Microsoft Word - 8441 7137 Copyright © 2025 The Author IDEAS is licensed under CC-BY-SA 4.0 License Issued by English study program of IAIN Palopo IDEAS Journal on Language Teaching and Learning, Linguistics and Literature ISSN 2338-4778 (Print) ISSN 2548-4192 (Online) Volume 13, Number 2, December 2025 pp. 7137 - 7148 The Relationship Between the Intensity of Watching Netflix Series in English and the Speaking Ability of 3rd Semester English Education Students at Sriwijaya University Vigo Dikaprio1, Eryansyah2 1,2 Faculty of Teacher Training and Education Sriwijaya University Indralaya Corresponding E-Mail: vigodikaprio@gmail.com Received: 2025-10-13 Accepted: 2025-12-09 DOI: 10.24256/ideas.v13i2.8441 Abstract This study investigates whether the viewing intensity of English Netflix series correlates with speaking ability among 24 third-semester English Language Education students at Sriwijaya University. Using a quantitative correlational design, data were collected over one semester via a viewing intensity questionnaire and a speaking ability test, and analyzed using Pearson Correlation. The results indicated no significant relationship between viewing intensity and speaking ability (r = 0.123, Sig. = 0.519). The remarkably low coefficient of determination (r2 = 1.51) suggests that variance in speaking ability is almost entirely explained by factors other than the intensity of passive viewing. Consequently, the study concludes that passive viewing of Netflix alone is ineffective as a sole tool for improving speaking ability, and its potential as a language learning medium is only realized when integrated with active learning strategies and productive language tasks. Keywords: Netflix Viewing Intensity, Speaking Ability, English Language Learning (EFL), Correlation, Audiovisual Input. Introduction In the contemporary digital landscape, Subscription Video-on-Demand (SVOD) platforms, most notably Netflix, have established themselves as essential conduits for media consumption, particularly among the younger demographic. This accessibility has naturally led to its widespread adoption as a potent resource for Second Language (L2) acquisition, specifically within the domain of English as a Foreign Language (EFL) (Dizon, 2018; Hakim & Chiani, 2019). Diverging from Vigo Dikaprio, Eryansyah The Relationship Between the Intensity of Watching Netflix Series in English and the Speaking Ability of 3rd Semester English Education Students at Sriwijaya University 7138 traditional broadcast models, services like Netflix provide users with autonomy over an extensive, multi-genre catalog available in a multitude of languages, offering an authentic and rich source of language input (Chen & Hwang, 2020; Dizon & Thanyawatpokin, 2021). The technical ability to pause, rewind, and utilize adjustable multilingual subtitles further empowers students to customize their viewing experience to align with their current proficiency level, making the platform a powerful prospective tool for language instruction (Vanderplank, 2016). A significant body of academic inquiry supports the connection between audiovisual consumption and subsequent oral proficiency in English. Consistent exposure to genuine, contextualized English media, such as series and films, is instrumental in acclimating students to various native dialects, the natural tempo of speech, and idiomatic expressions (Polio & Lee, 2019). Research has established a measurable link between viewing English content and enhanced speaking capabilities, citing advantages such as an expanded lexical repertoire, more precise articulation, and a deeper grasp of cultural context (Maulisa et al., 2023; Tajgozari, 2019). However, it is crucial to distinguish between passive and active video use. While passive viewing, which is inherent in general media consumption, primarily aids listening comprehension and vocabulary, the literature consensus emphasizes that maximizing the pedagogical efficacy of video resources requires active strategies, such as focused practice, self-recording, and integrating content into productive tasks (Saed et al, 2021; Shabani & P Zanussi, 2015). This active engagement is vital for translating comprehensible input into measurable oral outcomes (Montero Perez et al., 2013). Despite the widespread acknowledgement in numerous studies demonstrating a positive link between exposure to English-language video content and the resultant enhancement of bilingual skills, a distinct research deficit persists within the Indonesian higher education context. While prior investigations have generally documented the broad merits of consuming English content (Tajgozari et al, 2019), they have insufficiently explored the precise impact of viewing habits in a quantitative manner. Existing studies have not tested how much viewing intensity, as a measurable behavioral habit, predicts speaking performance in Indonesian EFL university settings. This lacuna is particularly significant given the environment in Indonesian tertiary education, where students are undergoing concurrent intensive language development and cultural adjustment (Maharani et al, 2024). Consequently, the present research is designed to bridge this identified gap by meticulously investigating the specific correlation between patterns of Netflix consumption (viewing frequency and duration) and measurable English speaking proficiency outcomes among third-semester students enrolled in the English education program at Universitas Sriwijaya. A secondary objective is to evaluate the platform's effectiveness and propose a practical pedagogical framework that IDEAS, Vol. 13, No. 2, December 2025 ISSN 2338-4778 (Print) ISSN 2548-4192 (Online) 7139 would allow instructors to effectively integrate Netflix viewing as a structured, evidence-based element of the language learning curriculum in higher education. Method The research employed a quantitative approach utilizing a correlational research design to systematically investigate the relationship between two principal variables. The independent variable (X) was the Intensity of Watching Netflix English Series, while the dependent variable (Y) was the students' English- Speaking Ability. According to Creswell (2013), this statistical approach was chosen to characterize and quantify the extent of the association between these two variables. Operationally, viewing intensity was defined by five core indicators: weekly viewing frequency, total duration of viewing, preferred subtitle usage, content type variety, and the level of active engagement during watching. Speaking Ability was measured based on the students' oral effectiveness, assessed through their fluency, grammatical accuracy, pronunciation clarity, vocabulary breadth, and observable confidence in English (Creswell, 2013). The population for this study consisted of all 93 second-semester (later referred to as 3rd semester) students enrolled in the English Education Study Program at Sriwijaya University during the 2024/2025 academic year. The researcher implemented purposive sampling, a nonprobability technique, to carefully select participants based on specific, predefined inclusion criteria. These criteria required students to be active 3rd-semester students, possess access to and confirmed experience watching Netflix, and willingly commit to participating in all research phases. This method ensured the quality and relevance of the collected data. This targeted selection process resulted in a final sample size of 30 students, a number which is statistically appropriate for conducting a rigorous correlational analysis (Willie, 2022). Data collection relied on two distinct instruments: a questionnaire and a speaking ability test. The intensity questionnaire was administered electronically via Google Forms and measured the independent variable using 25 statement items rated on a 5-point Likert scale (ranging from Very Often to Never) across the five operational indicators. The speaking ability test was conducted online using platforms like Zoom Meeting and WhatsApp, with each student undergoing a 10- minute session. The test involved a picture description task followed by a free speaking segment chosen by the student. Assessment utilized a detailed rubric with a 1–4 scale to score key aspects pronunciation, grammar, vocabulary, and fluency and all speaking sessions were digitally recorded to maintain the objectivity and reliability of the evaluation process (Ginther, 2012). The collected quantitative data was processed and interpreted using the Statistical Package for the Social Sciences (SPSS) version 25.0. Data preparation involved converting the Likert scale responses into total numerical scores for the intensity variable (X) and averaging the speaking test rubric scores for the ability variable (Y). Prior to the main analysis, essential prerequisite tests specifically the Vigo Dikaprio, Eryansyah The Relationship Between the Intensity of Watching Netflix Series in English and the Speaking Ability of 3rd Semester English Education Students at Sriwijaya University 7140 Kolmogorov-Smirnov Normality Test and a Linearity Test were performed to ensure the data met the necessary assumptions for parametric statistics. The core analysis involved the Pearson Product-Moment Correlation to determine the strength and direction of the variables' relationship. The Hypothesis Test was conducted using a significance level (alpha) of 0.05: the null hypothesis (H0), stating no significant relationship, would be rejected only if the calculated significance value (Sig. 2-tailed) was less than 0.05. Results Normality Test The normality test using the Kolmogorov-Smirnov method was conducted to assess the distribution of anxiety scores (ZSRAS) across the two groups of pregnancy exercise intensity (3.00 and 4.00). Results indicated non-significant values (p = 0.200 for intensity 3.00 and p = 0.182 for intensity 4.00, both > 0.05), confirming that the data in each group follow a normal distribution. This fulfillment of the normality assumption supports the validity of applying parametric tests, such as the independent samples t-test, to compare mean differences in anxiety levels between the groups. Table 1. Tests of Normality Tests of Normality Kolmogorov-Smirnova Shapiro-Wilk VariabelX Statistic df .106 30 Sig. .200* Statistic df .977 30 Sig. .745 VariabelY .142 30 .129 .968 30 .481 According to Table 4.4, normality assessment was performed on VariableX and VariableY using both Kolmogorov-Smirnov (with Lilliefors adjustment) and Shapiro-Wilk tests, each applied to a sample size corresponding to 30 degrees of freedom. The Kolmogorov-Smirnov outcomes revealed a statistic of 0.106 (p = 0.200) for VariableX and 0.142 (p = 0.129) for VariableY, whereas the Shapiro-Wilk results displayed statistics of 0.977 (p = 0.745) and 0.968 (p = 0.481), respectively. Since every p-value exceeded the 0.05 threshold across the two methods, the distribution of both variables is confirmed to be normal, satisfying the prerequisite for subsequent parametric procedures. Focusing specifically on the Kolmogorov-Smirnov approach, the analysis yielded identical statistics and significance levels for the two variables under a df of 30. With p-values of 0.200 for VariableX (adjusted via Lilliefors, representing the conservative estimate) and 0.129 for VariableY—both above 0.05—the null hypothesis of non-normality is retained. Consequently, the normality condition is met, enabling the application of parametric statistical techniques for further investigation. IDEAS, Vol. 13, No. 2, December 2025 ISSN 2338-4778 (Print) ISSN 2548-4192 (Online) 7141 Linearity Test Table 2. Tests of Linearity Source Sum of Squares df Mean Square F Sig. Between Groups (Combined) 514.200 24 21.425 0.401 .941 Linearity 11.742 1 11.742 0.220 .659 Deviation from Linearity 502.458 23 21.846 0.409 .935 Within Groups 267.000 5 53.400 Total 781.200 29 According to Table 4.5 from the ANOVA output for the linearity test, the evaluation aimed to determine if a straight-line association exists between English- language Netflix series viewing frequency (Variable X) and speaking proficiency (Variable Y). In the Between Groups (Combined) row, the Sum of Squares reaches 514.200 across 24 degrees of freedom, yielding a Mean Square of 21.425, an F statistic of 0.401, and a p-value of 0.941. The Linearity row reports a Sum of Squares of 11.742 for 1 degree of freedom, a Mean Square of 11.742, an F of 0.220, and p = 0.659, while the Deviation from Linearity row displays a Sum of Squares of 502.458 over 23 degrees of freedom, a Mean Square of 21.846, an F of 0.409, and p = 0.935. The Within Groups section records a Sum of Squares of 267.000 with 5 degrees of freedom and a Mean Square of 53.400, and the Total Sum of Squares stands at 781.200 for 29 degrees of freedom. With the deviation from linearity p-value at 0.935 (exceeding 0.05), non- linearity is statistically insignificant, confirming that the connection between Netflix viewing intensity and speaking skills adheres to a linear model. This outcome satisfies the linearity prerequisite for Pearson correlation, permitting parametric procedures to quantify the association's magnitude and direction. The test verifies that the scatter diagram linking viewing intensity to speaking performance exhibits a straight rather than curved trajectory, thereby justifying the application of the Pearson coefficient to assess the variables' relational strength. Correlation Analysis and Hypothesis Testing Table 3. Pearson Correlation Results Variable X Variable Y Variable X Pearson Correlation 1 .123 Sig. (2-tailed) .519 N 30 30 Variable Y Pearson Correlation .123 1 Sig. (2-tailed) .519 Vigo Dikaprio, Eryansyah The Relationship Between the Intensity of Watching Netflix Series in English and the Speaking Ability of 3rd Semester English Education Students at Sriwijaya University 7142 N 30 30 Table 3 presents the Pearson correlation coefficient matrix examining the linear relationship between Variable X (intensity of watching English Netflix series) and Variable Y (speaking ability) based on a sample of 30 participants. The correlation value between the two variables is r = .123, indicating a very weak positive association. This means that as the frequency or duration of watching Netflix series in English increases, speaking ability tends to improve slightly, but the magnitude of this change is minimal and practically negligible. The diagonal elements show perfect correlations of 1.000 for each variable with itself, which is expected in a correlation matrix, while the sample size (N = 30) remains consistent across all computations, ensuring reliability in the pairwise analysis. The two- tailed significance level is reported as p = .519, which is substantially higher than the conventional alpha threshold of 0.05, confirming that the observed correlation is not statistically significant. The non-significant p-value suggests that the slight positive trend could easily occur by random chance in the population, and there is insufficient evidence to reject the null hypothesis of no linear relationship between the variables. In practical terms, this implies that watching English Netflix series, at least within the measured intensity levels in this study, does not meaningfully contribute to enhancing speaking proficiency among the participants. Researchers and educators should interpret this result cautiously; while a weak positive link exists, it lacks both statistical backing and substantive impact. Future studies may benefit from larger samples, more precise measurement of viewing habits (e.g., active vs. passive exposure, subtitle usage), or inclusion of mediating factors such as learner motivation, language input quality, or deliberate practice to better capture potential influences on speaking development. Hypothesis Testing Results Based on the correlation analysis results and following the methodology established in Chapter III, hypothesis testing was conducted to examine the relationship between the intensity of watching English-language Netflix series and the speaking ability of third-semester students in the English Education Study Program at Sriwijaya University. The research hypotheses proposed were H0, which stated that there was no significant relationship between the variables, and H1, which stated that there was a significant relationship between the intensity of watching English-language Netflix series and English-speaking ability. Table 4 Hypothesis Testing Results Statistical Component Value Interpretation Pearson correlation 0.123 Very weak positive correlation Significance (p-value) 0.519 Not significant Sample size (N) 30 – Alpha level (α) 0.05 Significance threshold IDEAS, Vol. 13, No. 2, December 2025 ISSN 2338-4778 (Print) ISSN 2548-4192 (Online) 7143 Table 4 summarizes the hypothesis testing outcomes for the relationship between Variable X (intensity of watching English Netflix series) and Variable Y (speaking ability), revealing a Pearson correlation coefficient of 0.123. This value falls within the range of 0.00 to 0.19, conventionally classified as a very weak positive correlation, indicating that higher levels of Netflix viewing are associated with only marginal improvements in speaking performance. With a sample size of 30 participants, the correlation reflects a pattern where increased exposure to English-language content through streaming slightly aligns with better speaking scores, yet the effect size is so small that it offers negligible practical significance. In educational contexts, such a coefficient suggests that passive consumption of Netflix series alone contributes minimally to oral proficiency development, as the shared variance between the variables is approximately 1.5% (calculated as r² = 0.123² ≈ 0.015), meaning over 98% of the variation in speaking ability remains unexplained by viewing intensity. The significance test yields a p-value of 0.519, far exceeding the predetermined alpha level of 0.05, leading to failure to reject the null hypothesis of no linear relationship. This non-significant result implies that the observed weak correlation could readily arise from random sampling variation rather than a true population effect. Given the modest sample size (N = 30), statistical power is limited, increasing the risk of Type II error; however, the extremely low correlation magnitude reinforces that even with greater power, any underlying association would remain trivial. Educators and language practitioners should thus prioritize active speaking practice, interactive language use, and structured output activities over reliance on passive media consumption. Future research could enhance precision by employing larger samples, longitudinal designs, or controlled experiments that distinguish between subtitle use, binge-watching duration, and deliberate language-focused viewing to isolate more meaningful predictors of speaking improvement. Discussion The primary finding from the Pearson correlation analysis indicates an extremely weak positive relationship (r = 0.123) between the intensity of watching English-language Netflix series and speaking ability among the 30 participants. This coefficient, though positive, falls far below thresholds typically considered meaningful in educational research (e.g., r ≥ 0.30 for moderate effect). Such a low value suggests that passive exposure to spoken English via streaming platforms contributes only marginally to oral proficiency. In practical terms, even substantial increases in viewing hours are unlikely to yield noticeable gains in fluency, accuracy, or confidence in spoken production. The non-significant p-value of 0.519 reinforces the conclusion that this weak association does not differ reliably from zero in the population. With an alpha level set at 0.05, the evidence fails to support the hypothesis that Netflix viewing intensity meaningfully influences speaking performance. This outcome aligns with Vigo Dikaprio, Eryansyah The Relationship Between the Intensity of Watching Netflix Series in English and the Speaking Ability of 3rd Semester English Education Students at Sriwijaya University 7144 second language acquisition (SLA) principles emphasizing the critical role of output practice and interaction over mere input exposure. While comprehensible input (Krashen, 1985) is foundational for language development, speaking—a productive skill—requires active retrieval, negotiation of meaning, and corrective feedback, elements largely absent in passive viewing contexts. Several methodological factors may explain the negligible correlation. First, the measurement of “intensity” likely captured total viewing time rather than focused, deliberate engagement with linguistic features. Participants may have watched for entertainment, with subtitles in their native language, or during multitasking—conditions that dilute linguistic processing. Second, speaking ability was presumably assessed via a single instrument (e.g., a test or interview), which may not fully capture dynamic, context-dependent oral skills. A more nuanced operationalization—such as tracking active shadowing, repetition, or post-viewing discussion—could reveal different patterns. The sample size of 30, while adequate for basic correlation, limits statistical power and generalizability. With only 30 data points, the study is vulnerable to sampling error, and subtle effects may go undetected. Moreover, participant homogeneity (e.g., similar proficiency levels, age, or motivation) could suppress variability in both variables, artificially constraining the correlation. Future investigations should recruit larger, more diverse samples and control for confounding variables such as prior English exposure, subtitle usage, and extracurricular language practice. Another critical consideration is the nature of Netflix content itself. Series vary widely in speech rate, vocabulary load, accent diversity, and narrative complexity. A learner watching fast-paced dialogue in regional British English with slang may extract less transferable input than one viewing slower, clearer speech in standardized American English. The study did not differentiate content type, treating all English-language viewing equally. This aggregation likely masks differential impacts, as not all input is equally facilitative for speaking development. Theoretically, the results challenge popular claims that extensive media consumption alone can significantly boost spoken fluency. While incidental vocabulary acquisition may occur through viewing (Rodgers & Webb, 2011), the leap to productive use especially in real-time conversation requires deliberate practice. Swain’s (1995) Output Hypothesis posits that pushing learners to produce language fosters noticing of gaps and triggers deeper processing. Netflix, as a one- way medium, offers no such push, explaining why viewing intensity correlates so weakly with speaking outcomes. From a pedagogical standpoint, these findings urge caution against overpromoting streaming as a primary language-learning tool. Language programs should integrate media strategically perhaps through pre-viewing vocabulary activation, post-viewing speaking tasks (e.g., summaries, role-plays), or subtitled viewing followed by shadow-speaking exercises. Such scaffolding transforms passive consumption into active practice, aligning input with output demands. IDEAS, Vol. 13, No. 2, December 2025 ISSN 2338-4778 (Print) ISSN 2548-4192 (Online) 7145 Standalone binge-watching, however, appears insufficient for measurable speaking gains. In conclusion, while watching English Netflix series may provide enjoyable, low-anxiety exposure to the target language, the current study demonstrates that intensity of viewing does not translate into improved speaking ability in any substantial or statistically reliable way. Educators, learners, and curriculum designers should prioritize interactive, output-focused activities and view media as a supplementary rather than central component of speaking development. Future research with refined measures, larger samples, and experimental controls may yet identify specific viewing conditions under which streaming supports oral proficiency. Conclusion The study reveals that the intensity of watching English-language Netflix series shares only a very weak and statistically non-significant positive correlation (r = 0.123, p = 0.519) with speaking ability among the 30 participants. This finding indicates that passive exposure to spoken English through streaming media, even when frequent, contributes minimally to the development of oral proficiency. The effect size is practically negligible, with less than 2% of the variance in speaking scores explained by viewing intensity (r² ≈ 0.015). Consequently, learners and educators cannot reasonably expect substantial improvements in fluency, accuracy, or communicative confidence from increased Netflix consumption alone. The results align with established SLA theories that emphasize the necessity of active language production and interaction—processes largely unsupported by one-way media intake—for meaningful gains in productive skills. In light of these outcomes, it is clear that while Netflix offers accessible and engaging comprehensible input, it should be positioned as a supplementary rather than primary tool for speaking development. Language programs are advised to integrate viewing strategically with output-oriented tasks, such as post-episode discussions, role-plays, or structured retelling, to bridge the gap between input and production. The non-significant correlation, combined with the small sample and potential measurement limitations, underscores the need for future research employing larger, more diverse cohorts, longitudinal designs, and controlled variables (e.g., subtitle use, content type, active engagement) to identify specific conditions under which media exposure may support speaking improvement. Until such evidence emerges, deliberate practice remains the cornerstone of effective oral language acquisition. References Agram, A., Mokhtari, N., & Laaboudi, D. (2024). 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