ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 13, Issue 2, June 2025 https://journal.uniku.ac.id/index.php/ERJEE 633 EVALUATING GENRE-BASED APPROACH ON SPEAKING PERFORMANCE ACROSS DIFFRENT ANXIETY LEVELS IN INDONESIAN EFL STUDENTS Hendra Putra1, Rudi Hartono*2, Januarius Mujianto3, Yuliati4 1,2,3,4English Language Education Program,Universitas Negeri Semarang,Semarang,Indonesia Corresponding author: rudi.hartono@mail.unnes.ac.id APA Citation: Putra, H., Hartono, R., Mujianto, J., & Yuliati. (2025). Evaluating genre-based approach on Received: 23-02-2024 Accepted: 25-04-2024 Published: 30-06-2025 Abstract: One of speaking performance is presentation the topic material. In presentation the topic material nursing students implement the genre-based approach. This study examines the effectiveness of genre-based approach to enhance speaking performance. This study employed One-Group Pretest-Post-test Design. To collect the data used questionnaire and pre-test and post- speaking test. In analyzing the data of questionaire used Horwitz et.al and grouped them into three level anxety. The result found that the effectiveness of genre- based approach to enhance speaking performance on EFL students for high level anxiety is significant. It can be seen from the p-value = 0.022 is smaller than α = 0.05. If the p-value < α, then the null hypothesis (H0) is rejected, and the alternative hypothesis (H1) is accepted.The effectiveness of genre-based approach to enhance speaking performance on EFL students for moderate level anxiety is not signficant because the p- value = 0.165 is greater than α = 0.05. If the p-value > α, then the null hypothesis (H0) is not rejected, and the alternative hypothesis (H1) is not accepted. The effectiveness of genre-based approach to enhance speaking performance on EFL students for low level anxiety is significant because the p-value = 0.001 is smaller than α = 0.05. If the p-value is very small like this, then the null hypothesis (H0) is rejected very strongly, and the alternative hypothesis (H1) is accepted very strongly. It can be concluded that the genre-based approach was found to significantly improve speaking performance in students with high and low anxiety, but not moderate anxiety. Keywords:level of anxiety,EFL students, genre-based approach; speaking performance INTRODUCTION English is taught differently depending on the students' and university's needs. It is stated that in Ministry of Law and Human Rights or Kementrian Hukum dan HAM (2012) number 12 of 2012 about higher education article 37 paragraph 3 stated that foreign languages can be used as languages introduction to universities. It means that English still exists to be held at the university level. Many countries study English in the world. Because English is needed to communicate. Based on Richard and Yorkey C (2000) in Supeno & Suseno, (2020) elucidate how this makes English one of the most widely spoken languages worldwide. English is a mandatory subject in Indonesia. All students, regardless of educational level, from basic to advanced, must take this topic. In the field,English is taught four times at Universitas Fort De Kock Bukittinggi- West Sumatera Indonesia. The course's goal is for nursing students to be able to comprehend the fundamentals of English, the English for Nursing (English III) description equips students with the skills to read, listen, speak, and write in English while comprehending the nursing process and discussing medical-surgical nursing in particular. The third English course builds on the material covered in courses I and II that students took the semester before. One of skills must be mastered by students is speaking. Based on Marley (2005) in Knezevic (2017) shows how speaking and listening are intimately intertwined. Listening is the most used ability in daily life, being used five times more speaking performance across diffrent anxiety levels in Indonesian EFL students. English Review: Journal of English Education, 13(2), 633-652. https://doi.org/10.25134/erjee.v13i2.11844 mailto:rudi.hartono@mail.unnes.ac.id Hendra Putra, Rudi Hartono, Januarius Mujianto, Yuliati Evaluating genre-based approach on speaking performance across diffrent anxiety levels in Indonesian EFL students 634 than writing, four times more than reading, and twice as much as speaking. Furter, Susilawati et al.(2017) in Khasinah et al. (2024), Speaking is a skill that is commonly evaluated by looking at how well one performs in different situations and presentations. Then, Nanthaboot (2014) in Chulee et al. (2023) the "ability to share information fluently and accurately, including the ability to choose appropriate vocabulary and structures in all contexts" is what is meant by speaking competence as a productive macro skill. Speaking is therefore seen as a crucial ability that aids pupils in learning English In English III (English for nursing), nursing students are taught by team. It means that a half semester is taught by one lecturer and a half semester does too. From the materials or topics stated above, of course, English lecturers and nurse students have some difficulties in understanding them. English lecturers can be seen from two things. The first thing is from English who graduate from non-English departments. She or he has difficulty in teaching English III about how to explain the material with correct grammar, pronounce sentence by sentence, and master vocabulary. It is supported by the researcher's question and answers the previous time, she said that I have difficulties in teaching English III even though theoretically I know the knowledge. After that from an English lecturer who graduates from the English department. She said that she did not have knowledge or experience about the materials and does not know what approach, strategy, method, and technique to teach. More specifically, the study discovered a few issues in the classroom. Based on first hand observations made in the classroom, the researcher discovered several notes. A lecturer in English often uses a reading technique when teaching nursing students. She stated in the interview that she employs the reading strategy when teaching a certain subject in the classroom, which lends more credence to it. It is evident from the explanation. In pre-teaching, examine the learners prior knowledge regarding oxygen. For example what they already know about definition, uses the oxygen, and installation tools). Then whilst teaching, give the text related to how to install the oxygen in a group. Finally, in post- teaching, ask the students to make the text on how to install the oxygen by using their own words and ask them to prepare themself to practice it in the laboratory to use the real object at that university. The researcher was interviewed in March 2023. In addition, the researcher also interviews some alumni who graduated from the university. He said that English used in the hospital is a daily conversation form. So English is needed in the hospital. The other alumni said that the kinds of English that are needed are explaining the procedure something. It means that the explanation of alumni makes the researcher want to know more details about what suitable approach can be used in mastering English III. Not only English lecturers get difficulties,the nursing students have difficulties understanding the material for English III to be highlighted in this research. Some problems can be found when students speak up in front of the classroom when they deliver the material or topic of English III. The problems are mispronouncing, not being smooth, not being in order or free, sweating, getting nervous, not confident, mixing language, unstable voice, lack of concentration, and shivering, there was no generic structure in delivering the topic when presentation, reading aloud when presentation in front of the class. These conditions were approved by Ur (2014) says that there are some difficulties in English speaking such as, fear of making mistakes, shyness, students‟ have no motivation, lack of vocabulary, they prefer to use their mother tongue and tend to have low participation in the class. In general, speaking is a challenge for many students. According to Cheng, (2017) in Cancino & Cabello (2024) elucidate how foreign language speaking anxiety (FLSA) is one of the main things preventing language progress. The speaking issues were divided into three categories: linguistic issues (fluency, grammar, vocabulary, and pronunciation), affected-related issues (anxiety and self-confidence), and social issues (difficulties finding opportunities to study English and comprehension in speaking class).However, Purwati et al. (2023) discover that teaching and learning to speak is complicated by three factors: the external factors (the classroom environment and negative remarks from teachers and peers), the psychological factors (anxiety, lack of motivation, and lack of confidence), and the linguistics factor (the complexity of the competencies). Moreover, Pinter (2006) in Cabañas & Mercado (2024) Speaking involves two simultaneous processes: speaking and thinking, which is what makes it a difficult action. As we speak, we organize our thoughts to convey them clearly while simultaneously keeping an eye on ourselves to fix any errors.In addition,, Nakazawa (2012) in Berry (2021) Speaking in a foreign language can ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 13, Issue 2, June 2025 https://journal.uniku.ac.id/index.php/ERJEE 635 induce anxiety in kids because they worry about how they pronounce words. Mispronouncing, not being smooth, not being in order or free, sweating, being anxious, lacking confidence, mixing language, having an unstable voice, losing focus, and shaking are the issues that stand out when compared to the nursing students in this study. Most of nursing students are passive in answering the questions given. They did not spontaneously answer the questions and even the lecturers pointed them to answer the question given. Also they do not want to speak if the lecturer asks them to speak up. Moreover, they did not use the simple approach or pattern to deliver their idea in presentation. When it is seen from ministry of labour, many countries need health workers. According to Kurniati et al. (2020) say that in 2030 there will be 23 foreign countries in the world that need health workers as nurses and midwives. In contrast in Indonesia itself, Indonesia has overlap nurses. To overcome this condition, the health ministry collaborates with the world to distribute health workers from Indonesia. Furthermore, the health minister delivers that the constraint of graduates or alumni in applying for the opportunity is in the English language. It is vital to investigate how nursing students convey the genre-based approach or text genres, as this influences speaking and English for certain reasons. The researcher is therefore excited to look at how the nursing students communicate to present the subject by using a genre-based approach or different text kinds. Specifically, teaching and studying English is done to improve speaking abilities in the classroom. Given how education is changing in the modern world, a genre-based approach is becoming more and more significant. In the classroom, genre- based instruction helps students comprehend textual structures, which facilitates the development of strong analytical abilities and helps students understand the function and target audience of various genres. Because it offers a methodical, useful, and efficient way to educate students on how to comprehend, analyse, and create texts within particular genres. Its use is supported by both theoretical and real-world advantages that cater to students' demands in social, professional, and academic settings. GBA is a crucial method in contemporary education because it gives students the skills they need to navigate and create texts in a range of contexts by emphasizing the function, structure, and linguistic characteristics of genres. This study aims to investigate the effectiveness of genre-based approach to enhance speaking performance of nursing students. These are the studies inquire: 1.How is the effectiveness of the Genre-Based Approach to Enhance the Speaking Performance of Nursing Students with High anxiety, Moderate anxiety and Low anxiety? To avoid misunderstanding the researchers made the theoretical perspective. They are: firstly, Derewianka (2003) explores that Genre- based approaches, where teaching and learning focuses on the understanding and production of selected genres of texts (both spoken and written), have become increasingly influential in the field of English language teaching (ELT). Secondly it is about speaking performance. According to H. Douglas Brown (2004) When nursing students present the topic materials, they must pay attention to some aspects. The marks as folow 3 = Excellent, 2 = good, 1= fair and 0 = Poor. Thirdly, English for specific purpose means that teaching and learning proces based on students request. When it is related to the topic provided in the syllabus of course can be said all of the materials or topic needed when they work in the public health hospital. It is supported by Richards & Schmidt (2010) recognized ESP as a movement that aims to meet the language requirements of learners who use English to fulfill certain tasks (such as those of a student, engineer, or nurse) and who must acquire content and practical skills through the language rather than mastering it for its own sake. Lastly is anxiety, in this study focusses on level anxiety made by nursing students when presenting the topic presentation povided. It is used the theory from Horwitz et al. (1986) explain that there are 33 statements that must be filled by nusing students then analyze the result which is included into high enxiety,moderately high anxiety, moderate anxiety, moderately low anxiety and very low anxiety. Beside knowing the level anxiety. Then,it was grouped by ranking the students anxiety. it was grouped into high anxiety, moderate anxiety and low anxiety. METHOD The authors employed a One-Group Pretest- Posttest Design to carry out this study. It alludes to the fact that a single group is tested before and after the intervention. There are 71 nursing Hendra Putra, Rudi Hartono, Januarius Mujianto, Yuliati Evaluating genre-based approach on speaking performance across diffrent anxiety levels in Indonesian EFL students 636 students in all that consist of 42 of whom are in the control group and 29 of them are in the treatment group. Yet, only experimental group get intervention or treatment. So, a genre-based approach is used in the treatment group to enhance speaking performance. Meanwhile, control group implemented the conventional approach. In collecting dara,the questionnaire and test are the two instruments employed in this study. First, it has to do with the survey. The steps are as follows: a). Foreign Language Classroom Anxiety Scale (FLCAS) questionnaire created into a Google Form. There are thirty-three statements in the questionnaire. b). Nursing students from Universitas Riau in Indonesia were given the questionnaires. It indicates that neither the participants nor the sample. c). the questionnaires rechecked validity and reliability after receiving the results of the tryout. The statements then total twenty-six d). a questionnaire comprising 26 statements was created using Google Form and given to the sample of 71 nursing students. e). they were categorized based on the calculated results. The speaking test process goes as follows: a) the questions are validated by a validator; b) the questions are based on the syllabus or taught materials; c) the 71 students are asked to select one topic to present via a brief video; d) two inter- raters correct the recording video by analyzing the speaking performance rubric proposed by Brown; e) the speaking test is analyzed, and the students are divided into control and treatment groups. It can be seen that nursing class A is the control group and nursing class B is the treatment group. The following methods can be used to analyze the data (speaking test and questionnaire). First, when examining the questionnaire, the author followed the guidelines suggested by the Horwitz et al. (1986) the FLCAS questionnaire provides the first set of quantitative data.The questionnaire included 33 statements at first, but after being tested at various universities and having its validity and reliability checked, it had 26 statements overall. Additionally, the information gathered from the students' completed surveys was calculated using the Horwitz computation rubric below: For positive context questions, students received a score of 1 if they answered "Strongly Agree," 2 if they agreed, 3 if they answered "Neutral," 4 if they disagreed, and 5 if they severely disagreed. As an alternative, pupils receive a score of 5, "Agree" receives a score of 4, and "Neutral" receives a score of 3 if they choose "Strongly Agree" in response to questions with a negative background. Additionally, students who selected "Disagree" received a score of 2, while those who selected "strongly disagree" received a score of 1. Following the compilation of all student responses into numerical values, Krinis conducted an analysis of the data using an anxiety-level scale to ascertain the students' anxiety levels, as reported by Widia Utari et al., (2022) in Krinis, (2007); Alrabai, (2014). The researchers then modified these questions, starting with very low anxiety (scale 33–82), moderately low anxiety (scale 83–89), moderately high anxiety (scale 99–108), moderately low anxiety (scale 47–67), moderately low anxiety (scale 68– 88), moderately high anxiety (scale 89–109), and high anxiety (scale 109–165). Based on the quartile value, the researcher divided the anxiety into three levels: low anxiety (starting from 1– 36.49), moderate anxiety (starting from 36.50- 52.99), and high anxiety (starting from 53.00– 71.00). It involved there are 12 participants in high anxiety level, 10 participants in moderate level and there are 7 participants in low anxiety level. When evaluating the speaking test, the speaking test is corrected by the inter rater using a video recording. Fifteen items need to be examined. Based on evaluation of the several facets of the speaker's presentation, give each item or element a number or score. Three means excellent, two is decent, one is average, and zero is poor. In summary, to analyze the test used descriptive analysis and inferencial analysis. It means that descriptive analysis used standard deviation and mean, test of normality, test of homogeneity, and hypothesis tests employed for inferential analysis. To know more detail rubric speaking performance from Brown Rubric of Oral Presentation Checklist (Brown:2001) Evaluation of Oral Presentation. Assign a number to each box according to your assessment of the various aspects of the speaker's' presentation. 3 = Excellent,2 = good,1= fair and 0 = Poor. The are 15 aspect as rubri speaking perormance. They are 1) the purpose or objective of the presentation was accomplished,2) the introduction was lively and got my attention.,3) the main idea or point was clearly stated toward the beginning,4) the supporting,were clearly expressed and supported well by facts, argument,5) the conclusion restated the main- idea or purpose. 6). the speaker used gestures and-body language well,7) the speaker maintained eye contact with the audience,8) the speaker's language was natural ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 13, Issue 2, June 2025 https://journal.uniku.ac.id/index.php/ERJEE 637 and fluent, 9) the speaker's volume of speech was appropriate,10) the speaker's rate of speech was appropriate,11) the speaker's pronunciation was clear and comprehensiblem,12) the speaker's grammar was correct and didn't prevent understanding,13) the speaker used visual aids, handouts, etc., effectively,14) the speaker showed enthusiasm and interest,15) [If appropriate] the speaker responded to audience questions well. Result 1.Finding the Effectiveness of the Genre-Based Approach to Enhance the Speaking Performace of Nursing Students with high anxiety To comprehend the finding can be seen from two side, namely descriptive analysis and inferential analysis. 1.1 Descriptive Analysis ( mean score, standard deviation and test absolute of gain score). 1.1.1Mean The mean is calculated by adding together all of the scores and dividing that amount by the number of scores. Finding the average score of the pupils in both groups was the purpose of the mean.The formula can be used from Hatch and Farhady. (1982) in T, (2011) x̄ = Σx N x̄ = Mean Σx = Total score N = Number of the students Hatch and Farhady. (1982) 1.1.2 Standard Deviation Standard deviation showed the spread of scores’ distribution. The larger the standard deviation, the more variability from the control point in the distribution, vice versa. SD= N N SD = Standard deviation ΣX = Total score N = Number of the students Hatch and Farhady.(1982) The classification section is created in this instance. The categorizations were separated into four primary sections, which were the classification of the categorization of experimental group’s pre-test, the categorization of experimental group’s post-test, the categorization of control group’s pre-test and the categorization of control group’s post-test. categorization of speaking performance with high anxiety CONTROL WITH HIGH ANXIETY No Name of participants V1 V2 V3V4V5V6V7V8V9V10V11V12V13V14V15V16V17V18V19V20V21V22V23V24V25V26 RSUM RAN002 Ranking Anxitey pre-test post test No Name of participants pre-test post test 1 Sahdam anarqi 3 5 3 2 3 3 4 4 4 3 3 3 3 3 4 3 5 3 4 3 4 4 4 3 4 3 52 52 3 23 19 1 Sahdam anarqi 23 19 2 Rima purnama sari 3 3 4 4 4 5 4 4 3 4 4 5 4 4 4 4 4 4 4 4 4 4 4 1 4 4 64,5 64,5 3 20 21 2 Rima purnama sari 20 21 3 Ruli nurfadilla 3 4 3 5 4 3 5 4 4 3 4 5 2 3 2 3 3 4 3 2 3 4 3 4 3 4 52 52 3 22 24 3 Ruli nurfadilla 22 24 4 Titi mardianti 3 4 4 4 4 4 3 4 4 3 4 4 2 3 4 4 4 4 4 4 4 4 4 4 4 4 62,5 62,5 3 22 28 4 Titi mardianti 22 28 5 Ade anggraini putri 3 4 4 4 4 3 4 4 3 3 4 4 4 2 4 4 3 3 3 3 3 4 3 3 4 2 49,5 49,5 3 16 28 5 Ade anggraini putri 16 28 6 Sherly 3 4 4 4 3 3 4 4 4 4 3 4 4 3 3 4 3 3 5 4 4 4 5 4 4 4 62,5 62,5 3 26 27 6 Sherly 26 27 7 Hainil hayati 3 1 5 5 3 4 4 5 4 5 4 4 3 4 4 5 5 3 5 5 4 5 5 3 5 5 69,5 69,5 3 22 25 7 Hainil hayati 22 25 8 Rumrowi 3 5 5 5 5 5 4 4 4 5 4 2 5 5 3 5 2 5 5 3 3 2 5 4 5 5 69,5 69,5 3 16 24 8 Rumrowi 16 24 9 Oktarina lestari 3 4 4 4 2 3 4 4 4 4 4 4 2 3 4 3 3 4 4 4 3 3 3 3 3 3 49,5 49,5 3 22 23 9 Oktarina lestari 22 23 10 Shofia ittaqi fella 3 1 5 5 2 4 5 5 4 4 5 4 3 2 4 3 3 5 4 3 3 4 4 3 4 5 61 61 3 26 31 10 Shofia ittaqi fella 26 31 11 Husnatul azizah 3 1 5 5 5 5 5 5 5 5 5 5 4 4 3 5 3 5 5 5 4 5 5 4 5 5 71 71 3 26 30 11 Husnatul azizah 26 30 12 Dhelmi azra putri 4 2 4 4 3 5 5 4 4 5 4 4 4 2 4 4 4 4 4 4 4 4 4 4 5 5 66 66 3 24 36 MEAN 21,9090909 25,4545455 13 Laura selvia putri 4 2 4 4 2 4 4 4 3 4 3 4 4 4 5 4 3 3 3 4 4 4 3 3 4 4 57 57 3 10 36 SD 3,36977327 3,55127727 14 Adila aldinia putri 4 2 4 4 3 3 4 4 4 4 3 4 3 4 3 4 4 3 4 4 4 4 3 4 4 4 59 59 3 19 33 15 Putri hadist shalsabila 4 2 4 4 3 3 4 4 4 4 4 4 2 2 3 4 2 4 4 4 3 4 4 2 4 4 52 52 3 19 33 TREATMENT WITH HIGH ANXIETY LEVEL 16 Selviana ramadani 4 2 3 4 3 4 3 4 3 3 3 3 3 3 4 4 3 4 5 4 5 3 4 3 5 4 55,5 55,5 3 29 29 No Name of participants pre-test post test 17 Maviola triyardi 4 5 4 3 5 3 3 3 4 5 4 4 5 3 5 5 5 4 3 3 4 3 5 5 3 5 67 67 3 16 32 12 Dhelmi azra putri 24 36 18 Salsabila daratul h 2 1 4 4 3 3 4 5 4 3 4 4 2 3 5 5 4 3 3 4 3 4 4 3 5 4 55,5 55,5 3 21 32 13 Laura selvia putri 10 36 19 Pebriani 3 4 4 4 3 5 4 3 3 3 5 4 3 4 2 2 1 4 3 3 5 3 5 4 3 4 54 54 3 32 27 14 Adila aldinia putri 19 33 20 Muhamad Ridwan 4 3 4 5 4 5 5 5 5 3 4 5 3 2 4 4 4 5 5 3 3 4 4 4 5 4 68 68 3 26 28 15 Putri hadist shalsabila 19 33 21 Oktavina dewani f 4 2 4 4 2 4 5 3 5 4 4 4 2 1 4 4 4 4 4 3 3 4 5 2 5 5 59 59 3 27 25 16 Selviana ramadani 29 29 22 Amelia putri 4 4 2 2 4 4 5 4 3 4 4 4 3 3 3 5 3 4 4 3 4 4 3 3 5 4 59 59 3 24 18 17 Maviola triyardi 16 32 23 M.Ikhsan maulana 4 1 5 4 4 4 5 5 5 4 3 4 5 2 4 4 2 3 4 4 4 4 3 3 5 5 64,5 64,5 3 19 26 18 Salsabila daratul h 21 32 MEAN 22,04347826 27,60869565 19 Pebriani 32 27 SD 4,804692099 4,80705216 20 Muhamad Ridwan 26 28 21 Oktavina dewani f 27 25 22 Amelia putri 24 18 23 M.Ikhsan maulana 19 26 MEAN 22,1666667 29,5833333 SD 5,81425451 4,95745791 Figure 1. Categorization of speaking performance wth high anxiety level The categorization of control group’s pre-test scores Table 1. Mean and standard deviation of the pre- test in the control Group term Quantity Mean (M) 21.90 Standard Deviation (SD) 18.54 Table 2. The formula in categorizing the control group’s pre-test Hendra Putra, Rudi Hartono, Januarius Mujianto, Yuliati Evaluating genre-based approach on speaking performance across diffrent anxiety levels in Indonesian EFL students 638 Score category Basic formula Defined formula Good X ≥ M + SD X≥25.26 Average M – SD ≤ X < M + SD 18.54≤ X < 25.26 Low X < M – SD X < 18.54 Tables above show that the pre-test control mean (M) is 21.90 and the standard deviation (SD) is 3.36. When a student's speaking performance score (X) exceeds or equals the mean plus standard deviation (X > M + SD (25.26)), it is deemed "good." Meanwhile, the student's speaking performance score is considered "average" if X is greater than or equal to mean minus standard deviation (X ≥M – SD (18.54)) and less than mean plus standard deviation (X < M + SD (25.26)). If a student's score (X) is less than the mean minus standard deviation (X < M – SD (18.541)), they are said to have a "low" speaking performance score. The results of applying the method to the control group's speaking performance scores are displayed in table above, where the frequency of the "good" category is 3, the "average" category is 6, and the "low" category is 2. Furthermore, it is evident from the percentage that the "good" category achieves 27%, the "average" category reaches 55%, and the "low" category only reaches 18%. When the data is categorized, it is evident that the pre-test results for the control group's students' speaking performance are primarily on the average level. The categorization of control group’s post-test Table 3. Mean and standard deviation of the post- test in the control Group term Quantity Mean (M) 25.45 Standard Deviation (SD) 3.55 Table 4. The formula in categorizing the control group’s post-test Score category Basic formula Defined formula Good X ≥ M + SD X≥29 Average M – SD ≤ X < M + SD 21.9≤ X < 29 Low X < M – SD X < 21.9 It is clear from tables above that the post-test control mean (M) is 25.45 and the standard deviation (SD) is 3.55. If the student's speaking performance score (X) is greater than or equal to the mean plus standard deviation (X ≥ M + SD (29)), it is classified as "good." In the meantime, if X is larger than or equal to mean minus standard deviation (X ≥M – SD (21.9)) and less than mean plus standard deviation (X < M + SD (29)), the student's speaking performance score is deemed "average." A student is considered to have a "low" speaking performance score if their score (X) is less than the mean minus standard deviation (X < M – SD (21.9)). Tables above displays the results of applying the algorithm to the control group's speaking performance scores. It indicates that the frequency of the "good" category is 2, the "average" category is 8, and the "low" category is 1. Furthermore, it is evident from the percentage that the "good" group achieves 18%, the "average" category gets 73.72%, and the "low" category only reaches 9%. When the data is categorized, it is evident that the post-test results for the control group's students' speaking performance are primarily on the average level. The categorization of treatment group’s pre-test Table 5. Mean and standard deviation of the pre- test in the treatment Group term Quantity Mean (M) 22.16 Standard Deviation (SD) 5.81 Table 6. The formula in categorizing the treatment group’s pre-test Score category Basic formula Defined formula Good X ≥ M + SD X≥27.97 Average M – SD ≤ X < M + SD 16.35≤ X < 27.97 Low X < M – SD X < 16.35 The pre-test treatment mean (M) is 22.16, and the standard deviation (SD) is 5.81, according to tables above. If the student's speaking performance score (X) is greater than or equal to the mean plus standard deviation (X ≥ M + SD (27.97)), it is classified as "good." In the meantime, if X is larger than or equal to mean minus standard deviation (X ≥M – SD (16.35)) and less than mean plus standard deviation (X < M + SD (27.97)), the student's speaking performance score is deemed "average." A student is considered to have a "low" speaking performance score if their score (X) is less than the mean minus standard deviation (X < M – SD (16.35)). The frequency of the "good" category is 2, the "average" category is 9, and the "low" category is 1, as can be seen in table above, which displays the results of applying the algorithm to the speaking performance scores of the treatment ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 13, Issue 2, June 2025 https://journal.uniku.ac.id/index.php/ERJEE 639 group. Furthermore, it is evident from the percentage that the "good" group only achieves 17%, the "average" category gets 75%, and the "low" category only reaches 8%. It is evident from the data categorization that the pre-test results for the treatment group's students' speaking performance are primarily on the average level. The categorization of treatment group’s post-test Table 7. Mean and standard deviation of the post- test in the treatment Group term Quantity Mean (M) 29.58 Standard Deviation (SD) 4.95 Table 8. The formula in categorizing the treatment group’s pre-test Score category Basic formula Defined formula Good X ≥ M + SD X≥34.53 Average M – SD ≤ X < M + SD 24.63≤ X < 34.53 Low X < M – SD X < 24.63 The pre-test treatment mean (M) is 29.58, and the standard deviation (SD) is 4.95, according to tables above. If the student's speaking performance score (X) is greater than or equal to the mean plus standard deviation (X ≥ M + SD (34.53)), it is classified as "good." In the meantime, if X is larger than or equal to mean minus standard deviation (X ≥M – SD (24.63)) and less than mean plus standard deviation (X < M + SD (34.53)), the student's speaking performance score is deemed "average." A student is considered to have a "low" speaking performance score if their score (X) is less than the mean minus standard deviation (X < M – SD (24.63)). The results, which are displayed in Table 8 above, indicate that the frequency of the "good" category is 2, the "average" category is 9, and the "low" category is 1, following the application of the algorithm to the speaking performance scores of the treatment group. Furthermore, it is evident from the percentage that the "good" group achieves 17%, the "average" category gets 75%, and the "low" category only reaches 8%. It is evident from the data categorization that the post- test results for the students' speaking performance from the treatment group are primarily on the average level. Test absolute gain score The author created an absolute gain score test to see whether the experimental group's pupils, who received the genre-based approach, performed better than the control group's students, who received the conventional technique. This test was performed simply by comparing the experimental group's and the control group's pre-test and post- test scores. Stated differently, the score was calculated by subtracting the mean score from the pre-test from the mean score from the post- test.The result of the absolute gain score test could be seen in Table 9 and Table 10 below. Table 9. The absolute gain score of the experimental group Data: Experimental Pre-Test Post-test Gain score Number 23 23 Mean 22.16 29.58 7.42 SD 5.81 4.95 Table 10. The absolute gain score of the control group Data: Control Pre-Test Post- test Gain score Number 23 23 Mean 21.90 25.45 3.55 SD 3.36 3.55 Once the pre-test and post-test mean scores have been processed, Tables 9 and 10 make it evident that the experimental group's gain score is 7.42 points whereas the control group's gain score is only 3.53 points. The experimental group's gain score was unquestionably higher than the control group's. Thus, it can serve as proof that the genre-based strategy is superior to the traditional method for improving university- level nursing students' speaking performance. Inferential analysis Normality test and homogenity test Table 11. Tests of normality speaking performance with high anxiety Kolmogorov-Smirnova Shapiro-Wilk Statistic df Sig. Statistic df Sig. pre-test treatment (high anxiety) ,133 12 ,200* ,984 12 ,995 post-test treatment (high anxiety) ,180 12 ,200* ,931 12 ,388 *. This is a lower bound of the true significance. Hendra Putra, Rudi Hartono, Januarius Mujianto, Yuliati Evaluating genre-based approach on speaking performance across diffrent anxiety levels in Indonesian EFL students 640 a. Lilliefors Significance Correction Table 12. Test of homogeneity of variances speaking performance with high anxiety Levene Statistic df1 df2 Sig. post -test treatment general 1,501 2 26 ,242 pre-test treatment general ,422 2 26 ,660 Hypothesis test Table 13. Paired samples test speaking performance with high anxiety Paired Differences t df Sig. (2-tailed) Mean Std. Deviati on Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 pre-test treatment (high anxiety) - post-test treatment (high anxiety) -7,750 10,065 2,905 -14,145 -1,355 -2,667 11 ,022 This table presents the results of a statistical test called a "Paired Samples Test." This test is used to compare two sets of related data. In this case, it looks at the differences between pre-test and post-test scores for a treatment group experiencing high anxiety. In this table consists of Paired Differences: This section shows the differences between the pre-test and post-test scores.Mean: This is the average difference in scores. For example, a mean of -7.750 indicates that, on average, the post-test scores were lower than the pre-test scores by 7.750 points.Standard Deviation: This number (10.065) tells us how much the differences vary from the average. A higher standard deviation means the scores are more spread out.Standard Error Mean**: This value (2.90) indicates how much the sample mean (average) is expected to vary from the true population mean. It helps us understand the reliability of the mean difference.95% Confidence Interval of the Difference: this section has two values, "Lower" and "Upper." These values (- 14.145 and -1.355) show the range in which we can be 95% confident that the true mean difference lies. Since both values are negative, it suggests that the post-test scores are likely lower than the pre-test scores.**t**: this is the t-statistic value (-2.667). It is used to determine if the differences between the two sets of scores are statistically significant. df: this stands for degrees of freedom (11 in this case). It is a value used in statistical tests that helps determine the critical value for the t-test. And Sig. (2-tailed)**: This value (.022) indicates the p-value. A p-value less than 0.05 suggests that the results are statistically significant, meaning there is a strong likelihood that the observed differences are not due to random chance. The Results can be displayed that the negative mean difference (-7.750) indicates that the treatment had an effect, reducing anxiety levels as measured by the test scores.The p-value of .022 is less than the common threshold of .05, which means we can conclude that the treatment was effective in reducing anxiety.The confidence interval (-14.145 to -1.355) reinforces this finding, as it does not include zero. This suggests that the treatment likely led to a real decrease in anxiety levels. Overall, this table provides strong evidence that the treatment was effective in reducing anxiety among participants. The statistical analysis shows that the differences in scores before and after the treatment are significant, indicating that the treatment had a meaningful impact. This type of test is particularly useful in research where the same subjects are measured before and after an intervention. Finding the effectiveness of the genre-based approach to enhance the speaking performace of nursing students with moderate anxiety To comprehend the finding can be seen from two side, namely descriptive analysis and inferential analysis. ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 13, Issue 2, June 2025 https://journal.uniku.ac.id/index.php/ERJEE 641 Descriptive analysis (mean score, and standard deviation and test absolute of gain score). The classification section is created in this instance. The categorizations were separated into four primary sections, which were the classification of the categorization of experimental group’s pre-test, the categorization of experimental group’s post-test, the categorization of control group’s pre-test and the categorization of control group’s post-test. categorization of speaking performance with moderate anxiety CONTROL GROUP WITH MOERATE ANXIETY LEVEL No Name of participants V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16V17V18 V19 V20 V21 V22 V23 V24 V25 V26 RSUM RAN002 Ranking Anxitey PRE-TEST POST-TEST No Name of participants PRE-TEST POST-TEST 1 Rahul wirdana putra 3 3 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 33,5 33,5 2 22 25 1 Rahul wirdana putra 22 25 2 Vania okta farahgita 3 1 3 4 3 3 3 4 4 2 3 4 2 2 4 5 3 3 4 3 3 3 3 2 4 4 33,5 33,5 2 20 25 2 Vania okta farahgita 20 25 3 Anna fitri 3 1 4 4 2 3 4 4 4 3 2 4 3 2 3 3 3 3 3 4 3 3 3 3 3 3 28,5 28,5 2 28 36 3 Anna fitri 28 36 4 Laila nafisah 3 1 5 4 1 4 5 5 5 4 2 4 1 4 4 5 1 5 5 4 1 3 4 1 1 4 45 45 2 22 27 4 Laila nafisah 22 27 5 Suci anisa rahmawati 3 2 3 4 3 3 4 3 3 3 4 3 4 3 3 3 3 3 3 3 3 3 4 3 4 4 40,5 40,5 2 22 25 5 Suci anisa rahmawati 22 25 6 Putri maharani 3 4 2 3 5 4 3 3 4 3 3 4 3 4 3 3 1 3 3 3 3 3 3 2 2 3 28,5 28,5 2 30 28 6 Putri maharani 30 28 7 Sinta oktaviani 3 2 5 5 5 4 4 3 4 3 2 4 2 3 2 3 2 3 3 4 2 3 3 3 3 3 36,5 36,5 2 23 28 7 Sinta oktaviani 23 28 8 Madonna putri 3 4 4 4 2 4 4 3 3 4 4 4 2 3 3 3 3 3 4 3 3 3 4 3 4 4 47,5 47,5 2 23 23 8 Madonna putri 23 23 9 Miftahul jannah 3 3 3 4 3 5 4 3 4 4 3 3 4 4 3 2 4 1 2 4 3 2 4 4 4 5 47,5 47,5 2 25 28 9 Miftahul jannah 25 28 10 Giska 3 3 3 1 2 3 4 4 3 3 4 4 3 4 3 4 3 4 3 3 3 3 3 3 3 4 36,5 36,5 2 23 25 10 Giska 23 25 11 Najmi hanifah kamil 3 4 3 3 3 3 4 3 4 3 2 3 3 3 4 4 4 3 4 3 3 3 4 4 3 4 46 46 2 24 29 11 Najmi hanifah kamil 24 29 12 Esis erlinatasari 3 2 3 3 3 3 3 3 3 4 4 4 3 3 3 3 3 3 3 4 3 3 3 3 3 3 32 32 2 24 20 12 Esis erlinatasari 24 20 13 Wulan delva eka 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 3 28,5 28,5 2 23 27 13 Wulan delva eka 23 27 14 Hafiz urniawam 2 2 3 4 2 4 5 3 3 4 4 3 2 3 2 3 3 4 4 2 3 3 3 3 3 3 28,5 28,5 2 16 23 MEAN 23,76923077 26,61538462 15 Afiyah 4 2 4 4 3 4 3 3 4 3 3 3 1 3 3 4 1 4 4 3 3 3 4 3 4 4 40,5 40,5 2 18 18 SD 2,546606978 3,584978522 16 Muthia syahrina 3 3 1 2 3 4 4 4 3 3 5 4 1 3 1 5 2 4 3 5 3 3 4 2 3 5 36,5 36,5 2 33 35 17 Zabeli syahbani ponda 3 3 3 1 3 3 5 4 3 4 4 3 3 3 4 1 2 4 4 4 3 4 3 3 4 4 43,5 43,5 2 23 23 18 Winda septria 3 4 4 3 3 3 4 3 3 3 4 3 3 3 3 4 4 3 3 3 2 3 3 3 3 4 40,5 40,5 2 22 17 TREATMENT WITH MODERATE ANXIETY LEVEL 19 Dwi yona afrilia h 3 3 3 3 3 3 4 4 4 3 4 3 3 3 3 4 4 3 3 3 3 3 3 3 3 3 40,5 40,5 2 16 25 No Name of participants PRE-TEST POST-TEST 20 Dea ananda 4 2 4 4 2 4 4 2 4 3 3 5 2 3 3 4 2 3 3 3 2 4 3 2 4 4 36,5 36,5 2 38 29 14 Hafiz urniawam 16 23 21 Endah pertama putri 4 3 3 4 4 3 4 4 3 4 3 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 43,5 43,5 2 13 30 15 Afiyah 18 18 22 Fazel prima filcan 3 2 2 3 3 3 5 4 4 2 2 4 3 3 3 4 1 4 3 2 3 4 4 1 3 5 28,5 28,5 2 13 26 16 Muthia syahrina 33 35 23 Fitri cahyani 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 28,5 28,5 2 24 28 17 Zabeli syahbani ponda 23 23 MEAN 22,82609 26,086957 18 Winda septria 22 17 SD 5,677202 4,4026972 19 Dwi yona afrilia h 16 25 20 Dea ananda 38 29 21 Endah pertama putri 13 30 22 Fazel prima filcan 13 26 23 Fitri cahyani 24 28 MEAN 21,6 25,4 SD 7,939773297 5,2 Figure 2. Categorization of speaking performance with moderate anxiety The categorization of control group’s pre-test scores Table 14. Mean and standard deviation of the pre-test in the control Group term Quantity Mean (M) 23.76 Standard Deviation (SD) 2.54 Table 15. The formula in categorizing the control group’s pre-test Score category Basic formula Defined formula Good X ≥ M + SD X≥26.3 Average M – SD ≤ X < M + SD 21.22≤ X < 26.3 Low X < M – SD X < 21.22 Tables above show that the pre-test control mean (M) is 23.76 and the standard deviation (SD) is 2.54. When a student's speaking performance score (X) exceeds or equals the mean plus standard deviation (X > M + SD (26.3)), it is deemed "good." Meanwhile, the student's speaking performance score is considered "average" if X is greater than or equal to mean minus standard deviation (X ≥M – SD (21.22)) and less than mean plus standard deviation (X < M + SD (26.3)). If a student's score (X) is less than the mean minus standard deviation (X < M – SD (21.22)), they are said to have a "low" speaking performance score. The results of applying the method to the control group's speaking performance scores are displayed in tables above, where the frequency of the "good" category is 2, the "average" category is 10, and the "low" category is 1. Furthermore, it is evident from the percentage that the "good" category achieves 15%, the "average" category reaches 77%, and the "low" category only reaches 8%. When the data is categorized, it is evident that the pre-test results for the control group's students' speaking performance are primarily on the average level. The categorization of control group’s post-test Table 16. Mean and standard deviation of the post-test in the control Group term Quantity Mean (M) 26.61 Standard Deviation (SD) 3.58 Table 17. The formula in categorizing the control group’s post-test Score category Basic formula Defined formula Good X ≥ M + SD X≥30.19 Average M – SD ≤ X < M + SD 23.03≤ X < 30.19 Low X < M – SD X < 23.03 Hendra Putra, Rudi Hartono, Januarius Mujianto, Yuliati Evaluating genre-based approach on speaking performance across diffrent anxiety levels in Indonesian EFL students 642 It is clear from tables above that the post-test control mean (M) is 26.61 and the standard deviation (SD) is 3.58. If the student's speaking performance score (X) is greater than or equal to the mean plus standard deviation (X ≥ M + SD (30.19)), it is classified as "good." In the meantime, if X is larger than or equal to mean minus standard deviation (X ≥M – SD (23.03)) and less than mean plus standard deviation (X < M + SD (30.19)), the student's speaking performance score is deemed "average." A student is considered to have a "low" speaking performance score if their score (X) is less than the mean minus standard deviation (X < M – SD (23.03)). Tables above displays the results of applying the algorithm to the control group's speaking performance scores. It indicates that the frequency of the "good" category is 1, the "average" category is 11, and the "low" category is 1. Furthermore, it is evident from the percentage that the "good" group achieves 7.5%, the "average" category gets 85%, and the "low" category only reaches 7.5%. When the data is categorized, it is evident that the post-test results for the control group's students' speaking performance are primarily on the average level. The categorization of treatment group’s pre-test Table 18. Mean and standard deviation of the pre-test in the treatment Group term Quantity Mean (M) 21.6 Standard Deviation (SD) 7.93 Table 19. The formula in categorizing the treatment group’s pre-test Score category Basic formula Defined formula Good X ≥ M + SD X≥29.53 Average M – SD ≤ X < M + SD 13.67≤ X < 29.53 Low X < M – SD X < 13.67 The pre-test treatment mean (M) is 21.6, and the standard deviation (SD) is 7.93, according to tables above. If the student's speaking performance score (X) is greater than or equal to the mean plus standard deviation (X ≥ M + SD (29.53)), it is classified as "good." In the meantime, if X is larger than or equal to mean minus standard deviation (X ≥M – SD (13.67)) and less than mean plus standard deviation (X < M + SD (29.53)), the student's speaking performance score is deemed "average." A student is considered to have a "low" speaking performance score if their score (X) is less than the mean minus standard deviation (X < M – SD (13.67)). The frequency of the "good" category is 1, the "average" category is 9, and the "low" category is 0, as can be seen in table above, which displays the results of applying the algorithm to the speaking performance scores of the treatment group. Furthermore, it is evident from the percentage that the "good" group only achieves 10%, the "average" category gets 90%, and the "low" category only reaches 0%. It is evident from the data categorization that the pre-test results for the treatment group's students' speaking performance are primarily on the average level. The categorization of treatment group’s post-test Table 20. Mean and standard deviation of the post-test in the treatment Group term Quantity Mean (M) 25.4 Standard Deviation (SD) 5.2 Table 21. The formula in categorizing the treatment group’s pre-test Score category Basic formula Defined formula Good X ≥ M + SD X≥30.6 Average M – SD ≤ X < M + SD 20.2≤ X < 30.6 Low X < M – SD X < 20.2 The pre-test treatment mean (M) is 25.4, and the standard deviation (SD) is 5.2, according to tables above. If the student's speaking performance score (X) is greater than or equal to the mean plus standard deviation (X ≥ M + SD (30.6)), it is classified as "good." In the meantime, if X is larger than or equal to mean minus standard deviation (X ≥M – SD (20.2)) and less than mean plus standard deviation (X < M + SD (30.6)), the student's speaking performance score is deemed "average." A student is considered to have a "low" speaking performance score if their score (X) is less than the mean minus standard deviation (X < M – SD (20.2)). The results, which are displayed in Table 8 above, indicate that the frequency of the "good" category is 2, the "average" category is 6, and the "low" category is 2, following the application of the algorithm to the speaking performance scores of the treatment group. Furthermore, it is evident from the percentage that the "good" group achieves 20%, the "average" category gets 60%, and the "low" category only reaches 20%. It is evident from the data categorization that the post- ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 13, Issue 2, June 2025 https://journal.uniku.ac.id/index.php/ERJEE 643 test results for the students' speaking performance from the treatment group are primarily on the average level. Test absolute gain score The author created an absolute gain score test to see whether the experimental group's pupils, who received the genre-based approach, performed better than the control group's students, who received the conventional technique. This test was performed simply by comparing the experimental group's and the control group's pre-test and post- test scores. Stated differently, the score was calculated by subtracting the mean score from the pre-test from the mean score from the post- test.The result of the absolute gain score test could be seen in tables below. Table 22. The absolute gain score of the experimental group Data: Experimental Pre-Test Post-test Gain score Number 23 23 Mean 21.6 25.4 3.8 SD 7.93 5.2 Table 23. The absolute gain score of the control group Data: Control Pre-Test Post-test Gain score Number 23 23 Mean 23.76 26.61 2.85 SD 2.54 3.58 Once the pre-test and post-test mean scores have been processed, Tables above make it evident that the experimental group's gain score is 3.8 points whereas the control group's gain score is only 2.85 points. The experimental group's gain score was unquestionably higher than the control group's. Thus, it can serve as proof that the genre- based strategy is superior to the traditional method for improving university-level nursing students' speaking performance. Inferential analysis Normality test and homogenity test Table 24, Tests of normality speaking performance with moderate anxiety Kolmogorov-Smirnova Shapiro-Wilk Statistic df Sig. Statistic df Sig. pre-test treatment (moderate anxiety) ,187 10 ,200* ,888 10 ,160 post-test treatment (moderate anxiety) ,131 10 ,200* ,972 10 ,911 *. This is a lower bound of the true significance. a. Lilliefors Significance Correction Table 25. Test of homogeneity of variances speaking performance with moderate anxiety Levene Statistic df1 df2 Sig. post -test treatment general 1,501 2 26 ,242 pre-test treatment general ,422 2 26 ,660 Hypothesis test Table 26. Paired samples test speaking performance with moderate anxiety Paired Differences t df Sig. (2- tailed) Mean Std. Deviatio n Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 pre-test treatment (moderate anxiety) - post-test treatment (moderate anxiety) -3,800 7,955 2,516 -9,491 1,891 -1,510 9 ,165 From the table, the test is used a Paired Samples Test. As it is known that a paired samples test is a statistical method used to compare two related groups. It helps researchers understand if there is a significant difference between the two sets of data. In this case, the test compares scores from a pre-test and a post-test for the same group of participants. Hendra Putra, Rudi Hartono, Januarius Mujianto, Yuliati Evaluating genre-based approach on speaking performance across diffrent anxiety levels in Indonesian EFL students 644 The table has some Structures. They are Mean: this is the average difference between the pre-test and post-test scores. In this case, the mean difference is -3.800, which suggests that, on average, the post-test scores are lower than the pre-test scores. Standard Deviation:this number (7.955) shows how much the differences between the scores vary. A higher standard deviation means that the scores are spread out over a wider range. Standard Error Mean: This value (2.516) indicates how much the sample mean (average) is expected to vary from the true population mean. It gives an idea of the accuracy of the sample mean. Confidence Interval: This section provides a range (from -9.491 to 1.891) within which we can be 85% confident that the true mean difference lies. If this range includes zero, it suggests that there may not be a significant difference between the two tests. t-value: The t-value (-1.510) is a statistic that helps determine if the differences observed are statistically significant. A larger absolute value of t typically indicates a more significant difference. df (degrees of freedom):This value (9) is calculated based on the number of pairs of scores. It helps in determining the critical value for the t-test. Significance (Sig. (2-tailed)):** This value (.165) tells us whether the results are statistically significant. A common threshold for significance is 0.05. Since .165 is greater than 0.05, we conclude that the difference between the pre-test and post-test scores is not statistically significant. Interpreting the Results can be explained that the negative mean difference (-3.800) indicates that, on average, participants scored lower on the post-test compared to the pre-test. This could suggest that the treatment or intervention had an effect, but we need to consider the significance level. The confidence interval ranges from -9.491 to 1.891. Since this range includes zero, it implies that we cannot confidently say there is a significant difference between the pre-test and post-test scores. The significance value of .165 indicates that there is a 16.5% chance that the observed difference is due to random variation rather than a true effect. This is above the common threshold of 5%, suggesting that the results are not statistically significant. In summary, the paired samples test results show that while there is a noticeable average decrease in scores from the pre-test to the post- test, this difference is not statistically significant. This means that we cannot conclude that the treatment had a meaningful impact on reducing anxiety levels based on this data alone. Further research with larger sample sizes or different methodologies may be needed to draw more definitive conclusions. Finding of the effectiveness of genre-based approah to enhance speaking performance of nursing students with low anxiety level at university fort de kock Bukittinggi To comprehend the finding can be seen from two side, namely descriptive analysis and inferential analysis. Descriptive Analysis ( mean score, and standard deviation and test absolute of gain score). The classification section is created in this instance. The categorizations were separated into four primary sections, which were the classification of the categorization of experimental group’s pre-test, the categorization of experimental group’s post-test, the categorization of control group’s pre-test and the categorization of control group’s post-test. Table 27. Categorization of speaking performance with low anxiety ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 13, Issue 2, June 2025 https://journal.uniku.ac.id/index.php/ERJEE 645 categorization of speaking performance with low anxiety control with ;ow anxiety No Name of participants V1 V2V3 V4 V5V6V7V8V9V10V11V12V13V14V15V16V17V18V19V20V21V22V23V24V25V26 RSUM RAN002 Ranking Anxitey Pre-test Post-test No Name of participants pre-test post-test 1 Dina febri monita 3 3 3 3 3 3 3 3 3 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 23,5 23,5 1 24 28 1 Dina febri monita 24 28 2 Bella tania hasibuan 3 3 3 2 3 3 3 3 1 1 3 3 3 3 3 3 3 3 3 2 3 3 3 2 1 2 7 7 1 20 27 2 Bella tania hasibuan 20 27 3 Endang dian pratiwi 3 2 3 3 3 3 3 3 3 4 3 4 3 3 3 3 2 3 3 4 4 3 3 3 2 3 23,5 23,5 1 13 26 3 Endang dian pratiwi 13 26 4 Yelma widiya 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 18,5 18,5 1 22 27 4 Yelma widiya 22 27 5 Sindi ramadhani 3 1 3 3 2 4 3 3 4 4 2 3 2 2 3 3 2 4 4 4 3 4 3 2 4 4 23,5 23,5 1 16 29 5 Sindi ramadhani 16 29 6 Tiara mustika 3 3 1 1 2 2 1 2 2 2 3 2 1 4 2 1 1 2 1 1 1 1 2 2 2 2 1 1 1 30 32 6 Tiara mustika 30 32 7 Tarisa 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 18,5 18,5 1 23 27 7 Tarisa 23 27 8 Oriana ulandari 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 18,5 18,5 1 21 25 8 Oriana ulandari 21 25 9 Nurul husni binti 3 3 1 3 4 1 3 2 3 3 3 3 1 4 3 3 2 3 2 4 3 3 3 3 2 2 9 9 1 41 27 9 Nurul husni binti 41 27 10 Suci dwi sari 3 4 1 2 5 2 2 3 3 3 4 5 2 3 1 3 1 2 1 1 3 3 2 3 1 3 6 6 1 31 37 10 Suci dwi sari 31 37 11 Sabrilla fandari 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 18,5 18,5 1 37 27 11 Sabrilla fandari 37 27 12 Melani putri dewita 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 23,5 23,5 1 24 24 12 Melani putri dewita 24 24 13 Rahmi annisa 3 2 3 3 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 14 14 1 20 20 13 Rahmi annisa 20 20 14 Rosdeva yani 3 2 3 3 3 3 3 3 3 3 3 3 3 2 2 3 3 2 2 3 3 3 4 1 4 4 11 11 1 21 20 14 Rosdeva yani 21 20 15 Chalisa rizky hafidzah 3 1 1 1 1 2 3 3 3 3 2 3 2 3 2 3 2 3 3 3 3 3 3 2 3 3 5 5 1 22 39 15 Chalisa rizky hafidzah 22 39 16 Muhammad dicky.R. 3 5 3 2 2 1 3 3 1 2 3 3 1 3 1 3 2 1 1 5 3 3 2 2 1 3 3 3 1 34 39 16 Muhammad dicky.R. 34 39 17 Agyta putri utami 3 3 3 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 3 3 3 3 3 3 3 18,5 18,5 1 12 32 17 Agyta putri utami 12 32 18 Nabilla tahma y 3 2 2 1 1 1 3 3 2 2 3 3 1 5 1 2 1 1 1 1 2 3 1 1 1 2 2 2 1 26 39 18 Nabilla tahma y 26 39 19 Hafiz akbar 3 3 3 2 3 1 2 2 3 2 2 2 1 3 2 5 4 2 3 3 2 4 3 3 2 4 8 8 1 13 29 MEAN 24,27777778 29,16666667 20 Mujahidah al fidayah 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 18,5 18,5 1 22 34 SD 7,577785924 5,842849381 21 Dhea aprilia 2 2 3 4 3 2 2 2 1 2 3 3 3 3 4 2 3 3 2 2 3 2 2 2 1 2 4 4 1 13 22 22 Dinda khairunisa 4 3 3 3 3 3 3 3 2 3 2 3 2 4 2 3 2 3 3 3 3 3 3 3 3 3 13 13 1 22 37 TREATMENT WITH LOW ANXIETY 23 Hanif muhamad a 3 2 3 2 3 4 4 2 2 4 4 3 3 2 3 3 2 3 4 3 3 2 2 2 4 2 11 11 1 13 22 No Name of participants pre-test post-test 24 Nurfazira 3 1 3 2 2 3 4 3 4 4 3 3 3 3 3 4 2 3 2 3 2 3 3 2 3 3 11 11 1 17 20 19 Hafiz akbar 13 29 25 Cindy Assifa husna 3 3 1 3 3 3 3 5 4 3 5 4 1 3 1 3 2 2 3 4 3 3 3 1 5 3 15 15 1 31 38 20 Mujahidah al fidayah 22 34 MEAN 22,72 29,08 21 Dhea aprilia 13 22 SD 7,6499412 6,209155 22 Dinda khairunisa 22 37 23 Hanif muhamad a 13 22 24 Nurfazira 17 20 25 Cindy Assifa husna 31 38 MEAN 18,71428571 28,85714286 SD 6,249897958 7,059513772 The categorization of control group’s pre-test scores Table 28. Mean and standard deviation of the pre-test in the control Group term Quantity Mean (M) 24.27 Standard Deviation (SD) 7.57 Table 29. The formula in categorizing the control group’s pre-test Score category Basic formula Defined formula Good X ≥ M + SD X≥31.84 Average M – SD ≤ X < M + SD 16.7≤ X < 31.84 Low X < M – SD X < 16.7 Tables above show that the pre-test control mean (M) is 24.27 and the standard deviation (SD) is 7.57. When a student's speaking performance score (X) exceeds or equals the mean plus standard deviation (X > M + SD (31.84)), it is deemed "good." Meanwhile, the student's speaking performance score is considered "average" if X is greater than or equal to mean minus standard deviation (X ≥M – SD (16.7)) and less than mean plus standard deviation (X < M + SD (31.84)). If a student's score (X) is less than the mean minus standard deviation (X < M – SD (16.7)), they are said to have a "low" speaking performance score. The results of applying the method to the control group's speaking performance scores are displayed in tables above, where the frequency of the "good" category is 3, the "average" category is 13, and the "low" category is 2. Furthermore, it is evident from the percentage that the "good" category achieves 17%, the "average" category reaches 72%, and the "low" category only reaches 11%. When the data is categorized, it is evident that the pre-test results for the control group's students' speaking performance are primarily on the average level. The categorization of control group’s post-test Table 30. Mean and standard deviation of the post-test in the control Group term Quantity Mean (M) 29.16 Standard Deviation (SD) 5.84 Table 31. The formula in categorizing the control group’s post-test Score category Basic formula Defined formula Good X ≥ M + SD X≥35 Average M – SD ≤ X < M + SD 23.32≤ X < 35 Low X < M – SD X < 23.32 It is clear from tables above that the post-test control mean (M) is 29.16 and the standard deviation (SD) is 5.84. If the student's speaking performance score (X) is greater than or equal to the mean plus standard deviation (X ≥ M + SD (35)), it is classified as "good." In the meantime, if X is larger than or equal to mean minus standard deviation (X ≥M – SD (23.32)) and less than mean plus standard deviation (X < M + SD (35)), the student's speaking performance score is deemed "average." A student is considered to have a "low" speaking performance score if their score (X) is less than the mean minus standard deviation (X < M – SD (23.32)). Hendra Putra, Rudi Hartono, Januarius Mujianto, Yuliati Evaluating genre-based approach on speaking performance across diffrent anxiety levels in Indonesian EFL students 646 Tables above display the results of applying the algorithm to the control group's speaking performance scores. It indicates that the frequency of the "good" category is 4, the "average" category is 12, and the "low" category is 2. Furthermore, it is evident from the percentage that the "good" group achieves 22%, the "average" category gets 67%, and the "low" category only reaches 11%. When the data is categorized, it is evident that the post-test results for the control group's students' speaking performance are primarily on the average level The categorization of treatment group’s pre-test Table 32. Mean and standard deviation of the pre-test in the treatment Group term Quantity Mean (M) 18.71 Standard Deviation (SD) 6.24 Table 33. The formula in categorizing the treatment group’s pre-test Score category Basic formula Defined formula Good X ≥ M + SD X≥24.95 Average M – SD ≤ X < M + SD 12.47≤ X < 24.95 Low X < M – SD X < 12.47 The pre-test treatment mean (M) is 18.71, and the standard deviation (SD) is 6.24, according to tables above. If the student's speaking performance score (X) is greater than or equal to the mean plus standard deviation (X ≥ M + SD (24.95)), it is classified as "good." In the meantime, if X is larger than or equal to mean minus standard deviation (X ≥M – SD (12.47)) and less than mean plus standard deviation (X < M + SD (24.95)), the student's speaking performance score is deemed "average." A student is considered to have a "low" speaking performance score if their score (X) is less than the mean minus standard deviation (X < M – SD (1.47)). The frequency of the "good" category is 1, the "average" category is 6, and the "low" category is 0, as can be seen in table above, which displays the results of applying the algorithm to the speaking performance scores of the treatment group. Furthermore, it is evident from the percentage that the "good" group only achieves 14%, the "average" category gets 86%, and the "low" category only reaches 0%. It is evident from the data categorization that the pre-test results for the treatment group's students' speaking performance are primarily on the average level. The categorization of treatment group’s post-test Table 34. Mean and standard deviation of the post-test in the treatment Group term Quantity Mean (M) 28.85 Standard Deviation (SD) 7.05 Table 35. The formula in categorizing the treatment group’s pre-test Score category Basic formula Defined formula Good X ≥ M + SD X≥35.9 Average M – SD ≤ X < M + SD 21.8≤ X < 35.9 Low X < M – SD X < 21.8 The pre-test treatment mean (M) is 28.85, and the standard deviation (SD) is 7.05, according to tables above. If the student's speaking performance score (X) is greater than or equal to the mean plus standard deviation (X ≥ M + SD (35.9)), it is classified as "good." In the meantime, if X is larger than or equal to mean minus standard deviation (X ≥M – SD (21.8)) and less than mean plus standard deviation (X < M + SD (35.9)), the student's speaking performance score is deemed "average." A student is considered to have a "low" speaking performance score if their score (X) is less than the mean minus standard deviation (X < M – SD (21.8)). The results, which are displayed in tables above, indicate that the frequency of the "good" category is 2, the "average" category is 4, and the "low" category is 1, following the application of the algorithm to the speaking performance scores of the treatment group. Furthermore, it is evident from the percentage that the "good" group achieves 29%, the "average" category gets 57%, and the "low" category only reaches 14%. It is evident from the data categorization that the post- test results for the students' speaking performance from the treatment group are primarily on the average level. Test absolute gain score The author created an absolute gain score test to see whether the experimental group's pupils, who received the genre-based approach, performed better than the control group's students, who received the conventional technique. This test was performed simply by comparing the experimental group's and the control group's pre-test and post- test scores. Stated differently, the score was ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 13, Issue 2, June 2025 https://journal.uniku.ac.id/index.php/ERJEE 647 calculated by subtracting the mean score from the pre-test from the mean score from the post- test.The result of the absolute gain score test could be seen in Table 9 and Table 10 below. Table 36. The absolute gain score of the experimental group Data: Experimental Pre-Test Post-test Gain score Number 25 25 Mean 18.71 28.85 10.14 SD 6.24 7.05 Table 37. The absolute gain score of the control group Data: Control Pre-Test Post-test Gain score Number 25 25 Mean 24.7 29.16 4,46 SD 7.57 5.84 Once the pre-test and post-test mean scores have been processed, Tables 9 and 10 make it evident that the experimental group's gain score is 10.14 points whereas the control group's gain score is only 4.46 points. The experimental group's gain score was unquestionably higher than the control group's. Thus, it can serve as proof that the genre-based strategy is superior to the traditional method for improving university-level nursing students' speaking performance. Inferential analysis Normality test and homogenity test Table 38. Tests of normality speaking performance with low anxiety Kolmogorov-Smirnova Shapiro-Wilk Statistic df Sig. Statistic df Sig. pre-test treatment (low anxiety) ,230 7 ,200* ,846 7 ,114 post-test treatment (low anxiety) ,244 7 ,200* ,873 7 ,198 *. This is a lower bound of the true significance. a. Lilliefors Significance Correction Table 39. Test of homogeneity of variances speaking performance with low anxiety Levene Statistic df1 df2 Sig. post -test treatment general 1,501 2 26 ,242 pre-test treatment general ,422 2 26 ,660 Hypothesis test Table 40. Paired samples test speaking performance with low anxiety Paired Differences t df Sig. (2-tailed) Mean Std. Deviatio n Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 pre-test treatment (low anxiety) - post- test treatment (low anxiety) -10,143 4,562 1,724 -14,362 -5,924 -5,883 6 ,001 The Paired Samples test is a statistical method used to compare two sets of related data. This means that the data points in one set are matched with data points in the other set. For example, you might measure the same group of people before and after a treatment to see if there was any change.This test is useful when you want to see if there is a significant difference between two related groups. It helps researchers understand if a treatment or intervention has had an effect. For instance, if you want to know if a new teaching method improves student scores, you would compare scores from the same students before and after using the method. Interpreting Results tells that whether the differences are significant. If the test shows a significant result, it means that the treatment or condition likely had an effect. If the result is not significant, it suggests that any observed differences could be due to random chance rather Hendra Putra, Rudi Hartono, Januarius Mujianto, Yuliati Evaluating genre-based approach on speaking performance across diffrent anxiety levels in Indonesian EFL students 648 than the treatment. Interpreting results tells that whether the differences are significant. If the test shows a significant result, it means that the treatment or condition likely had an effect. If the result is not significant, it suggests that any observed differences could be due to random chance rather than the treatment.The p-value = 0.001 is smaller than α = 0.05. In statistics, if the p-value is very small like this, then the null hypothesis (H0) is rejected very strongly, and the alternative hypothesis (H1) is accepted very strongly. So, in this case, because the p-value = 0.001 is very small than α = 0.05, then the hypothesis can be accepted very strongly, and the conclusion is that there is a very significant difference between genre-based approach and conventional approach. In this section, the authors discussed about the effectiveness of genre-based approach to enhance speaking performance implemented by the English teacher. To know the effectiveness of genre-based approach to enhance speaking performance means that the authors discussed some opinion about who pro and contrast about this statement. First, Herazo Rivera (2012) and Angraini & Rozimela (2020) found that Various curriculum areas have employed the genre-based approach (GBA) to enhance students' capacity for meaning- making. This approach views language learning and use as a social, textual, and goal-oriented process, using the text as the primary unit of communication and pedagogy. Additionally, using GBA in senior high school English instruction helps students' language proficiency to improve. Nahid et al. (2013); Aji et al. (2018) concluded that genre based approach is effective in improving Japanese speaking skill and added that GBA is effective to develop students’ speaking descriptive text and the improvement of students is seen from the social function, text organization and linguistic features of the text In contrast, Tachia & Loeneto (2018); Putra (2019) showed that not more than half students succeed in achieving the passing grade of English subject and the rest still got score under the passing grade the obtained that the English teacher still had some weakness in implementing genre-based approach and also the students still had many difficulties in generic structure and social function of the text. It can be commented that genre-based approach is not successful to improve tedachers’ strategy in teaching English and for the students got difficulties in using genre- based approach. Afterward, Emilia (2005) revealed that despite some limitations, the teaching program was successful in many ways in the Indonesian EFL tertiary teaching context. Most significantly, the students’ argumentative writing skills in English improved in that they achieved enhanced control of the target argumentative genre, at greater length, with clear schematic structure and improved use of evidence and information in support of their arguments, using various linguistic resources, which also indicates their development in critical thinking and critical literacy. Moreover, data from classroom observations, students’ journals and interviews showed that the students were aware of having made progress in terms of meta language for discussing critical reading and writing; a good grasp of those critical thinking dispositions, abilities and skills taught in the program; and enhanced awareness of the values of class dialogue, a democratic atmosphere, and the different roles of the teacher which allowed them to actively participate in their learning. Subsequently, Ramadhan et al. (2022) ; Y (2022) concluded that the genre-based approach can improve EFL pre-service English teacher students' capability in speaking. The pre-service English teacher students’ significant enhancement in their speaking capability is exhibited by the generic structure of the descriptive text, such as the social function, the organization, and grammatical features. All informants could fulfill relatively all parts, which is fundamental to composing a descriptive text. It can be meant that genre-based approach is also good for pre-service English teacher to enhance speaking performancerevealed that the experimental groups‟ Creative Writing Skills are enhanced than the control group as the result of teaching through Genre Based Approach. Likewise, Ahmad (2018); Nagao (2019) showed that the implementation of Genre-Based Approach significantly improves students writing ability. Furthermore, Haryanti & Sari (2019) interpreted that all aspects of writing are increased after taught by using GBA. The best-achieved writing aspect was style and quality expressionresults suggest that their understanding of “interpersonal meaning” such as modal verbs improved. Improvements in the use of modal auxiliaries were also noted, in that the word “should” did not appear in prewriting texts; however, the frequency improved in post-writing ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 13, Issue 2, June 2025 https://journal.uniku.ac.id/index.php/ERJEE 649 texts, especially in the final paragraph, which comprised the writers’ opinions and suggestions. Additionally, Siti Fathonah Wijayanti (2009); Rina Amelia, Slamet Triyadi (2023) suggests that GBA contributes positively to the teaching and learning process in that it helps developing learners’ productive skills. Nevertheless, insufficient scaffolding during the learning process resulted in learners’ skills which are superficial rather than communicative in nature.in this study the methods of genre based approach prove that the correlation between the text and speaking was help the students to speak English well, by the step by step genre based approach help to understand about the structure of the text also can understand clearly what they speak about. While, Nahid et al. (2013); Sarwati (2012) the result reveals that GBA is effective to develop students’ speaking descriptive text and the improvement of students is seen from the social function, text organization and linguistic features of the textsays that in the teaching speaking by using genre-based approach the teacher faced some problems. The problems are the student’s lack of mastering vocabulary and different capability of the stuents. The researcher also found that there three stages or procedures used by english teacher in applying genre-based approach name BKOF, MOT and ICT. As well as, H. Putra et al. (2023) Ahyarudin (2024) this study found that genre based approach has significance effect toward students’ speaking performance. findings revealed that AI-IT significantly enhanced students’ vocabulary, pronunciation, and confidence, particularly in transactional language relevant to their field. The approach also increased classroom engagement and active participation. This study contributes to the evolving field of language teaching by demonstrating the potential of AI to support the development of speaking skills in vocational education, ultimately preparing students for real- world communication challenges in their careers. Initially, Dirgeyasa (2016);Herman et al. (2020) genre as an approach to teaching and learning writing is a matter of mixed approach between process and product approach.This GBA model can be used as a framework to enable teachers and students to develop their writing skills. It is hoped that this model can become a classroom strategy in allowing teachers and students to achieve a higher level of writing skill. Anxiety makes bad speaking performance it is explained by Rofida (2021) found that the students’ mostly experienced communication apprehension (M = 3.4) and fear of negative evaluation (M = 3.4) rather than test anxiety (M = 3.1). This research also showed that foreign language anxiety has significant negative correlation with students’ speaking performance (p = 0.000, r = -0.98) and the correlation strength was categorized as very strong. The higher level of students’ foreign language anxiety, the worse their speaking performance. This finding is different with this study. In this stuy found that high anxiety makes high speaking performance. Regardless of Sani et al. (2023); Js et al. (2023) obtained that the teacher implemented the Genre-based Approach in the EFL classroom, which is recognized by MerdekaCurriculum. However, it was found that one crucial stage known as the Joint Construction of the Text (JCoT) was missing in the implementation, and the teacher did not provide.revealed GBA contributes positively to the teaching and learning process in that it helps developing learners’ productive skills. Nevertheless, insufficient scaffolding during the learning process resulted in learners’ skills which are superficial rather than communicative in nature. Wibowo & Lengkanawati (2024); Luhur et al. (2023) GBA is found to be able to build students' character, such as developing students' creativity and critical thinking skills. Nonetheless, GBA can also be time-consuming as it needs thorough preparation, and it's challenging, as well, if it is applied to teach low-achiever students. There are some teacher misunderstandings about GBA, so it is necessary to provide teachers with comprehensive training and simulations of the GBA stages to implement this method optimally. the results of hypothesis testing showed a significant increase in the experimental group. For interpersonal conversation text, the experimental group had a significance value of 0.000, while the control group had a value of 0.001. The N gain for the experimental group was 0.6447, and for the control group was -0.4452. In the same way, for transactional conversational text, the experimental group had a significance value of 0.000, while the control group had a value of 0.146. The N gain for the experimental group was 0.6808, and for the control group was 0.0640. Therefore, the genre-based approach significantly improves students' understanding of interpersonal and transactional conversation texts. Additionally, Maknun (2019) showed that the implementation of scientific and genre-based approach in reading comprehension teaching Hendra Putra, Rudi Hartono, Januarius Mujianto, Yuliati Evaluating genre-based approach on speaking performance across diffrent anxiety levels in Indonesian EFL students 650 leads to better reading comprehension ability of the students. The result proved that students were able to understand the items post-test of narrative texts after 12 meeting of treatments using those approaches and also there were significant difference after conducting treatments. Lastly,Kusumahati & Yulianti (2023) the results of this research show an increase in students' speaking abilities from pre-cycle to cycle II. Where in the pre-cycle the average student score was 55.3, then in cycle I it was 60.06, and in cycle II it was 76.3. Based on the resulting data, it shows that research on the application of the Genre Based Approach assisted by Canva can improve students' speaking abilities. Based on finding above, it can be meant that genre-based approach has good effect to some English language skills speaking, reading, listeninag and writing. This approach also has good efect to pre-service English teacher, mastery vocabulary, students’character, teachers’ teaching. In contrast, genre-based approach is not significantly to solve some difficulties faced by the teacher and students in the teaching and learning process. CONCLUSIONS Regarding speaking performance of nursing students in this study can be summarized that. The effectiveness of genre-based approach to enhance speaking performance of EFL students with high and low level anxiety is significant. However, the effectiveness of genre-based approach to enhance speaking performance of EFL students with moderate level anxiety is nog significant. By having high level anxiety can motivate, concentrate, well prepare, self confident, fluent and being creative to speak properly in front of the class in presenting topic material. When EFL student having high anxiety level does not mean make the speaking performance become bad. Because many prepartion must be done it to speak in front of the class. ACKNOWLEDGEMENT I would like to express my deep gratitude to my respected promoters, Prof. Dr. Rudi Hartono, M.Pd, co-promoter Prof. Dr. Januarius Mujiyanto, M.Hum., and Yuliati, S.Pd.,M.Pd.,M.Ed.,Ph.D. for their valuable support, guidance, comments, and feedback in this dissertation so that the researcher can complete this work. Then, it is adressed to all of participants involved in this study. REFERENCES Ahmad, I. (2018). The implementation of genre-based approach in improving students’ descriptive writing ability through sidney sheldon’s novel rage of angels as role models. 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