Students’ Speaking Skill Self-Efficacy, Peer-Modeling Behavior and Speaking Skill Achievement: a Correlational Study

Introduction

Airey (2003) explains that there are many common advantages of teaching English and using it as the language in higher education. In Ethiopia, for instance, the English language is used to prepare students for their academic careers, align lectures and with course literature as most books are written in English, to enhance students’ self-confidence and researchers skills, to prepare them for study abroad and to increase access to employment, as English is becoming a valuable asset in jobs market.

According to Giday (2019), although English is extremely valued as a language that offers the possibility for access to advanced education and international opportunities beyound Ethiopia, it is not familiar to most people. It is known and utilized only by the literate. Berhanu (2009) also states that the adoption of English in Ethiopia is restricted to less practical areas. Moreover, Seidel and Moritz (2009) note that English has been a compulsory subject in schools since kindergarten, a medium of instruction beginning in grades five, seven, or nine, depending on the region, as well as a common course, and a university department. However, most Ethiopian higher education students, in general, and English language and literature students, in particular, hardly speak English. Gelete and Dhaba (2023) state that students struggle with spoken English in both formal and informal settings. Furthermore, many studies have been conducted to alleviate challenges in Ethiopian students English language proficiency. However these challenges persist evidenced by studies such as Chemir and Kitila (2022), Endale et al., (2024), Engida et al. (2024), Telore and Damtew (2023) and Tesfaye (2014).

Additionally, based on the researchers’ personal experiences teaching English language and literature in different institutions such as high schools, colleges, and universities, they observe that English language and literature students struggle communicate to in English. They also feel nervous during presentations and hesitate to do tasks while they are assigned. Additionally, students score very low marks in courses that focus on speaking skills. Consequently, it appears impossible to achieve English language teaching objectives. Bearing this in mind Usman et al. (2023a) note that Ethiopian educational goal would benefit from support of all societal levels. The government aims to achieve these goals by providing education through three channels: formal, non-formal, and informal education (Driver, 2009; Usman et al., 2023b). Singh and Gelat (2022) state that educational research helps advance educational improvement in different areas, including teaching methods and students' behavior. Consequently, researching students' low achievement and confidence issues, and providing support is necessary.

A variety of researches have made significant effort to address educational problems and proposed solutions. Eghterafi et al. (2022), for instance, researched the effect of feedback with video-based peer modeling on learning and self-efficacy and proved that peer modeling improves both. Therefore, students who learn from their peers achieve higher academic success.

Seraoui (2017) also states the affective side of the learner is believed to play a major role in the process of language learning. Although research factors in learning have been limited, scholars are now increasingly turning to the learners' mindset and psychology when learning languages. Student self-belief and academic achievement are very important factors in terms of language learning; however, studies are still limited, especially in developing countries' second and foreign language fields.

To understand how learners construct their personal views on the self and how they become successful in their academic achievement, English language self-efficacy, peer-modeling, and speaking skills achievements are the center of language learning. According to Bandura (1997), self-efficacy (SE) is the learners’ belief in their abilities to do tasks, and Lopez-Garrido (2023) notes that one of the elements of speaking skill SE is peer modeling. Generally, in students’ education life, academic achievement is the means that demonstrates students’ progress in language learning.

Philp, Adams, and Iwashita (2014) wrote that peer interaction and peer modeling support that a variety of different types of language use and practice. Since peer interaction is practiced in language classrooms, second or foreign-language learners spend ample time interacting with their classmates instead of expecting communication only from their teacher. This increased emphasis on the role of peer interaction in education shifted recent research into an interdisciplinary study across social, cognitive, and other perspectives. Muir (2018) explains the concept of peer model for second or foreign language student means, which might be learners who are in class or school, recent graduates or even their teacher at times. Modeling a peer lets students choose the most convenient, appropriate, and engaging way to learn.

Students' efficacy-testing experiences change as they move into the larger communities. In peer relationships, they broaden and refine self-awareness concerning their capabilities. Peers serve several important efficacy functions. Those who are most experienced and competent provide models of efficacious thinking and behavior styles. (Bandura, 1989) noted that a vast amount of social learning occurs among peers. According to Murphey and Arao (2001), when peers model each other, they learn either from their success or their mistakes. Moreover, mistakes become a part of learning and transform into fun for students.

Bandura (1997) stated that peers could play a powerful role in influencing their friends' self-efficacy in various ways, including in an academic settings, through social comparison academic instruction, and interpersonal affiliation. Raoofi et al. (2012) have found that learners can enhance SE and develop positive beliefs about themselves when engaging with peers performing tasks effectively. Furthermore, Bailey (2005) proved that foreign language students' speech confidence improves when engaging within mutually supportive their peer groups.

Mills (2014) notes that in the 21st century, significant self-efficacy research, has translated into academic practicalities in educational psychology in the context of foreign language learning it pertains to the relationship between self-efficacy and language skill development.

Self-efficacy plays a significant role in optimizing academic achievement. It is enhanced with personal experiences in connection with own successes, but also with modeling other people who demonstrate performance and achievements (Bandura, 1997). In terms of students’ English language learning process more specifically, self-efficacy development is observed to improve the presence of peer modeling (Bhati & Sethy, 2022; Lopez-Garrido, 2023).

According to Lopez-Garrido's (2023) interpretation of Bandura’s SE with in social cognitive theory, people's beliefs about their abilities profoundly influences the development of those abilities. Ability is not a fixed property as there is broad variability in how one can perform. People with a sense of self-efficacy recover from failure rather than anticipating further failures (Bandura, 1977). In this sense, language students depend on different components of self-efficacy to remain resilient and spring back. One of these components is peer modeling: learning from examples provided by those around us occurs at any age, for instance, a teacher often serves as a role model for a student. According to Lopez (2023), peer modeling occurs when students demonstrate positive social relationships and are actively engaged in tarnsmitting and receiving the values upheld as exemplary among their peers. Furthermore, peer modeling is also the sharing of ideas, knowledge, and communication styles with students of the same profession, age, and grade level among students who share mutual respect and admiration (Dörnyei & Murphey, 2008).

The Ruddick & Nadasdy (2013) study was conducted to assess the influence of Near Peer Role Models (NPRMs) in second-language classrooms with the expressed intent of improving student pronunciation when teacher intervention is lacking. Based on the result of this research, the effectiveness of NPRMs was found to be an agent of positive change in the English language classroom. Distinct for the research cited above, the current study addresses the correlation among student speaking skill self-efficacy, peer modeling, and speaking skill achievement.

Thus, the current researcher was concluded that assessing the relationship between students' speaking skills, self-efficacy, peer modeling, and speaking skill achievement is worthwhile for several reasons: Richard Tucker (1977) shows that affective variables are more closely related to students’ oral production and listening than to writing and reading. Next, based on the researchers’ experience teaching spoken English courses, the researcher observed that students’ self-evaluation of their speaking ability affects their achievement. Additionally, as students become more confident in introducing themselves in English they generally improve overall achievement. The study aims to investigate his observation further. Finally, self-efficacy and peer modeling have received rather less attention than some other constructs here in our country, Ethiopia.

The present study seeks to evaluate:

1. The level of students’ speaking skill self-efficacy.

2. Students beliefs concerning peer modeling and whether it positively influences speaking skill achievement.

3. The relationship between students' peer modeling and speaking skill achievement.

4. The relationship between students' peer modeling and speaking skill self-efficacy.

Method

Research Design

The present study aimed to evaluate the relationship across student self-efficacy, peer-modeling behavior, and speaking skill development. The study adopted a mixed-method approach and collected data from 33 participants. Gay, Milles, and Airasian (2012) note that a mixed-method research approach combines quantitative and qualitative research methods to understand phenomena such as those reflected in this study in a balanced holistic manner. A correlational research design was also employed to analyze the data and explain the nature of the variables’ relationship. Correlational research design helps us to evaluate the strength and direction of variables’ relationships with each other. In other words, it involves collecting data to determine whether, and to what degree, a relationship exists between two or more quantifiable variables (Gay et al., 2012).

Sampling and Sample Size

Approximately 33 students voluntarily enrolled in the English language and literature department in Wolaita Sodo and Wachamo Universities. On average, students were 19 years old. At Wolaita Sodo University, 21 students, 17 males and 4 females, were seeking to complete the Spoken English course. There were 12 students: 11 males and 1 female student at Wachamo University. The researcher included all students for the data collection using census or availability sampling technique. The majority of participants were undergraduate 2nd-year English language and literature students attending the Spoken II English course.

Data Collection Methods and Procedure

Both quantitative and qualitative data were collected consecutively. First, the quantitative data was collected using a speaking skill self-efficacy questionnaire which consisted of 14 items, and a peer-modeling self-report questionnaire consisted of 12 items. The speaking skill self-efficacy questionnaire was derived from research observed by Idrus and Sivapalan (2007) as well as Sağlam and Arslan (2018) which was originally developed by Bandura, (1990) and Mikulecky (1996) (see appendix A for further detail). The peer-modeling self-report questionnaire was adapted from (Paradewari, 2017) (see appendix B for further detail). The researcher conducted an initial set of pilot tests to check the reliability of the speaking skill self-efficacy and peer-modeling self-report questionnaires. In addition, Cronbach's alpha value of the speaking skill self-efficacy and peer-modeling self-report questionnaires were checked with results indicating 0.87 and 0.79, respectively. The questionnaires’ items were stated both positively and negatively for validity purposes.

An interview-based speaking skill test was then administered. This test was adapted from the International English Language Testing System (IELTS). Finally, qualitative data was collected using the five semi-structured interview questions followed by probing from two indicative interviewees. The five semi-structured interview questions were prepared according to the scope of the study and consistent with existing literature.

Data Analysis

The quantitative data were descriptively analyzed using SPSS version 25: applying Pearson’s correlation coefficient, mean, standard deviation, frequency and percentage. Diagnosis tests for the assumptions of Pearson’s correlation coefficient were conducted. A linearity test suggested the relationships between the variables are linear. A normality of the data distribution was also assessed. The histogram illustrated that the distribution of the residuals approximated a normal distribution. Additionally, a Shapiro Wilk-test was conducted to confirm the normality assumption. Moreover, no outliers were detected. Finally, the qualitative data was thematically analyzed using NVivo version 10. Interview data was transcribed, read, and re-read for deeper understanding, open coded, categorized, and thematically analyzed.

Diagnosis Test About the Assumptions of Pearson Correlation Coefficient Analysis

Several tests were conducted and described to ensure that the data met the assumptions of regression analysis, as follows.

Figure 1. Linearity test

Linearity refers to the assumption that the variance of the criterion variable is a linear combination of the parameters (regression coefficient) and the predictor variables meaning that changes in the independent variable are proportionally related to the change in the dependent variable. The relationships across independent variables-student speaking skill self-efficacy and peer-modeling, and the dependent variable, students’ speaking skill achievement, were linear, the correlation residuals were analyzed using SPSS version 25.

Observing the graph above from left to right, the P-P plot of standardized residuals shows no large difference in the spread of the residuals, suggesting that the relationships relevant to this study are linear.

Figure 2. Normality test.

The normality of the residuals was assessed using a histogram. The histogram (see Figure 2) visually depicts the distribution of the residuals. It shows the frequency of the residuals on the y-axis and the range of values on the x-axis.

Upon visual inspection, the histogram suggests that the distribution of the residuals approximates a normal distribution. The data appear to be approximately symmetric and bell-shaped, indicative of a normality assumption. Additionally, statistical tests were conducted to confirm the normality assumption. For example, a Shapiro-Wilk test was performed to assess the normality of the residuals as illustrated below.

Table 1

Shapiro-Wilk test results

The Shapiro-Wilk test yielded a p-value of (0.297) p > 0.05, indicating that the distribution of the residuals was significant and normally distributed. Therefore, the assumption of normality for the residuals was not violated.

Results

Descriptive Analysis of the Students’ Speaking Skill Self-Efficacy

The 33 participants provided quantitative data by responding to speaking skill self-efficacy questionnaire. The speaking skill self-efficacy questionnaire comprised fourteen items. The following table illustrates the findings concerning the level of speaking self-efficacy.

Descriptive statistics indicating the level of students’ speaking skill self-efficacy

To ensure the students’ speaking skill self-efficacy level, a speaking skill self-efficacy questionnaire, rated on a 5-point Likert scale, was compiled. The minimum (1.86) and maximum (4.26) values indicated that there were no outliers, ensuring that the data were valid and accurate. Although the main focus of the study was the relationship between students’ self-efficacy and their speaking skill achievement, measures of central tendency also helped in understanding the participants’ level of English self-efficacy. Participant English self-efficacy mean result was (3.46) and the standard deviation was (0.61) indicating that most language students possess moderate speaking skill self-efficacy.

Descriptive Analysis of the Students’ Self-report Questionnaire

Data was collected from 33 students using the student peer modeling behavior questionnaire. The self-report peer-modeling questionnaire consisted of twelve items. The purpose of measuring student peer-modeling behavior in English language and literature classrooms was to assess whether students believe that their peer-modeling behavior influences speaking skill self-efficacy, indicative of question two of the questionnaire. The questionnaire was also used to validate the speaking skill self-efficacy responses. The following table illustrates these quantified findings.

Table 3

Descriptive Statistical Results Correlating Student perceptions of Peer Modeling Behavior and Speaking Skill Achievement

The peer-modeling behaviors mean score table above indicates students believe peer-modeling and increases their abilities and confidence in doing English language course tasks. The minimum (1.71) and maximum (3) descriptive statistics indicates that the data are clean to compute. The central tendency measures, including the mean and standard deviation scores for peer modeling (M = 2.4, SD = 0.36), also indicate that respondents agreed that their peer-modeling behavior influences their abilities and confidence in performing tasks in the English language and literature classroom.

Correlational Analysis of the Peer-Modeling Scale and Students’ Speaking Skill Achievement

Question three of the peer modeling behavior questionnaire aimed to establish any association between students' peer modeling behavior and speaking skill achievement. To this end, a Pearson correlation coefficient was computed to examine if an increase in one variable leads to an increase in another variable. The quantified findings are shown in the following table.

Table 4

Associations Between Student Peer-modeling Behavior and Student Speaking Skill Achievement

Table 4 shows the correlation between students’ peer-modeling behavior scores and speaking skill achievement collected from 33 participants. According to the table, the correlation between the variables was r = 0.60. The Pearson correlation coefficient value established that there was a relationship between student peer-modeling behavior and student speaking skill achievement. Moreover, the increase or decrease in the students’ peer-modeling behavior leads to an increase or decrease in the students’ speaking skill achievement. Therefore, there was a positive correlation between student peer-modeling behavior scores and overall speaking skill achievement. Furthermore, the association was also statistically significant as the sig. value of the correlation was less than the cut-off threshold P = 0.000 overall. Overall, the relationship between student peer-modeling behavior and speaking skill achievement was moderately positive and statistically significant.

Correlational Analysis of Students’ Peer-modeling Behavior and Speaking Skill Self-Efficacy

Question number four was designed to establish any association between student peer-modeling behavior and student speaking skill self-efficacy. The Pearson correlation coefficient was conducted to observe if an increase in one variable leads to an increase in another variable. The following table shows the quantified findings.

Table 5

Association Between Students’ Peer-modeling Behavior and Students’ Speaking Skill Self-efficacy

Table 5 shows the correlation between student peer-modeling behavior scores and student speaking skill SE scores collected from 33 participants. The table indicates that the correlation between the variables is r = 0.62. The Pearson correlation coefficient value indicates that there was a relationship between student peer-modeling behavior and student speaking skill self-efficacy. Therefore, the increase or decrease in the students’ peer-modeling behavior leads to an increase or decrease in student speaking skill self-efficacy. Furthermore, there were moderately positive correlations between student peer-modeling behavior scores and overall speaking skill self-efficacy scores. The association was also statistically important since the significance-value of correlation was less than the cut-off threshold (P = 0.000). The relationship between student peer-modeling behavior and overall speaking skill self-efficacy was highly positive. Generally, the relationship was also statistically significant.

Analysis of the Interview Data

In addition to the test-based data collection, a semi-structured interview consisting of four questions was conducted with two purposively selected second-year students to triangulate the results with the quantitative data analysis. The interview data collected from these two students were recorded and transcribed word for word. The interview transcript was coded, thematically categorized and inductively analyzed using NVivo version 10. The researcher assigned participant one (P1) and participant two (P2) for analysis convenience.

Analysis of the Student's English Language Learning Experience and Level of Proficiency

Both P1 and P2 were asked about their English language experience. Both participants responded that they began their education in grade one at the age of seven. Since then, they said they learned English language as a subject up until grade twelve. Once they enrolled with the university, they pursued their bachelor degrees in English language and literature. At the time they gave the interview, they were second-year students. However, despite their English language training, they both students stated that they could have been better listeners in understanding the English language, which affected their academic achievement. It stands to reason therefore that educators could be supportive to English language students in mitigating their language understanding problems.

Analysis of Students’ Belief in Their Ability to Do Tasks in the English Language Classroom

Regarding the question about students’ belief in their ability to do tasks in the English language, the interview participants answered that they lose confidence while solving any tasks in and out of the classroom. Regardless of the uncomfortable language learning environment, the interviewees explained that they have a strong motivation to improve their speaking abilities.

These responses were probed further by asking “so, what do they each think they could do to improve your speaking skills, confidence, and abilities?”.

The participants replied that they had yet to be supported in learning the English language with special training, like the students from private schools. They said we learned only in government schools. There was no supportive class in the government school except the formal one. Thus, we need more supplementary courses if the government wants us to be good professionals in the English language. They added that they wanted to practice more grammar, the four skills, and English vocabulary. The students stated that if we understood the grammatical structure of language, we could develop confidence in speaking English. Therefore, students expect government schools’ English language and literature teachers to support them with additional tutoring on English language grammar, the four basic skills, and vocabulary to enhance their confidence in speaking the English language.

Analysis of Student Peer Modeling Behavior

In terms of the question of to what extent students learn from their peers, P1 said that he always learns from his classmates, whereas P2 replied that this only sometimes occurs. Additionally, the respondents explained, in reference to the question about when they learned from their classmates, that the first student described his classmate became a model for him during a classroom presentation. He said that he learned how to organize ideas from his friend and was impressed by his speaking ability. That means the peer student's presentation style, confidence, speech fluency, and accuracy was instructive for him. While the second student believes that, in some cases, peer modeling enhances self-confidence in using English language, her peer’s positive' reinforcement helps her improve her speaking by giving less attention to mistakes and avoiding unnecessary apprehension. Generally, the interviewees believe peer modeling plays a significant role in improving students' speaking skills and self-confidence.

Analysis of Students’ Current Status of Speaking Skill Achievement

Regarding the participants’ current speaking skill achievement, the students reported that they consider themselves average students. P1 said that he scored at the top of his classmates, while P2 said she was an average student among her classmates. Additionally, they said they planned to learn more and become an intermediate learner. They believe that it is an indignity for them to be under-intermediate English language students while attending English language and literature at university. Consequently, the students are eager to enhance their proficiency in the English language. As a result, it is vital for language teachers to identify the student areas of weakness, offer consistent support, supply authentic and relevant materials, and provide constructive guidance for improvement.

Discussion

The main purpose of the present study was to investigate the correlation between students’ speaking skill self-efficacy, peer modeling, and speaking skill achievement. The study comprised four research questions. The study participants included 33 students enrolled in English language and English literature university courses. The data gathering instruments, included the speaking skill self-efficacy questionnaire, self-report questionnaire, speaking skill achievement test, and an interview, all of which were utilized to address each research objective. The quantitative data were analyzed using SPSS version 25. The descriptive statistics used to analyze the data were mean, standard deviation, Pearson correlation coefficient, and the reliability analysis of Alpha. The qualitative data were analyzed using NVIVO 10 software.

Question One: Finding out the level of students' speaking skill self-efficacy

Question one was designed to determine whether the level of students’ speaking skill self-efficacy varies depending on peer modeling behavior or not. Descriptive statistics, mean, and standard deviation were computed in addition to the interview analysis to achieve this objective.

The researcher examined the level of students’ speaking skill self-efficacy among 33 students. A speaking skill SE questionnaire comprising a 5-point Likert scale and a self-report questionnaire consisting of a 3-point Likert scale, both of which were used to assess students' self-efficacy regarding their speaking abilities. The questionnaires demonstrated good reliability (Cronbach's Alpha = 0.87 and 0.79 respectively). The result indicated that the average speaking skill self-efficacy measures according to the self-report questionnaire scores were 3.45 (SD=0.62) and 2.45 (SD=0.35) on a 5 & 3-point Likert scale, indicating moderate levels of self-confidence in speaking skill abilities. The standard deviation (0.62 and 0.35) signifies a low level of variability in self-efficacy scores.

The qualitative analysis of the interview data revealed several themes relating to students’ speaking skill self-efficacy. Of the interview participants, the first student expressed a moderate belief in their ability to communicate effectively, showing instances of successful presentations and group discussions. However, the other student expressed a low level of self-efficacy due to anxiety and experience. Therefore, students’ speaking skill self-efficacy varies depending on their peer modeling behavior.

These findings highlight an overall positive level of speaking skill self-efficacy among the peer modeling students, suggesting that they acquire confidence in their ability to speak in different situations. However, it is significant that some students indicated lower self-efficacy and desired help to overcome any difficulties they may face in improving their speaking skills. Similar research findings were reported showing both moderate and high levels of student self-efficacy (Agustin, Pertamina & Rahmat, 2022; Demirel, Turkel & Aydin, 2020; Ifdil, Apriani, Yendi&yendi, 2016).

Question Two: Students Believe Positive Modeling Influences Their Speaking Skill Achievement

To assess whether students believe that their peer modeling habits may positively influence their speaking skill achievement or not, the mean value was computed. The mean value of students’ peer modeling activities is 2.43. The finding showed that students believe that speaking skill self-efficacy positively influences their speaking skill achievement. The overall descriptive statistics, frequency, and percentage results indicated that students who usually learn from their surroundings, such as observing their classmate's strengths, are able to speak the English language and possess high speaking skill self-efficacy relative to those who weren't engaged in the same manner (see Table 2). Therefore, students believe that peer modeling positively influences speaking skill achievement. An investigation and analysis of data on whether student peer modeling behavior influences students' self-efficacy or achievement indicated that observing and modeling peers increases students' self-efficacy and academic achievement in contrast to student who limit engagement to observing and modeling their teacher alone or not engaging at all; which is consistent with the previous Schunk and Hanson (1985) findings.

Question Three: Identifying the Relationship between Student Peer-Modeling and Speaking Skill Achievement

The third question was designed to identify any relationship between students’ peer-modeling behavior and speaking skill achievements. As shown in Table 3, descriptive statistics were computed to evaluate this correlation between the students' peer-modeling habits and speaking skill achievement. The table indicates the correlation between the students’ peer modeling behavior and speaking skills achievement was r = 0.60. The Pearson correlation coefficient value also supported the correlation. That means an increase or decrease in the students’ peer-modeling behavior leads to an increase or decrease in speaking skill achievement. Therefore, there was a moderate positive correlation between student peer-modeling habit scores and overall student speaking skill achievement.

Moreover, the correlation is statistically significant as the sig. value of correlation is less than the cutoff threshold (P= 0.000). The relationship between students’ peer-modeling behavior and the overall students’ speaking skill achievement was moderately positive, and it was statistically significant.

Various researchers have also found that peer modeling positively influenced students’ speaking skill achievement increasing or decreasing with the former variable leading to an increase or decrease in the latter variable (Biggs et al., 2018; Eghterafi et al., 2022; Muir, 2018; Murphey & Arao, 2001; Wang, 2023). Therefore, a positive correlation between the student peer-modeling behavior and student speaking skill achievement has been established.

Question Four: Assessing the Relationship between Students' Peer-Modeling and Speaking Skill Self–Efficacy

Question four was designed to evaluate whether student peer-modeling activities are positively associated with speaking skill self-efficacy or not. To answer this question, descriptive statistics and the Pearson correlation coefficient were computed as indicated in Table 4. Descriptive statistics of students’ peer-modeling activities (r = 0.62), sig. value 0.000 showed that there was a relationship between students’ peer-modeling activities and speaking skill self-efficacy. That means an increase or decrease in the students’ peer-modeling activities leads to an increase or decrease in the students’ speaking skill self-efficacy. Therefore, the result showed that student peer-modeling activities were moderately associated with student speaking skill self-efficacy.

Additionally, the interview data analysis found that students who acted as models had high levels of self-confidence and high speaking skill self-efficacy. One can understand this from observing their general classroom activities and their respective speaking skill achievement. A similar study, examined the effect of video-based feedback designed to highlight a peer engaged in effective thinking processes on self-efficacy beliefs and learning outcomes (performance on a delayed quiz). The findings showed that statistics students who received video feedback rated higher self-efficacy and scored higher than those who did not (Eghterafi et al., 2022). Another study on the relationship between peer social support and academic self-efficacy also showed a relationship between peer social support and academic self-efficacy (Yuri, Yendi, & Ardi, 2020). This finding also supports research that observing peer modeling leads to high self-efficacy and achievement (Schunk & Hanson, 1985).

Conclusion

Although this research may be regarded as a very small step, it deepens insight into the correlation between student speaking skill self-efficacy, peer modeling, and speaking skill achievement. These findings suggest that most students possess an average degree of self-efficacy in speaking, as shown by the quantitative methods of self-efficacy and self-report questionnaires. The findings from qualitative studies further support this and illustrate that student self-efficacy may be contextualized with peer modeling experiences.

Peer-modeling has been shown to be useful in enhancing student speaking skill self-efficacy. Language students who engage in peer modeling exhibit greater positive self-perception in their speaking abilities and consequently their speaking skills performance. Therefore, peer modeling in language classrooms significantly enhances student speaking skills.

However, some students score low on self-efficacy often due to phobias or have past discouraging or demotivating experiences. Educators can play crucial role in addressing the challenges by establishing an atmosphere of encouragement that can enhance student speech competencies and create the conditions that lead to greater academic success.

The study has effectively highlighted the relationship between self-efficacy and peer-modeling in language learning. Further studies could target other variables that help to achieve speaking skill proficiency and examine the long-term impact of students' peer modeling on language proficiency. Should these studies commence more improvement in teaching practices designed to enhance student speaking abilities and achievement would be expected.

Ethical Statements

A formal letter was initially submitted to the Academic Vice President of Wolaita Sodo and Wachamo Universities to obtain authorization for data collection. Upon approval, the Vice Presidents wrote a letter to the College of Social Sciences in both Universities. Subsequently, the Universities’ college deans wrote letters to the department heads who then informed participants. Following this process data collection was conducted in accordance with ethical guidelines.

Author Contributions

Melkamu Dessalegn Jara designed and directed the study, developed the theoretical framework, performed the analysis, and drafted the manuscript. Hailu Gutema aided in interpreting the results and worked on the manuscript. Both authors discussed the results and contributed to the final manuscript.

Limitations

The limited availability of participants in the study area restricted the sample size, thereby constraining data collection. Additionally, time and financial constrains further impeded efforts to expand the sample size. Furthermore, the absence of prior internal research on the topic posed a challenge in establishing a baseline foundational framework for the current study.

Funding

The author received funding from Addis Ababa University for this research.

Acknowledgment

The researchers would like to thank Addis Ababa University for funding this research. We also thank students, instructors, and colleagues at Wolaita Sodo & Wachamo Universities who were directly and indirectly involved in the study process.

Appendix A. Speaking Skill Self-Efficacy Questionnaire

Instruction I: In the following table there are different statements to the left and five possible response scales strongly agree (SA), agree (A), undecided (U), disagree (D), and strongly disagree (SD) to the right. For each of the statements, put the sign (X) under the response scale that most closely corresponds to how you think and feel about the statements.

Appendix B. Peer-modeling Self-report Questionnaire

Instruction I: read the following items one by one and put an X mark under “Agree (A)” if you agree with the statement; neutral (N) if you “agree or disagree"; otherwise, “Disagree (DA)” if you disagree with the statement.

Day/Date_________________         University_______________

Session __________________          Class ________________

Appendix C

General Instruction

Dear students,

The objective of this questionnaire is to compile data for research. The answer you give may be used to improve the quality of English language teaching, particularly in the spoken course classroom, by realizing students’ English language self-efficacy and peer modeling behavior. The study investigates the correlation between students’ speaking skill self-efficacy, peer modeling, and speaking skill achievement. Therefore, through this questionnaire, the researcher wants to find out how you think, feel, and behave when attending a spoken course in a classroom. Use your experiences from the class to answer these statements below. Your cooperation in completing this questionnaire is greatly appreciated.

Thank you for your support!

References

Agustin, T. R. D. N., Pertamana, D., & Rahmat, R. (2022). Students’ Self-Efficacy in Public Speaking: A Case Study in Indonesian EFL Context. TLEMC (Teaching and Learning English in Multicultural Contexts), 6(2), 83–95. https://doi.org/10.37058/tlemc.v6i2.5220

Airey, J. (2003). Teaching University Courses through the Medium of English: The current state of the art. In: Didaktikens mångfald, 1, 11–18.

Bailey, K. (2005). Practical English Language Teaching: Speaking. McGraw-Hill ESL/ELT

Bandura, A. (1989). Social Cognitive Theory. In R. Vasta (Ed.), Annals of Child Development. Six Theories of Child Development (pp. 1-60). JAI Press

Bandura, A. (1997). Self-Efficacy: The exercise of control. New-York, W.H. Freeman & Co.

Berhanu, H. (2009). An Evaluation of the Implementation of the Current ELT Syllabus for Grade 9 in terms of the Communicative Language: Unpublished MA Thesis, Addis Ababa University.

Bhati, M. K., & Sethy, T. P. (2022). Self-Efficacy: Theory to Educational Practice. International Journal of Indian Psychology, 10(1), 1123-1128. DIP:18.01.112.20221001. https://doi.org/10.25215/1001.112

Biggs, E. E., Carter, E. W., Bumble, J. L., Barnes, K., & Mazur, E. L. (2018). Enhancing Peer Network Interventions for Students with Complex Communication Needs. Exceptional Children, 85(1), 66–85. https://doi.org/10.1177/0014402918792899

Chemir, S., & Kitila, T. (2022). English for Academic Purposes Learners’ Needs Analysis: Language Difficulties Encountered by University Students in Ethiopia. Celtic: A Journal of Culture, English Language Teaching, Literature and Linguistics, 9(1), 97–119. https://doi.org/10.22219/celtic.v9i1.20646

Demirel, M. V., Türkel, A., & Aydın, İ. S. (2020). Speaking self-efficacy beliefs of Turkish university students. Cypriot Journal of Educational Sciences, 15(3), 399–411. https://doi.org/10.18844/cjes.v15i3.4905

Dörnyei, Z., & Murphey, T. (2008). Group dynamics in the language classroom (Nachdr.). Cambridge University Press.

Driver, M. (2009). Curriculum Framework for Ethiopian Education: Federal Democratic Republic of Ethiopia Ministry of Education. Available at https://moe.gov.et/storage/Books/Curriculum%20Framework%20for%20Ethiopian%20Education%20(KG%20%E2%80...

Eghterafi, W., Tucker, M. C., Zhang, I. (Yunyi), & Son, J. Y. (2022). Effect of Feedback with Video-based Peer Modeling on Learning and Self-efficacy. Online Learning, 26(2). https://doi.org/10.24059/olj.v26i2.2732

Endale, D., Tadesse, A., Admasu, A., & Getachew, A. (2024). University teachers’ underlying assumptions about assessment in English as a foreign language context in Ethiopia. Cogent Education, 11(1), 2335748. https://doi.org/10.1080/2331186X.2024.2335748

Engida, M. A., Iyasu, A. S., & Fentie, Y. M. (2024). Impact of teaching quality on student achievement: Student evidence. Frontiers in Education, 9, 1367317. https://doi.org/10.3389/feduc.2024.1367317

Gay, L. R., Mills, G. E., & Airasian, P. W. (2012). Educational research: Competencies for analysis and applications (10th ed). Pearson.

Gelete, L. W., & Dhaba, T. K. (2023). Psychosocial Learning Environments of English Classes and Students’ Motivational Intensity in Learning English Language. ELT Worldwide Journal of English Language Teaching, 10(2), 429. https://doi.org/10.26858/eltww.v10i2.53767

Giday, W. G. (2019). History of Education and English Language Teaching in Ethiopia. A Brief            Survey, 6(1), 34-50.

Idrus, H., & Sivapalan, S. (2007). Perceived self-efficacy of ESL students with regard to their oral communication ability: Conference Proceedings Paper presented at International Conference on Social Sciences and Humanities 2007, Bangi, Malaysia. Available at https://www.academia.edu/960453/Perceived_Self_efficacy_of_ESL_Students_with_Regard_to_Their_Oral_Co...

Ifdil, I., Apriani, R., Yendi, F. M., & Rangka, I. B. (2016). Level of students` self-efficacy based on gender. The International Journal of Counseling and Education, 1(1), 29. https://doi.org/10.23916/29-33.0016.11-i41b

Lopez-Garrido, G. (2023). Self-Efficacy Theory in Psychology: Definition & Examples. Simply Psychology. Available at https://www.simplypsychology.org/about-us

Mills, N. (2014). 2. Self-Efficacy in Second Language Acquisition. In S. Mercer & M. Williams (Eds.), Multiple Perspectives on the Self in SLA (pp. 6–22). Multilingual Matters. https://doi.org/10.21832/9781783091362-003

Muir, C. (2018). Motivational aspects of using near peers as role models Part of the Cambridge Papers in ELT series. Cambridge University Press.

Murphey, T., & Arao, H. (2001). Reported Belief Changes through Near Peer Role Modeling. TESL-EJ, 5(3). Available at http://tesl-ej.org/ej19/a1.html

Paradewari, D. S. (2017). Investigating Students’ Self-efficacy of Public Speaking, 5(10). Available at https://www.ijern.com/journal/2017/October-2017/09.pdf

Philp, J., Adams, R., & Iwashita, N. (2014). Peer Interaction and Second Language Learning. Taylor & Francis. https://doi.org/10.4324/9780203551349

Raoofi, S., Hoon Tan, B., & Heng Chan, S. (2012). Self-efficacy in Second/Foreign Language Learning Contexts. English Language Teaching, 5(11), 60. https://doi.org/10.5539/elt.v5n11p60

Ruddick, M., & Nadasdy, P. (2013). The Influence of Near Peer Role Models (NPRMs) in Second Language Classrooms Intended to Improve Students’ Pronunciation When Teacher Intervention is not enough. The Asian EFL Journal Professional Teaching Articles, 65, 28-40.

Sağlam, D., & Arslan, A. (2018). The Development of English Language Skills Self-Efficacy Scale for Higher Education Students. International Journal of Psycho Educational Service, 7(2). Available at https://files.eric.ed.gov/fulltext/EJ1252951.pdf

Schunk, D. H., & Hanson, A. R. (1985). Peer Models: Influence on Children’s Self-Efficacy and Achievement.Journal of Educational Psychology, 77(3), 313–322. https://doi.org/10.1037/0022-0663.77.3.313

Seidel, K., & Moritz, J. (2009). Changes in Ethiopia’s Language and Education Policy – Pioneering Reforms: Proceedings of the 16th International Conference of Ethiopian Studies. Available at https://www.gcedclearinghouse.org/sites/default/files/resources/K.%20Seidel%20and%20J.%20Moritz%20-%...

Seraoui, H. (2017). The Effect of Self-efficacy and Need for Achievement in Learning the Speaking Skill in English as a Foreign Language. The Case of Second Year Females and Males Students at the University. Unpublished, 406.

Singh, R., & Gelat, V. K. (2022). Importance and Necessity of Research in Education. 3(9), 894–901. Available at https://ijrpr.com/uploads/V3ISSUE9/IJRPR6996.pdf

Telore, T., & Damtew, A. (2023). Role of the Teacher in Active Learning: EFL Teachers’ Perceptions, Practices and Challenges of Implementation. Celtic: A Journal of Culture, English Language Teaching, Literature and Linguistics, 10(2), 172–193. https://doi.org/10.22219/celtic.v10i2.28096

Tesfaye, Y. (2014). An Investigation of Grade 9 English Language Teachers’ Awareness and Practices of Continuous Assessment in Reading Classes: The Cases of Abdi Bori and Gore High Schools. Jimma University Press. http://10.140.5.162//handle/123456789/381

Usman, M., Idawati, I., & Muhammad, A. F. (2023a). Enhancing Speaking Proficiency through Kampus Mengajar: Empirical Insights from Bosowa University’s English Education Department. ELT Worldwide: Journal of English Language Teaching, 10(2), 471. https://doi.org/10.26858/eltww.v10i2.57867

Usman, M., Idawati, I., & Muhammad, A. F. (2023b). Enhancing Speaking Proficiency through Kampus Mengajar: Empirical Insights from Bosowa University’s English Education Department. ELT Worldwide: Journal of English Language Teaching, 10(2), 471. https://doi.org/10.26858/eltww.v10i2.57867

Wang, T. (2023). An exploratory motivational intervention on the construction of Chinese undergraduates’ ideal LOTE and multilingual selves: The role of near peer role modeling. Language Teaching Research, 27(2), 441–465. https://doi.org/10.1177/1362168820940097

Yuri, N. P., Yendi, F. M., & Ardi, Z. (2020). The Relationship of Peer Social Support with Academic Self Efficacy. Jurnal Neo Konseling, 2(3). https://doi.org/10.24036/00319kons2020