71 Studies in Second Language Learning and Teaching Department of English Studies, Faculty of Pedagogy and Fine Arts, Adam Mickiewicz University, Kalisz SSLLT 13 (1). 2023. 71-100 https://doi.org/10.14746/ssllt.31733 http://pressto.amu.edu.pl/index.php/ssllt The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ affective learning: The mediating role of instructor understanding Ali Derakhshan Golestan University, Gorgan, Iran https://orcid.org/0000-0002-6639-9339 a.derakhshan@gu.ac.ir Lawrence Jun Zhang The University of Auckland, Auckland, New Zealand https://orcid.org/0000-0003-1025-1746 lj.zhang@auckland.ac.nz Kiyana Zhaleh Allameh Tabataba’i University, Tehran, Iran https://orcid.org/0000-0002-0918-5246 k_zhaleh97@atu.ac.ir Abstract Drawing on the rhetorical/relational goal theory, this study examined the role of instructor clarity and non-verbal immediacy in affective learning through the mediation of instructor understanding. Data were gathered through close- ended questionnaires from 756 Chinese and 715 Iranian English as a foreign lan- guage (EFL) students, the factor structure and cross-cultural validity of which were supported via confirmatory factor analysis and testing measurement in- variance, respectively. Path analysis results indicated that clarity and non-verbal immediacy positively predicted instructor understanding and affective learning; instructor understanding positively predicted affective learning; and under- standing was a significant positive mediator in the relationship of non-verbal immediacy and clarity with affective learning. Except for the positive associa- tion of non-verbal immediacy with understanding which was significantly higher Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 72 for the Iranian group, no significant difference was found between the Chi- nese and Iranian groups in all other associations, providing empirical support for the role of EFL teachers’ positive interpersonal communication behaviors in EFL students’ affective learning, irrespective of the cultural context. Keywords: affective learning; cross-cultural comparison; non-verbal immedi- acy; rhetorical/relational goal theory; teacher clarity; teacher understanding 1. Introduction Emotion is one of the factors that can play a role in the process of second/foreign language (FL) learning. FL students might experience numerous positive and neg- ative emotions (Dai & Wang, 2023; Derakhshan, 2022b; Derakhshan, Dewaele, et al., 2022; Derakhshan, Doliński, et al., 2022; Derakhshan, Kruk, et al., 2021a, 2021b; Gao et al., 2020; Kruk et al., 2022; Li et al., 2021; Li & Wei, 2022; Pawlak et al., 2021; Pishghadam et al., 2021; Teo et al., 2022; Wang, 2023; Wang et al., 2021; Wang et al., 2022; Zare et al., 2023). While negative emotions hinder students’ FL learning, willingness to communicate, and willingness to attend English as a for- eign language (EFL) classes (MacIntyre & Gregersen, 2012; Wang & Derakhshan, 2023; Zhang et al., 2022), their positive counterparts increase FL learning enjoy- ment and motivation (Jin & Zhang, 2021; Li, 2020; Li et al., 2020; Zhang & Tsung, 2021). Despite their importance, emotions were regarded for a long time as “the elephants in the room” in FL research (Swain, 2013, p. 195), metaphorically refer- ring to the fact that they were largely ignored or misunderstood for decades (Dewaele, 2010). However, rather recently, the field of second language acquisi- tion (SLA) has experienced an affective turn, attempting to rectify the universal disregard of emotion and its inferior position in cognition (Dewaele & Li, 2021; Prior, 2019). SLA researchers are now endeavoring to study emotions in order not to disregard the elephant anymore (Douglas Fir Group, 2016). Following this timely paradigm shift, there has been an increasing acknowledgment that affec- tive factors are as indispensable – if not more significant – as cognitive factors (Derakhshan & Nazari, 2022; Miller & Godfroid, 2020; Richards, 2020). One im- portant affective variable with direct effects on students’ academic accomplish- ments is affective learning (Bolkan, 2014). Affective learning refers to positive/negative attitudes that students have toward the instructor, content, and behaviors recommended in the course (Kearney et al., 1985). While affective learning is a well-established variable in general education (Myers & Goodboy, 2015), it is completely under-represented in SLA. Thereby, now that “the elephant is no longer invisible” (Dewaele, 2019b, p. 535), it seems incumbent on SLA researchers to have a more holistic look at The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 73 how students affectively respond to FL classes, by exploring not only behavioral and cognitive factors but also students’ affective learning gains (Dewaele, 2019a). Pre- vious studies on affective learning have revealed that it is a by-product of an amal- gam of factors. Although contextual and student-related factors influence affective learning, they are subordinate to perceived teacher positive interpersonal commu- nication behaviors, which foster the creation of a positive classroom climate (De- rakhshan et al., 2022; Derakhshan, Fathi, et al., 2022; Finn & Schrodt, 2012; Gabryś- Barker, 2016). This is because teacher communication behaviors play a major role in conveying affect in language classrooms (Gabryś-Barker, 2018; Gregersen, 2010). This is supported by the tenets of the rhetorical/relational goal theory, which argues for the indispensable role of teacher positive interpersonal communication behav- iors in meeting students’ relational and academic goals and wants including affec- tive learning (Mottet et al., 2006). In this respect, non-verbal immediacy – teacher communication behaviors increasing non-verbal interaction and closeness between the teacher and students (Gregersen, 2005; Mehrabian, 1969) – and clarity – verbal and non-verbal cues employed by a teacher to facilitate understanding and learning of course processes and content (Violanti et al., 2018) – are among the most indis- pensable teacher interpersonal communication instances found to be positively im- pacting students’ learning, in general (Bolkan, 2015; Violanti et al., 2018) and affec- tive learning, in particular (Titsworth et al., 2015; Zhang, 2011). It is also posited that FL learning entails instructors’ interpersonal, cognitive, and emotional understanding of students (King & Ng, 2018). In this regard, by drawing on the rhetorical/relational goal theory, Schrodt and Finn (2011) posited that students’ perceptions of instructors’ understanding of them function as a conceptual mechanism associating teacher communication behaviors with stu- dents’ educational outcomes and attitudes. Consequently, it seems that per- ceived instructor understanding plays a mediating role in the relationship of teacher non-verbal immediacy and teacher clarity with students’ academic atti- tudes including affective learning. While evidence-based studies in education and instructional communication have substantiated these relationships (e.g., Finn & Schrodt, 2012, 2016), there is a dearth of empirical investigations in this respect in FL education. Furthermore, it remains to be seen how the role of clarity and non-verbal immediacy in affective learning through the mediation of teacher un- derstanding converges or diverges across similar or dissimilar cultural contexts. Therefore, to address these gaps, in the current study, we replicate these pre- vious studies on the role of teacher communication behaviors in students’ attitudes through the mediation of perceived understanding (e.g., Finn & Schrodt, 2012, 2016; Schrodt & Finn, 2011) in the EFL context. More specifically, we drew on the tenets of the rhetorical/relational goal theory to investigate the degree to which teacher clarity and non-verbal immediacy, as two instances of teacher communication behaviors, Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 74 influence Chinese and Iranian EFL students’ affective learning through the mediation of perceived understanding. 2. Literature review 2.1. The rhetorical/relational goal theory The present study is theoretically underpinned by the rhetorical/relational goal theory (Mottet et al., 2006) in instructional communication, which presents a practical point of reference for explaining how perceptions of non-verbal imme- diacy and clarity join perceptions of teacher understanding to impact students’ affective learning. Accordingly, when learners’ relational and academic wants are fulfilled through teachers’ employment of a set of appropriate relational and rhe- torical communication cues, students are more engaged, motivated, satisfied, and as a result, achieve and learn more. Thus, successful instruction happens when instructors set rhetorical and relational objectives and employ appropriate inter- personal communication behaviors to achieve those objectives (Houser & Hosek, 2018). The rhetorical/relational goal theory is worthy of attention in FL education because FL education “is inherently relational” (Mercer & Dörnyei, 2020, p. 72). Based on this theory, instructors employ communication behaviors like non-ver- bal immediacy and clarity to accomplish different goals and wants, including in- creasing perceived understanding and communicating learning. While non-verbal immediacy supports relational goals, clarity supports rhetorical goals (Finn & Schrodt, 2012). Thus, like the two wings of a bird, they complement each other to accomplish educational outcomes like affective learning (Derakhshan, 2022a). 2.2. Affective learning As a significant indicator of instructional effectiveness, affective learning in- volves students’ attitudes toward (1) behaviors recommended in the course, (2) course instructor, and (3) course content (Goldman et al., 2014), showing whether students like or dislike what they are learning and appreciate or disap- prove of their teachers (Myers & Goodboy, 2015). Affective learning attitudes are formed when students have such positive feelings as contentment, liking, valuing, and satisfaction (Bolkan, 2015; Goldman et al., 2014). Teachers can pro- mote students’ positive affective experiences by creating a positive learning en- vironment, which increases their willingness to learn and ultimate success in the course (Bolkan & Goodboy, 2015). In the domain of language education research, many studies have investigated students’ positive/negative attitudes toward learning the target language, language teachers, and language teachers’ pedagogical practices The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 75 (e.g., Getie & Popescu, 2020; Tavassoli & Kasraeean, 2014; Ziaee et al., 2021). For instance, research has already examined language learners’ learning atti- tudes and their attitudes towards different types of language teachers (native speakers vs. non-native speakers) (e.g., Ling & Braine, 2007). Inspired by the rhetorical/relational goal theory (Mottet et al., 2006), previ- ous empirical studies have consistently indicated that teachers’ employment of positive teacher interpersonal communication behaviors fosters the creation of a positive classroom climate and through satisfying students’ academic and rela- tional wants, bring about students’ positive/negative attitudes like affective learn- ing (Frymier et al., 2019). In fact, as stated by Bolkan (2015), instructional commu- nication researchers have been mainly concerned with studying the communica- tion-learning interface. Accordingly, as instances of teacher communication behav- iors well established in the domain of instructional communication research, teacher immediacy and clarity have been empirically found to be positively influ- encing students’ affective learning (e.g., Enskat et al., 2017; Frymier et al., 2019; Myers & Goodboy, 2015; Violanti et al., 2018; Zhang, 2011). In this empirical inves- tigation, we replicate these previous studies on the role of teacher clarity and im- mediacy in affective learning in the particular domain of L2 education. 2.3. Teacher clarity Teacher clarity is a high-inference variable referring to students’ perceptions of the teacher’s employment of verbal and non-verbal communication signals to make instruction more transparent and facilitate understanding and learning of course processes and content (Violanti et al., 2018). Such clarity cues include repeating points, using visuals, reviewing and previewing materials, highlighting main ideas, bringing examples, and paraphrasing ideas (Limperos et al., 2015). By using such devices, instructors make information more comprehensible to students and deliver a clearer instruction (Segabutla & Evans, 2019). Thus, teacher clarity is conceived as a process where both learners and teachers shape understanding (Titsworth et al., 2015). Clarity behaviors can reduce learners’ cognitive load and thus ease the learning process (Bolkan, 2015). In FL educa- tion, clarity plays a major role as teachers can employ prosodic modifications when modeling language intonation and pronunciation, for example, to give clearer instructions and create a more understandable message, which facili- tates creating students’ positive affective responses (Gabryś-Barker, 2018). Two theories inform teacher clarity: The first is information processing, which regards teachers as providers of information and learners as processors of information (Violanti et al., 2018). Accordingly, teacher input received by students goes to the short-term memory where some mental operations are performed on Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 76 it, and, the information is prepared for transference to the long-term memory. Teach- ers’ enactment of clarity cues assists in more effective processing, retaining, and re- trieving of information (Titsworth et al., 2015). The second theory is adaptive in- struction, propounding that teachers are required to constantly adjust their teach- ing practice while imparting information to learners (Titsworth et al., 2010). Studies on clarity have been mainly concerned with exploring its associative or causal link to students’ cognitive and affective learning. The results pertaining to affective learning have been constantly positive: increased teacher clarity is related to in- creased affect toward the behaviors in the course, teacher, and course content (i.e., affective learning) (e.g., Comadena et al., 2007; Titsworth et al., 2015; Zhang, 2011). 2.4. Non-verbal immediacy Another teacher communication factor under investigation in this study is non- verbal immediacy. As a type of teacher non-verbal affective signal (Gabryś-Barker, 2018), it refers to those teacher communication behaviors increasing non-verbal interaction and closeness between the teacher and students (Frymier et al., 2019; Mehrabian, 1969) and mitigate their psychological and physical distance (Gregersen, 2010). According to the rhetorical/relational goal theory, teacher immediacy can satisfy students’ academic and relational needs (Frymier et al., 2019). Non-verbal immediacy cues include leaning forward, relaxed body posture, movements, smil- ing, eye contact, appropriate touching, and nodding (Derakhshan, 2021; Gregersen, 2006). Gregerson (2010) has posited that the employment of such non-verbal im- mediacy cues is effective for developing teacher-student relations and positive at- titudes in FL classrooms. Non-verbal immediacy is operationalized as high infer- ence perception, acting as an affective arousal cue, potentially influencing stu- dents’ psychological reactions (Frymier et al., 2019). Immediacy behaviors can also encourage efficient teaching and positive attitudes toward instruction (Gab- ryś-Barker, 2018). Such immediacy behaviors increase positive interpersonal teacher- student relationships, promoting learners to learn more efficiently and achieve better academic gains (Gkonou & Mercer, 2018; Gregersen, 2005). Numerous stud- ies have confirmed the positive link between immediacy and students’ affective learning (e.g., Enskat et al., 2017; Frymier et al., 2019; Violanti et al., 2018). Based on the rhetorical/relational goal theory (Mottet et al., 2006), re- searchers have provided evidence mainly in support of the main effects of clarity and non-verbal immediacy on students’ learning goals. Moreover, some other researchers have found their interaction effects (Kelly & Gaytan, 2019) by draw- ing on the additivity hypothesis (Comadena et al., 2007), which posits that “the positive main effects of immediacy and clarity will combine to create an ideal learning situation for students” (Titsworth et al., 2015, p. 391). Thus, instructor The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 77 non-verbal immediacy complements clarity to increase affective learning (Vio- lanti et al., 2018; Zhang, 2011). In this research conducted in the EFL contexts of China and Iran and foregrounded in the rhetorical/relational goal theory (Mottet et al., 2006), we replicated previous communication studies which examined the interaction effects of clarity and immediacy on students’ affective learning by considering the mediating role of perceived understanding. Perceived under- standing was added to this relationship based on previous conceptualizations of Finn and Schrodt (2012, 2016) and Schrodt and Finn (2011) about the mediating role of teacher perceived understanding in the linkage of teacher communica- tion behaviors and student attitudes. 2.5. Instructor perceived understanding According to Schrodt and Finn (2011), based on the rhetorical/relational goal the- ory, a potential way of accomplishing relational and rhetorical goals is teachers’ em- ployment of (non)verbal behaviors, such as clarity and non-verbal immediacy, which communicate to learners whether they are understood by the teacher or not. Perceived understanding refers to a person’s evaluation of his/her failure or success in effective communication with others. To communicate understanding, teachers can explicitly mention that they understand learners, employ follow-up inquiries, summarize the information that students provide, and approve emotions accom- panying learners’ messages. Through these communication behaviors, learners per- ceive being understood by their instructors (Finn & Schrodt, 2012). By drawing on the rhetorical/relational goal theory (Mottet et al., 2006), Schrodt and Finn (2011) conceptualized that students’ perceptions of instructor understanding function as a conceptual mechanism associating teacher communication behaviors like clarity and non-verbal immediacy with students’ educational outcomes and atti- tudes like affective learning. This conceptualization was empirically substantiated by Finn and Schrodt (2012, 2016) in later evidence-based studies. Consequently, it seems that instructor understanding plays a mediating role in the linkages of teacher non- verbal immediacy, teacher clarity, and students’ affective learning. In the FL education context, Gabryś-Barker (2018) asserted that when teachers employ verbal and non- verbal affective communication behaviors to facilitate understanding and comprehen- sion of messages, more positive students’ attitudes toward the learning process (i.e., affective learning) happen. That is, teachers who impart class lectures, assignments, and objectives through employing both non-verbal immediacy and verbal clarity sig- nals may be more capable of employing behaviors enhancing understanding, which can ultimately promote students’ positive attitudes toward the course instructor, be- haviors, and content (Schrodt & Finn, 2011). In the present study, we sought to inves- tigate this relationship in Chinese and Iranian FL education contexts. Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 78 2.6. Culture-centered instructional communication research McCroskey and McCroskey (2006) recommended that researchers worldwide par- ticipate in culture-centered instructional communication studies and extend com- munication research originated in the West to other less investigated non-Western cultures. Thus, the justification for undertaking this cross-cultural study is McCros- key and McCroskey’s (2006) claim that an “overwhelming proportion of instruc- tional communication research has been conducted by researchers representing the Anglo culture of the United States and has involved participants who were also representing the predominant culture” (p. 42). Therefore, there is a need to identify “the extent to which effective teaching practices found in the United States trans- late to classrooms from other cultures” (Goldman et al., 2014, p. 46). In addressing this call, the association of teacher clarity and immediacy in re- lation to affective learning in Chinese classrooms has been tested in some stud- ies. In line with previous findings in the US classrooms, Zhang and Zhang (2005), and Zhang (2011) found a significant positive association between clarity, imme- diacy, and affective learning in the Chinese culture. This finding supported the assumption that clear instruction seems to influence students’ affect toward the course content and teacher, disregarding culture. Similarly, in a cross-cultural study of Japanese, German, Chinese, and United States classrooms, Zhang and Huang (2008) investigated the influence of clarity on student learning. The re- sults revealed the mediating role of motivation and affective learning in the re- lationship of clarity with cognitive learning. They noted that there is a need for more cross-cultural studies to accurately identify the influence of instructor communication behaviors on learning gains across cultures. In the present study, we explored the influence of teacher communication behaviors on affective learning in China and Iran to extend the originally West- ern line of communication research into our non-Western educational contexts. As two cases of Asian nations, China and Iran might be culturally similar in some respects. However, they are distinct regarding some cultural norms and values according to Hofstede’s (2001) 6-D model depicted in Figure 1. Figure 1 Cross-cultural comparison of China (in blue) and Iran (in purple) on Hofstede’s (2001) 6-D model (https://www.hofstede-insights.com/product/compare-countries/) The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 79 According to Figure 1, the scores of both nations on individualism are below 50, showing that both are collectivist cultures, which typically include people who care about solidarity and group membership as well as the well-being of others, try to develop interdependent identities, and care about maintaining good interper- sonal relationships. The scores on power distance for both countries are above the cut-off point of 50, with the Chinese country being outstandingly more hierarchical. On the other hand, while China is a more masculine nation, Iran is more feminine where people deem solidarity and equity in social, work-related, and personal as- pects of life important. Regarding uncertainty avoidance, Chinese people are more flexible in the face of dynamic and unpredictable situations while Iranian people, with a score of 59, tend to favor fixed and static circumstances and environments. Moreover, compared to Chinese people, Iranians tend to be more indulgent, which is also in line with the scores of both countries on long-term orientation. Accord- ingly, while Iranians are remarkably focused on fulfilling immediate goals in life, Chi- nese people are highly perseverant and focused on reaching long-term goals. Altogether, based on the similarities and differences delineated between Chinese and Iranian cultures, in the present study, we set out to determine if their cultural divergences and convergences could bring about differences in their perceptions of the role of teacher clarity and non-vernal immediacy in their affective learning when mediated through perceived teacher understanding. Ac- cordingly, the following research questions were formulated: 1. Do Chinese and Iranian EFL students’ perceptions of instructor under- standing mediate the effects of teacher clarity and nonverbal immediacy on their affective learning? 2. Are there any significant differences between Chinese and Iranian EFL groups regarding the relationship between teacher clarity, non-verbal immediacy, instructor understanding, and affective learning? 3. Methodology 3.1. Participants A total number of 1,471 (756 Chinese and 715 Iranians) participants were tar- geted to participate in this study. After the initial screening (i.e., checking for missing data, constant patterns within each scale, standard deviation, and in- creasing/decreasing patterns within each scale), the problematic data were ex- cluded, which resulted in a finalized sample of 1,190 (584 Chinese and 606 Ira- nian) respondents. To maximize variation within the sample with the likelihood of enhancing sample-to-population generalizability of findings (Miles et al., 2014), Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 80 the participants were intentionally chosen from different genders, levels of ed- ucation (i.e., BA, MA, PhD, or post-doctoral), age groups (detailed demographic information is presented in Table 1), and English-related majors (i.e., teaching Eng- lish as a second/foreign language, English translation, applied linguistics, English language and literature, philology, and TESOL). Table 1 Demographic information of the participants Chinese Iranian Age 17-19 116 80 20-24 268 419 25-29 17 52 30-more 183 55 Gender Male 115 155 Female 459 436 Others 2 2 Not mentioned 8 13 Academic degree BA 423 446 MA 93 111 PhD 57 47 PD 11 2 3.2. Instruments 3.2.1. Teacher Clarity Short Inventory (TCSI) This scale was designed and validated by Chesebro and McCroskey (1998) in the American higher education context. It includes 10 items which assess teacher clarity from the perspective of students (e.g., “My teacher is explicit in her or his instruction” or “My teacher’s answers to student questions are unclear”). Students’ responses could range on a five-point Likert scale, ranging from (1) “strongly disagree” to (5) “strongly agree.” Reverse scoring was applied for items 2, 4, 7, and 9. Reliability and construct validity of this scale were supported by previous studies (Chesebro & McCros- key, 1998; Finn & Schrodt, 2012). A composite reliability of .81 was reported for the scale in the present study. Furthermore, construct validity (see Figure 2) and discrimi- nant validity (see Table 3) of the scale were confirmed in this study as well. 3.2.2. Non-verbal Immediacy Scale (NIS) This scale, originally developed by Richmond et al. (1987) in the American higher edu- cation context, includes 14 Likert-scale items assessing teachers’ non-verbal immediacy The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 81 behaviors from students’ perspectives (e.g., “My teacher gestures while talking to class” or “My teacher uses a variety of vocal expressions while talking to the class”). The responses to the items could range from (0) “never” to (4) “very often.” In their study, after removing items 1 and 9 due to low factor loading, Derakhshan, Eslami, et al. (2022) confirmed the construct validity of the scale in the Iranian university EFL context. In the present study, another item (i.e., item 27: “My teacher touches stu- dents in the class”) was omitted because of the socio-cultural values of the population in this research. Thus, in the present study, the nonverbal immediacy scale, with 11 items, was used. Reverse scoring was applied for the non-immediate items (i.e., items 2, 5, 7, and 8). Acceptable reliability (α = .70 or higher) was reported for the scale by previous studies (Derakhshan, Eslami, et al., 2022; Richmond et al., 1987). In the cur- rent study, a composite reliability of .72 was reported for the scale, and its construct validity (see Figure 2) and discriminant validity (see Table 3) were confirmed. 3.2.3. Student Perceptions of Instructor Understanding Scale (SPIUS) This scale was developed and validated by Schrodt and Finn (2011) in the American higher education context. It includes 15 items measuring students’ perceptions of instructor understanding (PIU) (e.g., “My teacher’s tone of voice indicates under- standing” or “My teacher makes follow-up comments which reflect understand- ing”), and 15 items measuring students’ perceptions of instructor misunderstand- ing (PIM) (e.g., “My teacher fails to maintain direct eye contact with me” or “My teacher answers my questions incorrectly”). The responses to the items could vary from (1) “never” to (5) “very often.” The reliability as well as discriminant and con- current validity of the scale were confirmed by previous studies (Finn & Schrodt, 2012; Schrodt & Finn, 2011). It should be noted that multicollinearity is one of the primary assumptions of multiple regression, which happens when any predictor variable of a regression model is highly associated with other predictor variables (r = .90 or higher). It is assumed that as multicollinearity extremely decreases the pre- dictive power of predictor variables of a regression model, it should not be present (Plonsky & Ghanbar, 2018). In the present study, through employing squared mul- tiple correlations, multicollinearity was detected between PIM and TCSI (r = -0.798). Therefore, the 15 items pertaining to PIM were omitted from the SPIUS scale. In the current study, a composite reliability of .91 was reported for the scale, and its con- struct validity (see Figure 2) and discriminant validity (see Table 3) were confirmed. 3.2.4. Affective Learning Scale (ALS) This scale was developed by Kearney et al. (1985), in order to measure students’ attitudes toward behaviors recommended in the course (ABRC), attitudes toward Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 82 course content (ACC), and attitudes toward course instructor (ACI) through eight seven-point bipolar adjective subscales (i.e., worthless-valuable, positive-negative, good-bad, fair-unfair, likely-unlikely, possible-impossible, probable-improbable, and would-would not). Previous studies have confirmed the strong reliability and con- struct validity of the scale (Hsu, 2012; Kearney et al., 1985). Similarly, a composite reliability of .97 was reported for the scale in the present study, and its construct validity (see Figure 2) and discriminant validity (see Table 3) were confirmed. 3.3. Procedure To follow the ethical standards in doing educational research, the participants signed a consent letter, showing that they voluntarily participated in the study and were informed of their rights as participants. The researchers took neces- sary actions to protect the participants’ identities and ensure data confidential- ity. As data collection happened during the COVID-19 pandemic, in line with the COVID-19 Safety and Health Compliance Protocol, all the data were collected online. All four scales were prepared through Google Forms and KwikSurveys for Iranian and Chinese participants, respectively. The links to the scales were dis- tributed among the participants through email or WhatsApp. Answering the scales required participants at most 30 minutes. At the time of data collection, all the participants were enrolled in EFL clas- ses. The participants were instructed to consistently complete the teacher clarity, non-verbal immediacy, and perceived understanding scales by thinking only of the instructor they had at the time of data collection for their EFL class. Data collection lasted for two months (i.e., from January 2021 to February 2021). In fact, data were collected at the end of the semester so that students could become ac- quainted with their EFL teachers before making an accurate report of their teach- ers’ communication behaviors. Moreover, the scales were presented in English since all the participants were university students of different EFL-related majors who were participating in both EFL classes (i.e., receiving English instruction) and content classes in English (i.e., English as a medium of instruction, EMI). Thus, they were regarded to be able to understand and respond to the scales in English. 3.4. Data analyses For analyzing the data, AMOS (Version 24) was run. Before conducting the main statistical analyses, the researchers took into account some pre-processes (i.e., checking for missing data, constant patterns within each scale, standard devia- tion, and increasing/decreasing patterns within each scale) to exclude the prob- lematic data. Confirmatory factor analysis (CFA) with the maximum likelihood The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 83 method was performed to validate the factor structure of the four scales in the uni- versity EFL context. Furthermore, to check measurement invariance (i.e., configural, metric, and scalar invariance), being essential when making meaningful compari- sons of the hypothesized models between two groups (Meredith, 1993), multiple group CFA was conducted. According to Hu and Bentler’s (1999) recommendation, the fit indices of Chi-square (CMIN), degrees of freedom (DF), minimum discrepancy per degree of freedom (CMIN/df), the root mean square error of approximation (RMSEA), root mean squared residual (SRMR), parsimony-adjusted normed fit in- dex (PNFI), goodness-of-fit index (GFI), the comparative fit index (CFI), and incre- mental fit index (IFI) were checked. The composite reliability and discriminant va- lidity for each factor was checked. Subsequently, regression imputation, descriptive statistics, multiple correlations, and path analysis were done on the data. 4. Results 4.1. Pre-processing of the data Before starting the analysis, data went through some pre-processes to exclude the problematic data. As mentioned above, 1,471 solid answers (756 by Chinese and 715 by Iranians) were recorded. After the initial screening, no more than 5% missing answers were inspected for each respondent. The missing values were replaced with the median of the two nearby answers for the questionnaires as they made less than one percent of the values in each variable. Then, the data were inspected for constant patterns within each scale. This resulted in the ex- clusion of 97 cases from the Chinese and 58 cases from the Iranian respondents’ answers. Next, the standard deviation for each participant’s answers to each of the questionnaires was calculated, and those answers with a standard deviation below 0.3 in each scale were excluded as they were considered unengaged re- spondents (75 Chinese and 51 Iranian). Finally, the answers were inspected for increasing/decreasing patterns within each scale. No such cases were found in the remaining answers. Therefore, the remaining 1,190 (584 Chinese and 606 Iranian) respondents’ answers were used to answer the research questions. Regarding the adequacy of the sample for path analysis (SEM), various rules-of-thumb have been proposed: Boomsma (1982) recommended the use of at least 150 observations; Bentler and Chou (1987) set the rule of 5 to 10 observations per estimated parameter; Kline (2016) recommended 20 observa- tions per estimated parameter, and Nunnally (1967) proposed 10 cases per var- iable. Considering the number of variables and parameters in our study, based on the above-mentioned recommendations, a sample from 150 to 750 was re- quired. Having 1190 observations, the sample seemed large enough. Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 84 4.2. Confirmatory factor analysis To validate the scales in this study, CFA with the maximum likelihood method was performed using IBM AMOS. Initially, we opted for running first-order CFA with all components of the constructs included. However, the results of HTMT showed that the three components of the ALS are nearly indistinguishable as the correlations between ABRC on the one hand, and ACC and ACI, on the other hand, were above 0.9. Therefore, second-order CFA was run. To make sure of the convergent validity, two measures were tested. First, items with non-signif- icant loadings in unstandardized estimation were excluded. Then, items with standardized loadings estimates below 0.5 were omitted. Moreover, two items (S02 from PIU and T01 from TCSI) were removed to improve convergent validity. Figure 2 shows the results of the analysis with standardized estimates. For de- tailed values of both standardized and unstandardized estimations in the initial CFA model (see Supplementary Materials). Then, the modifications suggested by software with the threshold of 10 were considered, and those with no con- flict with the literature and positive par change in the model were applied. Figure 2 The CFA model (NIS: Nonverbal-Immediacy Scale; TCSI: Teacher Clarity Short Inventory; PIU: Perceived instructor understanding; ABRC: Attitudes to- ward behavior recommended in the course; ALS: Affective Learning Scale; ACI: Attitudes towards course instructor; ACC: Attitude toward course content) The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 85 4.3. Checking the model-to-data fit After applying the modifications, the model’s goodness of fit was examined. Ac- cording to Hu and Bentler (1999), for the model to have a goodness of fit, a number of criteria have to be met. These criteria, alongside the values obtained from the data, are reported in Table 2. Table 2 Evaluation of the CFA goodness of fit Criteria Observed values Threshold Evaluation Chinese Iranian Overall CMIN 1908.139 1874.768 3025.002 Df 645 645 645 CMIN/df 2.958 2.907 4.690 between 3 and 5 Acceptable RMSEA .059 .056 .056 < .06 Excellent SRMR .055 .049 .046 <.08 Excellent PNFI .746 .755 .770 > .5 Excellent GFI .847 .843 .875 > .85 Excellent CFI .901 .908 .907 > .9 Acceptable IFI .902 .902 .907 > .9 Acceptable The above results show that the model fits our context. Moreover, the difference in RMSEA (0.003) and CFI (0.007) of the two groups were very low, indicating configural invariance. To further make sure of the invariance, mul- tigroup comparison was made. The results showed that the constrained (χ2 (1386) = 6419) and unconstrained (χ2 (1431) = 6453.1) models were not signifi- cantly different (Δχ2 = 34.1, p = 0.693), showing that the identical constructs of the four scales used in this study are confirmed in both Chinese and Iranian data. The composite reliability and discriminant validity for each factor are re- ported in Table 3. As reported, all of the variables had values above 0.7, which shows acceptable reliability. Moreover, the square root of AVE (the bold values in the table) was above inter-correlations of the factors, indicating discriminant validity according to Fornell and Larcker (1981). Table 3 Composite reliability and discriminant validity of the factors CR Fornell Larcker criterion NIS TCSI PIU ALS NIS 0.721 0.615 TCSI 0.812 0.217 0.657 PIU 0.911 0.588 0.541 0.680 ALS 0.979 0.408 0.582 0.643 0.969 Note. NIS: Nonverbal-Immediacy Scale; TCSI: Teacher Clarity Inventory; PIU: Perceived Instructor Un- derstanding; ALS: Affective Learning Scale Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 86 4.4. Descriptive statistics and correlation After making sure of the validity and reliability of the factors in the constructs, they were imputed using regression imputation. Data imputation gives an ag- gregated mean for each factor, and its advantage over the simple calculation of average is that the share of each item and error in the construct is built in the computation. The descriptive statistics of each factor and the correlation matrix is presented in Table 4. Table 4 Descriptive statistics and correlation matrix Mean SD NIS TCSI PIU ALS NIS Chinese 2.6869 .51505 1.000 Iranian 2.5469 .49263 1.000 Total 2.6156 .50839 1.000 TCSI Chinese 4.0253 .72500 .250** 1.000 Iranian 3.9809 .78436 .309** 1.000 Total 4.0027 .75582 .281** 1.000 PIU Chinese 3.9127 .55309 .664** .592** 1.000 Iranian 3.8351 .57323 .702** .609** 1.000 Total 2.6782 .39727 .689** .600** 1.000 ALS Chinese 5.4042 .90243 .466** .624** .664** 1.000 Iranian 5.2296 .95056 .492** .656** .703** 1.000 Total 5.3153 .93097 .485** .641** .688** 1.000 Note. ** Correlation is significant at the 0.01 level (2-tailed); Correlations indicate effect sizes via their absolute values (Cohen, 1992); NIS: Nonverbal-Immediacy Scale; TCSI: Teacher Clarity Inventory; PIU: Perceived Instructor Understanding; ALS: Affective Learning Scale As reported in Table 4, all factors in the model were significantly inter-re- lated (p < .01). The relationship between one of the independent variables, clarity, and the dependent variable, affective learning, was relatively high (r = .64), while non-verbal immediacy and affective learning showed a moderate relationship (r = .49). The mediating variable, PIU, had relatively high correlations with both inde- pendent variables of non-verbal immediacy (r = .69) and clarity (r = .60), and the dependent variable (r = .69). The inter-correlations of the items were very close for both contexts. Although few high correlations (above 0.7) were observed, they were both minor and not endangering the discriminant validity as already con- firmed by Forenell and Larckers’ (1981) criterion (see Table 2). 4.5. Path analysis results To answer the first research question, initially, a path analysis was done. Figure 3 depicts the results of the direct effects. The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 87 Figure 3 The measurement model (NIS: Nonverbal-Immediacy Scale; TCSI: Teacher Clarity Inventory; PIU: Perceived instructor understanding; ABRC: Atti- tudes toward behavior recommended in the course; ALS: Affective Learning Scale; ACI: Attitudes towards course instructor; ACC: Attitude toward course content) The model fit results showed excellent indices (CMIN/df = 20.738/ 12 = 1.728, RMSEA = 0.025, SRMR = 0.004, CFI = 0.999, GFI = 0.994; TLI = 0.998). The multi-group analysis also indicated invariance across the two groups (uncon- strained χ2 (12) = 20.738; constrained χ2 (14) = 24.873, p = 0.17). The results of the direct path analysis are reported in Table 5. Table 5 Direct effects Direct path Group Regression weight S.E. C.R. P Β Difference (Z-score) PIU <--- NIS Chinese .591 .028 21.302 .000 .550 -1.999**Iranian .672 .029 22.876 .000 .568 Total .636 .020 31.706 .000 .564 PIU <--- TCSI Chinese .347 .020 17.603 .000 .455 0.926Iranian .322 .018 17.456 .000 .433 Total .334 .014 24.767 .000 .441 ALS <--- NIS Chinese .257 .071 3.621 .000 .144 0.852Iranian .168 .076 2.222 .026 .086 Total .217 .052 4.199 .000 .117 ALS <--- TCSI Chinese .485 .047 10.359 .000 .383 0.427Iranian .458 .043 10.694 .000 .373 Total .469 .032 14.862 .000 .375 ALS <--- PIU Chinese .550 .079 6.927 .000 .331 1.072Iranian .668 .077 8.693 .000 .405 Total .614 .055 11.162 .000 .372 Note. ** Difference is significant at α = 0.01; NIS: Nonverbal-Immediacy Scale; TCSI: Teacher Clarity Inventory; PIU: Perceived Instructor Understanding; ALS: Affective Learning Scale As evident in Table 5, all of the paths showed significant results for both groups. The lowest relationship was between non-verbal immediacy and affec- tive learning, while the highest one existed between non-verbal immediacy and PIU. The indirect effects are presented in Table 6. Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 88 Table 6 Indirect effects Indirect path Group Regression weight Lower Upper P Β NIS --> PIU --> ALS Chinese .325 .244 .428 .000 .182** Iranian .449 .338 .575 .001 .230** Total .391 .321 .473 .001 .210** TCSI --> PIU --> ALS Chinese .191 .143 .249 .001 .151** Iranian .215 .164 .272 .001 .175** Total .205 .169 .243 .001 .164** Note. ** Significant at α = 0.01; NIS: Nonverbal-Immediacy Scale; TCSI: Teacher Clarity Inventory; PIU: Perceived instructor understanding; ALS: Affective Learning Scale As reported in Table 6, both indirect paths were significant, and PIU worked as a significant mediator for both non-verbal immediacy and clarity in relation to affective learning. Moreover, in response to the second research question, it should be noted that the positive relationship between non-verbal immediacy and PIU was significantly higher for the Iranian group. In all other cases, no signif- icant difference was found between the two groups. 5. Discussion Following the recent call for the need to immediately attend to teacher positive interpersonal communication behaviors in FL education (Xie & Derakhshan, 2021), in this replication study, by drawing on the rhetorical/relational goal the- ory in communication research (Mottet et al., 2006), we engaged in a cross-cul- tural comparison of the effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ affective learning through the mediation of instructor understanding. Initially, before responding to the research questions, we examined the factor structure and reliability of the TCSI, NIS, SPIUS, and ALS. Although validity and reliability of these scales were confirmed by previous researchers (Finn & Schrodt, 2012; Hsu, 2012; Richmond et al., 1987; Schrodt & Finn, 2011), all of them were originally developed in the American educational context, meaning that in order to use them across other contexts, their validity and reliability in- dices needed to be reexamined. Besides, none of them was originally developed in FL education. In this study, the results of CFA, composite reliability, and discri- minant validity analyses confirmed that the four scales enjoyed good psycho- metric properties in Chinese and Iranian EFL contexts. With regard to the first research question, the results of the direct effects in the measurement model of the path analysis indicated that both teacher clarity and non-verbal immediacy positively, significantly predicted instructor under- standing as well as affective learning, and instructor understanding positively, The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 89 significantly predicted affective learning. These results provide support for the theoretical and empirical backgrounds of the study. First, these results empiri- cally support the rhetorical/relational goal theory positing that when students’ academic and relational needs are satisfied by instructors’ employment of pos- itive rhetorical and relational resources (e.g., teacher immediacy, clarity, and un- derstanding), students will attain more desirable educational outcomes and at- titudes (e.g., affective learning) (Houser & Hosek, 2018). Furthermore, the pos- itive predictability of affective learning through clarity in this study was in line with previous empirical findings (Comadena et al., 2007; Titsworth et al., 2015; Zhang, 2011). Similarly, the positive influence of non-verbal immediacy on af- fective learning was in concomitance with the extant literature (Enskat et al., 2017; Frymier et al., 2019; Violanti et al., 2018). The positive causal role of clarity and immediacy in understanding, on the one hand, and the positive predictive role of understanding in affective learning, on the other hand, supports Mercer and Dörnyei’s (2020) argument regarding the importance of teacher positive interpersonal behaviors toward students in the FL learning and teaching context because of its inherently relational nature. This finding is also in line with the Derakhshan’s (2022a) statement that attain- ment of FL learning gains in EFL classes requires successful teacher-student in- terpersonal relationships and interactions, facilitated through FL instructors’ emotional and interpersonal understanding of students. The results of the indirect effects in the path analysis model illuminated that instructor understanding was a significant positive mediator in the relation- ship of non-verbal immediacy and clarity with affective learning. Schrodt and Finn (2011) proposed a conceptual model of the role of positive teacher inter- personal communication behaviors like clarity and non-verbal immediacy in stu- dents’ educational outcomes and attitudes through the mediation of perceived instructor understanding, and previous studies found evidence-based support for this relationship in communication education (Finn & Schrodt, 2012, 2016). As the results of the present study revealed, we also substantiated the credibil- ity of this model in FL education. Concerning the second research question, it was found that, except for the positive association of non-verbal immediacy with instructor understanding which was significantly higher for the Iranian group, no significant difference was found between the two groups in all other cases. This finding addressed McCroskey and McCroskey’s (2006) and Derakhshan’s (2022a) call for increasing engagement in culture-centered instructional communication research as in this study we extended this line of research to the Chinese and Iranian EFL contexts. The insignificance of the differences in the relationships among the variables in both cultures supported previous researchers’ (Zhang, 2011; Zhang & Huang, Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 90 2008; Zhang & Zhang, 2005) assertion that positive teacher interpersonal com- munication behaviors seem to increase students’ affective learning, disregard- ing the cultural context. This result is justifiable by considering the fact that due to the unique nature of FL education, where a good interpersonal relationship between the teacher and students is a key to successful language instruction and learning (Mercer & Gkonou, 2020), teachers’ interpersonally good and ef- fective treatment of students is important to FL teachers and students in any cultural context. How well instructors and learners make harmonious and friendly relationships can determine learners’ learning experiences (Mercer & Dörnyei, 2020). Thus, as the results of the present study showed, when teachers employ more positive interpersonal communication behaviors, students’ affective learning will be similarly facilitated in both Chinese and Iranian EFL classes. These results can be also justified by considering the remarkably collectivist nature of both Chinese and Iranian societies as presented in Hofstede’s (2001) model (see Figure 1). Tending to be more collectivist, people within both societies typically regard maintaining interpersonal relationships important, deem group member- ship significant, and highly value the well-being and comfort of others. Thus, it is justifiable that Chinese and Iranian EFL teachers care about satisfying their stu- dents’ academic and relational wants through employing positive interpersonal communication behaviors, resulting in more understanding between them and students, which in turn, increases students’ affective learning. 6. Conclusion This study highlights that communication behaviors have fruitful implications for both FL research and instruction. Thus, FL researchers are urged to give verbal and non-verbal channels of communication a place of prominence in their research agendas, and similarly, FL instructors are suggested to integrate them into their classroom practices. FL instructors are recommended to increase their verbal clarity by taking such actions as planning and organizing instructional materials before teaching them, presenting a transparent preview of what learners will learn, review- ing what learners have learned, presenting transparent directions of learners’ learn- ing attitudes, employing illustrations and visuals as well as using intentional expla- nations and examples to enhance or supplement ideas. It is also advocated that teachers show adaptability and flexibility concerning instructional messages by, for example, evaluating content and changing behaviors during a lesson or simultane- ously employing several clarity behaviors, which ensures the highest clarity level for students. In the same vein, as non-verbal immediacy was found a significant predic- tor of students’ affective learning, it is beneficial for FL instructors to be trained to employ subtle non-verbal immediacy behaviors such as nodding, eye contact, The effects of instructor clarity and non-verbal immediacy on Chinese and Iranian EFL students’ . . . 91 appropriate touching, open body positions and gestures, and smiling. It is also in- cumbent on FL teacher educators to hold ongoing teacher professional develop- ment programs, where pre- and in-service FL teachers can learn about clarity and non-verbal immediacy for increasing students’ affect toward the course elements. Teacher educators can provide teacher trainees with practical strategies for increas- ing teacher-student immediacy and teacher verbal clarity so that they can facilitate teachers’ understanding of students and create more engaging and fulfilling learn- ing environments for students. Moreover, the results of this cross-cultural study can provide significant insights to its readers as they become aware of whether imme- diacy, clarity, and perceived understanding predict EFL students’ affective learning similarly or dissimilarly in Chinese and Iranian cultural contexts. Nevertheless, the study is not without its limitations. First, the findings may be influenced to some extent by halo effects, as students who like their teachers may be more prone to feel understood by them and perceive them as being non-verbally immediate and clear. Moreover, EFL students from two coun- tries were targeted as the sample for checking the factor structure and meas- urement invariance of the scales. Future research gathering data from other cul- tures would be beneficial for confirming the cross-cultural validity of these scales in EFL education. The present study employed a quantitative approach to investigate the relationships between its variables and answer its research ques- tions by collecting numerical data from a rather large sample. Future research- ers can employ mixed methods research and purely qualitative approaches as they potentially allow researchers to collect textual or auditory data from par- ticipants in order to answer “what,” “how,” “in what ways,” or “to what extent” research questions and consequently reach a more in-depth understanding of these relationships. Future studies can also study the impacts of particular ped- agogical interventions, delivered by teacher educators well-versed in instruc- tional communication research, to see if such interventions can enhance teach- ers’ employment of clarity and non-verbal immediacy. The present study fo- cused only on immediacy and clarity behaviors. Future studies should examine additional teacher communication cues like teacher confirmation, care, class- room justice, support, and humor as potential contributors to FL students’ af- fective learning. Lastly, the findings of this replication study lent further empiri- cal support to an explanatory mechanism (i.e., teacher understanding) that as- sociates teacher verbal clarity and non-verbal immediacy perceptions to lan- guage students’ affective learning. Future studies can extend these attempts by investigating teacher understanding as a potential mediator of other educa- tional outcomes in the FL classroom, such as willingness to attend classes/com- municate, engagement, attainment, or success. Ali Derakhshan, Lawrence Jun Zhang, Kiyana Zhaleh 92 Acknowledgments This work was supported by Golestan University under Grant Number 1459. The authors wish to thank Golestan University for its support. 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