners’ speaking skills. Therefore, a gap remains in the existing literature regarding the contribution of high-frequency words to the development of speaking skills among rural ESL secondary school students. This study aims to bridge this gap by investigating the impact of high-frequency vocabulary activation strategies on improving rural ESL secondary school learners’ speaking skills and vocabulary knowledge.

RQ1. How and in what ways do high-frequency vocabulary activation strategies improve rural ESL learners’ speaking skills?
R2Q. How does the conversion of students’ receptive vocabulary knowledge into productive vocabulary knowledge improve their speaking skills?

Speaking and Vocabulary Assessments Used in the Study

The Key English Test (KET), formerly known as A2 Key, is an English language proficiency test. It is intended for students at the A2 level of the Common European Framework of Reference for Languages (CEFR).  The KET is designed to evaluate basic English skills and is often utilized to ensure that students in a study group have similar levels of language proficiency, which is crucial for the validity of educational research (Cambridge ESOL, 2006). As a stepping-stone to more advanced English tests, students who have finished an introductory English course frequently take KET. The capacity to utilize English for basic, everyday interactions is shown by passing the KET exam.  The test assesses listening, written, speaking, and reading comprehension. Each of the four sections carries 25% of the marks. Depending on the scores on the test, students get a CERF level. If score is between 100 and119 then the CEFR A1 level is assigned to the student; if a score is between 120 and 139, then the CEFR A2 level is assigned to the student (Cambridge Assessment English, 2023).

In addition to general proficiency, vocabulary knowledge—especially receptive vocabulary—is a key component of language competence. Receptive vocabulary refers to vocabulary that learners can recognize while reading or listening to a text (Nation, 1993). The Receptive Vocabulary Levels Test (RVLT) assesses learners’ knowledge at five frequency levels of English word families: 2,000, 3,000, 5,000, University Words Level (UWL), and 10,000, hence the name “Levels Test.” Each section of the revised VLT consists of 30 items in a multiple-matching format. The New General Service List (new-GSL) developed by Browne et al. (2013), included 2,494-word families.

To complement the receptive assessment, the Controlled Productive Vocabulary Level Test (CPVLT), developed by Laufer and Nation (1995), is used to measure students’ level of controlled productive vocabulary knowledge. This test is structured into five portions that assess knowledge of 2,000, 3000, 5000, UWL and 10,000-word frequency levels. Each level represented 1000 words, excluding UWL level, which contains a list of 836 words. Each level contains 18 items, which all sample from the VLT word pool. Therefore, the maximum score for the PVLT in total is 90 points for 5 frequency levels.

Methodology

Participants

This study included rural ESL learners who were 9th grade students from five different government secondary schools in Khurdha district, Odisha, India. These students hailed from different villages in Khurdha district. Before conducting the study, the researcher informed both the students and institutional heads of the fact that the responses of the students would be published. Since the learners were minors, the researcher obtained written consent from the institutional heads of the respective schools. Moreover, the students were informed that the intervention would not affect their grades. Also, these students belonged to the same age group of 14 and15.

The KET Test

Prior to selecting the students for the study, the researcher administered the KET test with 600 students to verify the homogeneity of the sample participants. Two university professors as evaluators were involved in scoring the KET test results through a blind scoring method to ensure scoring reliability. The evaluators independently rated the students’ performance; their extensive research experience in language assessment guaranteed consistent and fair evaluations. Based on these scores, the researcher divided the students into control and experimental groups.

Table 1 below presents the results of the KET test, revealing that 520 students out of 600 students demonstrated a similar level of English language proficiency. In order to ensure homogeneity of the participants, those 80 students who exhibited poor performance in the KET test were excluded from the study, as their language proficiency was notably lower than that of the remaining 520 students. Moreover, Table 1 shows that the mean score (128.22) of the experimental group was closely aligned with that of the control group (128.62), along with comparable standard deviations and skews. Since these students obtained scores within the range of 120 to 139, they could be said they belong to the A2 level in the CEFR grading level. Therefore, the researcher proceeded to conduct the main study with both the groups.

Table 1. Descriptive Statistics of KET Test

N Min Max Mean SD Skewness Kurtosis
E 290 120.00 139.00 128.22 4.622 .319 -.464
C 230 120.00 139.00 128.62 4.125 .400 .126
T 600 56.00 139.00 120.65 20.495 -2.108 3.016

Subsequently, the researcher assigned the sample to the experimental group, which contained 290 students, and the control group containing 230 students. The reason the experimental group included 290 students and the control group consisted of 230 students was that their language proficiency levels were found to be similar, and their mean scores were statistically comparable. Moreover, the difference in group sizes resulted from administrative and teaching constraints encountered during the grouping process. Notably, the difference in group sizes did not compromise the reliability and validity of the study, as both groups demonstrated comparable levels of language proficiency as measured by the KET test. Hence, the researcher assigned the sample participants into two unequal groups as stated above. The experimental group engaged in learning high-frequency vocabulary through Vocabulary Learning Strategies (VLS), whereas the control group was instructed in high-frequency words through rote memorization.

Instruments

Speaking Proficiency Test

The KET test aimed to assess students’ speaking ability in English.  The researcher administered this test to 520 students in three steps: The first section (the warm-up stage): The goal of the warm-up was to establish a welcoming environment and encourage greetings (hello, how are you, how is everything, and so on). The second section (exchanging personal information): Students were asked to respond simple questions about their personal information, such as name, residency, family details, and habits to make students feel relaxed and engage in speaking test. The third section (Giving Opinions on a Topic): the researcher asked the students to choose one of the topics (see Appendix A) written on paper cards for proceeding the test. The topics were meticulously selected in accordance with the students’ level, and two evaluators were involved in verifying the validity of the topics developed for the speaking test.  The researcher employed IELTS speaking assessment criteria for speaking test in the current study. It measured four skills, including fluency and coherence, grammar and accuracy, pronunciation and lexical resource. Each of the four skills was allocated equal weight of five marks, contributing to a total of 20 marks.

Receptive Vocabulary Levels Test (RVLT)

This study employed receptive vocabulary level test in order to assess the receptive knowledge of students’ vocabulary. In this test, the researcher employed the revised VLT where each section consists of 30 items in a multiple matching format, three items represent 100 words of any given frequency band. For this purpose, items were grouped into 10 clusters, with six words in a column on the right and three senses of meaning corresponding to three of these words in a column on the left for each cluster. This test format could be found in Appendix B. Learners must match each meaning sensation in the left-hand column to a single word in the right-hand column. As the students were low-proficiency adolescents, the researcher focused New General Service List (new-GSL), which indicated the students’ mastery of the 2,494 words in the list. It contained 75 multiple-choice questions and each correct answer carried one mark.

Controlled Productive Vocabulary Level Test (CPVLT)

Concerning the productive vocabulary knowledge of students, the researcher administered controlled productive vocabulary level test which was designed using only 2494 high-frequency words, which was New General Service List (NGSL) because the students were low-proficient learners. Thus, the researcher administered CPVLT (see Appendix C) within 2494 words; this test sampled 18 items at the first 1000-word list, second 1000-word list and for the remaining 494 words, the researcher added 9 items, so total items for this test are 45 items. The test required students to fill up the gaps in sentences with a suitable word based on the initial letters provided as prompts.

Vocabulary Learning Strategies

The researcher employed these vocabulary learning strategies in order to enhance students’ speaking proficiency and vocabulary knowledge. Among the myriad taxonomies available, the Schmitt (1997)’s taxonomy of Vocabulary Learning Strategies (VLS) emerged as the focal point due to its comprehensive categorization of these strategies. This taxonomy offered a comprehensive classification, which has become advantageous for the study’s objectives. Specifically, the chosen strategies were tailored to accommodate the students’ varying educational backgrounds and language proficiency levels. The study strategically focused on a subset of strategies delineated within the Schmitt (1997)’s taxonomy, meticulously considering factors, such as the students’ proficiency in the language and their educational history. This subset comprised social, memory, cognitive, and discovery strategies. Notably, the exclusion of metacognitive strategies was deliberate, as they necessitated higher-order thinking skills set that might surpass the grasp of low-proficient learners. Consequently, the researcher deliberately omitted metacognitive strategies, ensuring a tailored approach to cater to the targeted cohort of learners. The following are the examples of strategies employed in this study as a part of instruction:

Social Strategies (SS)

  1. Speaking with the teachers in English to use a new word in sentences to improve vocabulary knowledge.
  2. Speaking with the teacher in English to know a synonym of a new word or ask to explain it.
  3. Discussing with classmates in English to know and enlarge the meaning of a new vocabulary item.
  4. Engaging in games, such as spellbee, Duolingo and crossword puzzles to find meaning of a new word through group work activities.
  5. Asking friends and teachers for the meaning of the words.

Memory Strategies (MS)

  1. Using new words in sentences repeatedly.
  2. Gathering and grouping new words together to improve new vocabulary.
  3. Classifying new words according to similar pronunciation and spelling.
  4. Grouping new words according to their synonyms and antonyms.
  5. Utilizing semantic maps to learn new words.

Cognitive Strategies (CS)

  1. Revising previous English lessons and taking notes in class to learn the new vocabulary items.
  2. Repeating orally learned words with their meanings to learn them.
  3. Writing five sentences with the learned words.
  4. Practicing writing words repeatedly to remember them better.
  5. Writing newly learned words with meanings on papers and sticking them on the wall in my bedroom and repeatedly spelling the words.

Discovery Strategies (DS)

  1. Utilizing an English–Odia dictionary to find out the meaning of new words.
  2. Guessing the meaning of words from word classes like noun, verb, adjective, and adverb.
  3. Guessing the meaning of the new words from gestures.
  4. Guessing the meaning of the new words from available pictures, graphs, figures, etc.

Treatment Procedure

This study employed Kramsch’s (1979, as cited in Faraj, 2015) procedure of vocabulary teaching and learning, which included the following steps:

  • Selecting the words
  • Recording the words and monitoring the recording
  • Learning the words
  • Sharing with others
  • Assessing and monitoring learning
  • Recycling the vocabulary

Here, the first step, selecting the words, involved choosing words from the NGSL word list. The second step, recording the words and monitoring the recording, meant students were instructed to note down the words and document key aspects of the chosen words from the stipulated word list. Such aspects included meaning, spelling, usage in context or sentence examples, synonyms, and antonyms. To support this, students were also encouraged to use the recommended dictionary, Longman English Dictionary of Contemporary, to obtain accurate and comprehensive word information. In the third step, learning the words, vocabulary was taught through interactive activities, including reading picture books, newspapers, and short stories. Students also learned the grammatical forms of words like go, going, went, and gone. Furthermore, the students applied a range of strategies, such as social, cognitive, discovery, and memory strategies to activate vocabulary knowledge. In addition, this step emphasized communicative functions, such as questioning, requesting, asking for permission, expressing necessity, possibility, ability, greeting, contrasting, and informing. The fourth step, sharing with others, involved students sharing their knowledge of the words with their classmates through discussions, role-plays in pairs or groups, and story narration. It included interaction with students and teachers, asking them to talk about their friends, favorite places, etc. The fifth step, assessing and monitoring learning, encompassed evaluating students’ vocabulary knowledge and speaking skills through a variety of tasks, including spelling exercises, word dictation, and word completion activities, as well as oral tasks where students spoke on specific topics or described people or places. In the final step, recycling the vocabulary, students reinforced and used the vocabulary by engaging in speaking activities on various topics, writing five sentences about themselves or their families, and reading short stories and translating them into their mother tongue. This step assisted students in practicing and correctly using the newly learned words.

Data Collection

The pre-receptive and pre-productive vocabulary level tests were administered to the participants by the researcher in a single session lasting around sixty minutes. In addition, the researcher administered pre-speaking test to the students. Subsequently, two evaluators were involved in validating the speaking test topics to ensure content validity. IELTS speaking band descriptors were selected for scoring purpose in order to ensure a comprehensive assessment of fluency, coherence, and lexical resource, which was consistent with the focus of study on vocabulary and speaking skills. Here, IELTS speaking band descriptors differed from KET speaking descriptors because KET speaking criteria focused solely on A2-level competencies; whereas, the IELTS descriptors furnished a comprehensive scale for evaluating speaking progress beyond A2 level. This broader scale was particularly beneficial for assessing variation in students’ performance beyond basic proficiency. A blind scoring method was employed in order to ensure scoring reliability. Here, blind scoring method involved the evaluators grading the responses of speaking skills without knowing whether the students belonged to the control or experimental group. This approach was particularly relevant to speaking assessment as it involved subjective judgment; therefore, the blind scoring method was employed to make sure equality and reliability by concentrating exclusively on students’ responses. The class teacher oversaw and the researcher conducted all of the testing sessions. Throughout the testing sessions, all the students received the same instruction, and testing sessions in a structured format with a fixed time limit for each student. This ensured equality, consistency and comparability in assessments. The time limit provided students with sufficient opportunity to demonstrate their speaking skills while maintaining controlled testing conditions.

After the pre-study, intervention or treatment of high-frequency vocabulary through vocabulary learning strategies was given to experiment group for over 120 instructional sessions but the control group learned high-frequency words through rote memorization. Following the treatment, the researcher conducted a post-speaking test as well as post-receptive and post-productive vocabulary level tests. Upon obtaining the results of the speaking tests’ holistic judgment and vocabulary assessments, descriptive and reliability, statistics were calculated to guarantee the data’s dependability. The difference and improvement in the mean speaking proficiency scores of the control and experiment groups were then determined using two-way ANOVA with one repeated measure and descriptive statistics. Moreover, descriptive statistics were run to find out the mean, minimum and maximum scores of controls and experiment group in all vocabulary level tests.

Results

Table 2 presents descriptive statistics for speaking proficiency scores measured before and after the intervention of VLSs for both the experimental and control groups; the experimental group exhibited a substantial increase in their mean scores from 8.824 (SD = 1.660) before treatment to 16.331 (SD = 1.813) after treatment. This significant improvement suggests that the intervention had a strong positive impact on the dependent variable, effectively enhancing the performance of this group. In contrast, the control group showed negligible change in scores over time, with a mean of 8.457 (SD = 1.506) before treatment and 8.565 (SD = 1.303) after treatment.

Table 2. Descriptive Statistics for Scores by Time and Group

Time Group N Mean SD Coefficient of variation
Before Treatment Experimental 290 8.824 1.660 0.188
Control 230 8.457 1.506 0.178
After Treatment Experimental 290 16.331 1.813 0.111
Control 230 8.565 1.303 0.152

In addition, the minimal variation indicated that the absence of intervention did not result in any noticeable improvement for this group. After treatment, the Experimental group had a smaller coefficient of variation (0.111) compared to the Control group (0.152), suggesting less variability in scores within the Experimental group post-treatment. Furthermore, the inferential statistics of speaking skills between the experimental and control groups are presented in Tables 3 and 4 below.

Table 3 presents the results of the two-way repeated measures ANOVA for speaking skills scores, examining the effects of Time (pre- and post-test) and the Time  x  Group interaction (Experimental vs. Control group over time). The effect of indicates a statistically significant difference in the dependent variable (speaking proficiency) across the two time points (before and after Treatment). This implies that scores changed substantially over time overall. The effect size (η2) suggests that 26.3% of the variance in speaking proficiency scores is explained by the passage of time. This means that participants improved their speaking skills overall, regardless of the group they were in. Additionally, the Time  x  Group interaction finding shows that the score changes over time for the Experimental and Control groups differed considerably. This indicates that the changes in the Experimental and Control groups over time varied, suggesting that the treatment’s impact depended on the group. The effect size indicates that 24.8% of the variance in speaking proficiency improvement is due to the interaction between time and group, confirming that the experimental group demonstrates significantly greater gains in speaking proficiency compared to the control group.

Table 3. Within & Between Subjects Effects for Speaking Test Scores

Cases df Mean Square F p η2
Within-Subjects Effects
Time 1 3719.631 1401.914 < .001 0.263
Time x Group 1 3510.304 1323.020 < .001 0.248
Between-Subjects Effects
Group 1 4242.680 1717.692 < .001 0.300

Note. All analyses use Type III Sum of Squares

The inferential statistics presented in Table 4 were based on the speaking skills scores of the experimental and control groups before and after the intervention of Vocabulary Learning Strategies (VLSs). A significant impact of the group was found in the between-subjects analysis (F (1, 518) = 1717.692, p < .001, η2 = 0.300), suggesting that there were significant variations in the total scores of the experimental and control groups. The effect size (η2 = 0.300) indicated that 30.0% of the variance in speaking skills test scores could be attributed to group differences. This moderate to large effect size confirmed that the experimental group, which received VLS instruction, significantly outperformed the control group in speaking skills acquisition.

Table 4 summarizes the descriptive statistics of the post-vocabulary level tests for both groups. The results indicate that the experimental group outperformed the control group in the post-RVLT test; the experimental group’s mean score of 61.39 was higher than the control group’s mean score of 35.56 in the post-RVL test. In addition, the experimental group’s mean score of 33.93 surpassed the control group’s mean score of 17.67 in the post-PVLT, as shown in the table above. Hence, it can be inferred that the given treatment, i.e., high-frequency vocabulary instruction through activation strategies, has proven effective in enhancing students’ vocabulary knowledge.

Table 4. Descriptive Statistics of the Post-Receptive and Productive Vocabulary Level Test.

Post-Receptive Vocabulary Level Test
Group N Total Score Min. Max. Mean SD
Control 230 75 24 42 35.56 4.041
Experimental 290 75 50 72 61.39 3.906
Post-Productive Vocabulary Level Test
Group N Total Score Min. Max. Mean SD
Control 230 45 10 27 17.67 3.422
Experimental 290 45 23 41 33.93 2.757

Table 5 presents the results of descriptive statistics for the post-Receptive and Productive Vocabulary Level Tests of the Experimental Group. The experimental group’s mean score in the post-RVLT was higher than their mean score in the pre-RVLT. Additionally, the experimental group’s post-PVLT mean score exceeded the mean score in the pre-PVLT.

Table 5. Descriptive Statistics of the Post-Receptive and Productive Vocabulary Level Tests of Experimental Group.

 Type of Group N Total Score Min Max Mean SD
Pre-RVLT Experiment Group 290 75 28 45 37.33 3.408
Post-RVLT Experiment Group 290 75 50 72 61.39 3.906
Pre-PVLT Experiment Group 290 45 7 30 15.53 3.615
Post-PVLT Experiment Group 290 45 23 41 33.93 2.757

Therefore, it can be concluded that the experimental group’s receptive and productive vocabulary knowledge improved through the instruction of high-frequency vocabulary. Furthermore, the inferential statistics of the receptive and productive vocabulary tests are presented in the tables below.

Table 6 presents the results of the two-way repeated measures ANOVA for receptive vocabulary test scores, examining the effects of Time (pre- and post-test) and the Time x Group interaction (experimental vs. control group over time). The main effect of Time was statistically significant indicating that participants’ receptive vocabulary scores significantly improved from the pre-test to the post-test across both groups. The effect size suggests that Time had a moderate-to-large impact on vocabulary improvement. The Time x Group interaction effect was also statistically significant demonstrating that the experimental and control groups experienced different levels of improvement over time. The large effect size indicates that a substantial portion of the variance in post-test scores could be attributed to the interaction between time and group membership. This suggests that the experimental group’s receptive vocabulary gains were significantly greater than those of the control group, confirming the effectiveness of the intervention.

Table 6. Within & Between Subjects Effects for Receptive Vocabulary Test Scores

Cases df Mean Square F p η2
Within-Subjects Effects
Time 1 30875.529 2607.392 < .001 0.238
Time x Group 1 43943.987 3711.003 < .001 0.339
Between-Subjects Effects
Group 41751.115 3041.774 < .001 0.322

The between-subjects effects for receptive vocabulary test scores of the experimental and control groups, examines the overall differences in vocabulary knowledge between them. The effect of group was statistically significant indicating a difference in receptive vocabulary knowledge between the experimental and control groups. The effect size suggests that 32.2% of the variance in receptive vocabulary test scores can be attributed to group differences. This large effect size confirms that the experimental group, which received VLS instruction, significantly outperformed the control group in receptive vocabulary acquisition.

Table 7 presents the results of a two-way repeated measures ANOVA for productive vocabulary test scores, analyzing the effects of Time (pretest and posttest) and the Time  x  Group interaction (experimental and control group). The main effect of Time was statistically significant, suggesting that participants’ productive vocabulary knowledge increased significantly from pretest to posttest across both groups. The effect size indicates that 36.9% of the variance in productive vocabulary scores was attributed to the passage of time, meaning that participants improved their vocabulary knowledge overall. The Time x Group interaction effect shows that the extent of improvement varied significantly between the experimental and control groups. The effect size of 0,251 indicates that 25.1% of the variance in productive vocabulary improvement was due to the interaction between time and group, confirming that the experimental group outperformed the control group.

The between-subjects effects for productive vocabulary test scores of the experimental and control groups, examines the overall differences in vocabulary knowledge between them. The effect of Group was statistically, indicating a significant difference in productive vocabulary knowledge between the experimental and control groups. The effect size (η2 = 0.229) suggests that 22.9% of the variance in productive vocabulary test scores can be attributed to group differences. This large effect size confirms that the experimental group, which received VLS instruction, significantly outperformed the control group in productive vocabulary acquisition.

Table 7. Within-Subjects Effects for Productive Vocabulary Test Scores

Cases df Mean Square F p η2
Within-Subjects Effects
Time 1 26077.116 2544.913 < .001 0.369
Time x Group 1 17763.712 1733.593 < .001 0.251
Between-Subjects Effects
Group 1 16191.559 1554.285 < .001 0.229

Discussion

The overall results of the current study revealed important connections between the extent to which rural ESL learners improved their speaking skills and how they optimized specific high-frequency vocabulary learning activation strategies. The study also found that learners enhanced both receptive and productive vocabulary knowledge by effectively using the vocabulary strategies listed in the methodology section. First, the results of a two-way ANOVA with one repeated measure indicated that learners in the experimental group outperformed those in the control group on the speaking test. Within-subjects effects for Time and the interaction between Time and Group revealed that the eta squared (η² = 0.263) suggested that 26.3% of the variance in speaking proficiency scores could be attributed to the effect of time, indicating that a substantial portion of score improvement was due to the intervention. According to Plonsky and Oswald (2014), η² values of 0.01, 0.06, and 0.14 correspond to small, medium, and large effects, respectively. Similarly, Norouzian and Plonsky (2018) emphasize that η² values above 0.14 should be interpreted as large effects. Given that η² = 0.263 was well above the conventional threshold for a large effect, this finding provided strong evidence that the intervention had a substantial impact on speaking proficiency.

Additionally, the Time x Group interaction result indicated that the experimental and control groups exhibited a substantial change in their scores over time, as shown in Table 3. These results were consistent with those of Alharthi (2020) and Rajy and Najah (2020), who demonstrated that teaching vocabulary through strategies enables students to improve their speaking skills. This indicates that the changes over time differed between the experimental and control groups, suggesting that the treatment had varying effects depending on the group. The descriptive statistics presented in Table 2 reinforced these findings, showing that the experimental group’s mean speaking proficiency score increased after treatment, whereas the control group exhibited negligible. The coefficient of variation was also lower in the experimental group post-treatment, indicating more uniform improvements among participants.

Regarding RQ 2, which addresses whether there is a difference in receptive and productive vocabulary knowledge between the experimental group and the control group, the within-subjects effects for receptive vocabulary, as shown in Table 6, indicated a significant main effect of time, suggesting an overall improvement in receptive vocabulary scores across both groups. However, the interaction effect of time and group demonstrated that the experimental group showed significantly greater gains than the control group. The between-subjects analysis, as shown in Table 7, further confirmed this effect, with the experimental group outperforming the control group by a substantial margin.

A similar trend is observable for productive vocabulary knowledge, as shown in Table 7, where the main effect of time was statistically significant confirming improvements over time. The interaction effect indicated that the experimental group showed significantly greater gains than the control group. The between-subjects effects, presented in Table 7, supported this finding, indicating that a significant portion of the variance in productive vocabulary scores could be attributed to the intervention. Table 4 further supported these results. In the post-receptive vocabulary test, the experimental group achieved a mean score of 61.39, compared to 35.56 for the control group. Similarly, in the post-productive vocabulary test, the experimental group’s mean score of 33.93 far exceeded that of the control group, which was 17.67. When examining only the experimental group’s progress, as shown in Table 6, there was a clear improvement from pre-test to post-test in both receptive (from 37.33 to 61.39) and productive vocabulary scores (from 15.53 to 33.93). These results highlighted the significant role of high-frequency vocabulary activation strategies in fostering both receptive and productive vocabulary knowledge.

Limitations and Suggestions

The current study presents several limitations that should be acknowledged. First, the research exclusively focuses on high-frequency vocabulary commonly used in everyday communication and academic contexts while overlooking mid-frequency and low-frequency vocabulary. This restricts the scope of the findings, as vocabulary development across the full frequency spectrum was not explored. Second, although both receptive and productive vocabulary knowledge were assessed, the study did not delve into the depth and breadth of vocabulary knowledge. Given that the participants are low-proficient ESL learners from rural areas, their vocabulary is inherently limited. Third, the study concentrates exclusively on improving speaking skills through vocabulary knowledge, ignoring other language skills such as writing, listening, and reading. Additionally, the research is confined to secondary-level learners, which means it did not consider primary or tertiary-level students. Consequently, the findings may not be applicable to learners who are more proficient. Therefore, future research could expand on these limitations by exploring the role of high-frequency vocabulary strategies across various educational levels and proficiency groups. Moreover, longitudinal studies examining the long-term effects of teaching high-, mid-, and low-frequency vocabulary on speaking proficiency would offer more comprehensive insights. Further investigations could examine the use of digital tools, such as mobile applications and online platforms, to teach high-frequency vocabulary in both rural and urban ESL contexts, thereby enhancing accessibility and learner engagement.

Conclusion

This study highlighted the importance of vocabulary learning strategies in teaching high-frequency vocabulary to improve speaking skills among rural ESL learners. It proposes that teaching a threshold of 2,494 word families through vocabulary learning strategies is essential for enhancing the speaking skills of these students. The results reveal that the experimental group outperformed the control group in both post-speaking and post-vocabulary level tests. This indicates that the treatment implemented in this study effectively improved the speaking skills and vocabulary knowledge of the students. Moreover, these findings have significant pedagogical implications, advocating for the integration of such strategies into ESL curricula to support language acquisition in rural contexts. Therefore, teachers should incorporate these strategies into vocabulary instruction, and learners need to engage in more pedagogically practical activities to enhance their speaking performance. Despite the positive results, this study has limitations: it focused solely on rural learners. Future research could investigate the long-term effects of these strategies, explore the impact across different age groups and proficiency levels, and compare the speaking skill performance of urban and rural learners. Overall, this study underscores the potential of high-frequency vocabulary activation strategies in improving the speaking skills and vocabulary knowledge of rural ESL learners.

Acknowledgements

I would like to extend my sincere gratitude to the heads of institutions and English teachers across five government secondary schools for their support and assistance during this study. Moreover, I am deeply thankful to the students who voluntarily participated in this research and helped me gain insights from this study.

About the Authors

Raju Dhuli is a PhD scholar in English Language Teaching at the School of Humanities, Social Sciences, and Management at the Indian Institute of Technology Bhubaneswar, India. He earned an MA in English from the Central University of Andhra Pradesh and excelled in the UGC NET in Linguistics in 2019. His research began in 2021, aiming to improve speaking skills among rural secondary school students through vocabulary knowledge. His research interests include vocabulary development, speaking skills, second language acquisition, language assessment, and teacher education. ORCID ID: 0000-0001-8909-5103

Rajakumar Guduru is currently serving as an Assistant Professor of English Language Teaching at the School of Humanities, Social Sciences, and Management at the Indian Institute of Technology Bhubaneswar, India. He earned his MA, M.Phil, and PhD degrees in English Language Teaching (ELT) from the English and Foreign Languages University (EFLU), Hyderabad, India. His research interests encompass developing critical vocabulary for ESL learners, cognitive reading skills, second language acquisition, teacher education and development, communication skills, and the integration of technology in language learning. ORCID ID: 0000-0002-0928-1166

To Cite this Article

Dhuli, R. & Guduru, R. (2025). The impact of high-frequency vocabulary activation strategies in improving speaking skills and vocabulary knowledge of rural ESL learners.  Teaching English as a Second Language Electronic Journal (TESL-EJ), 29(2). https://doi.org/10.55593/ej.29114a2

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Appendices:

Appendix A: Speaking Test Topics

1. Describe your favorite animal and explain why you like it.

You should say:
What is the favorite animal?
Why you like it?
Qualities of the animal

2. Talk about a family member or friend who is important to you.

You should say:
Who is that person?
Why is she/he important
Their qualities

3. Share a story about a memorable day at school.

You should say:
What is the memorable day?
When it was
What happened on that day?

4. Discuss your favorite hobby or activity and why you enjoy it.

You should say:
What is the hobby/activity?
Why you enjoy it
What you do it in it

5. Describe a book or a movie that you really like.

You should say:
What is the name of book/movie?
Who are the characters in it
Why you like it

6. Talk about your favorite season and the activities you like to do during that time.

You should say:
What is the season?
What are the activities?
Why you like the season

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Appendix-B: Receptive Vocabulary-Level Test

1st 1000 Word List:

Game Island Note mouth Plan Think
ପାଟି ✓
ଧ୍ୟାନ ଦିଅନ୍ତୁ ✓
ଯୋଜନ ✓

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Appendix-C: Controlled Productive Vocabulary-Level Test:

  1. I am glad we had this opp————– to talk.
  2. There are a doz—–eggs in the basket.
  3. Every working person must pay income t—–.
  4. The thieves buried the trea——-on a desert island.
  5. Her beauty and ch——- had a powerful effect on men.
  6. La——– of rain led to a shortage of water in the city.
  7. He takes cr—————- and sugar in his coffee.
  8. The rich man died and left all his we——–to his son.
  9. Stud—————-must hand in their papers by the end of the week.

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