Language Learning Background Factors and ESL Proficiency

Language Learning Background Factors and ESL ProficiencyAuthor(s): Harry L. Gradman and Edith HananiaSource: The Modern Language Journal, Vol. 75, No. 1 (Spring, 1991), pp. 39-51Published by: Wiley on behalf of the National Federation of Modern Language Teachers AssociationsStable URL: http://www.jstor.org/stable/329833 .

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Language Learning Background Factors and ESL Proficiency HARRY L. GRADMAN Department of Linguistics Indiana University Bloomington, IN 47405

EDITH HANANIA Department of Linguistics Indiana University Bloomington, IN 47405

AT THE CENTER FOR ENGLISH LANGUAGE Training at Indiana University, we have for some time been interested in the language learning background of our incoming ESL students. These students enter our Intensive Eng- lish Program with noticeably different levels of English language proficiency and achieve progress with varying degrees of success. We have designed a study to investigate the relationship between the students' language achievement and a number of variables in the students' language learning background, with the purpose of identifying those factors which have the most prominent effect on the learner's English language proficiency.

The investigation of factors which promote success in language learning has been a focus of interest in second language acquisition research. Some of the areas that have received attention in this field are those related to affective variables (8; 9), sociocultural variables (10; 19), age (7; 21), language practice (2; 20), and learning strategies (18). These and other factors have been taken into consideration in designing comprehensive models of language learning (22; 23).

In our present study, rather than focus on one type of factor, we sought to investigate which of a large number of variables in a student's language background would turn out to be important in second language learning. We obtained, through individual interviews with our students, extensive information about their language learning background before they joined our program. On the basis of this information, we compiled forty-four background variables for examination. By measuring the strength of the relationship between each of

these variables and the students' level of language proficiency, as determined by their TOEFL scores, we sought to identify those background factors which have a significant effect on language learning.

PROCEDURE

The Sample. Our sample consists of 101 students who were enrolled in regular seven-week sessions of the Intensive English Program. They had been in the program for varying lengths of time. However, as we were interested in their initial level of proficiency, we took as a reference point the TOEFL scores which they obtained when they first entered the program.

The students came from different national and first language backgrounds. The largest group was Arabic-speaking (twenty-nine percent), followed by Japanese (twenty-six percent) and by speakers of romance languages, including Spanish, French, and Portuguese (twenty-two percent). Other first languages represented in the sample included Chinese, Korean, Indonesian, Turkish, and Thai (twenty-three percent).

The degree of formal learning of English which the students had received also varied widely. Some had studied English only in school (fifteen percent), some in both school and university (twenty-six percent); others had studied English additionally in intensive Eng- lish programs in the home country or abroad (only with school twenty-eight percent, with school and university thirty-one percent).

The entry TOEFL scores of the sample of students covered a wide range and showed a fairly normal distribution: ten percent were below 351; thirty-nine percent, between 351 and 450; forty-one percent, between 451 and 550; and ten percent, over 550.

The Questionnaire. The questionnaire used for collecting the data was developed in stages.

The Modern Language Journal, 75, i (1991) 0026-7902/91/0001/039 $1.50/0 ?1991 The Modern Language Journal



40 The Modern Language Journal 75 (1991)

First, anticipating the types of background factors that might influence language learning, we prepared a set of questions that would elicit relevant information. We then tested out the preliminary questionnaire in about forty interviews with students in the Intensive English Program (IEP). This procedure enabled us to prepare a revised version, which we then used in gathering extensive background information from 101 students in the program. The information fell into the following categories: 1) general; 2) formal learning of English; 3) exposure to and use of English in class; 4) extracurricular exposure to and use of English; 5) attitudes and motivation; and 6) personal observations by the students on their language learning background and current needs.

Data Collection. The collection of data was carried out entirely through individual interviews. Although this procedure was time consuming (each interview lasting about one hour), we felt that it had at least two advantages over the fill- ing out of a questionnaire by the students: 1) an oral interview would help avoid possible inter- ference from student difficulty with reading or writing skills; and 2) interaction with the students would improve the chances that the information elicited is accurate and complete.

The interviews were conducted in a friendly, informal atmosphere. They were not tape re- corded to avoid possible anxiety on the part of the students. We carried out the interviews ourselves. Since we are not teachers in the program, our involvement eliminated another possible source of anxiety (that background information might adversely affect the students' standings or their grades). The students, who were told the purpose of the interview, seemed to enjoy talking about themselves and regarded the occasion as an opportunity to get conver- sation practice in the target language.

Coding of Data. In preparation for data analysis, the elicited information was grouped and quantified. Under the category of formal learning of English, values were based on the numbers provided by the students, contact hours being calculated on the basis of hours per week and weeks per month, per semester, or per academic year. Under the remaining categories (exposure to and use of English in class, extracurricular exposure to and use of English, attitude and motivation) numerical scales were developed for each variable on the basis of information from the whole sample. Coded values therefore reflected degree in each case.

Examples of the coding scales are given in Appendix I. Other types of information, such as first language, sex, and intended field of study, were coded on a nominal (categorical) scale and were not included in the present analysis.

Analysis of Data. The coding procedure described above yielded forty-four variables which are listed in Appendix II. These variables as well as the TOEFL scores and subscores formed the data for statistical analysis.' Analyses carried out were:

1) pairwise correlations between all the variables, including the TOEFL scores; the results gave an overview of relationships between variables and enabled the selection of twenty-two independent variables for further analysis;

2) multiple regression analysis for the twenty- two independent variables, with TOEFL scores as the dependent variable;

3) path analysis, involving construction of a model for the interrelationships among selected variables, testing its fit to the data, and identifying variables that have statistically significant effects;

4) t-tests to determine the effect of the presence or absence of specific variables on the mean TOEFL scores of the groups concerned.

Finally, the students' invited observations on aspects of their language learning background were categorized and summarized.

RESULTS AND DISCUSSION

Correlations with TOEFL Scores. The first step in the analysis was to obtain pairwise correlations between all variables: the forty-four background variables listed in Appendix II and four proficiency variables consisting of the TOEFL scores and scores on the separate TOEFL sections of Listening Comprehension, Structure and Written Expression, and Vocabulary and Reading Comprehension.2

Table I gives Pearson correlation coefficients for those background variables that showed significant correlations (at the p = .05 level) with the TOEFL scores. Significant correlations between the background variables and scores for the separate TOEFL sections are also included in Table I to provide a more complete picture of relationships. The last column gives correlation coefficients with the variable extracurricular reading (ECR) and will be referred to below.

Focusing first on the TOEFL scores, which



Harry Gradman & Edith Hanania 41 TABLE I Background Variables which Correlated Significantly with TOEFL Scores, TOEFL Subscores, and Extracurricular Reading (Pearson Correlation Coefficients)

TOEFL LC SW VR ECR Formal Learning *Age at start of English -.18 -.18 Years of English in school .20

*Months of intensive/special English .26 .28 .23 .22 .17 *Total contact hours .24 .20 *Private school .20

Exposure and Use in Class

*Native-speaking teachers .39 .45 .35 .27 .27 *English as language of instruction .36 .46 .30 .30 .27 *French/Spanish as language of instruction .21 Index of exposure .20 .26 Index of oral use .24 .29 Oral use-sentence practice .18 .27

*Oral use communicatively .26 .27 *Index of writing use .24 .27 Writing--sentence practice .21 .30 Writing communicatively .22 .19 Index of communicative use .27 .25

*Language lab .23 *Total index of exposure .19 .25 Type of intensive English program .23

Extracurricular Exposure and Use * Listening .19

*Reading .53 .50 .47 .50 -

*Speaking .20 .31 *Writing .35

Attitudes and Motivation *Attitude to English class in high school .17 *Recognition of need .17 *Effective teachers .21 .24 .24 * Family encouragement -.16 *Family graduates of English-speaking countries -.18 -.16 *Current English use .26 *Future need .21 .19 .23 .20 N = 101; p = .05; LC = Listening Comprehension; SW = Structure and Written Expression; VR = Vocabulary and Reading Comprehension; ECR = Extracurricular Reading; * = variables selected for multiple regression analysis on the basis stated in the text and in note 3.

are used in this study as the criterion of proficiency, it can be seen that the variable which correlates most highly with TOEFL is extracurricular reading, followed by extent of exposure to teachers who are native speakers of English, use of English as the language of instruction, and months of previous intensive or special English. Two other variables, extent of exposure to effective English teachers and extent of future need for use of English in the home country, have lower but still significant correlations.

Table I also shows that all the variables that correlated significantly with the TOEFL scores also correlated significantly with the scores of at least two of the three TOEFL subsections. Of the variables that did not correlate well with TOEFL, some nonetheless had a distinctive relationship with one of the TOEFL subsections. Total contact hours, indices of exposure, oral use and written use, and extracurricular speaking all correlate with listening comprehension. So does age at the start of English. These findings are not surprising and lend support to



42 The Modern Language Journal 75 (1991) our coding system. Two variables correlate with scores on vocabulary and reading comprehension: study in private schools and use of French or Spanish as the language of instruction. Again, the distinctive relationship between these variables and reading is not hard to understand. Recognition of the need for Eng- lish seems to relate to higher performance on the structure and written expression section of the TOEFL, which may suggest a relationship between motivation and level of accuracy.

Three aspects of the overall results in Table I are of special interest. First is the relative strength of the relationship between extracurricular reading and performance on TOEFL. Although extensive reading has been shown to enhance language performance (5; 24), we did not anticipate that it would feature so prominently. Second is the absence of direct correlation with TOEFL of many variables, such as total contact hours, indices of exposure and oral use, and attitude toward English class, although these factors would be expected to promote language learning. The third feature is that most of the variables that do not correlate with TOEFL nevertheless correlate with extracurricular reading, which in turn correlates well with TOEFL. This pattern suggests possible direct and indirect relationships among these variables, a point which will be considered further in the section on path analysis.

The above intercorrelation analysis led to the selection of twenty-two independent variables (out of the original forty-four) to be used in the next stage, multiple regression analysis. Vari- ables that correlated with TOEFL and its parts or with extracurricular reading were included, unless they provided overlapping information.3 All pairwise correlation coefficients for the twenty-two variables were well below .70, the level at which concern about multicollinearity would arise (12: p. 118).

Multiple Regression. Multiple regression analysis explores the extent to which several independent variables, singly or in combination, can explain or predict a single dependent variable, which, in this case, is the TOEFL score. Two of the procedures that can be applied in this analysis are: 1) stepwise forward selection, which selects the independent variable with the strongest effect first, then adds one at a time any other variables that meet the criterion for inclusion (default criterion, p= .05); and 2) backward elimination, which eliminates variables with the lowest effect, one at a time,

ending up with a set of variables which have a significant effect (default criterion for removal, p = .10). The results of these two procedures applied to the same set of data can be quite different. In our analysis, we applied both procedures to determine whether the same variables would be identified regardless of approach.

The results of the multiple regression analysis are summarized in Table II. The stepwise procedure shows the strongest effect to be that of the extracurricular reading. Over a quarter of the variation in the TOEFL scores can be attributed to this variable (R2 = .28). The next most prominent effect is that of native-speaking teachers of English, which accounts for an additional seven percent of the variation. The other two variables which met the selection criterion are total index of exposure and extracurricular speaking. Surprisingly, these variables have a negative relationship with the TOEFL scores, as evident from the negative beta values. This negative relationship may in fact hide indirect effects, as we will see below.

The backward regression procedure confirmed the findings of forward selection. All four variables were retained in the equation as above, with a slight shift in position of extracurricular speaking. Since the criterion for

TABLE II

Multiple Regression Analysis

Forward Selection

Steps R R2 Beta

1 Extracurricular reading .53 .28 .53 2 + Native-speaking teachers .59 .35 .43 3 + Total index of exposure .64 .40 -.21 4 + Extracurricular speaking .66 .43 -.20

Backward Elimination All 22 variables .75 .57 Final Step

Extracurricular reading .49

Native-speaking teachers .32 Total index of exposure -.26 Extracurricular writing -.21

English as language of instruction .19 Months of intensive English .17 Extracurricular speaking -.17

Recognition of need .16

Age at start of English -.15 Future need for English .13

N = 101; dependent variable = TOEFL scores; independent variables as listed in Table I, marked with *; forward selection criterion, p = .05; backward elimination criterion,

p = .10; forward beta values are for final step.



Harry Gradman & Edith Hanania 43

removal was set at p = .10 (rather than .05), it is not surprising that the analysis retained six additional variables in the equation. Four of these additional variables had a positive relationship with TOEFL scores: 1) English as the language of instruction; 2) months of intensive or special English; 3) recognition of need (when in high school); and 4) future need for English (after their return home). The remaining two, extracurricular writing and age, had a negative (or inverse) relationship. For age, however, the negative relationship really represents a positive effect of length of exposure, since it indicates that the earlier (younger) the start, the better the TOEFL score.

Finally, it may be noted that the combined effect of all twenty-two variables is an R value of .75, which accounts for fifty-seven percent of the variation in TOEFL scores. This result is impressive, considering the multitude of variables - cognitive, affective, social, pedagogic - which must affect the complex process of language learning and language performance.

Path Analysis. Two aspects of the above results

suggested the need for a further stage in the analysis: 1) the possible indirect effects observed through the pairwise correlations; and 2) the unexpected negative effects observed in the multiple regression.

Path analysis was therefore undertaken, using the statistical program LISREL (Analy- sis of Linear Structural Relations). In this approach, a causal model is formulated, consisting of a set of variables and a set of paths indicating the direction of effects. The statistical procedures of the progam calculate coefficients for the effects and evaluate the model by deter- mining the extent to which it fits the available data.

To date, we have constructed a basic model comprising six variables: two classroom variables (oral exposure and communicative oral use), three extracurricular or outside class variables (listening, reading, and speaking), and the TOEFL scores.4 The model showing the variables and the selected paths, all unidirec- tional, is illustrated in Figure I.

Table III gives the results of the application

FIGURE I Structural Equation Model Used for Path Analysis (LISREL) (Results appear in Table III)

Listening Outside Class

Oral Exposure

Reading TOEFL Outside Class Communicative

Oral Use

Speaking Outside Class



44 The Modern Language Journal 75 (1991) TABLE III Structural Equation Model (LISREL) Standardized Solution: Coefficients and (T-Values)

Beta Gamma

ECS ECR ECL TOEFL TIE OUC

ECS ..... ..... .22 .36

( 1.99) (3.22) ECR .23 ... .07 .05 .09

(2.03) ( 0.66) ( 0.39) (0.71) ECL .. . ... ... .. . .44 .10

( 3.90) (0.85) TOEFL -.11 .58 -.21 . . . -.08 .17

(-1.13) (6.69) (-2.24) (-0.69) (1.50) Goodness-of-fit index = 1.00. EC = extracurricular; S = speaking; R = reading; L = listening; TIE = total index of exposure; OUC = communicative oral use; Beta = endogenous variables; Gamma = exogenous variables.

of the statistical program (LISREL) to all the relationships specified in this model. The coefficients show the effects of variables in the top row on variables in the left column. The high goodness-of-fit index (1.00) indicates that the model accounts well for the data. However, a number of paths in this model did not represent statistically significant effects (their t-values being less than 2.0). The model was therefore trimmed by eliminating these relationships from the equation. The resulting modified

model, showing the remaining paths and their coefficients, is presented in Figure II.

As can be seen in Figure II, reading outside class again has a strong direct effect on the TOEFL scores. The only other variable in this model that has a direct effect on TOEFL is listening outside class, but the relationship here is negative. Speaking outside class, which had a negative relation with TOEFL in the multiple regression analysis, now shows a positive effect on TOEFL through its effect on reading. Like-

FIGURE II Modified Structural Equation Model Showing Significant Paths and Their Coefficients. Goodness-of-Fit Index = .98

Listening .50 Outside Class

Oral -.21

Exposure

Reading .57 TOEFL .22 Outside Class

Communicative .31 Oral Use

.36 Speaking Outside Class




wise, the two classroom variables, oral exposure to English and communicative oral use of English, are now seen to affect TOEFL indirectly. Both have paths with positive direct effects on outside speaking, which in turn leads through outside reading to TOEFL. Oral exposure, in addition, has a path to outside listening, which has a negative relationship with TOEFL.

What this model seems to indicate is that the single most important factor in improving proficiency as reflected in the TOEFL scores is outside reading. Extent of oral exposure and communicative use of English in class and out of class have a positive, though indirect, effect on TOEFL insofar as they promote outside reading, but not through their effect on outside listening. Outside listening, which reflects the extent to which learners were exposed to Eng- lish speech via radio, television, or film, appears to have a negative relationship with TOEFL. These results require further com- ment.

Starting with outside listening, the scores for this variable do not necessarily reflect active listening. In many cases, students reported that, in viewing English programs, they relied on the native language subtitles and that they did not pay attention to or were unable to understand the English speech. This type of exposure, therefore, unlike reading or the active classroom listening included in the variable oral exposure, did not represent comprehensible input.5 However, this still leaves the negative relationship with TOEFL unexplained. One possible interpretation is that the outside listening scores represent a tendency toward passive viewing at the expense of more de- manding activities, such as reading and social communication. Another related explanation may well be that outside listening is indulged in more extensively, and possibly more profit- ably, only at lower levels of ability. The possibility that the relative importance of some background factors varies with the learners' level of proficiency merits further investigation.

Another recognized source of comprehensible input is the oral use of English in and out of class for communicative purposes (13: p. 47). The positive role of these factors, though indirect, is apparent in the model. Apparently, many students who had an opportunity to listen to and use English in meaningful situations in class also engaged in outside reading, leading to further language input. Particularly inter-

esting, however, is that the role of these factors in promoting language proficiency seems to be restricted to their positive effect on reading.6

The dominant role of outside reading is perhaps the most striking result of this study. Reading for personal information or pleasure appears to be a more important means of implicit learning than exposure to and use of spoken English in and out of the classroom. One may argue that the prominence of this factor reflects the degree to which good performance on the TOEFL depends on reading ability. However, it seems unlikely that the use of reading as a medium for this examination can adequately account for the strength of the relationship of outside reading with TOEFL and its subsections; it is more likely that extensive outside reading helps to improve the level of proficiency in a global sense, enhancing acquisition of grammar, vocabulary, and rhetorical structure, as well as increasing the general knowledge base which helps in reading comprehension.7

To explore this point further, we ran a multiple regression analysis using only those students in our sample who had entered at the three upper levels of our program (levels four, five, and six), on the assumption that, for these more advanced students, basic reading skills had already been acquired. The results of this analysis (not tabulated here) confirmed our finding for the whole sample. Here again, outside reading emerged as the most important, indeed the only, factor with a significant effect on TOEFL scores (p = .05; beta = .32; N = 49). Those students who read extensively out of class within this advanced group attained higher levels of proficiency than did those with no extracurricular reading.

The results of our analysis may therefore be taken to support the findings of previous experi- mental studies which have shown that extensive reading enhances language proficiency (5; 24). Our work is also in accord with the view put forward by Krashen that extensive comprehensible input is crucial to language acquisition (13; 14) and that reading, by providing extensive comprehensible input, is an important and effective means of acquiring language (15; 16).

Effect of Specific Variables. The above results have so far enabled the identification of several background variables that have strong direct and indirect effects on TOEFL scores. In the next stage of the work, we sought to look more closely at individual variables and their effects.



46 The Modern Language Journal 75 (1991)

We divided the whole sample into two groups with respect to a particular variable and then compared the mean TOEFL scores of the two groups. The t-test was applied to measure the significance of differences. However, to control for the effect of intensive English programs, which obviously provided an advantage to students who participated in them, the two groups were subdivided into those who had taken intensive English courses and those who had not. This four-way division enabled us to examine not only the effect of a particular variable but also the effect of intensive English programs with respect to that variable. The results of this analysis have interesting pedagogical implications. Three examples are presented here.

The first variable we examined in this way was age at the start of learning English. One of the relevant questions in planning English language teaching abroad is whether those who start English early, in the elementary school, have an advantage over those who start later. We compared the TOEFL scores of students who had started learning English at age twelve and below with those who started at age thir-

teen and above. Figure III illustrates the results. Looking first at students who have had no intensive English, we see that those who started early have a distinct advantage over those who started later, though the difference is not statistically significant. However, when we look at students in either group who had also studied English in intensive programs, we find that the advantage of starting at an early age disappears. In other words, joining an intensive English program for a few months seems to compensate for the disadvantage of starting English late. This finding is important and holds promise for those who may have had the disadvantage of a late start. It appears that students can still learn another language, even at a later age, given the motivation and the opportunity to do so. This finding may also be taken to underline the importance of motivation. Stu- dents usually join an intensive English program only when learning English has become a press- ing and recognized need.

Another factor that we examined in this way is attitude toward studying English, which did not show much effect in the correlation and regression analyses, probably because of its

FIGURE III Effect of Age at the Start of Learning English: Mean TOEFL Scores for Students with and without Intensive English Program (IEP)

Age < 13 Age 13

TOEFL 500 -

456 466 460

450- 423

400 -

350 -

300 No IEP IEP




limited scope. At the interview, students were asked if they had liked English class when they were in high school. With respect to this variable, the two groups were those students whose answers were negative and those who said they had liked English class in varying degrees. The results are shown in Figure IV. For the group who had not taken an intensive English program, there was a marked difference in the TOEFL mean scores between those who liked English and those who did not, though this difference was again not statistically significant. For students who went on to join intensive Eng- lish programs, the differences related to earlier attitudes toward studying English in school disappear. It may also be noted that for those who did not like English in school, an intensive English program resulted in significantly improved mean TOEFL scores (at the p = .05 level). For those who liked English, performance on TOEFL was not significantly different, whether or not they had taken intensive English. These results suggest that a positive attitude toward English class is an important factor in learning the language.

One more variable that we ran through this

type of analysis is extracurricular reading, which has already featured prominently in the correlation and regression analyses. Figure V shows a marked difference in the performance of students who have engaged in extracurricular reading and those who have not (significant at p = .06 for the no IEP group and at p = .01 for the IEP group). In fact, unlike the previous cases, an intensive English program here does not seem to help nonreaders, while the readers seem to do quite well whether or not they have taken intensive English. This observation certainly confirms our previous findings that outside reading is a very important factor in promoting language learning, and it strongly suggests that ESL (and foreign language) programs would do well to encourage this language activity.

Student Observations. During our interviews with the students, we asked them for their personal observations and suggestions on how the teaching of English could be improved in their home countries. We present here a summary of their views on this subject. We realize, of course, that the teaching of English in most countries has changed dramatically over the last

FIGURE IV Effect of Attitude toward English Class when in High School: Mean TOEFL Scores for Students with and without Intensive English Program (IEP)

Negative E Positive

TOEFL 500 -

463 463 454

450-

409

400-

350-

300 No IEP IEP



48 The Modern Language Journal 75 (1991) few years and that many improvements have been introduced. Nonetheless, the suggestions made by the students are relevant in that they tend to support some new directions in language teaching.

Most students called for the extensive use of English in English class and for increased attention to listening and speaking. Many stressed the importance of having teachers who are highly proficient in English, either native speakers or teachers who have received their professional education in English-speaking countries. Another set of suggestions relates to the interest factor in the classroom: varying teaching methods and materials to include songs, games, tapes, movies, and reading analyses rather than mere translation. Students also suggested that reading and discussion should be on topics of current interest and that grammar study and analysis should be of prac- tical value rather than consisting of formal rules memorized with the intent to pass exams. The opinion was also expressed that teachers should help their students recognize the importance of English in the modern world, encourage their efforts to learn the language, and make allow-

ance for differences in individual ability within the class. We should perhaps add here that we were struck by the degree of consistency in the observations the students made about their language learning experiences and their prefer- ences, regardless of their native language and educational background.

CONCLUSIONS

To summarize, in this study we systemati- cally collected information about the language learning background of our students in an attempt to identify the major factors that influence the language proficiency of ESL students. Our results demonstrate that, out of a large number of background factors which must con- tribute to success in language learning, a few stand out as particularly important. Foremost among these is the extent of active exposure to the language through individual outside reading. This result emerged consistently from different analyses of the data, including the path analysis model.

Other background factors that appear to con- tribute prominently to enhancing students' lan-

FIGURE V Effect of Extracurricular Reading (ECR): Mean TOEFL Scores for Students with and without Intensive English Program (IEP)

I No ECR E ECR

TOEFL 500 -

471 457

450

404

400

350

300 No IEP IEP




guage proficiency include exposure to teachers who are native speakers of English, the use of English as a language of instruction, and par- ticipation in intensive English programs, all of which represent further sources of comprehensible input and of meaningful language use. Interestingly, however, oral communication in the language (oral exposure in the classroom and speaking in class and out of class) affected TOEFL scores only indirectly through its relation to outside reading, a finding which further stresses the importance of that factor. In addition, two variables underline the importance

of motivation: early recognition of the need for English when still in high school and antici- pated need for the use of English in future occupations.

The present work, with an expanded data base, is being extended along two lines. First, we hope to investigate whether the role of background factors varies according to specific language groups and to levels of proficiency. Second, we intend to explore the effect of current outside reading on the progress of students within our Intensive English Program.8

NOTES

1The SPSSx statistical package was used for statistical

analysis. 2The institutional form of the TOEFL, which is given

to our students at the end of each session, consists of these three sections only.

3When variables overlapped, selection was done on the

following basis. In cases where component variables gave similar correlations with TOEFL as did the combined vari-

able, the combined variable was selected (e.g., the two

components of the index of oral exposure). In cases where the components showed differences, the separate variables were selected (e.g., the four parts of the index of extracurricular use: listening, reading, speaking, and writing). In other cases of overlap, such as that between age at which formal learning of English started and years in school, only one of the variables was included.

4The terms extracurricular, outside class, and outside are used interchangeably to refer to language activities undertaken outside class.

5The results of a study carried out by Long (17) may also throw light on problems with this type of listening exposure. Long found that listening material that was specifically adapted to non-native speakers was significantly more com-

prehensible to ESL students than unadapted material prepared for native speakers. Radio, video, and film material which is directed at native speakers may therefore not be an effective source of comprehensible input.

6It would be interesting to find out whether these oral variables would show a more direct relationship with a

specific measure of spoken English, such as the ETS Test of Spoken English. This possibility merits further investigation.

7For the linguistic knowledge and complex processes involved in reading comprehension, see Goodman (11), Carrell (1), and Eskey (6). For the relationship between

general language competence and reading proficiency, see

Elley (4) and Devine (3). 8A revised version of a paper originally presented at the

MLJ/Ohio State University Symposium on Research Per-

spectives in Adult Language Learning and Acquisition, Columbus, Ohio, November 1989.

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APPENDIX I

Examples of Coding

Coding Scale

English as a Language of Instruction None 0

University (some reading) 1 University (lectures or extensive reading) 2

Secondary School + University 3

Elementary + Secondary School + University 4 US High School or University 5

Classroom Exposure to Spoken English A. Teachers' Instructions in English

Never 0 Sometimes 1

Usually 2 Scores are given for each level, as

applicable, and totalled. Levels are: elemen-

tary, intermediate, secondary, university, intensive English program.

B. Teachers' Explanations (Scores given and totalled as in A.)

C. Index of Exposure = Score A + Score B.

Extracurricular Reading Types of reading: (1) story books or novels;

(2) newspapers and magazines; (3) textbooks or references for a university

course; (4) reports or references related to occupation No outside reading 0 A little (one of the above occasionally) 1

Regularly (one or two of the above regularly) 2

Extensively (two or more of the above

frequently) 3

Scores are given for each level (elementary, intermediate,

secondary, university, intensive English program, period of employment) and are totalled.




APPENDIX II

Background Variables Considered

Formal Learning of English Age at start of English Years of English in school Years of English in university Months in intensive or special English programs Months of private English tutoring Contact hours for each of the above Total contact hours Years since last English class Private schooling

Exposure to and Use of English in Class Teachers who are native speakers of English English as language of instruction French or Spanish as language of instruction Index of exposure to oral English

Exposure to instructions

Exposure to explanations Index of oral use

Oral use - sentence practice Oral use communicatively

Index of writing Writing - sentence practice Writing communicatively (composition)

Index of communicative use (oral + written) Audio-visual index

Listening to tapes Language lab

Total index of exposure (index of exposure + listening to tapes)

Teaching focus (grammar translation/grammar reading/all skills)

Type of intensive/special English program (home country with no NS teachers/home country with

NS teachers/ES country)

Extracurricular Exposure to and Use of English Listening Reading Speaking Writing Travel to English-speaking countries

Attitude and Motivation Attitude to English class in high school Recognition of the need for English when in high school Effective teachers of English Family encouragement for learning English Family graduates from English-speaking countries Current English use out of class Current reason for intensive English Future need for English on return to the home country

1990 Kenneth W. Mildenberger Prize

THE COMMITTEE ON HONORS AND AWARDS of the Modern Language Association invites nominations for the eleventh annual Kenneth W. Mildenberger Prize, to be presented for an outstanding research publication in the field of teaching foreign languages and literatures. The prize will be awarded for a book or article published in 1990; nominations will be ac- cepted until 1 June 1991. Authors of works submitted for consideration need not be members of the Association. In choosing the prizewinner, the selection committee will look for evidence of fresh and effective approaches to teaching and for works likely to be widely useful.

To enter research publications into competi- tion, send six copies of each work and a letter of nomination indicating the titles submitted, the authors, and the dates of publication to the Kenneth W. Mildenberger Prize, Modern Lan- guage Association, 10 Astor Place, New York,

NY 10003-6981. Textbooks based on the author's original research are eligible to com- pete, but the letter nominating a textbook must include a 300-word statement specifying the extent to which the book constitutes or is based upon original research. Books limited to re- working or restating ideas and concepts origi- nating elsewhere should not be submitted. Nominators of textbooks must send their letters of nomination in advance and obtain clearance from the MLA before shipping books.

The award, which consists of a check for $500, an engrossed certificate, and a one-year membership in the MLA, will be announced and presented at the association's annual con- vention in December 1991. For further information, write to Richard Brod, Director of Special Projects, Modern Language Associa- tion, or call (212) 614-6406.



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Language Learning Background Factors and ESL Proficiency