TESL

Examining Teacher Competencies in Content and Language Integrated Learning: Professional Profiles and Ways Forward

EFL Studies/Southeast Asia/TESL/V14N2

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Hengzhi Hu

Universiti Kebangsaan Malaysia. ORCID: 0000-0001-5232-913X. Email: p108937@siswa.ukm.edu.my

Rupkatha Journal, Vol. 14, Issue 2, April-June, 2022, Pages https://doi.org/10.21659/rupkatha.v14n2.26

First published: June 27, 2022 | Area: EFL Studies | License: CC BY-NC 4.0

(This article is published under Volume 14, Number 2, 2022)
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Abstract

Despite the upsurge of research interest in Content and Language Integrated Learning (CLIL) teachers’ professional competencies, very little evidence has been presented from the Chinese academia. To bridge this gap and understand Chinese CLIL teachers’ status quo of competencies in relation to their demographic characteristics, the present study adopted a cross-sectional quantitative survey approach and investigated the differences of linguistic competence, content competence, pedagogic competence, CLIL fundamentals, interpersonal and collaborative competence, and reflective and developmental competence in a sample of 205 CLIL teachers from Chinese higher education providers. They had dissimilar genders, language expertise, content subject specialisation, affiliations, academic degrees, educational backgrounds, years of teaching CLIL and professional titles. Inferential analyses of the data obtained from a questionnaire indicated a high heterogeneity in the sample, allowing of the description of CLIL teachers’ profiles of professional competences in accordance with their demographic factors. It is concluded that professional training and ongoing research into CLIL teachers’ needs are essential to achieve the homogeneity of competencies and that a supportive network should be established to encourage active partnership amongst CLIL teachers and educational institutions.

Keywords: CLIL, teacher competencies, professional identities, professional development.

Introduction

Since the introduction of Content and Language Integrated Learning (CLIL) in the 1990s, this dual-focused pedagogical approach characterised by using an additional language other than learners’ mother tongue or shared language as the medium of instruction for both content and language learning has stimulated considerable research interest in various educational contexts. Although the level of emphasis placed on content learning and language learning differs from case to case due to the variation in educational policies and contextual needs (Dale & Tanner, 2012), it has been commonly acknowledged that CLIL has dual learning objectives of a discipline subject and a foreign language (L2), the dynamic amalgam of which can benefit learners both cognitively and motivationally (Coyle et al., 2010).

In Mainland China (hereafter referred to as China), CLIL has been pushed forward since its first domestic application about two decades ago (Lv, 2001), though some scholars maintain that it has already been implemented in the late 1990s in the English-Medium Instruction programmes organised for young learners in developed cities (Wei & Feng, 2015). However, with the upsurge of research and development activities on CLIL application and practices in the western world, there is a dearth of empirical studies in China (Liu, 2019a; Mi, 2015), providing little evidence concerning the feasibility of this educational approach and making it a rare phenomenon for teachers to switch from a conventional L2 teaching approach to CLIL (Liu, 2020).

Against this general backdrop, the present study attempts to contribute to the understanding of CLIL in China by offering practical insights and suggestions out of empirical evidence gathered from real people in contemporary real-life institutions and settings. The pertinent research agenda is quite extensive, while the study brings attention to investigating the competencies of in-service CLIL teachers working in Chinese higher education providers (HEPs), which have witnessed most of the CLIL implementations in China’s educational context (Hu, 2021). CLIL competences refer to the necessary professional skills that a teacher is expected to possess “to teach content subjects and an additional language in an integrated manner” (Marsh et al., 2011, p. 6) and are an important variable as a catalyst for teacher professional development (Coyle et al., 2010). Adopting a survey approach, the author of this paper wishes to answer the following question:

Do the survey participants who have differing demographic factors differ in the CLIL competences needed for successful implementation of this pedagogical approach?

It is expected that the research findings can provide valuable insights into CLIL practices in China and encourage more comprehensive teacher development and better organisation of CLIL programmes.

Literature Review

CLIL is a pedagogical approach arising from the foreign language teaching (FLT) practices in Europe, and it is known as “a generic umbrella term that represents a dual-focussed flexible educational approach with multiple dimensions and applications, in which an additional language is used for learning both content and language” (Gabillon, 2020, para. 10). Due to its dual-focused nature which is different from other FLT approaches, it has caught considerable attention of researchers and educators. A popular CLIL research agenda focuses on the investigation of performance evidence (i.e. students’ language and content learning outcomes), effective evidence (i.e. learners’ perceptions, feelings and emotions), process evidence (i.e. key moments when learning occurs) and materials and task evidence (i.e. learning materials used in classes, design and organisation of teaching and learning activities) (Coyle et al., 2010). It is expected that an ideal CLIL study should cover these aspects of evidence to present a comprehensive account of the studied programme, and this train of thought is still the mainstream in academia, underpinning most previous and ongoing studies.

Another CLIL research area is concerned with teachers’ professional development and competencies, which play a significant role in assuring the effectiveness of CLIL implementations. Pavesi et al. (2001) are some of the earliest scholars attempting to bring this topic to the public. While identifying the types of teachers suited to CLIL (e.g. teachers qualified in both L2 and content subject, classroom teachers proficient in using an L2 as the medium of instruction, L2 teachers instructing learners on content subject learning, an L2 teacher cooperating with a content subject teacher), they illustrated that qualified CLIL teachers should have full command of L2 and content knowledge, “deep understanding of the cognitive, socio-cultural and psychological elements” of L2 learning, considerable teamwork skills, willingness to cooperate with other stakeholders (e.g. teachers, specialists) and commitment to classroom-based research (Pavesi et al., 2001, p. 87). One year later, Marsh (2002) proposed the notion of CLIL teacher competencies as to a teacher’s proficiency in the target language (TL), mastery over language theories, ability to employ CLIL methodologies, understanding of the learning environment, capability to develop a range of appropriate learning materials, flexible use of interdisciplinary approaches, and expertise in designing and organising proper assessment tasks. This work has given rise to the proposal of the European Framework for CLIL Teacher Education (hereafter referred to as the Framework) (Marsh et al., 2011), which identifies a CLIL teacher’s competencies with personal reflection (commitment to one’s cognitive, social and affective development), CLIL fundamentals (understandings of CLIL features and theories), content and language awareness (a dual focus on both content learning and language learning), methodology and assessment (pedagogical and professional skills in creating a meaningful learning environment), research and evaluation (engagement in classroom research), learning resources and environments (adopting suitable and cognitively challenging materials), classroom management (knowledge of classroom dynamics and management skills) and CLIL management (developing quality CLIL programmes and courses in collaboration with other stakeholders).

Since the introduction of the Framework, it has been highly rated for its constructiveness in teacher education and professional development (Cinganotto & Cuccurullo, 2017; Wolff, 2012). However, Vilkancien? and Rozgien? (2017) argue that it is vague in that some competencies (e.g. personal reflection) concern more with a teacher’s general capabilities rather than CLIL-specific ones. In comparison, the CLIL Teacher’s Competences Grid (hereafter referred to as the Grid) formulated by Bertaux et al. (2010) tends to be more specific, as it identifies over ten sorts of competencies that are crucial in effective CLIL (i.e. programme parameters, CLIL policy, TL competencies for teaching CLIL, course development, partnerships in supporting student learning, integration, implementation, second language acquisition, interculturality, learning environment management, learner focus in the CLIL environment, learning skills focus in CLIL, learning assessment and evaluation in CLIL, lifelong learning and innovative teaching and learning approaches). However, due to a lack of explicit distinction among those competency areas, the Grid may be too detailed to be effectively adopted in teacher professional development (Vilkancien? & Rozgien?, 2017). In this vein, Pérez-Cañado’s (2018) summative interpretation seems briefer and more practical, and a CLIL teacher should have:

linguistic competence: a teacher’s proficiency in the TL being taught and used as the medium of instruction.
pedagogical competence: a teacher’s familiarity with a range of student-centred pedagogical skills and methodologies to provide an engaging learning environment, diversified learning materials and appropriate evaluation tasks.
scientific knowledge: a teacher’s knowledge of the specific content subject being taught and CLIL-related theories.
organisational competence: a teacher’s classroom management ability within CLIL.
interpersonal and collaborative competence: a teacher’s ability to address students’ needs and cooperate with colleagues.
reflective and developmental competence: a teacher’s awareness of lifelong learning and keeping up with the latest research or information on CLIL.

These frameworks or interpretations have been utilised as a valuable tool in studies to examine CLIL teachers’ competencies and yield insight into professional development (Banegas & del Pozo Beamud, 2020; Cortina-Pérez & Pino Rodríguez, 2021; Custodio-Espinar, 2019; Vázquez et al., 2020). Although the contexts of these studies are different, they have all highlighted the necessity of paying more attention to CLIL teachers’ competencies and providing more training opportunities for them, aimed at promoting professional development.

In China, the syntheses recorded by Mi (2015) demonstrate that divorced from the growing interest in CLIL teacher competencies and development in the western world, only a few Chinese scholars have given heed to these issues. For example, by reviewing the theories underpinning CLIL, Liu and Han (2015), in line with Liu et al. (2016), maintain that to maximise the potential of CLIL, teachers should be competent in CLIL fundamentals, content and language awareness, methodological implementation of CLIL and CLIL management with special attention to cooperation with colleagues. Despite these assumptions, one of the available empirical studies is Liu’s (2019b), the results of which point out various types of competencies expected from the CLIL teachers in a HEP (e.g. the abilities to teach the TL, teach the subject content, foster students’ comprehensive capabilities, manage the classroom, organise assessment activities and design teaching materials). However, her research also has shown unbalanced development of teacher competencies, with several areas (e.g. content awareness, ability to foster learners’ comprehension) deemphasised. This is in line with Cao’s (2021) study on the hindrances to the successful implementation of CLIL, which discloses that CLIL teachers with little content and language awareness may be incompetent to design cognitively appropriate learning materials to rectify the situation that students are less stretched in content learning and less supported in language learning when traditional textbooks are the only source of information. Both Cao (2021) and Liu (2019b), along with some other Chinese researchers (e.g. Li & Yang, 2015; Zhou, 2017) whose studies are not reviewed here because of the page limit, have acknowledged the context-dependent features of their findings and suggested that more attention should be paid to CLIL teachers themselves. This assumption justifies the needfulness and design of the present study set in the Chinese higher education context, which has witnessed and encouraged most of the development of CLIL in China.

Methodology

Research Design

This study adopted a cross-sectional quantitative survey approach, which emphasised the collection of data from a population at a specific point of time. This could allow the researcher to understand the status quo of CLIL teachers’ competencies and compare them among the participants with diverse characteristics (Creswell, 2012). This design corresponded to the research objective and question.

Research Participants

A sample of 205 licensed teachers was recruited from Chinese HEPs by snowball sampling, which was appropriate for the study due to the difficulty of identifying units to include in the sample without a list of the population the researcher was interested in (Creswell, 2012). All the participants were informed of the purpose and design of the study with consent. Their demographic information was recorded in Table 1, including gender, language taught, subject taught, affiliation, highest degree, educational background, years of teaching CLIL and professional title. They were taken as the independent variables (IVs) in this study. Although there were other factors that might also influence the participants’ competencies, namely the dependent variable (DV) of the study, the listed ones were assumed to be sufficient based on previous studies (e.g. Campillo-Ferrer et al., 2020; Custodio-Espinar, 2019; Skinnari & Bovellan, 2016) that had used similar variables to investigate CLIL teachers’ competencies. It should be noted: First, because of the diverse languages the participants taught and the scattered percentages they occupied, they were simply categorised into English and languages other than English (LOTE); Second, the content subjects taught were also categorised into general discipline streams per the educational context in China; Third, despite the various types of HEPs that the participants were affiliated to, they were generally categorised into non-985/211 HEPs and 985 and/or 211 universities¹; Fourth, in accordance with the participants’ years of teaching CLIL and Liu and He’s (2014) identification of Chinese teachers’ career stages, they were labelled as novice teachers with 0-5 years of teaching and proficient teachers with 6-14 years of teaching.

Table 1. Demographic Information of the Participants

Gender	Female: 54.6% (n = 112) Male: 45.4% (n = 93)
Language taught	English: 77.6% (n = 159) LOTE: 22.4% (n = 46)
Subject taught	Economics: 24.9% (n = 51) Law: 21.9% (n = 45) Education: 17.1% (n = 35) History: 15.6% (n = 32) Literature: 12.7% (n = 26) Science: 7.8% (n = 16)
Affiliation	Non-985/211 HEPs: 53.2% (n = 109) 985 and/or 211 universities: 46.8% (n = 96)
Highest degree	Doctoral degree: 50.7% (n = 133) Master’s degree: 35.1% (n = 72)
Educational background	Language-related: 70.2% (n = 104) Content-related: 29.8% (n = 61) Both language and content-related: 19.5% (n = 40)

Research Instruments

The instrument used in the survey was a researcher-made questionnaire named Chinese CLIL Teachers’ Self-Assessment of Competencies. It included six constructs, namely linguistic competence (LC), content competence (CC), pedagogic competence (PC), CLIL fundamentals (CFs), interpersonal and collaborative competence (ICC) and reflective and developmental competence (RDC). This conceptualisation was made based on Pérez-Cañado’s (2018) interpretation. However, the construct of scientific knowledge in her original work was divided into CC and CFs in this study due to her double-barrelled definition. Besides, Pérez-Cañado’s (2018) definition of ICC at a learner level somehow overlaps with the PC and the classroom-management-oriented focus of the organisational competence, because, to some degree, all of them reflect the construction of an engaging and meaningful learning context. Therefore, ICC in this study simply referred to a teacher’s ability to work with colleagues and specialists, and only PC was retained to represent a broad sense of CLIL teachers’ abilities to offer a meaningful learning context. The questionnaire included 31 items on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree), and they were adapted from the Framework (Marsh et al., 2011) and the Grid (Bertaux et al., 2010). A pilot study had been run before the study, and it suggested acceptable reliability and validity of the instrument (see Table 2).

Table 2. Reliability and Validity of the Instrument

	Cronbach’s Alpha	Confirmatory Factor Analysis
	Cronbach’s Alpha	Average Variance Extracted	Composite Reliability
LC	.82	.78	.80
CC	.86	.71	.84
PC	.76	.83	.88
CFs	.88	.62	.93
ICC	.74	.59	.81
RDC	.77	.69	.90
Entire Questionnaire	.80

Data Analysis

The questionnaire was distributed online via Wenjuanxing, a survey platform, and the response rate was 98.04% (n = 201). The collected data were then computed into Statisticsal Package for the Social Sciences 25.0 for analysis. The descriptive statistics reported in this paper included mean and standard deviation. Based on the normal distribution of the data, the inferential analyses were ANOVA when the factor had more than three groups and t-tests when the factor was dichotomous. When the homogeneity of variances was satisfied, one-way ANOVA was run with post hoc analyses with Turkey’s HSD. Otherwise, Welch’s ANOVA was run with Games-Howell. Due to a large amount of data, all the t-tests and ANOVA statistics were compiled together in Appendix. Only the key data with p-values less than .05 in post hoc analyses were recorded in the text.

Results

Linguistic Competence

As shown in Appendix, no statistical difference was found in LC with regard to the participants’ gender, the language taught and highest degree. However, it showed that affiliation influenced CLIL teachers’ LC, with those employed in non-985/211 HEPs having a lower score than those working in 985 and/or 211 universities (t = -3.12, p = .002). Likewise, years of teaching CLIL programmes also played an important role, as novice teachers had a lower level of LC than proficient teachers (t = -2.54, p = .012). In ANOVA analyses, significant statistical difference was only found regarding the educational backgrounds (p = .004). Post hoc analyses (see Table 3) revealed that the teachers with a language-related educational background had a considerably higher level of LC in the self-assessment than those with a content-related or language/content-related educational background (p < .05).

Table 3. Multiple Comparisons of Educational Backgrounds

(I) Educational Background	(J) Educational Background	Mean Difference (I-J)	Sig.
Language-related	Content-related	1.727	.018
Language-related	Both language and content-related	1.938	.022

Content Competence

As displayed in Appendix, inferential data analyses did not show any statistical difference between CC with the participants’ gender, subject taught, educational background or professional title but with the other IVs. Specifically, CLIL English teachers, 985 and/or 211 university teachers, teachers holding a doctoral degree and proficient teachers were more capable of content teaching than their counterparts, namely CLIL LOTE teachers, non-985/211 HEP teachers, teachers having a master’s degree and novice teachers (p < .05).

Pedagogic Competence

The data recorded in Appendix disclosed that no significant statistical difference was found between PC with the teachers’ gender, subject taught, affiliation, highest degree, educational background or years of teaching CLIL. Nevertheless, there was a substantial difference between CLIL English teachers with LOTE teachers (t = 3.21, p = .002). Meanwhile, a significant difference was found amongst the participants of dissimilar professional titles (F = 4.88, p = .003). Post hoc analyses (see Table 4) presented that teaching assistants had less PC than lecturers and associate professors.

Table 4. Multiple Comparisons of Professional Titles

(I) Professional Title	(J) Professional Title	Mean Difference (I-J)	Std. Error	Sig.
Teaching Assistant	Lecturer	-1.892	.56	.005
Teaching Assistant	Associate Professor	-1.705	.61	.029

CLIL Fundamentals

The data in Appendix indicated no statistical difference between the participants’ CFs with their gender, affiliation, educational background or years of CLIL teaching. However, English teachers had better mastery of CLIL-related theories than LOTE teachers (t = 2.48, p = .014). Such a difference could also be found between the teachers who had a doctorate with those who merely had a master’s degree (t = 3.21, p = .002). Besides, a substantial difference was found between the DV with the subject taught and the teachers’ title (p < .001). Post hoc analyses (see Table 5) indicated that CLIL education teachers had higher scores in CFs than all the other content teachers and that professors knew more CFs than the academics who had lower ranks of titles.

Table 5. Multiple Comparison of the Subject Taught and Professional Titles

(I) Subject	(J) Subject	Mean Difference (I-J)	Std. Error	Sig.
Education	Economics	3.231	.356	.000
	Law	2.933	.363
	History	2.752	.404
	Literature	3.524	.42
	Science	3.611	.49
(I) Professional Title	(I) Professional Title
Professor	Teaching Assistant	2.217	.460	.000
	Lecturer	1.844	.372
	Associate Professor	2.277	.409

Interpersonal and Collaborative Competence

Multifaceted statistical differences were found in this section between the DV with the IVs except for the language taught and the highest degree (see Appendix). T-tests revealed female teachers, 985 and/or 211 university teachers and proficient teachers had much higher scores than their counterparts, namely male teachers, non-985/211 HEP teachers and novice teachers. Statisticsal differences were also found in ANOVA analyses regarding the subject taught, educational background and professional title. Post hoc analyses (see Table 6) first showed multiple differences amongst the subjects taught in CLIL, and some teachers (e.g. law teachers) were less cooperative than the others. Besides, the CLIL teachers of a language-related educational background were less capable of interpersonal and collaborative work than those whose educational background was related to either the content subjects or a mix of language and content. Last, it was interesting to note that teaching assistants and lecturers had greater ICC than associate professors and professors.

Table 6. Multiple Comparisons of the Subject Taught, Educational Background and Professional Title

(I) Subject	(J) Subject	Mean Difference (I-J)	Std. Error	Sig.
Economics	Law	1.750	.413	.000
Economics	History	-1.492	.470	.021
Law	Education	-1.323	.456	.047
	History	-3.242	.477	.000
	Literature	-1.462	.499	.043
	Science	-3.121	.591	.000
Education	History	-1.919	.508	.003
Education	Science	-1.798	.616	.045
History	Literature	1.779	.547	.017
(I) Educational Background	(J) Educational Background
Language-related	Content-related	-1.670	.344	.000
Language-related	Both language and content-related	-1.821	.397	.000
(I) Professional Title	(J) Professional Title
Teaching Assistant	Associate Professor	3.381	.393	.000
Teaching Assistant	Professor	3.294	.426
Lecturer	Associate Professor	3.002	.304
Lecturer	Professor	2.915	.345

Reflective and Developmental Competence

Except for the participants’ diverse educational backgrounds, statistical differences in inferential analyses were detected in all the other variables (see Appendix). T-tests firstly presented that male teachers, CLIL English teachers, 985 and/211 university teachers, teachers having a doctorate and proficient teachers had much higher RDC than their counterparts, namely female teachers, LOTE teachers, non-985/211 HEP teachers, teachers having a master’s degree and novice teachers. ANOVA tests disclosed statistical differences in terms of the subject taught (p = .001) and professional title (p < .001). Post hoc analyses (see Table 7) indicated significant differences between education teachers with economics teachers, law teachers, history teachers and literature teachers, and between professors with teaching assistants, lecturers and associate professors.

Table 7. Multiple Comparisons of the Subject Taught and Professional Title

(I) Subject	(J) Subject	Mean Difference (I-J)	Std. Error	Sig.
Education	Economics	3.182	.578	.000
	Law	2.547	.588
	History	3.410	.655
	Literature	3.335	.682
(I) Professional Title	(J) Professional Title
Professor	Teaching Assistant	3.643	.731	.000
	Lecturer	3.185	.711
	Associate Professor	3.730	.706

Summary of Findings and Discussion

First, the above statistics indicated the participants’ affiliation played a significant role in their LC, CC, ICC and RDC in CLIL, with those employed in key universities more competent than the others working at ordinary HEPs. This is a context-specific finding due to China’s higher educational structures, which divide HEPs into various layers (Gu et al., 2018). It is worth noting that when HEPs at the top layers, which are normally top universities or 985 and/or 211 universities, receive more support (e.g. government funding) than ordinary HEPs at the bottom layers to improve teaching quality, enhance academic reputation and expand academic research, chances are that educational resources are unequally distributed, widening the gap between the HEPs at different levels (Chiang et al., 2015). The effect of such a dichotomous educational system on CLIL teachers’ competencies can be the same, as Espinar and Ramos’s (2020) study, though conducted in a different context, reveals that in-service teachers can be unequally trained, supported or prepared for delivering CLIL lessons due to the different administrative processes. In this vein, special attention must be paid to CLIL teachers who work at ordinary HEPs and may receive less professional support than those working in prestigious ones.

Another interesting finding was that the participants who had a master’s degree were less capable than those who had completed a doctorate, and specifically, the latter might have a sounder mastery over the content knowledge taught, a deeper understanding of CLIL-related theories and more commitment to lifelong learning and research than the former. Unfortunately, due to the research gap in CLIL teachers’ professional development (Banegas & Hemmi, 2021), no comparable findings from previous studies can as yet be found, though it seems to be a fait accompli that the higher degree a teacher has, the abler they are owing to the advanced education that has “improve(d) themselves academically and contribute(d) to their professional knowledge” of the subjects being taught, curriculum development, pedagogical instructions and professional development (Çal??o?lu & Yalvaç, 2019, p. 101). From an evidence-based perspective, this study confirms this view and brings forward the issue that some teachers, especially those who are not academically competitive enough, may need more support in delivering CLIL programmes.

Against the backdrop that LOTE education is deemphasised in CLIL in China (Hu, 2021), this study presents that LOTE teachers were less capable than English teachers in various CLIL aspects (e.g. CC, PC, CFs, RDC). This reflects the general picture that “the role of ‘global Englishes’…has led to the marginalising of LOTE contexts” in CLIL (Coyle & Meyer, 2021, p. 8) and that although multilingual education has been promoted in China, more should have been done at the governmental and institutional levels to support LOTE teachers’ professional development in the same way as how English teachers have been supported (Chen et al., 2020). Given the dual-focused nature of CLIL, the differences between CLIL teachers’ competencies with the subjects they taught were also investigated, which showed no significant difference in LC, CC and PC but in CFs, ICC and RDC. This confirms that the subjects taught can affect CLIL teachers’ competencies, just as the case reported by Custodio-Espinar (2019) that teachers of different subjects have disparate levels of professional competencies in organising CLIL programmes. This overall situation, on the one hand, reflects China’s endeavour to promote high-quality discipline construction, and Zhao and Dixon’s (2017, p. 11) work has confirmed this as evinced in the professional support offered to Chinese university and college teachers to ensure they possess high language proficiency, “good content knowledge, content pedagogical knowledge and also pedagogical knowledge for language teaching”. On the other hand, the disparities in certain competencies among different subject teachers reflect the criticism that the unequal support for the construction of different disciplines in China’s higher education system may cause segmentation between more favoured subjects with less favoured ones (Lo & Pan, 2021). It should also be mentioned that different educational backgrounds may also influence CLIL competencies, as the study demonstrated in a much commonsensical way that the teachers having a language-based educational background were more confident in teaching and using the TLs than those having a mixed or content-oriented educational background. Inevitably, many CLIL teachers are either language-driven or content-driven, and few of them may have received dual-focused teacher education specifically designed for CLIL (Lo, 2020), which justifies that they normally have divergent capabilities and perceptions of implementing CLIL (Villabona & Cenoz, 2021). This situation, along with the ones reflected by the findings about the languages and subjects being taught, sheds light on the need to unite language and subject educators of various fields to establish “not only a shared understanding of known practices but also a co-construction of new integrated pathways to guide meaning making through connecting language domains” and content domains (Coyle & Meyer, 2021, p. 8).

The last point to note is the findings about the participants’ gender, years of teaching and professional titles. First, gender was of little effect on the participants’ self-assessment of competencies. Nevertheless, female CLIL teachers were more willing to participate in interpersonal and collaborative work with others than male teachers who, in comparison, engaged more in reflective and developmental practices than their female counterparts. No comparable findings from previous research can be found to confirm or disconfirm this idea, while the ones of the research placed in a broader educational context do have illustrated that Chinese female teachers tend to be more interactive and enthusiastic about professional collaboration (Liang & Zhou, 2016) but less competent at lifelong learning and research, which is the essential indicator of RDC, than male teachers (Zhu & He, 2014). The reasons lying behind this are complicated and largely related to teacher identity discourses influenced by micro, meso and macro factors within a somewhat asymmetrical gender system in China (Luk-Fong, 2013). Thus, they will not be discussed in this text. Furthermore, the years of CLIL teaching also had little effect on the teachers’ competencies, but CC, ICC and RDC were subject to this variable with proficient teachers gaining an upper hand over novice teachers. This reflects Bier’s (2016) research finding that experienced teachers usually have a deeper understanding of CLIL and thus are more skilled than inexperienced teachers. Regarding the professional titles, teaching assistants had less PC than other academics of higher ranks, such as lecturers and associate professors; professors knew more CFs and were more involved in reflective and developmental work than other academics. This may sound commonsensical in the Chinese context, as an academic must have a thorough mastery of the basic theories of their branch of learning and superior “competence in education, teaching and research” to gain a higher academic title (Gu et al., 2018, p. 195). Still, it is surprising to find that teaching assistants and lecturers were more inclined to partake in interpersonal and collaborative work than associate professors and professors. This raises an interesting phenomenon in the field of CLIL. These findings correspond to the previous ones that the teaching experience gained over time and the types of teacher positions can indeed influence CLIL teachers’ professional practices and abilities (Campillo-Ferrer et al., 2020) and reject the assumptions that they may not necessarily explain teachers’ professional development (Skinnari & Bovellan, 2016).

The description and discussion of the heterogeneity of Chinese CLIL teachers’ profiles of professional competencies have mirrored the inevitable “gap between who CLIL teachers are and what ideal CLIL teachers need” (Lo, 2020, p. 21) and disclosed the complex challenges confronting them. It seems to be a consensus that CLIL is a “linguistic and cognitive challenge” (Bier, 2016, p. 396) or a psychological and pedagogical challenge (Lo, 2020) for teachers, while these views can be too simplistic to be linked with the dynamically interwoven CLIL competencies. Thus, given the research findings and the special higher educational context in China, it is proposed at the end of this paper that the challenges faced by Chinese CLIL teachers are related to micro, meso and macro factors. The micro factors are concerned with teachers themselves, such as gender, educational background and teaching experience; the meso factors (e.g. the languages and subjects taught, professional titles) are identified with the context-specific features at an institutional level; the macro factors are placed in a more general social context and normally associated with the regional and even national education moves or policies. They are interwoven with each other, challenge a CLIL teacher’s agency and influence their competencies. However, the recognition of these factors can help to better identify CLIL teachers’ professional growth needs, devise appropriate ways to improve their competencies and finally contribute to successful CLIL.

Conclusion

Regardless of the limitation that a non-probability sampling technique was adopted and thus prevented the researcher from generalising the findings to a wider population, the study can still be seen as one of the initiatives to bridge the CLIL research gap in the Chinese academia by focusing on teachers’ competencies in implementing this pedagogical approach. The results of the study are multifaceted, and various factors may shape CLIL teachers’ competencies of different types. In the process of professional development, the challenges confronting CLIL teachers can be varied, whether being linguistic, content-related, pedagogical, theoretical, cooperative or reflective. However, the identification of CLIL teachers’ profiles of professional competencies in accordance with the factors studied has underlined the need to establish an ecological milieu and a supportive network, wherein professional collaboration should be embraced among CLIL teachers of different profiles, information and resources should be shared amongst educational institutions, and support should be lent to the teachers who have just embarked upon their CLIL teaching journey. Continuous professional training programmes are essential to achieve this goal. The answer is straightforward: to help teachers better understand CLIL, identify the language and content learning needs, learn effective strategies to design and implement CLIL and become committed to lifelong learning. This can allow teachers to enhance their professional identities and students to reap the benefits of CLIL when teaching practices are effectively grounded in teachers’ exceptional competencies. The goal of the research is to open up new ways for keeping alive the sustainability of CLIL. To this end, ongoing research into teacher training needs is also a must, requiring Chinese researchers and scholars to endeavour to explore CLIL teachers’ dynamic agency in the long way ahead.

Note

985 and 211 mean Project 985 and Project 211 respectively, which are national projects initiated by the Chinese government to promote the development and reputation of Chinese HEPs and found world-class universities (Gu et al., 2018). It is believed that a 985 and/or 211 university is usually better than a non-985/211 HEP due to a higher admission threshold, more government support and larger educational resources (Lo & Pan, 2021).

Acknowledgement

Special thanks are extended to the participants of the study.

References

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Appendix: The Compilation of T-Tests and ANOVA Statisticss

		LC				CC				PC
IV		M	SD	Statistics	Sig.	M	SD	Statistics	Sig.	M	SD	Statistics	Sig.
Gender	Female	17.78	4.049	t = -1.461	.146	8.93	.667	t = -1.123	.263	32.48	2.518	t = 1.284	.201
Gender	Male	18.59	3.882	t = -1.461	.146	9.05	.925	t = -1.123	.263	31.98	3.007	t = 1.284	.201
Language taught	English	18.09	3.928	t = -.347	.729	9.05	.818	t = 2.195	.029	35.98	2.639	t = 3.210	.002
Language taught	LOTE	18.33	4.217	t = -.347	.729	8.76	.673	t = 2.195	.029	29.43	2.880	t = 3.210	.002
Subject taught	Economics	18.41	4.239	F = 2.101	.067	8.76	.619	F = 1.999	.080	31.63	3.206	F = 1.305	.271
	Law	19.26	3.511			9.06	.818			32.09	2.234
	Education	18.11	3.886			8.83	.568			32.11	2.447
	History	16.60	3.645			9.13	.629			33.23	2.812
	Literature	17.15	3.695			9.23	1.306			32.69	2.695
	Science	18.63	4.978			9.13	.719			32.50	2.989
Affiliation	Non-985/211 HEPs	17.35	3.895	t = -3.119	.002	8.84	.654	t = -2.422	.016	32.04	2.772	t = -1.034	.302
Affiliation	985 and/or 211 universities	19.05	3.910	t = -3.119	.002	9.11	.885	t = -2.422	.016	32.44	2.740	t = -1.034	.302
Highest level of degree	Doctoral degree	17.91	4.001	t = -1.156	.249	9.13	.830	t = 3.587	.000	32.49	2.667	t = 1.667	.097
Highest level of degree	Master’s degree	18.58	3.946	t = -1.156	.249	8.72	.655	t = 3.587	.000	31.82	2.879	t = 1.667	.097
Educational background	Language-related	19.04	3.844	F = 5.562	.004	8.88	.649	F = 2.195	.114	31.94	2.716	F = 1.377	.255
	Content-related	17.31	3.771			9.07	.998			32.62	2.703
	Both language and content-related	17.10	4.223			9.15	.770			32.50	2.909
Years of teaching CLIL	Novice	17.50	3.986	t = -2.539	.012	8.84	.661	t = -2.431	.016	32.02	2.740	t = -1.112	.268
Years of teaching CLIL	Proficient	18.90	3.869	t = -2.539	.012	9.11	.878	t = -2.431	.016	32.45	2.766	t = -1.112	.268
Professional title	Teaching Assistant	18.32	4.182	F = 2.916	.35	8.77	.717	F = 2.122	.103	30.90	3.134	F = 4.875	.003
	Lecturer	17.25	4.061			9.15	.953			32.80	2.713
	Associate Professor	18.92	3.862			8.86	.693			32.61	2.401
	Professor	19.11	3.428			8.94	.416			31.57	2.547

		CFs				ICC				RDC
IV		M	SD	Statistics	Sig.	M	SD	Statistics	Sig.	M	SD	Statistics	Sig.
Gender	Female	10.04	2.055	t = 1.303	.194	9.14	2.321	t = 2.691	.008	11.22	2.415	t = -2.477	.017
Gender	Male	9.68	1.951	t = 1.303	.194	8.29	2.180	t = 2.691	.008	12.20	3.249	t = -2.477	.017
Language taught	English	10.06	2.083	t = 2.476	.014	8.66	2.292	t = -1.112	.267	11.91	3.078	t = 3.113	.002
Language taught	LOTE	9.24	1.608	t = 2.476	.014	9.09	2.288	t = -1.112	.267	10.83	1.691	t = 3.113	.002
Subject taught	Economics	9.25	1.787	F = 22.860	.000	8.94	2.275	F = 11.624	.000	10.96	1.876	F = 4.757	.001
	Law	9.55	1.909			7.19	1.740			11.60	2.849
	Education	12.49	1.067			8.51	2.525			14.14	4.131
	History	9.73	1.258			10.43	1.524			10.73	1.660
	Literature	8.96	1.280			8.65	2.097			10.81	1.266
	Science	8.88	2.187			10.31	1.580			11.88	2.964
Affiliation	Non-985/211 HEPs	9.71	1.973	t = -1.134	.258	8.02	2.248	t = -4.510	.000	10.84	1.719	t = -4.172	.000
Affiliation	985 and/or 211 universities	10.03	2.043	t = -1.134	.258	9.40	2.139	t = -4.510	.000	12.39	3.421	t = -4.172	.000
Highest level of degree	Doctoral degree	10.20	2.092	t = 3.214	.002	8.98	2.253	t = 1.956	.052	12.11	3.226	t = 3.636	.000
Highest level of degree	Master’s degree	9.28	1.713	t = 3.214	.002	8.33	2.320	t = 1.956	.052	10.85	1.758	t = 3.636	.000
Educational background	Language-related	9.73	2.054	F = 1.315	.265	7.90	2.240	F = 16.931	.000	11.17	2.240	F = 1.327	.353
	Content-related	9.66	1.879			9.57	2.061			11.32	2.061
	Both language and content-related	9.08	1.716			9.73	1.935			11.20	2.233
Years of teaching CLIL	Novice	9.72	2.008	t = -1.013	.312	8.00	2.267	t = -4.562	.000	10.81	1.706	t = -4.114	.000
Years of teaching CLIL	Proficient	10.01	2.016	t = -1.013	.312	9.40	2.120	t = -4.562	.000	12.40	3.396	t = -4.114	.000
Professional Title	Teaching Assistant	10.04	2.055	t = 1.303	.194	10.32	1.301	F = 52.828	.000	10.87	1.765	F = 9.622	.000
	Lecturer	9.68	1.951			9.94	1.884			11.33	2.495
	Associate Professor	10.06	2.083			6.94	1.714			10.78	1.803
	Professor	9.24	1.608			7.03	1.654			14.51	3.899

The Association between Linguistic Competence Components and Listening Comprehension of Thai EFL Learners

TESL/V14N2

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Siwaporn Singhkum¹ & Chomraj Patanasorn²
¹English Program, Faculty of Humanities and Social Sciences, Khon Kaen University, Thailand. Email: siwaporn.singhkum@gmail.com

²English Program, Faculty of Humanities and Social Sciences, Khon Kaen University, Thailand. Email: chomraj@kku.ac.th

Rupkatha Journal, Vol. 14, Issue 2, April-June, 2022, Pages https://doi.org/10.21659/rupkatha.v14n2.09

First published: June 19, 2022 | Area: EFL Studies | License: CC BY-NC 4.0

(This article is published under Volume 14, Number2, 2022)
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The Association between Linguistic Competence Components and Listening Comprehension of Thai EFL Learners

Abstract

This study aimed to investigate the extent to which there is an association between components of linguistic competence and listening comprehension and to examine whether one component of linguistic competence is a stronger predictor of listening comprehension than another. Participants included 107 Thai EFL learners whose major is English, and they were asked to complete a linguistic competence test and a listening comprehension test. Correlation and multiple regression were used to determine the statistical relationship between linguistic competence components and listening comprehension. Results indicated that all components except syntactic competence significantly correlated with listening comprehension albeit mostly in small correlations. Listening comprehension significantly correlated with phonological competence (r = 0.296, p = 0.002), morphological competence (r = 0.292, p = 0.002), and the strongest predictor was semantic competence (r = 0.326, p = 0.001). Although linguistic competence significantly correlated with listening comprehension in EFL learners, it had only a small influence on listening comprehension due to the covariance of 16.4 per cent out of all factors involved in listening success.

Keywords: EFL Learners, Linguistic Competence, Listening Comprehension

INTRODUCTION

Listening is a cognitive process that intertwines various complex mechanisms involving the coordinated operation between neurological processing and linguistic processing (Barker, 1971; Weaver, 1972; Cutler, Dahan, & Van Donselaar, 1997). In order to comprehend audio input, the neurological processing primarily supports listeners in receiving the input, activating related constituents, such as attention or consciousness as well as transferring the input to the listeners’ minds (Liberman, Cooper, Shankweiler, & Studdert-Kennedy, 1967). Linguistic processing engages the manipulation of the input by integrating phonological, morphological, syntactic and semantic competence to help listeners understand a message before they generate a response (Cutler & Fodor, 1979). According to Cutler, Dahan and Van Donselaar (1997), the integral processing between neurological processing and linguistic processing automatically collaborates in terms of receiving, decoding and interpreting in comprehending the audio input. Hence, the more fluent neurological processing and linguistic processing contribute to the more effective listening comprehension.

Besides the cognitive systems, listening comprehension also involves two kinds of competence including non-linguistic as well as linguistic competence to deal with the incoming input (Buck, 2001). According to Eysenck (1998), non-linguistic competence utilizes macro-level mechanisms (e.g., accessibility of stored knowledge in long-term memory) to help listeners understand the concept, topic or context of what they listen to. In other words, the shared knowledge between listeners and speakers or listeners’ prior knowledge and the incoming audio input can provide understanding as well as mental images to promote listening comprehension. For instance, a speaker says that his dog did it again, and if the listener has shared knowledge about the speaker’s dog, the listener will be able to immediately recognize which dog he is talking about and what crime it had committed. To give another example, a listener listens to a happy-ending drama, and when the story is halfway through, they may correctly predict the ending. This is a result of the familiarity with the happy-ending theme, which the listener possesses in his/her prior knowledge. Al-Qaraghooly and Al-Bermani (2010) explain that non-linguistic competence is always coincidental with linguistic competence which can help listeners discriminate, recognize and understand the spoken message.

Linguistic competence relates to the application of phonological, morphological, syntactic and semantic knowledge in activating micro-level mechanisms, such as acoustic signal analysis, word retrieval as well as syntactic and semantic interpretation (Clark & Haviland, 1974). For example, a listener needs to segment the ending phoneme of the past-tense verb as well as recognize the adverb of time when listening to a story about the past or the listener may interpret the background event and the main event of past-continuous-tense and past-tense sentences to comprehend the circumstance in the story. According to Cutler and Cliftion (2000), linguistic components (i.e., phonological, morphological, syntactic and semantic competence) in listening can be neither completely separated nor combined when they are functioning. This means that in order to comprehend the continuity and coarticulation of the audio input, the simultaneous activation of partially overlapping components of linguistic competence functions.

Accordingly, these non-linguistic and linguistic components used to comprehend audio input operate depending on the cognitive tasks (e.g., for the familiar-context audio input, listeners’ mind weighs more on non-linguistic competence meanwhile for the speed and unfamiliar-context audio input, the linguistic competence is more activated.) (Cutlter & Cliftion, 2000; Clashsen & Felser, 2006). In other words, these phenomena of non-linguistic and linguistic competence activation occur in a form of problem-solving. However, the way to identify whether the non-linguistic competence or linguistic competence should be employed relies on linguistic competence to discriminate sounds or recognize words in the continuous audio input. Hence, it can be claimed that linguistic competence is the basis of listening comprehension. Subsequently, many scholars (e.g., Anderson, 1995; Cutler & Clifton, 2000; Schneider, Avivi-Reich, Leung, & Heinrich, 2016) have attempted to examine the relationship between linguistic competence and listening comprehension in different ways.

Over the past decade, research on linguistic competence and listening comprehension has become more extensive; however, it is still limited compared to the relationship between other dimensions of listening comprehension studies (e.g., listening strategy or affective filter studies) (Vandergrift & Cross, 2018; Rudner, Ahlander, Brännström, Nirme, Pichora-Fuller, & Sahlen, 2018). In addition, regarding linguistic competence, most studies have solely been found to emphasize each component of linguistic competence to listening comprehension. For example, Rabia (2019) studied only the relationship between phonological competence and listening comprehension whilst Becker (2016) studied the relationship between listening comprehension and semantic competence, Sapoetra (2017) studied listening comprehension and syntactic competence, and Masrai (2019) studied on listening comprehension and morphological competence. All the findings suggest a strong relationship between the individual linguistic competence component and listening comprehension; nevertheless, it remains unclear whether all linguistic competence components are interrelated in the identical context. Moreover, even though some researchers use the term linguistic competence in their studies, some parts of linguistic competence (e.g., only phonological and morphological competence) are illustrated in their research focus. To illustrate, the studies of Avivi-Reich, Daneman and Schneider (2014) as well as Schneider, Avivi-Reich, Leung, and Heinrich (2016) employed the term linguistic competence, but only phonological and morphological competence were tested. This entails insufficient information to account for the relationship between linguistic competence and listening comprehension. Additionally, the participants employed in most studies are natives of English and advanced English as a second language (ESL) learners. However, less proficient English as foreign language (EFL) learners who experience more difficulties with linguistic competence and listening comprehension are understudied.

Many EFL learners encounter serious obstacles in developing linguistic competence as well as achieving listening comprehension. According to Krashen, Long, and Scarcella (1982) as well as Karimi (2016), the development of linguistic competence of EFL learners is not parallel as a result of their different degrees of personal exposure to the English language. In other words, some learners may have a higher exposure to English morphology while others are more exposed to another component of linguistic competence. Many studies have examined factors affecting English exposure in a foreign language environment, and one of the key factors is the prior linguistic competence influence (Rast, 2010). There are cross-linguistic influences in every aspect of EFL learners’ interlanguage (e.g., phonology, morphology, syntax and semantics). The level of linguistic transferability or development depend on linguistic distance and salience. In addition, the higher or lower level of transferability or development associates with how English can be salient to learners (Lu, 2010). For instance, Thai learners may be easier to perceive the English syntax (e.g., subject-verb–object sentence structure) than phonology (e.g., dropped consonants or intonations).

This notion is supported by Samer and Zoubi (2018) that the learners have inconsistent exposure to components of linguistic competence of English as evidenced by the difference in exposure level. Therefore, due to the unequal exposure, the development of each type of linguistic competence is varied which consequently entails various difficulties in speech perception, such as the inability to discriminate acoustic cues because of lacking phonological competence or failing to interpret messages due to syntactic or semantic competence deficiency. According to Gilakjani and Ahmadi (2011), as a result of linguistic competence limitation during information processing in a speech perception process, the learners’ listening comprehension is unsuccessful. To illustrate, learners with limited vocabulary stop and think about the meaning of unfamiliar vocabulary causing them to miss the next part of the speech. Several studies reveal that developing only one component of linguistic competence (e.g., shadowing audio texts to develop phonological competence or vocabulary drilling to develop morphological competence) can improve listening comprehension (Rabia, 2019; Migdadi, Yunus, & Daradkeh, 2019). This implies that if one component out of four unequal linguistic competence components is higher and makes listening comprehension improved, there may be a dominant component in helping the learners comprehend audio input. Therefore, this study aims to investigate the extent of correlation between the linguistic competence components and listening comprehension as well as examine whether one component of linguistic competence is a stronger predictor of listening comprehension than another.

Linguistic competence

The term ‘linguistic competence’ was introduced by Chomsky (1965). It is suggested that this notion is directly related to the theory of generative grammar (i.e., a system of rules that generates language) and provides a clearer picture of language. Chomsky (1965) distinguished ‘linguistic competence’ from ‘linguistic performance’. Linguistic competence is one’s mental representation of linguistic rules while linguistic performance refers to the ability to produce or comprehend the language.

Later in the 1970s to early 1980s, when the social-oriented model of second language acquisition emerged, many scholars attempted to revise Chomsky’s notion of linguistic competence and performance. Hymes (1972), Halliday (1973) as well as Canale and Swain (1980) stated that Chomsky’s theory of linguistic competence (1968) was impractical. It did not account for differences among languages, and Chomsky’s (1965; 1968) definition of linguistic competence only focused on the grammar, but no reference was made to socio-cultural or contextual rules, which entails the lack of sufficient evidence to explain the output of performance. In other words, besides the grammatical rules which cover the competence of phonology and morphology, Chomsky’s definition of linguistic competence cannot explain why individuals produce speech differently in the same situation. Therefore, the components presented by Hymes (1972), Halliday (1973) as well as Canale and Swain (1980) are syntax and pragmatics. The phonology, morphology and semantics (i.e., how words, phrases, clauses or sentences are pronounced, structured and what they mean) are accounted for as parts of syntax and concerning the pragmatics (i.e., how language is used in situations) was added when the correspondence between competence and performance is considered.

In addition, Smith and Wilson (1990) also proposed their view of linguistic competence. They stated that linguistic competence does not only cover syntactic rules governed in a language, but also the pronunciation and meaning of words constructed by those rules. Smith and Wilson (1990) argued further that linguistic competence is used for two main tasks. First, it monitors language production (e.g., separating grammatical from ungrammatical sentences, right and wrong word choices, correct pronounced and mispronounced speech, or definite or indefinite meaning interpretation) and identifies potential mistakes or errors. In addition, they argue that L2 learners possess different levels of linguistic competence because competence is not simple but complex and subtle. Thus, the richness of linguistic competence relies upon an individual’s exposure as well as memory storage capacity. Linguistic competence is an unconscious stored knowledge of how the expression is pronounced and the meaning attached to those sound and orthographic features in a grammatical sentence (Smith & Wilson, 1990). Notably, there are four components specified by Smith and Wilson (1990) comprising phonology (i.e., stored information on phonological features as well as phonological rules), morphology (i.e., stored information of internal morphological features of the word), syntax (i.e., stored information of how words are put together to construct phrases, with how phrases are put together to build longer phrases or clauses as well as with how clauses are put together to create sentences) and semantics (i.e., stored information of meaning of words as well as the meaning of the word relations in a sentence, and these can be technically called lexical semantics and phrasal semantics). Unlike in the social-oriented model, pragmatic competence is not part of the notion of linguistic competence presented by Smith and Wilson as they consider it as a type of non-linguistic competence, and a part of semantics in cases of alteration of meaning based on contexts.

To sum up, there are different explanations of linguistic competence based on researchers’ interests as well as assumptions. In this study, linguistic competence is indicated based on Smith and Wilson (1990) due to the coherence of the listening process that listeners’ mind unconsciously employs four faculties of linguistic competence (i.e., phonological, morphological, syntactical and semantic competence) in comprehending audio input.

Listening comprehension

Similar to linguistic competence, listening comprehension has also been defined in a variety of ways. The most widely accepted explanation of listening comprehension relates to the process of constructing understanding from the audio input. In other words, listening comprehension normally relies upon subconscious competence stored within listeners’ minds. When audio input is internalized, different sources of competence are systematically and unconsciously derived.

Vandergrift (2002) explains that in listening comprehension, listeners usually employ two sources of competence including non-linguistic and linguistic competence. Firstly, non-linguistic competence involves listeners’ knowledge that has been acquired in their life as well as mental images stored in their minds. Both are drawn to process the audio input by calling on similar scenarios and previous experiences. In other words, for this source of competence, listeners can comprehend the theme or main idea of what they listen to. Secondly, linguistic competence relates to phonology (i.e., the sound system), morphology (i.e., the morphological form and morphological formation), syntax (i.e., how words are combined to form phrases, phrases are combined to form broader phrases or clauses, and clauses are combined to form sentences) as well as semantics (i.e., the meaning of words, phrases or sentences). It plays a role when we discriminate sounds, recognize words, and interpret the audio input by analyzing units in some linguistic dimensions. Explicitly, linguistic competence helps listeners gather the details for their listening comprehension. For example, listeners may know that the situation occurred in the past by segmenting the -ed sound of the verb used and/or noticing the adverb of time. It is seen from Buck (2001) and Vandergrift (2002) that the top-down process always involves the non-linguistic competence, and the bottom-up process relates to linguistic competence when the listening comprehension.

Regarding Buck (2001) and Brown (2007), listeners do not separately activate non-linguistic and linguistic competence to handle the flowing audio input. Instead, non-linguistic competence and linguistic competence are activated for different purposes during listening. To illustrate, for the non-linguistic competence activation in the top-down process, if listeners cannot catch all words in the audio input, they will get the gist from some words. As in top-down processing, listeners create metal images or know the contexts by building meaning based on supposition, conclusion, purpose, and other pertinent information in order to try to recognize linguistic expressions. On the other hand, for the linguistic competence activation in the bottom-up process, if listeners are not familiar with the topic they listen to, they will focus on every single word to know what it is about. In bottom-up processing, listeners initially try to decode a message by focusing on sound patterns or internal structures of words, rules and meaning before understanding scenarios. The co-existence of these two processes is basically an interactive process (Tokeshi, 2003).

Besides linguistic and non-linguistic competence engaging in listener factors in understanding the audio input, listening comprehension also involves audio-input and speaker factors. Cutler and Clifton (2000) explain that the audio input reaching the ear carries other noises in the environment. Therefore, listeners need to primarily distinguish the audio input from other background noises reaching the ear at the same time. In addition, different phonemes contain distinctive features from articulatory factors (e.g., a place of articulation to produce [k] is different from [b]), so it may lead to some obstacles in decoding the whole audio input when phonemes come together as a pattern. Besides decoding phonemes, there are other factors influencing decoding the audio input, such as the speakers’ coarticulated words as well as the quality of sound.

As the audio input produced by the speakers is normally coarticulated (i.e., they do not speak one segment discretely after another), the listeners have to be competent in phonology to identify and decode phonemes as well as phoneme patterns. If listeners cannot identify the sound they listen to, they will not be able to decode it into a phonetic representation. For instance, listeners cannot identify whether they hear the sound [?] or [?], so they cannot determine whether the word is complement or compliment. Moreover, the quality of sounds, such as speakers’ voice, amplitude and speech rate, also affects listeners’ audio input decoding. Different speakers have different voices (i.e., someone has a high-pitched voice, and someone has a low voice), and sometimes, the tones of voice may be difficult for listeners to identify the phonemes. Similarly, if the speakers utter too far from listeners to hear it, or even utter very fast, the listeners may not even detect anything (Cutler and Clifton 2000).

Objectives of the study

The objectives of the study were (1) to investigate the extent of the correlation between linguistic competence components and listening comprehension and (2) to examine whether one linguistic competence component is a stronger predictor of listening comprehension than another.

METHOD

Participants

The participants in the current study included 107 third-year English major students in the Faculty of Humanities and Social Sciences at Nakhon Ratchasima Rajabhat University for the academic year 2020 using convenience sampling.

The participants’ English listening proficiency level was classified into A1-B2 by using Dialang, the international placement test. According to Dialang (n.d.), learners who can understand very simple phrases about basic personal topics (e.g., personal information or friend) with slow and clear messages were classified as A1 level, learners who understand expressions and common words and get the main point of useful information (e.g., travel announcements and directions) in short, clear and simple messages were classified as A2 level, learners who can understand the main points of clear standard speech on familiar matters (e.g., school, tv or radio current affairs) in relatively slow and clear messages were classified as B1 level, and learners who understand longer stretches of speech and complex lines of argument involving reasonable familiar topics (e.g., personal and professional life).

Initially, there were 131 participants (i.e., seventy-four A1 participants, twenty-seven A2 participants, fifteen B1 participants and fifteen B2 participants); however, there was an exclusion due to the submission time of the online test. Some test submission checks detected too little time spent (less than 10 minutes out of the total 40 minutes) which could assume that the participants guessed the answers and too much time spent completing the tests (more than 40 minutes as a result of using time detection instead of time limitation). The total number of exclusions was twenty-four participants (i.e., fifteen A1 participants, two A2 participants, one B1 participant and five B2 participants).

Instruments

The instrument included a linguistic competence test and a listening comprehension test. A linguistic competence test comprised of four subtests including a phonological awareness test adapted from Venkatagiri and Levis (2007), a morphological awareness test adapted from Bian (2017), and a syntactic awareness test adapted from Cain (2007) and a semantic awareness test adapted from Lehmann (2007). The vocabularies used for the adaptation in all tests were randomly selected from the Oxford 3000 Word List (2019). For a phonological test, there were seven main tasks to assess different phonological constructs including phonological blending, phonological manipulation, phonological segmentation, phonological sequencing, rhyming and alliteration and non-word reading. In some tasks, participants needed to record and upload audio/video clips into the link provided. However, the tasks did not take time (e.g., saying one to two words). Additionally, participants were suggested to use mobile phones for this test in order to ease the recording and uploading. For a morphological awareness test, there were four main tasks to assess morphological awareness including morphological form, morphological formation, reading vocabulary and listening vocabulary. For a syntactic awareness test, there were three main tasks to assess syntactic awareness including knowing the grammatical structure of sentences (form) by using language element task, manipulating the grammatical structure of sentences (meaning) by using situational response task as well as producing the grammatical structure of sentences (use) by using grammar construction task. For a semantic awareness test, there were two main tasks to assess semantic awareness including lexical semantics and phrasal semantics. Each test contained 40 items and participants were allowed to complete it within 40 minutes.

Meanwhile, a listening comprehension test adopted from dialangweb.lancaster.ac.uk was used for the listening comprehension and placement test, and there are three tasks including listening for detail, inferencing, and identifying the main idea. The recording in each item was played once before allowing participants to select the correct answer. There were three different sets of the test varying texts according to the vocabulary level of participants and switching items for the same level. However, the total number and topic were the same.

Due to the coronavirus-19 transmission, a linguistic competence test was conducted online through Google form while a listening comprehension test was directly conducted via the website. The topic of the tests was selected by focusing on topic familiarity due to the control variable (i.e., non-linguistic competence). The specification of each test was presented in Appendix 1.

Data collection

The participants were given explanations about the listening and linguistic competence tests, and the time detection feature in each linguistic competence test, which required them to manage time and finish each linguistic competence test within forty minutes. The listening comprehension and placement tests were firstly conducted to get listening comprehension scores as well as separated them into English listening levels based on the Common European Framework of Reference for Languages (CEFR) (A1-B2), and the linguistic competence test was provided based on participants’ English listening level. After the English listening level of participants had been determined, participants were assigned to complete and submit a linguistic competence test including the phonological awareness test, morphological awareness test, syntactic awareness test and semantic awareness test within a month. Therefore, participants could manage their time to complete all sub-tests of the linguistic competence test.

Data analysis

All results of participants’ responses were assessed. For answers to filling in the blank and multiple-choice questions, the scores were checked according to the scoring rubric (i.e., one point per correct response). Meanwhile, performance in video clips in the phonological awareness test was rated by employing inter-rating scales from two people including the researcher as well as the university teacher majoring in English to avoid bias. After the result was scored, the statistics of correlation and multiple regression were used to generate the statistical outcome for answering research questions.

Descriptive statistics (i.e., mean and standard deviation) and correlation were employed to analyze the data from the linguistic competence test and listening comprehension test in order to investigate the statistical relationship between two variables including linguistic competence and listening comprehension. In addition, a multiple regression analysis was used to measure the relationship between independent variables (i.e., components of linguistic competence including phonological competence, morphological competence, syntactic competence and semantic competence) and a dependent variable (i.e., listening comprehension) in order to examine whether one linguistic competence component is a stronger predictor of listening comprehension than another.

FINDINGS AND DISCUSSION

Table1 Correlation and multiple regression predicting listening comprehension (N=107)

	Zero-order r						SE	p
Predictors	Semantic Competence	Syntactic Competence	Morphological Competence	Phonological Competence	Listening Comprehension
Intercept						7.204	1.855	.000
Phonological Competence					.296 (.002)	.184	.081	.025
Morphological Competence				.435	.292 (.002)	.062	.101	.542
Syntactic Competence			.519	.395	.147 (.131)	-.082	.098	.403
Semantic Competence		.406	.612	.240	.326 (.001)	.157	.070	.028
Linguistic Competence	.789	.731	.846	.661	.359 (.000)	.089	.023	.000

Mean	18.91	16.36	17.95	21.92	13.96	R² = .164
SD	8.423	5.711	6.490	6.537	5.103

*Significantly at 0.05.

According to the assumption testing, the association between linguistic competence components and listening comprehension is linear, and there is no multicollinearity in the association between linguistic competence components and listening comprehension as VIF values were below 10 and tolerance values were above 0.2. In addition, the values of residuals were independent as the obtained values were close to 2 as evidenced by the Durbin-Watson value of 1.037, and the values of residuals which were normally distributed were constant as the residuals showed no obvious signs of funnelling. Besides, there were no influential cases biasing the model as all values were under 1 suggesting individual cases were not influencing the model.

Based on the first research question, the extent of correlation between linguistic competence and listening comprehension was investigated. The result reveals that the correlation between linguistic competence and listening comprehension is less than 0.5 (r = 0.359, p = 0.000) which means there is a statistically significant relationship between linguistic competence and listening comprehension. However, considering the components of linguistic competence, it was found that all components except syntactic competence significantly correlate with listening comprehension. The following correlations were found: phonological competence (r = 0.296, p = 0.002), morphological competence (r = 0.292, p = 0.002), syntactic competence (r = 0.147, p = 0.131) and semantic competence (r = 0.326, p = 0.001).

Furthermore, to answer the second research question, a multiple regression was calculated to examine whether one linguistic competence component is a stronger predictor of listening comprehension than another. The result of multiple regression indicates that a significant regression equation is found (F(4,102) = 4.985, p < .001), with an R2 of .164. The predicted listening comprehension of participants is equal to 7.204 + 0.184 (phonological competence) + 0.062 (morphological competence) + 0.157 (semantic competence) – 0.082 (syntactic competence), where they are measured in scores. Participants’ listening comprehension increased by 0.184 scores for each score of phonological competence, 0.062 for each score of morphological competence, and 0.157 for each score of semantic competence. Meanwhile, participants’ listening comprehension is decreased by 0.082 scores for each syntactic competence which shows a negative relationship to listening comprehension. It is seen that phonological competence (? = 0.025) and semantic competence (p = 0.028) are significant predictors of listening comprehension, and the stronger predictor is semantic competence (r = 0.326).

Regarding the investigation of a correlation between linguistic competence and listening comprehension in the current study, the result shows a positive linear relationship between linguistic competence and listening comprehension. This corresponds to the findings of some other studies (Oh & Lee, 2014; Karal?k & Merç, 2019) showing that there are relative contributions of linguistic competence to L2 listening comprehension. Although linguistic competence significantly correlates with listening comprehension, it has only a small influence on listening comprehension due to the covariance of 16.4 per cent out of all factors involved in listening success.

Noticeably, besides linguistic competence, a number of factors affect listening comprehension achievement. Nichols (1948) suggests that apart from the listener’s competence and characteristic, the speaker’s characteristics, speech production ability and quality as well as channels or methods of speech delivery can apparently influence listening comprehension. Flowerdew and Miller (2005) claim that not only linguistic and non-linguistic competence plays a role in cognitive activities in the listening process, but also individualization, affective factors, and textuality. This study lends some support to this conclusion as linguistic competence accounted for less than 20 per cent of participants’ listening comprehension.

The findings are also consistent with a number of studies nowadays (Worthington & Fitch-Hauser 2012; Asriati, 2017; Oh & Lee, 2014). Worthington and Fitch-Hauser (2012) claim that elements affecting listening comprehension can be classified into five aspects including cognitive factors (e.g., curiosity, intelligence, concentration), linguistic factors (e.g., sound discrimination ability, recognition of correct grammatical usage, size of vocabulary), speaker-related factors (e.g., speaker effectiveness, speech delivery ability), contextual factors (e.g., interest of the topic, listener’s exhaustion), and demographic factors (e.g., listener’s gender or age). Asriati (2017) categorizes the dominant factors engaging in listening comprehension into four major aspects including linguistic competence, concentration, listener characteristics (e.g., experience or intelligence), and speaker characteristics (e.g., pronunciation or speed of delivery), and his result reveals only a small proportion of linguistic competence compared to other factors which can be supported by the result of Ghapanchi and Taheryan (2012) as well as Oh and Lee (2014) who investigate the linguistic competence in L2 listening exhibiting that linguistic competence can predict L2 listening with the covariance around 20 per cent. Nevertheless, linguistic competence in those studies consisted of receptive and productive vocabulary as well as grammar which can be one of the possible reasons why they generate a higher percentage than the current study. Linguistic competence in the current study is operationalized as four variables including phonological competence, morphological competence, syntactic competence and semantic competence.

It can be expected that EFL learners weigh more on some competence to comprehend incoming audio input. In listening, the cognitive system which basically relates to the competence of phonology, morphology, syntax and semantics is triggered to deal with different types of audio input (Bullmore & Sporn, 2012). When sequences of audio input are heard, learners’ mind systematically and unconsciously activates competence to decode them and there is repeated retry-step processing until competence can decode or capture the idea (Brownell, 1996). However, unequal and restricted development of linguistic competence components in EFL learners consequently makes their competence activation for comprehending the audio input limited (Krashen, Long, & Scarcella, 1982; Avivi-Reich, Daneman, & Schneider, 2014; Karimi, 2016; Schneider, Avivi-Reich, Leung, & Heinrich, 2016; Joyce, 2019).

In the current study, most EFL learners are in the A1 level which corresponds to low mean scores for their listening comprehension. Although the highest mean scores were obtained for phonological awareness followed by semantic awareness, then morphological awareness and syntactic awareness respectively, learners’ listening comprehension seemed to rely more on semantic competence than on other components. This suggests that EFL learners employ semantic competence the most when interpreting audio input. Previous studies suggest a similar conclusion. Fung and Macaro (2019) studied the relationship between linguistic competence and listening comprehension strategies used by secondary school learners. The findings revealed that the learners weigh more on translation strategies which implied that learners’ semantic competence was more accessed than other competence to comprehend what they are listening to. Moreover, Herrero (2017) claims that most learners tend to mentally translate individual words uttered to understand the meaning conveyed. It is also supported by Watthajarukiat, Chatupote and Sukseemuang (2012) as well as Namaziandost, Neisi, Mahdavirad and Nasri (2020) that EFL learners most frequently use translating or transferring the audio into their L1 for listening achievement.

The lack of correlation between syntactic competence and listening comprehension is in accordance with a previous study whose finding showed that the syntactic competence in EFL learners is inversed with listening comprehension (Mecartty, 2000). However, the finding of a differential effect of syntactic competence cannot completely lead to the conclusion that it has no relationship to listening comprehension. The fact that there is no significant correlation may be a result of the discrepancy between tests, the stream of continuity and coarticulation of the audio input or other possible factors. Thus, it should be noted that our interpretation of this result is preliminary and open to further discussion.

CONCLUSION AND LIMITATIONS

The current study has contributed to the field of psycholinguistics and other related fields by investigating the predictors for listening comprehension for providing further information on how components of linguistic competence relate to listening comprehension. In previous studies, the relationship between one component of linguistic competence and listening comprehension was clearly accounted for; however, the comparison of all components of linguistic competence in the identical context of listening comprehension remained ignored. Thus, the present study aimed to fill this gap.

Furthermore, the present study has provided pedagogical implications for the teaching and learning of listening comprehension. The finding of this study can contribute to listening education by showing that knowing the sorts of linguistic foundations promoting listening comprehension can be applied in developing pedagogy. The identification of specific types of competence that significantly trigger listening comprehension makes it possible to develop a comprehensive curriculum to help learners succeed more in listening comprehension. Emphasizing semantic competence which is a stronger predictor of listening comprehension presented in the current study may affect the contributions that updating and shifting made to learners’ L2 listening performance. Furthermore, the finding also benefits solving EFL learners’ listening comprehension difficulties caused by a deficiency in learners’ linguistic competence. A linguistic competence test can provide useful data for recognizing deficiencies in different aspects of subordinate competence (e.g., lexical and phrasal semantics in semantic competence) in order to be able to improve learners’ knowledge precisely.

Some limitations in conducting the online tests can be noticed in the current study, and these should be addressed in future investigations. Firstly, the selected software for linguistic competence assessment has hidden some anxiety for participants since online testing was new to them. Thus, providing a clear explanation and understanding of the test construct and process as well as the software used is important. The selected software contains a lack of time limit and inconvenient accessibility. Although it was easy to manage, the time-limit function was not available when the test in the current study was developed which entails the inability to control the time of the test. Moreover, in piloting, using the software sometimes obstructs test submission of participants who use IOS operation system which can solve by informing participants to use a web browser to open the link of the test instead of directly opening the software. Secondly, the use of online testing also confronts difficulties related to testing administration. Participants may be allowed virtually a limitless amount of time to complete tests provided outside of class which makes it difficult to proctor test performance that may lead to cheating. Hence, further studies should carefully consider this online testing drawback. Besides, the non-linguistic predictor missing in this study is a good candidate for further investigation, and the findings of the current study need to be replicated with different samples and testing methods.

ACKNOWLEDGEMENTS

My completion of the research paper could not have been accomplished without the support and encouragement of my advisor: Asst. Prof. Dr. Chomraj Patanasorn, as well as other teachers in the Faculty of Humanities and Social Sciences in Khon Kaen University including Asst. Prof. Kornwipa Poonpon, Asst. Prof. Sutida Ngonkum and Asst. Prof. Chongrak Liangpait. I also offer my sincere appreciation for my supportive friends who help me in the data collection process.

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APPENDIX

Appendix 1: Specification of Linguistic Competence and Listening Comprehension Test

Linguistic Competence Test consists of four subordinate tests including phonological awareness test, morphological awareness test, syntactic awareness test and semantic awareness test. The test specifications of each test are as below.

The phonological awareness test adapted from Venkatagiri and Levis (2007)

Tasks	No. of items	Time	Scoring (point)
1. Phonological blending	5	5 minutes	1 = correct; 0 = incorrect
2. Phonological manipulation	9	9 minutes	1 = correct; 0 = incorrect
3. Phonological segmentation	5	5 minutes	1 = correct; 0 = incorrect
4. Phonological sequencing	6	6 minutes	1 = correct; 0 = incorrect
5. Rhyming and alliteration	5	5 minutes	1 = correct; 0 = incorrect
6. Non-word reading	5	5 minutes	1 = correct no. of syllables and correct placement of stress; 0 point for incorrect
7. Phonological memory	5	5 minutes	1 = correct; 0 = incorrect
Total	40	40 minutes	40 points

The morphological awareness test adapted from Bian (2017)

Tasks	No. of items	Time	Scoring (point)
1. Morphological form	10	10 minutes	1 = correct; 0 = incorrect
2. Morphological formation	15	15 minutes	1 = correct; 0 = incorrect
3. Reading vocabulary	7	7 minutes	1 = correct; 0 = incorrect
4. Listening vocabulary	8	8 minutes	1 = correct; 0 = incorrect
Total	40	40 minutes	100 points

The syntactic awareness test adapted from Cain (2007)

Tasks	No. of items	Time	Scoring (point)
1. Language elements	10	10 minutes	1 = correct; 0 = incorrect
2. Situational responses	10	10 minutes	1 = correct; 0 = incorrect
3. Grammatical construction	20	20 minutes	1 = correct; 0 = incorrect
Total	40	40 minutes	40 points

The semantic awareness test adapted from Lehmann (2007)

Tasks	No. of items	Time	Scoring (point)
1. Lexical semantics	20	20 minutes	1 = correct; 0 = incorrect
2. Phrasal Semantics	20	20 minutes	1 = correct; 0 = incorrect
Total	40	40 minutes	40 points

The listening comprehension test adopted from dialangweb.lancaster.ac.uk

Tasks	No. of items	Time	Scoring (point)
1. Listening for detail	2	3 minutes	1 = correct; 0 = incorrect
2. Inferencing	8	17 minutes	1 = correct; 0 = incorrect
3. Identifying main idea	20	20 minutes	1 = correct; 0 = incorrect
Total	30	40 minutes	30 points

Modern Linguistic Technologies: Strategy for Teaching Translation Studies

Linguistics/TESL/Volume 13 No 4 2021

321 views

Bilous O¹, Mishchenko A², Datska T³, Ivanenko N⁴, Kit L⁵, Piankovska I⁶ & Vereshchak Y⁷

¹PhD, Full-Professor of German at the Department of Translation, Applied and General Linguistics, Dean of the School of Foreign Languages, Department of Translation, Applied and General Linguistics, the School of Foreign Languages, Volodymyr Vynnychenko Central Ukrainian State Pedagogical University, Ukraine.

²Phd, Full-Professor of German, Department of Translation, Applied and General Linguistics, the School of Foreign Languages, Volodymyr Vynnychenko Central Ukrainian State Pedagogical University, Ukraine.

³Doctor of Philosophy, Associate Professor, Department of the English Language and Methods of Teaching, Volodymyr Vynnychenko Central Ukrainian State Pedagogical University, Ukraine.

⁴Doctor of Philosophy, Associate Professor, Department of the English Language and Methods of Teaching, Volodymyr Vynnychenko Central Ukrainian State Pedagogical University, Ukraine.

⁵German Language Instructor, Department of Translation, Applied and General Linguistics, Volodymyr Vynnychenko Central Ukrainian State Pedagogical University, Ukraine.

⁶Doctor of Philosophy, Associate Professor, Head of the Department of the German Language and Methodology of Teaching, Volodymyr Vynnychenko Central Ukrainian State Pedagogical University, Ukraine.

⁷English Language Instructor, Department of Translation, Applied and General Linguistics, the School of Foreign Languages, Language Center Director, Volodymyr Vynnychenko Central Ukrainian State Pedagogical University, Ukraine.

Corresponding e-mail: gridina-98@bk.ru

Volume 13, Number 4, 2021 I Full-Text PDF

DOI: 10.21659/rupkatha.v13n4.65

Abstract

How often students use IT resources is a key factor in the acquisition of skills associated to the new technologies. Strategies aimed at increasing student autonomy need to be developed and should offer resources that encourage them to make use of computing tools in class hours. The analysis of the modern linguistic technologies, concerning intellectual language processing necessary for the creation and function of the highly effective technologies of knowledge operation was considered in the paper under consideration. Computerization of the information sphere has triggered extensive search for solving the problem of the use of natural language mechanisms in automated systems of various types. One of them was creating Controlled languages based on a set of features which made machine translation more refined. Triggered by the economic demand, they are not artificial languages like Esperanto, but natural simplified languages, in terms of vocabulary, grammatical and syntactic structures. More than ever, the tasks of modern computer linguistics behold creating software for natural language processing, information retrieval in large data sets, support of technical authors in the process of creating professional texts and users of computer technology, hence creating new translation tools. Such powerful linguistic resources as corpora of texts, terminology databases and ontologies may facilitate more efficient use of modern multilingual information technology. Creating and improving all methods considered will help make the job of a translator more efficient. One of the programs, CLAT does not aim at producing machine translation, but allows technical editors to create flawless, sequential professional texts through integrated punctuation and spelling modules. Other programs under consideration are to be implemented in Ukrainian translation departments. Moreover, the databases considered in the paper enable studying of the dynamics of the linguistic system and developing areas of applied research such as terminography, terminology, automated data processing etc. Effective cooperation of developers, translators and declarative institutes in the creation of innovative linguistic technologies will promote further development of translation and applied linguistics.

Keywords: computer linguistics, linguistic technology, teaching, machine translation, integrated translation tools, CLAT technology.

A Study on the New Design Thinking for Industrial Revolution 4.0, Requirements and Graduate Readiness

TESL/Volume 12 Number 4 2020

608 views

Swayamprabha Satpathy¹_, Kabita Kumari Dash² & Malvika Mohapatra³

¹Associate Professor, Shiksha “O” Anusandhan University, Bhubaneswar. Email: dr.swayam.prava@gmail.com

²Assistant Professor, Srusti Academy of Management, Bhubaneswar

³Assistant Professor, Shiksha “O” Anusandhan University, Bhubaneswar

Volume 12, Number 4, July-September, 2020 I Full Text PDF

DOI: 10.21659/rupkatha.v12n4.09

Abstract

The Fourth Industrial Revolution can be regarded as Industry 4.0 connected with the developments, innovative approaches and technological advancements held in the year 2011 at Germany. It is the amalgamation of many digital technologies such artificial intelligence (AI), robotics, Internet of Things (IoT) cloud computing, big data, 3D printing etc. The present study is qualitative in nature and focuses on graduate readiness, the challenges faced by the engineering students of SOA university, Bhubaneswar to meet the industry 4.0 requirements because technical degree is not only the gateway to their success in industry rather they should equip themselves with various soft skills like English language development, communication, personality development, leadership, critical thinking, problem solving and team building skills to meet the expectations of their employers. The objective of this study is to analyze the current education practices and the industry requirements and come out with best possible solutions for industry readiness of graduate engineers for a successful corporate career. The study has put some valuable insights on the problems faced by the 5^th semester students related to language acquisition and their readiness for future industrial demands. Furthermore, universities should also come out with appropriate suggestions and recommendations to enable graduate engineers for future industry readiness.

Keywords: English language, Communication, Industrial revolution 4.0, Graduates’ readiness, Employers Demand, Digital technology, Technical graduates

Teaching and Researching Reading in Indian Context

TESL/Volume 12 Number 2 2020

238 views

Megala M¹ & Anil Premraj J²

¹Research Scholar, ²Assistant Professor, Department of English, School of Social Science and Languages,Vellore Institute of Technology, Vellore. Email: megalamanisharaj@gmail.com

Volume 12, Number 2, April-June, 2020 I Full Text PDF

DOI: 10.21659/rupkatha.v12n2.17

Abstract

The importance placed on reading skill emerges from the necessity of performing well that starts from primary stage of learning to the workplace scenario. One of the first things children are pressurized to do at early schooling is ‘Learn to Read’ and of course that remarks their progressive transformation to become an expert in reading. Using descriptive method of research, the study traces the importance and efforts taken by second language teachers and students towards the development of reading skills from primary class to university education in Indian context. It also addresses the existing lag in English language education, necessity of infusing the requirement of specially designed curriculum, and to fulfil the need of learners especially who felt difficulty in reading. The study suggested skill-based instruction in detail at each level as a remedy for rectifying deficits in reading.

Keywords: ESL, Subskills instruction, Reading skill, NCERT.

Research Engagement of Foreign Language Teachers among Select Higher Education Institutions in Malaysia

Higher Education & Research/TESL/Volume 12 Number 1 2020

252 views

Sanil S Hishan¹, Suresh Ramakrishnan¹,Nur Naha binti Abu Mansor¹

¹Azman Hashim International Business School (AHIBS), Universiti Teknologi Malaysia, Malaysia. Corresponding Author: hishanssanil@gmail.com

Volume 12, Number 1, January-March, 2020 I Full Text PDF

DOI: 10.21659/rupkatha.v12n1.42

Abstract

This paper aims to add to established awareness on the extent of research capacity, theoretical ideas, and views on the challenges to their study involvement in Malaysia’s select universities. It used a hybrid system of concise quantitative and qualitative projects for 62 foreign language students. Data gathering methodologies such as questionnaires, individual and group interviews were used. Results from the quantitative portion of the paper showed that international teachers displayed a modest degree of research ability while they hold optimistic views on the principles of study as a method to offer answers to educational challenges transcending teacher subject awareness, pedagogical and instructional abilities, and optimistic student learning outcomes. Similarly, qualitative findings found that the barriers to international teachers ‘ participation in research are embodied in lack of time to do work and lack of study writing skills. Moreover, networking incentive and career growth are driving factors for international teachers in Malaysia. The research poses implications on instructional management among curriculum designers, scholars, and school administrators among universities in Malaysia to improve academic culture and professional development opportunities among international teachers in terms of research capability and participation.

Keywords – Research Capabilities, Foreign Teachers, Knowledge generation, Research, Educational Management, Research Productivity

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Examining Teacher Competencies in Content and Language Integrated Learning: Professional Profiles and Ways Forward

The Association between Linguistic Competence Components and Listening Comprehension of Thai EFL Learners

Modern Linguistic Technologies: Strategy for Teaching Translation Studies

A Study on the New Design Thinking for Industrial Revolution 4.0, Requirements and Graduate Readiness

Teaching and Researching Reading in Indian Context

Research Engagement of Foreign Language Teachers among Select Higher Education Institutions in Malaysia

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