85Correlative Analysis of TOEFL iBT Scores ….. (Almodad Biduk Asmani) CORRELATIVE ANALYSIS OF TOEFL iBT SCORES OF LISTENING SKILL VERSUS SCORES OF BUSINESS ENGLISH SPEAKING SKILL AMONG BINUS UNIVERSITY SOPHOMORES Almodad Biduk Asmani Language Center, Bina Nusantara University Jln. Kemanggisan Ilir III No. 45, Palmerah – Kemanggisan, Jakarta Barat 11480 aasmani@binus.edu ABSTRACT Article found out whether BINUS university sophomore’s TOEFL iBT scores of Listening skill are correlated with those of speaking skill. The research project was expected to result in the best teaching technique of delivering conversational tasks at BINUS University by using alternative approaches of integrated, isolated, or mixed skills. The research project applied the descriptive approach of quantitative method, and thus depends on numerical data. The research project examined the set of data under two skills of the same class groups, which were to compare the listening scores with the speaking ones. Then, the degree of correlation of the two skills was tested so as to find its significance. Interpretation and explanation of data was made based on the statistical results by using correlation research analysis. Based on the statistical results, the listening scores significantly correlated with those of the speaking skill, and there is a moderately linear relationship between these paired scores. Keywords: score correlation, speaking, listening, sophomore students, TOEFL ABSTRAK Artikel menjelaskan korelasi nilai TOEFL iBT Listening mahasiswa BINUS University yang sedang belajar di tahun kedua dengan nilai Business English Speaking mereka. Hasil penelitian diharapkan dapat menghasilkan teknik pengajaran yang lebih sesuai dengan tuntutan percakapan yang diharapkan oleh BINUS University, antara lain, dengan menggunakan pilihan pendekatan integrated, independen, atau campuran. Penelitian menggunakan metode pendekatan kuantitatif dengan memasukkan data berupa angka. Penelitian mengkaji kumpulan data dalam dua bentuk skill, yang semuanya ditarik dari satu kelompok subjek yang sama, yaitu dengan membandingkan nilai Listening dengan nilai Speaking mereka. Kemudian, tingkat korelasi dari dua skill ini diuji untuk mengetahui signifikansinya. Interpretasi dan penjabaran data dibuat berdasarkan penghitungan statistika dengan menggunakan correlation research analysis. Berdasarkan hasil peneltian, skor Listening berkorelasi secara signifikan dengan skor Speaking, dan terdapat hubungan yang cukup linear antara dua pasang skor ini. Kata kunci: korelasi nilai, berbicara, menyimak, mahasiswa tingkat dua, TOEFL 86 Jurnal LINGUA CULTURA Vol.8 No.2 November 2014 INTRODUCTION When teachers deliver courses for international language test preparation, like TOEFL, IELTS, or TOEIC, they tend to teach the four skills – Reading, Listening, Speaking and Listening – separately. The previous version of TOEFL, called TOEFL PBT (Paper-based Test), evaluates language skills in three separate sections, which are Listening Comprehension, Structure/Written Expression, and Reading Comprehension. Though it does not contain the speaking section, many English teachers assume that the higher the TOEFL PBT score is, the more likely the test taker is able to communicate English in academic contexts, though it is not always absolute. Based on this framework of assumption, many education institutions in Indonesia have set the minimum TOEFL PBT score of 500 as one of the requirements for postgraduate study entry level, regardless of the students’ actual communication performances. Thus, we can see here that in many TOEFL PBT preparation courses and tests, there has not been any emphasis on the value of highlighting the relationships between these skills, either in the teaching and learning process, or in the test format itself. BINUS University has the English course program that includes TOEFL iBT elements in its curriculum, which are Reading and Listening. On the other hand, the Speaking and Writing are more catered for general or business themes. The curriculum has been designed in such a way to serve the dual needs of both academic and business purposes. Based on my teaching experiences of the courses at BINUS University, I have observed that if my students scored higher on the TOEFL iBT listening, they tended to score higher on their speaking performance. From the circumstances and cases explained, this research would assume that it seems there is a hidden connection between the listening and speaking. Hence, this research project tries to consolidate the general connection, if any, between this pair of skills, so as to find the best format of teaching to deliver these two skills in the classroom with the expectation that it allows students achieve higher and better on their English performance, both in academic and business environment. Therefore, the problem formulation that the research project aims to address is to find out: whether there is a correlation between TOEFL iBT Listening scores and Business English Speaking scores of BINUS University sophomore of academic year 2012/2013, and the strength of the relationship, if any, between TOEFL iBT Listening scores and Business English Speaking scores of BINUS University sophomore of academic year 2012/2013 The significance of the research project is that it can generate the most suitable format of teaching and learning model in BINUS University to best deliver the two language skills, listening and speaking, in their proportion and functions under academic and business themes to finally meet the final expectation of academic and business purposes in the final year of their study. Hinkel (2006:113) argues: “in meaningful communication, people employ incremental language skills not in isolation, but in tandem”. According to Harmer (2007:265): “when we have a conversation, we need to listen as well as speak in order to maintain the interaction with the interlocutor.” Thus, in the actual use of daily conversation in English, we often depend on these two skills together to maintain the interaction. There might be a relationship to some extent between listening and speaking activities, in which the two skills correlate and interact to each other to play their roles and meet their purposes for the conversation process. Hence, language skills are often used in multi- dimensions in the communication process in the real world. It would be dangerous to look at each skill in isolation during the teaching and learning process, especially for international test preparation, where skills are often tested, scored, and described their competence individually. How receptive skills like, Listening and Reading, connected with productive skills, like Speaking and Writing needs to be examined. Another perspective to explain the connection between listening and speaking is given by Celce-Murcia and Olshtain (2000:104), as follows. Top-down processing Expectation based on discourse and sociocultural knowledge (formal schemata) Expectation based on prior knowledge (content schemata) Expectation based on the assessment of context/speaker’s intention Pragmatics Language knowledge (phonology, vocabulary, grammar) Interpretation of Spoken Discourse (input) Metacognition Listening Strategies Bottom-up processing Figure1 Celce-Murcia and Olshtain’s Connection between Listening and Speaking (p.104) Thus, the receptive skills activities as well as the productive skills activities each as the connections between top-down and bottom-up processing could be seen. Here, the global understanding of the topic in the written and spoken discourses and understanding of the details of the discourses help the users perform the language actively, in writing and speaking activities. There is also experimental evidence that listening practice is more important for oral skills development than speaking practice. Anderson and Lynch (1988:16) show that students who have had a substantial amount of task-based listening practice are better able to perform a similar oral tasks in the future, compared to other students who had been given only speaking practice. In this case, teaching listening only is more effective than teaching speaking only. Celce-Murcia and Olshtain (2000:108) 87Correlative Analysis of TOEFL iBT Scores ….. (Almodad Biduk Asmani) aptly assume that “giving practice with both skills—first listening and then speaking—would be the best possible preparation, but if the teacher doesn’t have time to do both, then listening practice … should take precedence.” Burns (1998) specifically mentions “sets of listening materials for developing language awareness” (p. 111). She also recommends that “learners can be engaged in listening prediction activities that require them to anticipate discourse structures, vocabulary, and functional forms and to draw on their knowledge of target socio-cultural practices in preparation for the production of spoken texts” (p. 113). Thus, we can see here how she tries to put the link between listening and speaking. METHOD Based on the nature of this research methodology, this research project is more of the positivist/empiricist epistemology and an attempt at gathering “objective”, verifiable data in numerical form. This quantitative strand is more concerned with “generalization, prediction and control” (Usher, 1996). Based on the brief overview presented, research used descriptive statistics in which the use of statistical procedures to summarize, tabulate, depict and describe the properties of sets of data (including quantitative data) (See Wiersma, 2000, chapter 13). Research applied the approach of quantitative data gathering and analysis. By using a quantitative methodology in the project, research focuses on more context-free generalizations of the observed social phenomenon by examining the relationship of the variables, which are the TOEFL iBT Listening scores and the Business English Speaking scores. Statistical results are represented with numbers. The correlation research was used to indicate the relationship between paired scores, to know how strong the relationship is, and whether it of positive and negative. To do this, a correlation coefficient that represents the correlation was calculated. The research project divided the raw scores into two pair domains, which are the paired TOEFL iBT Listening scores and Business English Speaking scores. The pair consists of two scores for the same individual. The scores are derived partly from the Mid Test and Final Test results for Listening, and from the results of Daily Assessment for Speaking. The Listening test is based on TOEFL iBT format with the score range from 0 to 30 respectively. The test is computer-based and its scores are calculated and generated by the computer. The computer- based scores are provided by BINUS University SLC (Software Laboratory Center) unit and sent to our emails by the end of each test. The Speaking tasks are based on general/business topics with the score range from 0 to 3.0 and converted to 0 to 23. The conversion of the Speaking scores is meant to equal with the TOEFL iBT score calculation. The Speaking tasks are scored by the teachers based on the standard score rubric and given to writer every quarter of the running semester. Target population is all BINUS University sophomore students who take the English in Focus subject in Academic Year 2012/2013. Research took the sample of three class groups, each with the range of students from 50 to 70 participants. These students are chosen as the participants in the research project due to some reasons. First, students of second year study are expected to have developed some basic skills of TOEFL iBT Listening and Business English Speaking that they had experienced before in English Entrant subject. Secondly, the sophomores are expected to reach the higher target score than the freshmen, which is TOEFL PBT 500 as the minimum pass score for the next level. This would contribute some degree of motivation for these students to perform higher and better in their study experiences. Since there are only some class groups to be sampled from a number of other English in Focus class groups running in Academic Year 2012/2013, research used the approach of simple random sampling, where “all members of the population have an equal and independent chance of being included in the random sample.” (Ary, Jacobs, Razavieh, & Sorensen, 2006) The mid test consists of two parts. The first part is the Listening tests at laboratories based on TOEFL iBT format on the computers. The computer-based test material is taken from BINUS University NG-TOEFL version 3. The second part is the Speaking tasks held by the teacher from the first meeting to around the seventh or eighth. The TOEFL iBT Listening scores are compared with the Business English Speaking scores. The quantitative calculation is used in this research by using the correlation statistical analysis to test the hypotheses with .05 level of confidence. We use the table that lists critical values of r for different numbers of degrees of freedom (df). By comparing the obtained r with the critical values of r listed in the table, we can determine the statistical significance of a product moment correlation. If the obtained correlation exceeds the critical value listed in the table, we can report that the correlation is statistically significant. The null hypothesis would be rejected, and we would tentatively conclude that the two variables are related in the population. Then, the writer tests the hypotheses as follows: (1) Null Hypothesis: the TOEFL iBT Listening scores are not significantly related to the General Speaking scores among BINUS University sophomores in Mid Test; (2) Alternate Hypothesis: the TOEFL iBT Listening scores are significantly related to the General Speaking scores among BINUS University sophomores in Mid Test. In the set of scores, the independent variable is the TOEFL iBT Listening scores, and the dependent variable is the Business English Speaking scores. The correlation statistical analysis was used due to several reasons. First, we would “determine the extent of any relationship between these variables” (Ary, Jacobs, Razavieh, & Sorensen, 2006). In this case, is there a relationship between Listening and Speaking? Secondly, in this research, we would measure the reliability (consistency) of the Mid- term Test through correlating Listening and Speaking scores. Thirdly, we would try to establish prediction on each of the two paired variables, if proven correlated. For example, we could use the Listening scores to predict the Speaking scores. The correlation statistical analysis best applies in prediction studies. The correlation coefficient derived from the calculation is to indicate both the direction and the strength of the relationship between two variables in the pair. The 88 Jurnal LINGUA CULTURA Vol.8 No.2 November 2014 coefficient can take any value from -1 to +1, with the following interpretations as shown in Table 1. The best practical way to illustrate and understand the relationship is by examining a scatterplot of the data. So, in this research, a scatterplot diagram is made to know whether it is of: (1) a positive correlation (as independent variable goes up, dependent variable also goes up), or; (2) a negative correlation (as independent variable goes up, dependent variable goes down). A scatterplot is also provided to know the strength of the relationship between variables whether it is of: (1) strong linear relationship, when the dots in the scatterplot form a narrow band, and scatter near the straight line through the band; (2) weak linear relationship, when the dots in the scatterplot scatter widely from the line; (3) curvilinear relationship, when a curved line is needed to express the relationship. All of the findings of each of the paired variables are described and interpreted so as to find the third variable, if any, as the cause of the relationship. The final conclusion and suggestion is given in the end of the research. RESULTS AND DISCUSSION The data presentation of the Listening and Speaking scores of the Binus University sophomores taking English in Focus subject during Mid Test of Even Semester in Academic Year 2012/2013 is provided in Table 2 below. In Table 2, column 1 shows the class codes, column 2 lists the students’ numbers, column 3 shows each student’s listening scaled score on TOEFL iBT (X), column 4 shows these scaled scores squared (X2), column 5 shows each student’s speaking scaled score on General English (Y), column 6 shows these scaled scores squared (Y2), and column 7 shows the product of each student’s X scaled score multiplied by his/her Y scaled core (XY). Table 1 The Correlation Coefficient of Listening and Speaking Scores -1.00 Perfect negative correlation If found, it would mean that the two sets of scores, Listening and Speaking, have the same rank order, only reversed. -0.80 Strong negative correlation High scores on one measure (Listening) usually mean low scores on the other (Speaking) -0.30 Weak negative correlation A slight tendency for those scoring highest on one measure (Listening) to score lowest on the other (Speaking) 0.00 No relationship at all Those who score high/low on one measure (Listening) are NO more likely to score higher/lower on the other (Speaking). +0.30 Weak positive correlation A slight tendency for those scoring highest on one measure (Listening) to score highest on the other (Speaking). +0.80 Strong positive correlation High scores on one measure (Listening) usually mean high scores on the other (Speaking). +1.00 Perfect positive correlation If found, the two sets of scores (Listening and Speaking) would have identical rank orderings from lowest to highest. Table 2 The Listening and Speaking Scores of the Binus University Sophomores Class Student No. Listening Scores Speaking Scores X X2 Y Y2 XY 02PXJ 1601219113 9 81 15 225 135 1601220033 15 225 17 289 255 1601221023 22 484 19 361 418 1601222581 19 361 19 361 361 1601223666 12 144 15 225 180 1601223893 6 36 14 196 84 1601225040 7 49 14 196 98 1601227052 23 529 19 361 437 1601228061 15 225 17 289 255 1601228332 4 16 15 225 60 1601231781 6 36 15 225 90 1601233276 20 400 19 361 380 1601233862 11 121 15 225 165 1601234000 17 289 17 289 289 1601234291 10 100 15 225 150 1601235565 17 289 17 289 289 1601235981 13 169 17 289 221 1601236100 18 324 19 361 342 89Correlative Analysis of TOEFL iBT Scores ….. (Almodad Biduk Asmani) Table 2 The Listening and Speaking Scores of the Binus University Sophomores (continued) Class Student No. Listening Scores Speaking Scores X X2 Y Y2 XY 1601237444 15 225 18 324 270 1601239651 12 144 15 225 180 1601242223 13 169 17 289 221 1601242671 15 225 19 361 285 1601252224 12 144 15 225 180 1601252363 14 196 15 225 210 1601258455 7 49 15 225 105 1601263745 11 121 15 225 165 1601266886 18 324 19 361 342 1601272825 12 144 17 289 204 1601273696 3 9 13 169 39 1601275360 8 64 13 169 104 1601276930 16 256 19 361 304 1601278955 15 225 18 324 270 1601283873 17 289 19 361 323 1601284876 7 49 17 289 119 02 PGT 1601232651 24 576 19 361 456 1601232701 20 400 19 361 380 1601233061 14 196 17 289 238 1601234732 13 169 17 289 221 1601234814 18 324 19 361 342 1601235104 15 225 17 289 255 1601235943 20 400 19 361 380 1601237570 15 225 20 400 300 1601237633 13 169 15 225 195 1601239916 19 361 19 361 361 1601239986 12 144 17 289 204 1601240722 8 64 15 225 120 1601242822 12 144 15 225 180 1601244121 11 121 15 225 165 1601245105 18 324 17 289 306 1601245225 13 169 15 225 195 1601247685 15 225 17 289 255 1601248284 9 81 15 225 135 1601251480 21 441 19 361 399 1601252621 22 484 17 289 374 1601252634 14 196 18 324 252 1601253385 13 169 15 225 195 1601254053 20 400 17 289 340 1601254532 11 121 17 289 187 1601254564 12 144 17 289 204 1601257351 16 256 15 225 240 1601258240 23 529 18 324 414 1601258266 28 784 19 361 532 1601258884 11 121 15 225 165 1601260176 8 64 15 225 120 1601264086 10 100 15 225 150 1601264722 9 81 15 225 135 1601266910 6 36 15 225 90 1601266936 14 196 15 225 210 1601267365 9 81 17 289 153 90 Jurnal LINGUA CULTURA Vol.8 No.2 November 2014 Table 2 The Listening and Speaking Scores of the Binus University Sophomores (continued) Class Student No. Listening Scores Speaking Scores X X2 Y Y2 XY 1601270315 17 289 17 289 289 1601272314 12 144 15 225 180 1601272485 9 81 17 289 153 1601272560 14 196 17 289 238 1601273235 10 100 15 225 150 1601273992 16 256 17 289 272 1601274635 17 289 19 361 323 1601278394 9 81 15 225 135 1601283652 13 169 15 225 195 1601284485 15 225 15 225 225 1601285052 10 100 18 324 180 1601286843 8 64 15 225 120 02PEF 1601229455 7 49 15 225 105 1601230122 13 169 15 225 195 1601231604 14 196 15 225 210 1601232696 21 441 17 289 357 1601239065 24 576 20 400 480 1601239992 21 441 19 361 399 1601241624 9 81 17 289 153 1601243213 11 121 15 225 165 1601244834 19 361 19 361 361 1601244853 6 36 15 225 90 1601246240 9 81 17 289 153 1601248725 13 169 17 289 221 1601252041 10 100 17 289 170 1601252086 13 169 19 361 247 1601253460 12 144 15 225 180 1601254690 13 169 17 289 221 1601254854 17 289 17 289 289 1601254923 6 36 13 169 78 1601256052 15 225 15 225 225 1601256203 11 121 15 225 165 1601256613 13 169 15 225 195 1601260144 12 144 15 225 180 1601260850 14 196 17 289 238 1601263543 11 121 15 225 165 1601264685 11 121 15 225 165 1601265561 21 441 19 361 399 1601265832 19 361 19 361 361 1601265845 11 121 15 225 165 1601266343 18 324 17 289 306 1601266362 14 196 15 225 210 1601267094 16 256 17 289 272 1601267503 17 289 19 361 323 1601270183 13 169 15 225 195 1601271021 15 225 17 289 255 1601273254 9 81 15 225 135 1601275234 22 484 19 361 418 1601275373 11 121 15 225 165 1601276615 13 169 15 225 195 TOTAL ∑X=1629 ∑X2=24987 ∑Y=1966 ∑Y2=32834 ∑XY=27644 91Correlative Analysis of TOEFL iBT Scores ….. (Almodad Biduk Asmani) Table 3 indicates that column 1 shows the class codes, column 2 lists the students’ numbers, column 3 shows each student’s listening scaled score on TOEFL iBT (X), column 4 shows the deviation of each score from the mean (x), column 5 shows the deviation of each score from the mean squared (x2), column 6 shows the Z scores of the TOEFL iBT Listening test (Zx), column 7 shows each student’s speaking scaled score on Business English task (Y), column 8 shows the deviation of each score from the mean (y), column 9 shows the deviation of each score from the mean squared (y2), and column 10 shows the Z scores of the Business English Speaking task (Zy). Table 3 Variance of TOEFL iBT ListeninVg Scores and Business English Speaking Scores Class Student No. Listening Scores Speaking Scores X x x2 Zx Y y y 2 Zy 02PXJ 1601219113 9 -4.68908 21.98747 -0.9867 15 -1.52101 2.313471 -0.88225 1601220033 15 1.31092 1.718511 0.275852 17 0.47899 0.229431 0.277833 1601221023 22 8.31092 69.07139 1.748834 19 2.47899 6.145391 1.437912 1601222581 19 5.31092 28.20587 1.117556 19 2.47899 6.145391 1.437912 1601223666 12 -1.68908 2.852991 -0.35543 15 -1.52101 2.313471 -0.88225 1601223893 6 -7.68908 59.12195 -1.61798 14 -2.52101 6.355491 -1.46229 1601225040 7 -6.68908 44.74379 -1.40756 14 -2.52101 6.355491 -1.46229 1601227052 23 9.31092 86.69323 1.95926 19 2.47899 6.145391 1.437912 1601228061 15 1.31092 1.718511 0.275852 17 0.47899 0.229431 0.277833 1601228332 4 -9.68908 93.87827 -2.03884 15 -1.52101 2.313471 -0.88225 1601231781 6 -7.68908 59.12195 -1.61798 15 -1.52101 2.313471 -0.88225 1601233276 20 6.31092 39.82771 1.327982 19 2.47899 6.145391 1.437912 1601233862 11 -2.68908 7.231151 -0.56585 15 -1.52101 2.313471 -0.88225 1601234000 17 3.31092 10.96219 0.696704 17 0.47899 0.229431 0.277833 1601234291 10 -3.68908 13.60931 -0.77628 15 -1.52101 2.313471 -0.88225 1601235565 17 3.31092 10.96219 0.696704 17 0.47899 0.229431 0.277833 1601235981 13 -0.68908 0.474831 -0.145 17 0.47899 0.229431 0.277833 1601236100 18 4.31092 18.58403 0.90713 19 2.47899 6.145391 1.437912 1601237444 15 1.31092 1.718511 0.275852 18 1.47899 2.187411 0.857872 1601239651 12 -1.68908 2.852991 -0.35543 15 -1.52101 2.313471 -0.88225 1601242223 13 -0.68908 0.474831 -0.145 17 0.47899 0.229431 0.277833 1601242671 15 1.31092 1.718511 0.275852 19 2.47899 6.145391 1.437912 1601252224 12 -1.68908 2.852991 -0.35543 15 -1.52101 2.313471 -0.88225 1601252363 14 0.31092 0.096671 0.065426 15 -1.52101 2.313471 -0.88225 1601258455 7 -6.68908 44.74379 -1.40756 15 -1.52101 2.313471 -0.88225 1601263745 11 -2.68908 7.231151 -0.56585 15 -1.52101 2.313471 -0.88225 1601266886 18 4.31092 18.58403 0.90713 19 2.47899 6.145391 1.437912 1601272825 12 -1.68908 2.852991 -0.35543 17 0.47899 0.229431 0.277833 1601273696 3 -10.6891 114.2564 -2.24926 13 -3.52101 12.39751 -2.04232 1601275360 8 -5.68908 32.36563 -1.19713 13 -3.52101 12.39751 -2.04232 1601276930 16 2.31092 5.340351 0.486278 19 2.47899 6.145391 1.437912 1601278955 15 1.31092 1.718511 0.275852 18 1.47899 2.187411 0.857872 1601283873 17 3.31092 10.96219 0.696704 19 2.47899 6.145391 1.437912 1601284876 7 -6.68908 44.74379 -1.40756 17 0.47899 0.229431 0.277833 02 PGT 1601232651 24 10.31092 106.3151 2.169686 19 2.47899 6.145391 1.437912 1601232701 20 6.31092 39.82771 1.327982 19 2.47899 6.145391 1.437912 1601233061 14 0.31092 0.096671 0.065426 17 0.47899 0.229431 0.277833 1601234732 13 -0.68908 0.474831 -0.145 17 0.47899 0.229431 0.277833 1601234814 18 4.31092 18.58403 0.90713 19 2.47899 6.145391 1.437912 1601235104 15 1.31092 1.718511 0.275852 17 0.47899 0.229431 0.277833 1601235943 20 6.31092 39.82771 1.327982 19 2.47899 6.145391 1.437912 1601237570 15 1.31092 1.718511 0.275852 20 3.47899 12.10337 2.017951 1601237633 13 -0.68908 0.474831 -0.145 15 -1.52101 2.313471 -0.88225 1601239916 19 5.31092 28.20587 1.117556 19 2.47899 6.145391 1.437912 1601239986 12 -1.68908 2.852991 -0.35543 17 0.47899 0.229431 0.277833 92 Jurnal LINGUA CULTURA Vol.8 No.2 November 2014 Table 3 Variance of TOEFL iBT ListeninVg Scores and Business English Speaking Scores (continued) Class Student No. Listening Scores Speaking Scores X x x2 Zx Y y y 2 Zy 02PXJ 1601240722 8 -5.68908 32.36563 -1.19713 15 -1.52101 2.313471 -0.88225 1601242822 12 -1.68908 2.852991 -0.35543 15 -1.52101 2.313471 -0.88225 1601244121 11 -2.68908 7.231151 -0.56585 15 -1.52101 2.313471 -0.88225 1601245105 18 4.31092 18.58403 0.90713 17 0.47899 0.229431 0.277833 1601245225 13 -0.68908 0.474831 -0.145 15 -1.52101 2.313471 -0.88225 1601247685 15 1.31092 1.718511 0.275852 17 0.47899 0.229431 0.277833 1601248284 9 -4.68908 21.98747 -0.9867 15 -1.52101 2.313471 -0.88225 1601251480 21 7.31092 53.44955 1.538408 19 2.47899 6.145391 1.437912 1601252621 22 8.31092 69.07139 1.748834 17 0.47899 0.229431 0.277833 1601252634 14 0.31092 0.096671 0.065426 18 1.47899 2.187411 0.857872 1601253385 13 -0.68908 0.474831 -0.145 15 -1.52101 2.313471 -0.88225 1601254053 20 6.31092 39.82771 1.327982 17 0.47899 0.229431 0.277833 1601254532 11 -2.68908 7.231151 -0.56585 17 0.47899 0.229431 0.277833 1601254564 12 -1.68908 2.852991 -0.35543 17 0.47899 0.229431 0.277833 1601257351 16 2.31092 5.340351 0.486278 15 -1.52101 2.313471 -0.88225 1601258240 23 9.31092 86.69323 1.95926 18 1.47899 2.187411 0.857872 1601258266 28 14.31092 204.8024 3.011391 19 2.47899 6.145391 1.437912 1601258884 11 -2.68908 7.231151 -0.56585 15 -1.52101 2.313471 -0.88225 1601260176 8 -5.68908 32.36563 -1.19713 15 -1.52101 2.313471 -0.88225 1601264086 10 -3.68908 13.60931 -0.77628 15 -1.52101 2.313471 -0.88225 1601264722 9 -4.68908 21.98747 -0.9867 15 -1.52101 2.313471 -0.88225 1601266910 6 -7.68908 59.12195 -1.61798 15 -1.52101 2.313471 -0.88225 1601266936 14 0.31092 0.096671 0.065426 15 -1.52101 2.313471 -0.88225 1601267365 9 -4.68908 21.98747 -0.9867 17 0.47899 0.229431 0.277833 1601270315 17 3.31092 10.96219 0.696704 17 0.47899 0.229431 0.277833 1601272314 12 -1.68908 2.852991 -0.35543 15 -1.52101 2.313471 -0.88225 1601272485 9 -4.68908 21.98747 -0.9867 17 0.47899 0.229431 0.277833 1601272560 14 0.31092 0.096671 0.065426 17 0.47899 0.229431 0.277833 1601273235 10 -3.68908 13.60931 -0.77628 15 -1.52101 2.313471 -0.88225 1601273992 16 2.31092 5.340351 0.486278 17 0.47899 0.229431 0.277833 1601274635 17 3.31092 10.96219 0.696704 19 2.47899 6.145391 1.437912 1601278394 9 -4.68908 21.98747 -0.9867 15 -1.52101 2.313471 -0.88225 1601283652 13 -0.68908 0.474831 -0.145 15 -1.52101 2.313471 -0.88225 1601284485 15 1.31092 1.718511 0.275852 15 -1.52101 2.313471 -0.88225 1601285052 10 -3.68908 13.60931 -0.77628 18 1.47899 2.187411 0.857872 1601286843 8 -5.68908 32.36563 -1.19713 15 -1.52101 2.313471 -0.88225 02 PEF 1601229455 7 -6.68908 44.74379 -1.40756 15 -1.52101 2.313471 -0.88225 1601230122 13 -0.68908 0.474831 -0.145 15 -1.52101 2.313471 -0.88225 1601252086 13 -0.68908 0.474831 -0.145 19 2.47899 6.145391 1.437912 1601253460 12 -1.68908 2.852991 -0.35543 15 -1.52101 2.313471 -0.88225 1601254690 13 -0.68908 0.474831 -0.145 17 0.47899 0.229431 0.277833 1601254854 17 3.31092 10.96219 0.696704 17 0.47899 0.229431 0.277833 1601254923 6 -7.68908 59.12195 -1.61798 13 -3.52101 12.39751 -2.04232 1601256052 15 1.31092 1.718511 0.275852 15 -1.52101 2.313471 -0.88225 1601256203 11 -2.68908 7.231151 -0.56585 15 -1.52101 2.313471 -0.88225 1601256613 13 -0.68908 0.474831 -0.145 15 -1.52101 2.313471 -0.88225 1601260144 12 -1.68908 2.852991 -0.35543 15 -1.52101 2.313471 -0.88225 1601260850 14 0.31092 0.096671 0.065426 17 0.47899 0.229431 0.277833 1601263543 11 -2.68908 7.231151 -0.56585 15 -1.52101 2.313471 -0.88225 1601264685 11 -2.68908 7.231151 -0.56585 15 -1.52101 2.313471 -0.88225 1601265561 21 7.31092 53.44955 1.538408 19 2.47899 6.145391 1.437912 1601265832 19 5.31092 28.20587 1.117556 19 2.47899 6.145391 1.437912 93Correlative Analysis of TOEFL iBT Scores ….. (Almodad Biduk Asmani) Table 3 Variance of TOEFL iBT ListeninVg Scores and Business English Speaking Scores (continued) Class Student No. Listening Scores Speaking Scores X x x2 Zx Y y y 2 Zy 02PXJ 1601265845 11 -2.68908 7.231151 -0.56585 15 -1.52101 2.313471 -0.88225 1601266343 18 4.31092 18.58403 0.90713 17 0.47899 0.229431 0.277833 1601266362 14 0.31092 0.096671 0.065426 15 -1.52101 2.313471 -0.88225 1601267094 16 2.31092 5.340351 0.486278 17 0.47899 0.229431 0.277833 1601267503 17 3.31092 10.96219 0.696704 19 2.47899 6.145391 1.437912 1601270183 13 -0.68908 0.474831 -0.145 15 -1.52101 2.313471 -0.88225 1601271021 15 1.31092 1.718511 0.275852 17 0.47899 0.229431 0.277833 1601273254 9 -4.68908 21.98747 -0.9867 15 -1.52101 2.313471 -0.88225 1601275234 22 8.31092 69.07139 1.748834 19 2.47899 6.145391 1.437912 1601275373 11 -2.68908 7.231151 -0.56585 15 -1.52101 2.313471 -0.88225 1601276615 13 -0.68908 0.474831 -0.145 15 -1.52101 2.313471 -0.88225 TOTAL The data calculation of the Listening and Speaking scores of the Binus University sophomores taking English in Focus subject during Mid Test of Even Semester in Academic Year 2012/2013 is provided below. The calculation is based on the following formula: where r = Pearson r ∑X = Sum of scores in X distribution ∑Y = Sum of scores in Y distribution ∑X2 = Sum of the squared scores in X distribution ∑Y2 = Sum of the squared scores in Y distribution ∑XY = Sum of products of paired X and Y scores N = Number of paired X and Y scores (subjects) Using the formula, we get the first Pearson r (r) to indicate the relationship between the paired scores of the TOEFL iBT listening results and the Business English speaking performances of the students: Based on the variance table of TOEFL iBT listening and Business English Speaking scores, we could make the scatterplot to represent each individual’s z scores on both dimensions, which are Independent and dependent variables. The z scores on the horizontal axis are those of the TOEFL iBT Listening scores (independent variable), with the lowest z scores on the left and the highest z scores on the right. The z scores on the vertical axis are those of the Business English Speaking scores (dependent variable), with the lowest z scores at the bottom and the highest z scores at the top. Figure 2 The Scatterplot of TOEFL iBT Listening and Business English Speaking Scores 94 Jurnal LINGUA CULTURA Vol.8 No.2 November 2014 The next step is to decide whether these observed correlation coefficients are statistically significant. With the Pearson r, the degrees of freedom (df) are the number of paired observations (N) minus 2. A significant r is equal to or larger than the tabled value with N – 2 degrees of freedom. The df for these calculations is 119 – 2 = 117. With df = 117 when a two-tailed test is performed, an observed Pearson r more than +.1946 or less than -.1946 is required to reject the null hypothesis at the .05 level. With the same degrees of freedom, an observed Pearson r more than +.2540 or less than -.2540 is required to reject the null hypothesis at the .01 level. The coefficient of correlation (r = .74) exceeds the values of both +.1946 and +.2540, and thus, is statistically significant at both .05 and .01 levels. As a result, the first null hypothesis would be rejected, and we conclude that the TOEFL iBT Listening scores are significantly related to the Business English Speaking scores among BINUS University sophomores in English in Focus Mid Test of Even Semester of Academic Year 2012/2013. Since the obtained coefficient (r1 = .74) is between +.30 (weak positive correlation) and +.80 (strong positive correlation), we conclude that high scores on TOEFL iBT listening mid test generally mean high scores on the Business English Speaking performances of the Binus university sophomores studying English in Focus in the Even Semester of Academic Year 2012/2013. The scatterplot of the Pearson r shows that the dots do not really form a narrow band near the line, so there are a moderate linear relationship and a moderate positive correlation between TOEFL iBT Listening scores and Business English Speaking Scores among Binus university sophomores studying English in Focus in the Even Semester of Academic Year 2012/2013. CONCLUSION Based on the significance of the Pearson r (r1 = .74), TOEFL iBT listening scores are positively associated with the Business English speaking scores among Binus university sophomores studying English in Focus in the Even Semester of Academic Year 2012/2013. The relationship between the paired scores is not strong, but not weak either. Furthermore, based on the computation of the z scores of Listening and Speaking scores of the students, the scatterplot shows that there is a moderate degree of linear relationship between the paired z scores. Thus, based on the statistical results, it could be concluded that the more Binus university sophomores achieve high scores on TOEFL iBT listening test, the more likely (not most likely, not least likely) they tend to achieve high scores on their Business English speaking performances as well. Suggestions Because there is evidence that the scores of the Listening skills of Binus university sophomores are significantly correlated in a moderate linear relationship with their scores of the Speaking skills, research suggests the following things to be applied during the teaching and learning process of an English subject for undergraduate students at Binus University. First, the more students listen to some language input in a certain topic, the more likely he or she is able to speak over the topic in his or her own way, and thus it encourages their natural and unique use of the spoken language. Second, integrated tasks are strongly recommended to be delivered more than the independent tasks, as students can learn the language skills not separately, but as a whole package, and thus it establishes a more similar condition of authentic language use that students face in the real world. Third, for integrated tasks of Listening and Speaking, it is highly recommended that fluency and clarity are given higher emphasis than accuracy, so that students are more encouraged to explore any possibility during their practice, and thus, can learn from their mistakes for better performances. REFERENCES Anderson, A., & Lynch, T. (1988). Listening. Oxford: Oxford University Press. Ary, D., Jacobs, L. C., Razavieh, A., & Sorensen, C. (2006). Introduction to research in education. USA: Thomson Wadsworth. Burns, A. (1998). Teaching speaking. Annual Review of Applied Linguistics, 18, 102–123. Celce-Murcia, M. & Olshtain, E. (2000). Discourse and context in language teaching. 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