The Role of Social and Educational Factors in Oral Participation of ELT Students

Document Type: Research Paper

Authors

1 Department of ELT, Ahar Branch, Islamic Azad University, Ahar, Iran

2 Department of English Language, Payame Noor University, -Tehran, Iran

Abstract

Oral participation (OP) in class is an important factor contributing to the development of oral fluency. Recent studies in language learning have addressed the necessity of classroom interaction, or rather students’ oral participation in class. A correlational research study was drawn upon to measure the oral participation and factors affecting oral activities of the ELT students studying at the M.A. level at Islamic Azad University of Ardabil in Iran. An initial pool of 93 participants was selected through purposive sampling. The data analysis was conducted using structural equation modeling (SEM). The results obtained indicated that there is a significant relationship between social and educational factors relative to the oral activities of EFL learners. The findings also showed that in oral participation, educational factors play the most important role in controlling the OP content. 

Keywords


The Role of Social and Educational Factors in Oral Participation of ELT Students

 

Masoud Zoghi1, Amir Reza Nemat Tabrizi2, Sara Ghobadi*3

   1, 3Department of ELT, Ahar Branch, Islamic Azad University, Ahar, Iran

  2Department of English Language, Payame Noor University, -Tehran, Iran

*Corresponding author: saracoroo2000@yahoo.com  

 

 

Received: 2014.3.5

Revisions received: 2016.1.24

Accepted: 2016.5.17

 

 

 

 

Abstract

Oral participation (OP) in class is an important factor contributing to the development of oral fluency. Recent studies in language learning have addressed the necessity of classroom interaction, or rather students’ oral participation in class. A correlational research study was drawn upon to measure the oral participation and factors affecting oral activities of the ELT students studying at the M.A. level at Islamic Azad University of Ardabil in Iran. An initial pool of 93 participants was selected through purposive sampling. The data analysis was conducted using structural equation modeling (SEM). The results obtained indicated that there is a significant relationship between social and educational factors relative to the oral activities of EFL learners. The findings also showed that in oral participation, educational factors play the most important role in controlling the OP content.

 

Keywords: oral participation, social and educational factors, structural equation modeling (SEM)                     

                                             Introduction

The benefits of active classroom participation have been researched quite extensively over the past years (Mustapha, Nik-Abd-Rahman, &Yunus, 2010). One of the rare concepts of unanimous approval in language education is learners’ active oral participation (Cole, 1996; Finn &Voelkl, 1993; Stanton-Salazar, 1997). Those students who are actively involved and constantly participate in class discussions have been reported to perform much better (Astin, 1999) than their comparatively passive peers. Active classroom participation exists within a hierarchy predicated upon students’ increasing engagement with school, classmates and teachers (Patchen, 2006; Tatar, 2005).

Unwillingness to participate in class discussions is a major concern for those who are involved in language teaching research. It is evident that English language learners (ELLs) need daily opportunities to learn and practice oral English in order for their language proficiency to flourish. The English language serves as the input or data that ELLs internalize and use to express their own meanings in their interactions with their classmates, teachers and others. Academic success in a foreign language classroom is largely dependent on active oral participation in the class. However, motivating students to participate orally is a struggle for many foreign language teachers (Gardner, Masgoret, Tennant, & Mihic, 2004). Exploring active classroom participation from students’ perspective could be an important undertaking as it provides a firsthand account and insight into their feelings and perceptions.

White (2004) argues that oral language has a key role in classroom teaching and learning. He goes on to argue that oral language "helps to encourage creativity, understanding, and imagination; it is a means of solving problems, speculating, sharing ideas and making decisions; language builds friendships and enhances motivation through social interaction" (p. 5). Harmer (2001) proposed that pair-work increases the amount of talking time available to every learner in a classroom. A recent study on Chinese EFL students found that students were least likely to participate in oral activities in class that required them to respond to teachers’ questioning; by contrast, they were much more likely to participate if it involved working in a pair with a peer (Liu & Jackson, 2009). Participation usually means students speaking in class in any conversation class: answering and asking questions, making comments, and joining in discussions. Having a supportive relationship with peers influences students’ sense of belonging, thereby affecting student effort, achievement, self-efficacy and even long-term goals (Walker & Greene, 2009; Anderman, 2003). In learner-learner interaction, the teacher plays the role of a monitor and learners are the main participants (Gillies, 2006).

There are several factors that affect the initiative of students when taking part in oral tasks inside the classroom. Learning environments can have a facilitating effect on oral production. The linkage between students, classroom participation and their academic achievement is undeniable (Wudong, 1994). Research has shown that participation in classroom activities is important in order for effective learning to take place (Tsou, 2005). A study by de Jong and Ferguson-Hessler (1996) also found that students who participate actively in class tend to have better academic achievement compared to those who are less likely to participate and are passive in class. In general, since OP is the most observable behavior, studies in the field of language learning have focused on the significance of students’ OP (Ellis, 1999). Therefore, increased emphasis has been placed on students’ interaction or OP in the classroom. Swain (1993) believes that language production provides an opportunity for meaningful practice of one’s linguistic resources, which, in turn, leads to fluency. In other words, it is by producing and using the language as frequently as possible that one can achieve fluency (Swain, 1993).

Fawzia (2002), on the other hand, divides the factors affecting students’ oral participation (OP) into three broad categories: student factors (SF), social factors (SOF), and pedagogical/educational factors (PF/EF). Factors such as students’ perception, attitudes, language factors, learning styles, students’ backgrounds and personal affective factors are examples of student factors, whereas social factors include the gender of students in class and community feelings in a group (Fawzia, 2002). Nevertheless, this present study focused on examining and analyzing SOF and EF factors affecting oral participation. The study also attempted to find out how OP facilitates the acquisition of oral skills throughout  different activities provided to the students and the way in which students’ motivation affects their participation and interaction in class.

The proposed conceptual model in this study is based on what is already acquired by the earlier research, that is to say, the correlations among variables that have already been validated and are known. Owing to the role and importance of educational and social factors in ELT students' OP, the need for the evaluation of these factors relative to OP is urgently required. Most of the earlier studies carried out in this respect utilize regression models and structural equation modeling (SEM) analysis to show the relationships between educational/social factors and oral participation. In this regard, all the variables together were entered into a single model in order to test the potential interactions between the independent and dependent variables using SEM. Fig. 1 shows a hypothesized model that presents all the basic constructs and the hypothesized correlations between them. The aim was to test whether the latent variables of (H1) student factors, (H2) educational factors, and (H3) social factors have a positive impact on OP.

 

 

 

Figure 1. Hypothesized Model of Oral Participation

 

Note. English learning experience (ELE), English proficiency (EP), teacher’s encouragement (TE), teacher-learner interaction (TLI), and learner-learner interaction (LLI).

 

                                            

Method

Participants

The study was performed at the Islamic Azad University of Ardabil. The participants were all M.A. majors from the academic year of 2010-2013. The ELT courses were selected because they required a high level of student participation and focused more on oral communication activities. The participants of the present study consisted of both male and female students and were selected by means of purposive sampling. Their ages ranged from 22 to 34. The sample size was estimated as 93 through the following sample size formula (De Vaus, 2001).

 

 

 

Instrumentation

Based on an extensive literature review and review of relevant theories, a researcher-made questionnaire was developed for this study comprising two major parts: the first part consisted of items measuring the English learning experience (ELE) and English proficiency (EP), teacher’s encouragement (TE), teacher-learner interaction (TLI) and learner-learner interaction (LLI), gender differences (male/female), course level and age, with the second part containing questions about the learners’ oral participation (speaking and listening). All of the items of the questionnaire were measured by means of six-point Likert scales or six-point rating scales, with 1, denoting “not at all,” and 6, meaning “very much,” anchoring each end of the scale.

After the design of the questionnaire was finalized, it was piloted among 83 ELT students before being used for the main study. Based on the initial data obtained from the pilot testing, modifications were made to the questionnaire. The reliability of the instrument was also calculated using Cronbach's alpha. The results indicated that the questionnaire enjoyed relatively high internal reliability, yielding an alpha coefficient of .90 for the whole measure. Table 1 shows an acceptable level of reliability for the instrument's subcategories, as well.

Table 1

Reliability coefficients of the instrument

Reliability Coefficient

Items

Research Variables

0.80

4

ELE

Social Factors(SF)

Independent Variables

0.72

4

EP

0.85

5

TLI

Educational

Factors(EF)

0.70

4

LLI

0.88

4

TE

0.79

6

Oral Participation (OP)

Dependent Variables

0.90

27

The Entire Instrument

 

Note: ELE (English learning experience), EP (English Proficiency), TLI (Teacher-learner interaction), LLI (Learner-learner interaction) and TE (Teacher’s encouragement).

 

Procedure

The researchers first made the necessary arrangements with the Islamic Azad University of Ardabil and obtained permission to administrate the questionnaires. This study was conducted on a voluntary basis, with almost all participants agreeing to participate in the study. Before distributing the questionnaires, the students were given instructions on how to complete them and were asked to do so faithfully. After completing the questionnaire, the researchers offered the participants prizes in appreciation of their participation in the study.

Design

Since this study aimed at investigating the relationships between educational and social factors relative to oral participation, it was designed as a correlational study, which is a quantitative research method.

 

                                                     Results

Structural equation modeling (SEM) was used to investigate how well the empirical data supported the hypothesized relationships among the set of variables. The advantages of SEM in path analysis are attributable to the possibility of testing the overall agreement between the path model and the data (Markland, 2006). The proposed structural relationships between the variables were analyzed through LISREL analysis. The two scales pertaining to social and educational factors were the predictor variables in this study, while oral participation was the outcome variable. The structural model of this study is presented in Fig. 1 above.

Each LISREL model is normally comprised of two sub-models (also referred to as models, for simplification reasons): the measurement model and the structural model. The former shows us how each latent variable is measured by its indicators, in other words, how each construct is operationalized; the latter characterizes the associations between the variables, indicating the direction and statistical significance of each association, as well as the amount of variance in the endogenous variables explained by the respective proposed determinants (Kunnan, 1998). In the present study, the effects of two latent variables on OP, that is, “Social Factors” and “Educational Factors,” were assessed. Each of these conceptual factors (latent variables) can be linked with observed variables (“what can be measured in the real world”), even though it is explicitly acknowledged that none of these variables perfectly represents the underlying property (measurement errors). Specifically, in this study it was hypothesized that of the two variables affecting OP, the first latent variable, social factors, can be measured by two indicator variables, while the second, educational factors, can be measured by three observed variables. The premise for the selection of these indicators was based on the findings of the principal factor analysis, which evidenced that the correlations between the measurement errors for the observable indicators of the exogenous latent variables are well-documented in the literature and strongly supported theoretically. The final step of this study involved simultaneously placing all the variables in a conceptual model in order to test the potential interactions between them.

In addition, standardized coefficients were used to evaluate the strength of path coefficients estimated. Fig. 2 shows that two hypotheses indicate causal relationships between (1) social and (2) educational factors with OP. Support was found for hypotheses H1 and H2 as they approached significance ( 0.52, 0.78, ) respectively. Therefore, the research hypotheses are supported, meaning that social and educational factors do have significant positive effects on OP.

Table 2 indicates that the theoretical model adequately constructed the observed covariance of the data, with all of the aforementioned indicators of good model fit exceeding the minimum specifications. The 2 statistic is non-significant, indicating a good model fit to the sample variance-covariance matrix, both statistically ( 2 = 22.04, =11,  = 2.00, ) and descriptively (GFI = 0.91, CFI = 0.93, RMSEA = 0.03). Standardized coefficients were used to evaluate the strength of the estimated path coefficients, as the variables involved were not measured by the same measurement tool. The coefficients for the paths in the model denoted the strength of the direct effect of the exogenous variables on the endogenous variables.

Fig. 2 shows path estimates for the accepted structural model. As can be seen, social and educational factors have significant positive effects on OP. According to the estimation of the standardized coefficients of the research structural model and the obtained significance level ( ) in Fig. 2, the coefficients for the effects of educational and social factors on oral participation were 0.78 and 0.52, respectively.

 

 

Figure 2: Accepted Theoretical Model of Oral Participation

 

Table 2 indicates that the theoretical model adequately constructed the observed covariance of the data, with all of the aforementioned indicators of good model fit exceeding the minimum specifications. The 2 for this model was 22.04 ( =11) while the  ratio of 2.00 is below the threshold of 3.0, as prescribed by Wheaton, Muthén, Alwin, and Summers (1977). All of the fit indexes (CFI and GFI) are above the 0.90 minimum prescribed by Bentler for well fit models (Bentler, 1990).

Table 2

 Results of structural model tests—goodness of fit summary

Measure

Full model values

Standard for acceptance

Chi-square

22.04

NA

df

11

NA

p-value

0.75

>0.05

2/df

2.00

3–1

CFI

0.92

>0.90

GFI

0. 91

>0.90

RMSEA

0.03

<0.08

Note: x2=Minimum fit function test; CFI=comparative fit index; GFI=goodness of fit index; RMSEA=root mean square error of approximation.

Discussion

The present study investigated the social and educational factors affecting the participation of ELT students in oral activities. The results suggest that there is a significant relationship between social and educational factors relative to oral activities. Similar results have been reported by Liu & Jackson (2009), Chaudron (1988), Cotter (2007) and Anderman (2003). The findings indicated that social factors – the English learning experience and English proficiency – could affect learners’ oral performance. These findings are in line with studies carried out by Walker & Greene (2009) as well as Mustapha, Nik-Abd-Rahman & Yunus (2010), who were able to demonstrate that a supportive relationship with peers and the teacher, which, in part, result from positive English learning experiences, can influence learners' language attainment.

The present study showed that the oral activities of ELT students are positively correlated with social and educational factors. In fact, the results indicated that in OP, educational factors play the most important role in controlling OP content. The proposed model also illustrates the main factors that affect OP in class discussions. Based on the interplay between both social and educational factors and oral activities as well as the significant impact of educational factors followed closely by social factors, the following suggestions are made for the improvement of oral participation:

1) Teachers should help students to develop a positive self-image as well as autonomy and self-responsibility for their own learning, which, in turn, can motivate them to participate in classroom activities; in order to maximize students' participation in class activities, it seems advisable that teachers assess students’ interests and needs in advance. This allows them to include in their classes topics and activities that are more engaging and tailor-made for the particular group of students. It is of the utmost importance to create a safe and comfortable environment where students are tolerant of other classmates’ mistakes and where the teacher avoids the traditional role of instructor, gradually adopting a facilitator role instead.

2) The grouping of students for class activities influences students’ participation in oral activities. Since low English proficiency students feel more capable of participating in class when they are exposed to small groups in which they feel confident to speak, this kind of arrangement should be maximized for conversation classes.

3) Teachers should provide as many opportunities as possible for learners to use the target language.

 

References

Anderman, L.H. (2003). Academic and social perceptions as predictors of change in middle school students’ sense of school        belonging. Journal of Experimental Education, 72, 5-22.   

Astin, A.W. (1999). Student involvement: A developmental theory for higher education. Journal of College Student Development,   40, 518-529.

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238-246.            

 Chaudron, C. (1988). Second language classrooms: Research on          teaching and learning. Cambridge: Cambridge University Press.     

Cole, M. (1996). Cultural psychology: A once and future discipline. Cambridge, England: Belknap Press.  

Cotter, Ch. (2007). Speaking well - four steps to improve your ESL  EFL students speaking ability. Retrieved March 12th, 2008 from: http://ezinearticles.com/?Speaking-Well----Four-Steps-To-Improve-Your-ESLEFL.

De Vaus, D. A. (2001). Research design in social research. London: Sage Publications. de Jong, T., & Ferguson-Hessler, M. (1996). Types and qualities of knowledge. Educational Psychologist, 31(2), 105-113.

Ellis, R. (1999). The study of second language acquisition. New   York: Oxford University Press.

 Fawzia, A. (2002). Factors Affecting Students’ Oral Participation in University Level Academic Classes within the Omani Context. Paper presented at Second Annual National ELT Conference, 27-28, March 2002. Sultan Qaboos University, Oman.     

Finn, J., & Voelkl, K. (1993). School characteristics related to student engagement. Journal of Negro Education, 62, 249-268.

Gardner, R., Masgoret, A. M., Tennant, J., & Mihic, L. (2004). Integrative motivation: changes during a year-long intermediate- level language course. Language Learning, 54(1), 1-34.

Gillies, R. M. (2006). Teacher’s and students’ verbal behaviours during cooperative and small-group learning. British Journal of educational Psychology, 76, 271-287.

Harmer, J. (2001). Mistakes and feedback? the practice of English        language teaching, Essex, UK: Pearson Education Limited.

Karahan, F. (2007). Language attitudes of Turkish students towards the English language and its use in Turkish context. Retrieved   March 12th, 2008.         

Kunnan, A.J. (1998). An introduction to structural equation modeling for language assessment research. Language Testing, 15 (3), 295–332.

Lee, P. (2005). Students’ personality type and attitudes toward classroom participation. Proceedings of the CATESOL state conference.

Liu, M.,& Jackson, J. (2009). An exploration of Chinese EFL learners’ unwillingness to communicate and foreign languageanxiety. Modern Language Journal, 92(1), 71-86.  

Markland, D. (2006). Latent variable modeling: An introduction to confirmatory factor analysis and structural equation modeling. Retrieved from http: www.bangor.ac.uk.      

Mustapha, M.S., Nik-Abd-Rahman, S.N., and Yunus, M. M.  (2010). Factors influencing classroom participation: a case study of Malaysian undergraduate students.Procedia Social and Behavioral Sciences, 9, 1079–1084.

Patchen, T. (2006). Engendering participation, deliberating dependence: inner-city adolescents’ perceptions of classroom practice. Teachers College Record, 108(10), 2053-2079.        

 Stanton-Salazar, R. (1997). A social capital framework for  understanding the socialization of racial minority children and youths. Harvard Educational Review, 67, 1-40.

 Swain, M. (1993). The output hypothesis: just speaking and writing aren’t enough. The Canadian Modern Language Review,      50(1), 158-164.

 Tatar, S. (2005). Why keep silent? The classroom participation experiences of non-native-English-speaking students. Language and Intercultural Communication, 5, 284-293.     

Tsou, W. (2005). Improving speaking skills through instruction in  oral classroom participation. Foreign Language Annals, 38(1), 46-55. 

Walker, C.O., & Greene, B.A. (2009). Student motivational beliefs and cognitive engagement. Journal of Educational Research, 102, 463-471.

Wheaton, B., Muthén, B., Alwin, D. & Summers, G. (1977). Assessing  reliabilityand stability in panel models. In D.R. Heise  (Ed.), Sociological Methodology(pp. 84-136). San Francisco: Jossey-Bass      

 White, J. (2004). Speaking, listening and learning materials. Qualifications and Curriculum Authority and the National Literacy Strategy Journal. Retrieved August 25th, 2008, from: http://www.literacytrust.org.uk/Pubs/white.html.       

 Wudong, W. (1994). English language development in China, Unpublished doctoral dissertation, University of Tasmania.         

 

                                                Biodata                

     

Masoud Zoghi is an Assistant Professor of TESL. He has taught courses on research methodology, ESP, applied linguistics, and language testing at the M.A. and Ph.D. programs in ELT and General Linguistics. His current research and teaching focus includes research methodology in applied linguistics and psychology of language.

 

Amir Reza Nemat Tabrizi is an Assistant Professor in the Department of English Language, Payame Noor University.

 

Sara Ghobadi is a graduate of Islamic Azad University, Ahar Branch, Iran.

 

Anderman, L.H. (2003). Academic and social perceptions as predictors of change in middle school students’ sense of school        belonging. Journal of Experimental Education, 72, 5-22.   

Astin, A.W. (1999). Student involvement: A developmental theory for higher education. Journal of College Student Development,   40, 518-529.

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238-246.            

 Chaudron, C. (1988). Second language classrooms: Research on          teaching and learning. Cambridge: Cambridge University Press.     

Cole, M. (1996). Cultural psychology: A once and future discipline. Cambridge, England: Belknap Press.  

Cotter, Ch. (2007). Speaking well - four steps to improve your ESL  EFL students speaking ability. Retrieved March 12th, 2008 from: http://ezinearticles.com/?Speaking-Well----Four-Steps-To-Improve-Your-ESLEFL.

De Vaus, D. A. (2001). Research design in social research. London: Sage Publications. de Jong, T., & Ferguson-Hessler, M. (1996). Types and qualities of knowledge. Educational Psychologist, 31(2), 105-113.

Ellis, R. (1999). The study of second language acquisition. New   York: Oxford University Press.

 Fawzia, A. (2002). Factors Affecting Students’ Oral Participation in University Level Academic Classes within the Omani Context. Paper presented at Second Annual National ELT Conference, 27-28, March 2002. Sultan Qaboos University, Oman.     

Finn, J., & Voelkl, K. (1993). School characteristics related to student engagement. Journal of Negro Education, 62, 249-268.

Gardner, R., Masgoret, A. M., Tennant, J., & Mihic, L. (2004). Integrative motivation: changes during a year-long intermediate- level language course. Language Learning, 54(1), 1-34.

Gillies, R. M. (2006). Teacher’s and students’ verbal behaviours during cooperative and small-group learning. British Journal of educational Psychology, 76, 271-287.

Harmer, J. (2001). Mistakes and feedback? the practice of English        language teaching, Essex, UK: Pearson Education Limited.

Karahan, F. (2007). Language attitudes of Turkish students towards the English language and its use in Turkish context. Retrieved   March 12th, 2008.         

Kunnan, A.J. (1998). An introduction to structural equation modeling for language assessment research. Language Testing, 15 (3), 295–332.

Lee, P. (2005). Students’ personality type and attitudes toward classroom participation. Proceedings of the CATESOL state conference.

Liu, M.,& Jackson, J. (2009). An exploration of Chinese EFL learners’ unwillingness to communicate and foreign languageanxiety. Modern Language Journal, 92(1), 71-86.  

Markland, D. (2006). Latent variable modeling: An introduction to confirmatory factor analysis and structural equation modeling. Retrieved from http: www.bangor.ac.uk.      

Mustapha, M.S., Nik-Abd-Rahman, S.N., and Yunus, M. M.  (2010). Factors influencing classroom participation: a case study of Malaysian undergraduate students.Procedia Social and Behavioral Sciences, 9, 1079–1084.

Patchen, T. (2006). Engendering participation, deliberating dependence: inner-city adolescents’ perceptions of classroom practice. Teachers College Record, 108(10), 2053-2079.        

 Stanton-Salazar, R. (1997). A social capital framework for  understanding the socialization of racial minority children and youths. Harvard Educational Review, 67, 1-40.

 Swain, M. (1993). The output hypothesis: just speaking and writing aren’t enough. The Canadian Modern Language Review,      50(1), 158-164.

 Tatar, S. (2005). Why keep silent? The classroom participation experiences of non-native-English-speaking students. Language and Intercultural Communication, 5, 284-293.     

Tsou, W. (2005). Improving speaking skills through instruction in  oral classroom participation. Foreign Language Annals, 38(1), 46-55. 

Walker, C.O., & Greene, B.A. (2009). Student motivational beliefs and cognitive engagement. Journal of Educational Research, 102, 463-471.

Wheaton, B., Muthén, B., Alwin, D. & Summers, G. (1977). Assessing  reliabilityand stability in panel models. In D.R. Heise  (Ed.), Sociological Methodology(pp. 84-136). San Francisco: Jossey-Bass      

 White, J. (2004). Speaking, listening and learning materials. Qualifications and Curriculum Authority and the National Literacy Strategy Journal. Retrieved August 25th, 2008, from: http://www.literacytrust.org.uk/Pubs/white.html.       

 Wudong, W. (1994). English language development in China, Unpublished doctoral dissertation, University of Tasmania.