Abstract

The English Language Teacher Learning Scale (ELTLS) has been tested in different academic fields worldwide. However, there is no evidence about its validation in Pakistan. This study reports on validation of ELTLS in Pakistan. The 49 items scale was tested on a sample of 112 teachers from pharmacy departments. The process of validation consisted of two stages. First, the scale was piloted to check reliability Second. Exploratory factor analysis was used to identify the factor structure of the scale. The four factors are teacher cognition, teacher emotion, teacher motivation, and contextual variables. The Principal Component Analysis was applied with orthogonal Varimox rotation method to test the four-factor scale. The results provided evidence for the reliability and validity of the scale. Hence, the scale may be used for assessing language teaching and learning among teachers and students in the field of pharmacy. It is recommended that ELTLS may be tested in other contexts.

Key Words

English Language Teaching, Higher Education, Exploratory Analysis, Psychometric Testing

Introduction

Effective communication is one of the most sought after and essential professional skills needed for individuals to be successful in the current 21st-century job market (Hulme, Snowling, West, Lervåg, & Melby-Lervåg, 2020). Pharmacy graduates also need to have quality language skills to perform better in the current competitive pharmacy professionals (Grabowski, 2015; Mesquita et al., 2010; Wallman, Vaudan, & Sporrong, 2013). The importance of English Language Teaching-learning cannot be disregarded in the reformation and development of language skills among pharmacy graduates (Cook, 2016; Stanley & Murray, 2013). Hence, the importance of using English language competency is very much focused on current pharmaceutical settings (Wallman et al., 2013). However, despite this realization, little evidence exists pertaining to psychometric validation of the ELTLS instrument in the field of pharmacy. Psychometric validation means validating a measuring instrument and assessing the reliability and validity of the measurement (Lee & Drajati, 2019; Oxford & Burry-Stock, 1995). The psychometric properties of a measuring instrument relate to the construction and validation of the assessment instrument. In this study, psychometric properties of an instrument are the reliability and validity of the assessment instrument used to evaluate the perspectives of principals, teachers and students in VTIs of Pakistan. The current study addresses this gap by assessing the psychometric features in the field of pharmacy education. The current existing adds to literature related to the context of language teaching and learning by extending the application of ELTLS into the context of pharmacy education. 

The existing research on English language teaching and learning in relation to pharmacy education does not include established scales, and it only assessed one aspect of student language development such as attitude towards patients (Adrian, Zeszotarski, & Ma, 2015; Coroban, 2019; Mesquita et al., 2010).

To remedy this gap, some researchers have used different scales in different social science fields for assessing the abilities of students about learning of English language skills(Echeverri, Brookover, & Kennedy, 2013; Syakur, Zainuddin, & Hasan, 2020).  However, these researchers argue that the scale results cannot be generalized to different socio-economic background, cultural contexts due to variations in language teaching and learning outcomes and experiences (Al-Sobhi & Preece, 2018; Tenney, Paiva, & Wang, 2020). Majority of the existing research studies related to the application of scales for assessing language teaching and learning have generally been limited to the traditional social sciences field.  These measures do not effectively cover the issues of language teaching, and learning in the field of pharmacy education rather covered alternative instructional delivery. Even the alternative did not include pharmacy concepts in the relation of language learning and teaching (Adrian et al., 2015; Dang, Truong, & Wade, 2019; Syakur, Junining, & Mubarok, 2020). This study specifically contributes to this gap by validating the ELTLS instrument for assessing the English language teaching and learning outcomes of students and also the factors influencing language teaching and learning implementation in the field of pharmacy education from developing country perspective. The results of this study contribute to the knowledge base of language teaching and learning research and the future design and implementation of language teaching practices. In contrast to previous studies which focused on the perspectives of students or teachers, this current study included both participants’ perspectives for the purpose of effectively addressing the long-standing gap in the methodological issues of English language teaching and learning in the field of pharmacy education by using valid measures developed to assess the perspectives of teachers and students in pharmacy institutes of higher education of Pakistan.

Literature Review

Developing an instrument representing different characteristics of teacher learning in ELT context for the current pharmacy education is important. There is a need to provide better language development opportunities for pharmacy graduates to enable them to perform as quality medical professionals(Kimberlin, 2006; Luiz Adrian, Zeszotarski, & Ma, 2015). Many studies have reported the application of different language-related scales to measure the students’ performance level in pharmacy (Bradshaw, Tomany-Korman, & Flores, 2007; Dilworth, Mott, & Young, 2009; Schwappach, Massetti, & Gehring, 2012). However, there is a lack of highly validated and reliable scales which could assess language teaching skills of the pharmacy graduates in the field of pharmacy. This issue exists in Pakistan, which possesses a large pharmacy industry. Hence, there is a need to develop and validate ELT related tools in the field of pharmacy. Furthermore, for the purpose of compensating the lack of an existing tool for measuring student’ language learning in ELT context, the existing tools need to be improvised and validated for assessing teacher learning in ELT in pharmacy education. Developing instrument and ensuring its reliability and validity is a challenging task in psychometric researchers (Aliakbari & Malmir, 2017; Hartmann & Siegrist, 2018). Standardized scales are important measuring tools for obtaining necessary information about service-learning implementation, programme evaluation and outcomes (Delgado-Ballester, Munuera-Aleman, & Yague-Guillen, 2003; Gagné et al., 2010). They can be easily coded and analysed. An important point about a questionnaire is related to its validity and reliability that how it measures students’ attitudes and skills and how accurately do students do self-evaluation on the basis of the questionnaire and its constructs (Crutzen & Peters, 2017; Gagné et al., 2015).

In short, the above discussion and analysis of existing literature show that there is a lack of systematically developed instrument to test English Language Teacher Learning Scale in pharmacy context, especially in Pakistan. For a better understanding of the impact of language teaching to pharmacy graduates and their language learning experiences, it is essential to develop an instrument that helps in exploring the issues, factors and barriers to the application of such scales and their validation in pharmacy field. Researchers argue that good instruments help in identifying key beliefs, attitudes and perceptions on the target experiences(Breaugh & Colihan, 1994; Silva, do Céu Taveira, Marques, & Gouveia, 2015).  The discussion given above shows that most of the existing scales available are either developed in the developed world context or does not properly cover all the psychometric principles of scale development in terms of reliability and validity. Although there were some existing measures developed by earlier researchers in the field of pharmacy to capture language learning experiences of learners, however, these measures focused either on language learning outcomes from students’ perspective in the developed world context. These measures lacked the ability to measure the evidence for its use in pharmacy context, which is an important area—the existing scales which did not effectively meet the requirements of this study.




Research Objectives

1. To validate the four-factor structure of the English Language Teacher Learning Scale (ELTLS) through exploratory factor analysis.

2. To determine the reliability of the scale in the context of the pharmacy field.

Methods and Materials

Sample

This descriptive survey study was designed for assessing the ELTLS in the context of the pharmaceutical setting of Pakistan.  For data collection, all teachers from pharmacy departments of universities from all over Pakistan were approached out of which 112 teachers showed a willingness to participate in the study by giving sharing their perceptions through a survey questionnaire distributed to them. The participants were informed about the purpose, and the objectives of the study and their consent were also obtained prior to data collection.

 

Measure

The English Language Teacher Learning Scale (ELTLS) was used for data collection. The scale consisted of 50 items and four sub-scales, as shown in Table 1.

 

Table 1. Sub-Scales of ELTLS

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S. No width="216" valign="top"> Sub-scales width="201" valign="top"> Number of items

1 width="216" valign="top"> Subscale one width="201" valign="top"> Ten items

2 width="216" valign="top"> Subscale two width="201" valign="top"> Ten items

3 width="216" valign="top"> Subscale three width="201" valign="top"> Eleven items

4 width="216" valign="top"> Subscale four width="201" valign="top"> Nineteen items

width="216" valign="top"> Total width="201" valign="top"> Fifty items

 

Data Screening

Skewness and kurtosis tests were conducted to check the data normality(Doherty, Mitchell, & O'Neill, 2011). The value of kurtosis for the items was within an acceptable range of ?3?, and the value of skewness was also greater than?8? which was also within the acceptable range (Das & Imon, 2016; White, 2003). In addition, we also applied Shapiro-Wilk test to further ensure the normality of data which showed 0.92, p >.05, indicating a normal distribution in the groups. No prominent issue was found in the data.

 

Reliability and Validity 

A pilot test was done for checking inter-item consistencies among all items and the variables the ELTLS (Cameron & MacKeigan, 2012). This helped to select and determine the difficulty level of the items of the scale. No items were found redundant, repetitive or ambiguous based on the perceptions of the participants. Cronbach’s alpha test was conducted to check the reliability of the scale, which was quite high being above .70 in all subscales, as shown in Table 2.

Table 2. Reliability Statistics for ELTLS

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S. No width="239" valign="top"> Sub-Scales width="126"> Number of Items width="102"> Alpha

1 width="239" valign="top"> Teacher cognition and belief width="126"> 9 width="102"> .75

2 width="239" valign="top"> Teacher emotions width="126"> 10 width="102"> .79

3 width="239" valign="top"> Teacher motivation width="126"> 11 width="102"> .93

4 width="239" valign="top"> Contextual variables width="126"> 18 width="102"> .87

width="239" valign="top"> Total width="126"> 49 width="102"> .95

Results

The main aim of this study was to explore and validate the dimension of ELTLS instrument in the context of pharmacy education. Sample adequacy was determined through various statistical applications, as discussed below. 

 

Exploratory Factor Analysis (EFA)

Forty-nine item-scale was subjected to factor analysis on 84 respondents who participated in the study. EFA was used based on varimax method and principal component analysis (PCA) to explore the factor structure.

 

Table 3. Sample Adequacy Test

> > >

KMO Measure width="74"> .91

BTS measure width="263"> Approximation of. Chi-Square width="74"> 1728.522

DF width="74"> 148

Level of significance width="74"> .000

 

The above table shows KMO value .91, which indicates that the sample is adequate for conducting factor analysis. Bartlett’s Test of Sphericity is .000 significant showing a strong relationship among the variables of the study which further supports the factor analysis

 

Table 4. Communalities for Extraction

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Items No width="197"> Initial width="207"> Extraction

1 width="197"> 1.000 width="207"> .541

2 width="197"> 1.000 width="207"> .639

3 width="197"> 1.000 width="207"> .597

4 width="197"> 1.000 width="207"> .463

5 width="197"> 1.000 width="207"> .423

6 width="197"> 1.000 width="207"> .098

7 width="197"> 1.000 width="207"> .477

8 width="197"> 1.000 width="207"> .575

9 width="197"> 1.000 width="207"> .485

10 width="197"> 1.000 width="207"> .644

11 width="197"> 1.000 width="207"> .509

12 width="197"> 1.000 width="207"> .718

13 width="197"> 1.000 width="207"> .643

14 width="197"> 1.000 width="207"> .709

15 width="197"> 1.000 width="207"> .563

16 width="197"> 1.000 width="207"> .556

17 width="197"> 1.000 width="207"> .410

18 width="197"> 1.000 width="207"> .493

19 width="197"> 1.000 width="207"> .690

20 width="197"> 1.000 width="207"> .702

21 width="197"> 1.000 width="207"> .589

22 width="197"> 1.000 width="207"> .642

23 width="197"> 1.000 width="207"> .660

24 width="197"> 1.000 width="207"> .419

25 width="197"> 1.000 width="207"> .522

26 width="197"> 1.000 width="207"> .613

27 width="197"> 1.000 width="207"> .594

28 width="197"> 1.000 width="207"> .664

29 width="197"> 1.000 width="207"> .712

30 width="197"> 1.000 width="207"> .721

31 width="197"> 1.000 width="207"> .728

32 width="197"> 1.000 width="207"> .670

33 width="197"> 1.000 width="207"> .652

34 width="197"> 1.000 width="207"> .688

35 width="197"> 1.000 width="207"> .726

36 width="197"> 1.000 width="207"> .689

37 width="197"> 1.000 width="207"> .662

38 width="197"> 1.000 width="207"> .712

39 width="197"> 1.000 width="207"> .749

40 width="197"> 1.000 width="207"> .564

41 width="197"> 1.000 width="207"> .670

42 width="197"> 1.000 width="207"> .652

43 width="197"> 1.000 width="207"> .688

44 width="197"> 1.000 width="207"> .726

45 width="197"> 1.000 width="207"> .689

46 width="197"> 1.000 width="207"> .662

47 width="197"> 1.000 width="207"> .712

48 width="197"> 1.000 width="207"> .749

49 width="197"> 1.000 width="207"> .564

 

Table 4 shows the communalities for extraction for the variables expressing the percentage of variance explained by the extracted factors. The table shows the variable of teaching material has the highest .749% variance, which is explained by the extracted factors in the commonalities list. PCA method was used for the purpose of extraction.

 

Table 5. Total Variance Explained

> > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >

Component width="233" colspan="3"> Initial Eigenvalues width="220" colspan="3"> Extraction Sums of Squared Loadings

Total width="89"> % of Variance width="84"> Cumulative % width="57"> Total width="78"> % of Variance width="84"> Cumulative %

1 width="61"> 20.665 width="89"> 42.173 width="84"> 42.173 width="57"> 20.665 width="78"> 42.173 width="84"> 42.173

2 width="61"> 3.994 width="89"> 8.151 width="84"> 50.324 width="57"> 3.994 width="78"> 8.151 width="84"> 50.324

3 width="61"> 2.688 width="89"> 5.485 width="84"> 55.810 width="57"> 2.688 width="78"> 5.485 width="84"> 55.810

4 width="61"> 2.076 width="89"> 4.238 width="84"> 60.047 width="57"> 2.076 width="78"> 4.238 width="84"> 60.047

5 width="61"> .985 width="89"> .938 width="84"> 63.485 width="57">   width="78">   width="84">

6 width="61"> .966 width="89"> .9196 width="84"> 66.681 width="57">   width="78">   width="84">

7 width="61"> .877 width="89"> .911 width="84"> 69.492 width="57">   width="78">   width="84">

8 width="61"> .755 width="89"> .962 width="84"> 72.054 width="57">   width="78">   width="84">

9 width="61"> .714 width="89"> .977 width="84"> 74.530 width="57">   width="78">   width="84">

10 width="61"> .783 width="89"> .910 width="84"> 76.740 width="57">   width="78">   width="84">

11 width="61"> .760 width="89"> .859 width="84"> 78.699 width="57">   width="78">   width="84">

12 width="61"> .665 width="89"> .866 width="84"> 80.465 width="57">   width="78">   width="84">

13 width="61"> .612 width="89"> .858 width="84"> 82.123 width="57">   width="78">   width="84">

14 width="61"> .659 width="89"> .850 width="84"> 83.673 width="57">   width="78">   width="84">

15 width="61"> .615 width="89"> .758 width="84"> 85.131 width="57">   width="78">   width="84">

16 width="61"> .614 width="89"> .753 width="84"> 86.384 width="57">   width="78">   width="84">

17 width="61"> .566 width="89"> .754 width="84"> 87.538 width="57">   width="78">   width="84">

18 width="61"> .558 width="89"> .739 width="84"> 88.677 width="57">   width="78">   width="84">

19 width="61"> .521 width="89"> .763 width="84"> 89.740 width="57">   width="78">   width="84">

20 width="61"> .483 width="89"> .785 width="84"> 90.725 width="57">   width="78">   width="84">

21 width="61"> .426 width="89"> .670 width="84"> 91.595 width="57">   width="78">   width="84">

22 width="61"> .410 width="89"> .637 width="84"> 92.432 width="57">   width="78">   width="84">

23 width="61"> .399 width="89"> .614 width="84"> 93.245 width="57">   width="78">   width="84">

24 width="61"> .335 width="89"> .684 width="84"> 93.929 width="57">   width="78">   width="84">

25 width="61"> .318 width="89"> .649 width="84"> 94.577 width="57">   width="78">   width="84">

26 width="61"> .309 width="89"> .630 width="84"> 95.207 width="57">   width="78">   width="84">

27 width="61"> .280 width="89"> .571 width="84"> 95.778 width="57">   width="78">   width="84">

28 width="61"> .255 width="89"> .521 width="84"> 96.299 width="57">   width="78">   width="84">

29 width="61"> .235 width="89"> .480 width="84"> 96.779 width="57">   width="78">   width="84">

30 width="61"> .228 width="89"> .465 width="84"> 97.244 width="57">   width="78">   width="84">

31 width="61"> .199 width="89"> .406 width="84"> 97.650 width="57">   width="78">   width="84">

32 width="61"> .196 width="89"> .400 width="84"> 98.051 width="57">   width="78">   width="84">

33 width="61"> .178 width="89"> .364 width="84"> 98.415 width="57">   width="78">   width="84">

34 width="61"> .176 width="89"> .358 width="84"> 98.773 width="57">   width="78">   width="84">

35 width="61"> .140 width="89"> .286 width="84"> 99.060 width="57">   width="78">   width="84">

36 width="61"> .125 width="89"> .254 width="84"> 99.314 width="57">   width="78">   width="84">

37 width="61"> .109 width="89"> .222 width="84"> 99.536 width="57">   width="78">   width="84">

38 width="61"> .199 width="89"> .203 width="84"> 99.738 width="57">   width="78">   width="84">

39 width="61"> .173 width="89"> .149 width="84"> 99.888 width="57">   width="78">   width="84">

40 width="61"> .155 width="89"> .112 width="84"> 100.000 width="57">   width="78">   width="84">

41 width="61"> .132 width="89"> .133 width="84"> 100.000 width="57">   width="78">   width="84">

42 width="61"> .102 width="89"> .108 width="84"> 100.000 width="57">   width="78">   width="84">

43 width="61"> .152 width="89"> .143 width="84"> 100.000 width="57">   width="78">   width="84">

44 width="61"> .159 width="89"> .112 width="84"> 100.000 width="57">   width="78">   width="84">

45 width="61"> .118 width="89"> .166 width="84"> 100.000 width="57">   width="78">   width="84">

46 width="61"> .133 width="89"> .191 width="84"> 100.000 width="57">   width="78">   width="84">

47 width="61"> .032 width="89"> .020 width="84"> 100.000 width="57">   width="78">   width="84">

48 width="61"> .037 width="89"> .027 width="84"> 100.000 width="57">   width="78">   width="84">

49 width="61"> .018 width="89"> .045 width="84"> 100.000 width="57">   width="78">   width="84">

 

Table 5 indicates the number of factors extracted using the PCA method. Based on EFA, four crucial factors emerged: teacher cognition and belief, teacher emotions, teacher motivation, and contextual realities. The first component ‘teacher cognition and belief’ has the highest variance (42.17 %) of the total variance. The second factor ‘teacher emotions’ explains 8.15% of the total variance. The third factor ‘teacher motivation’ explains 5.48 of the total variances. The fourth variable ‘contextual realities’ explains 4.23 in the variance. The four dimensions collectively explain 60.04 of the total variances.

 

Table 6

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S. No width="517" colspan="4"> Component

1 width="66"> 2 width="169"> 3 width="84"> 4

1 width="198"> .542 width="66">   width="169">   width="84">

2 width="198"> .605 width="66">   width="169">   width="84">

3 width="198"> .526 width="66">   width="169">   width="84">

4 width="198"> .580 width="66">   width="169">   width="84">

5 width="198"> .584 width="66">   width="169">   width="84">

6 width="198"> .438 width="66">   width="169">   width="84">

7 width="198"> .685 width="66">   width="169">   width="84">

8 width="198"> .696 width="66">   width="169">   width="84">

9 width="198"> .570 width="66">   width="169">   width="84">

10 width="198"> .701 width="66">   width="169">   width="84">

11 width="198">   width="66"> .534 width="169">   width="84">

12 width="198">   width="66"> .729 width="169">   width="84">

13 width="198">   width="66"> .769 width="169">   width="84">

14 width="198">   width="66"> .797 width="169">   width="84">

15 width="198">   width="66"> .619 width="169">   width="84">

16 width="198">   width="66"> .696 width="169">   width="84">

17 width="198">   width="66"> .671 width="169">   width="84">

18 width="198">   width="66"> .679 width="169">   width="84">

19 width="198">   width="66"> .623 width="169">   width="84">

20 width="198">   width="66">   width="169"> .785 width="84">

21 width="198">   width="66">   width="169"> .729 width="84">

22 width="198">   width="66">   width="169"> .772 width="84">

23 width="198">   width="66">   width="169"> .786 width="84">

24 width="198">   width="66">   width="169"> .584 width="84">

25 width="198">   width="66">   width="169"> .419 width="84">

26 width="198">   width="66">   width="169"> .641 width="84">

27 width="198">   width="66">   width="169"> .650 width="84">

28 width="198">   width="66">   width="169"> .750 width="84">

29 width="198">   width="66">   width="169"> .774 width="84">

30 width="198">   width="66">   width="169"> .789 width="84">

31 width="198">   width="66">   width="169">   width="84"> .776

32 width="198">   width="66">   width="169">   width="84"> .712

33 width="198">   width="66">   width="169">   width="84"> .741

34 width="198">   width="66">   width="169">   width="84"> .711

35 width="198">   width="66">   width="169">   width="84"> .639

36 width="198">   width="66">   width="169">   width="84"> .718

37 width="198">   width="66">   width="169">   width="84"> .634

38 width="198">   width="66">   width="169">   width="84"> .845

39 width="198">   width="66">   width="169">           width="84"> .512

40 width="198">   width="66">   width="169">   width="84"> .685

41 width="198">   width="66">   width="169">   width="84"> .651

42 width="198">   width="66">   width="169">   width="84"> .634

43 width="198">   width="66">   width="169">   width="84"> .711

44 width="198">   width="66">   width="169">   width="84"> .718

45 width="198">   width="66">   width="169">   width="84"> .634

46 width="198">   width="66">   width="169">   width="84"> .545

47 width="198">   width="66">   width="169">   width="84"> .551

48 width="198">   width="66">   width="169">   width="84"> .622

49 width="198">   width="66">   width="169">   width="84"> .685

 

Table 6 shows the factor loadings for the variables based on the rotation method. Variables below .40 were suppressed in the analysis. The rotated component matrix showed 49 items scale loading on four components:10 variables (items) from 1-10 loaded on factor ‘teacher cognition and belief’; Items 11-19 loaded on factor ‘teacher emotions’; Items 20-30 loaded on factor ‘teacher motivation’; Items 31-49 loaded on factor ‘contextual realities.

 

Table 7. Factor Loadings, Inter Item Total Correlation, Mean and Standard Deviation

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Item No width="156" valign="top"> Factor width="66"> Loadings width="167"> Inter Item Total Correlations width="48"> MEAN width="40"> SD

1 width="156" rowspan="10"> Teacher Cognition and Belief width="66"> .542 width="167"> .683 width="48"> 2.37 width="40"> .975

2 width="66"> .605 width="167"> .714 width="48"> 2.57 width="40"> .959

3 width="66"> .526 width="167"> .725 width="48"> 2.39 width="40"> .970

4 width="66"> .580 width="167"> .648 width="48"> 3.01 width="40"> 1.223

5 width="66"> .584 width="167"> .593 width="48"> 2.32 width="40"> .944

6 width="66"> .438 width="167"> .411 width="48"> 3.78 width="40"> .974

7 width="66"> .685 width="167"> .454 width="48"> 2.38 width="40"> .909

8 width="66"> .696 width="167"> .563 width="48"> 2.54 width="40"> .968

9 width="66"> .570 width="167"> .660 width="48"> 3.32 width="40"> 1.060

10 width="66"> .701 width="167"> .616 width="48"> 2.41 width="40"> .986

11 width="156" rowspan="9"> Teacher Emotions width="66"> .534 width="167"> .612 width="48"> 2.45 width="40"> .975

12 width="66"> .729 width="167"> .692 width="48"> 2.34 width="40"> .993

13 width="66"> .769 width="167"> .542 width="48"> 2.14 width="40"> .873

14 width="66"> .797 width="167"> -.608 width="48"> 3.79 width="40"> .978

15 width="66"> .619 width="167"> .642 width="48"> 2.74 width="40"> 1.042

16 width="66"> .696 width="167"> .547 width="48"> 2.44 width="40"> 1.018

17 width="66"> .671 width="167"> .531 width="48"> 2.46 width="40"> .945

18 width="66"> .679 width="167"> .595 width="48"> 2.30 width="40"> .899

19 width="66"> .623 width="167"> .737 width="48"> 2.73 width="40"> .943

20 width="156" rowspan="11"> Teacher Motivation width="66"> .785 width="167"> .717 width="48"> 2.86 width="40"> 1.135

21 width="66"> .729 width="167"> .658 width="48"> 2.46 width="40"> .975

22 width="66"> .772 width="167"> .713 width="48"> 2.57 width="40"> .903

23 width="66"> .786 width="167"> .712 width="48"> 2.77 width="40"> .989

24 width="66"> .584 width="167"> .564 width="48"> 2.83 width="40"> .973

25 width="66"> .519 width="167"> .572 width="48"> 2.45 width="40"> .929

26 width="66"> .641 width="167"> .728 width="48"> 2.46 width="40"> .960

27 width="66"> .650 width="167"> .737 width="48"> 2.41 width="40"> .942

28 width="66"> .750 width="167"> .755 width="48"> 2.59 width="40"> .998

29 width="66"> .774 width="167"> .767 width="48"> 2.54 width="40"> .975

30 width="66"> .789 width="167"> .769 width="48"> 2.61 width="40"> 1.155

31 width="156" rowspan="19"> Contextual Realities width="66"> .776 width="167"> .780 width="48"> 2.57 width="40"> .920

32 width="66"> .712 width="167"> .733 width="48"> 2.55 width="40"> .926

33 width="66"> .741 width="167"> .717 width="48"> 2.80 width="40"> 1.122

34 width="66"> .711 width="167"> .478 width="48"> 3.19 width="40"> 1.137

35 width="66"> .639 width="167"> .733 width="48"> 2.40 width="40"> .909

36 width="66"> .718 width="167"> .777 width="48"> 2.73 width="40"> 1.057

37 width="66"> .634 width="167"> .746 width="48"> 2.75 width="40"> .961

38 width="66"> .845 width="167"> .505 width="48"> 2.59 width="40"> .957

39 width="66"> .512 width="167"> .438 width="48"> 3.55 width="40"> 1.153

40 width="66"> .685 width="167"> .364 width="48"> 1.93 width="40"> .930

41 width="66"> .651 width="167"> .733 width="48"> 2.55 width="40"> .926

42 width="66"> .634 width="167"> .717 width="48"> 2.80 width="40"> .922

43 width="66"> .711 width="167"> .578 width="48"> 3.19 width="40"> 1.137

44 width="66"> .718 width="167"> .733 width="48"> 2.40 width="40"> .909

45 width="66"> .634 width="167"> .777 width="48"> 2.73 width="40"> .957

46 width="66"> .545 width="167"> .746 width="48"> 2.75 width="40"> 1.061

47 width="66"> .551 width="167"> .505 width="48"> 2.59 width="40"> .957

48 width="66"> .622 width="167"> .538 width="48"> 3.55 width="40"> 1.153

49 width="66"> .685 width="167"> .464 width="48"> 1.93 width="40"> .930

 

Table 7 shows that loadings for the first factor - ‘teacher cognition and belief’ (items 1-10) has loadings ranging from.438 to .701, which showed a good correlation among the variables. The mean for these variables ranged from2.34 to 3.01, and lower standard deviation showed homogeneity in the responses for this factor. Loadings for the second factor - ‘teacher emotion’ (items 11-19) has loadings which ranged from .534 to .797 showed a good correlation among the variables. The mean for these variables ranged from 2.14 to 3.79, and the low standard deviation also indicated a strong homogeneity in the responses for this factor. The third factor -‘teacher emotion’ (items 20-31) has loadings which ranged from .519 to .789 indicated a good correlation. The mean for these variables ranged from 2.41 to 3.19, and the low standard deviation showed strong homogeneity in the responses for this factor. Loadings for the fourth factor - ‘contextual realities’ (items 31-49) has loadings ranged from .614 to .845, which indicated a strong correlation among the variables. The mean for these variables ranged from 2.40 to 3.55, and the low standard deviation showed a strong homogeneity among the responses of the factor. 

Discussion

Health professionals are required to be highly prepared for addressing the ever-increasing needs of patients and desperate population because they encounter a diverse community in the interconnected world. The role of the English language is also increasing as health professionals alongside as the medium of communication between health professionals and the patients worldwide. Hence, they need to be highly effective in communication skills, especially the English language in the current health market. The aim of this paper was to determine the psychometric features of ELTLS in the field of pharmacy education in the  Pakistani context. The field of pharmacy supports the development of English language communication among students regarding their interaction with a global patient community. The global pharmacy standards also support the development of language skills, especially English, as a means of communication between patients and professionals.  According to the world sustainable development goals, language competency is an essential skill needed for both teachers and students in all fields of education, and effective communication is considered to be the most coveted and sought-after professionals’ skills in the 21st-century job market. This skill is considered a highly desirable skill for students in order to become a lifelong learner and also a useful professional. This also confirms the health education policy that fully supports the promotion of language skills among pharmacy students on a priority basis. The scale was purposefully developed to assess teacher’s language teaching and to learn for promoting language skills of pharmacy graduates. 

The scale was found to be highly reliable for measuring language teaching and learning in many other fields of education, such as social sciences and nursing. However, there was little evidence of its application and validation in the field of pharmacy in Pakistan. Findings of the present research showed overall higher reliability for the scale, which was at an acceptable level providing sufficient evidence with good reliability among high education teachers and pharmacy students in Pakistani universities. Additionally, the Cronbach’s alpha of all the four sub-scales in the instrument was also above .70, which is also an acceptable level for a scale to be truly reliable. In earlier studies, the reliability level of the scale was below this threshold point. However, this study provided the evidence having stronger reliability coefficient. The variability in the data might have contributed to this. It is predicted that future applications of the scale in a different field may bring different results. Hence, future work is recommended for assessing reliability and concurrent validity of the scale and its sub-scales in other fields using a large sample base. Against the estimation of previous studies, the actual reliability evidence of the ELTLS was found higher in the context of pharmacy. Hence, it is stated that the instrument can be highly useful for assessing language teaching and learning not only among teachers but also students in other fields of education. Thus, ELTLS is recommended to explore language competencies among pharmacy students and also language teaching capabilities of teachers. This study confirmed the utility of the instrument to evaluate language skills and proficiency assessment among teachers and students in the field of pharmacy.  

Although the ELTLS was found to be highly reliable and valid scale for assessing English language teaching and learning abilities of teachers and its application for promotion of language skills among pharmacy professionals in the Pakistani context, however, for data collection, the scale was administered to participants from universities in one province. It is possible that the results may be reliable and valid if used for data collection from other provinces due to high cultural, geographical and socio-economic variations. Therefore, it is suggested that in future studies, the instrument may be used for data collection in other provinces for more comprehensive and diverse results. Future validation studies may opt for larger samples and gender perspectives for getting more robust evidences for its reliability and validity. Confirmation factor analysis may also be used for construct validation of the instrument.  In this study, the ELTLS was used as a post-measuring scale to assess teachers’ English language teaching and to learn to pharmacy students in higher education institutions in Khyber Pakhtunkhwa Pakistan. The time and socio-linguistics variability might have affected the process of data collection and its results. Therefore, it is suggested that future studies should focus on a more focused sample in terms of sociolinguistic aspects. Students’ perspectives, in terms of gender, could be another area to look at while collecting data. This will provide more realistic data related to teachers’ language teaching and learning in other fields of study using the current ELTLS instrument.  

Testing and validating the psychometric features of ELTLS in the field of pharmacy education was important due to its worldwide application and its importance for the language teachers in all educational settings. It was important to validate the 49 items scale in the Malaysian context to further improve the scale due to the importance of effective language proficiency for the respective teachers.The analysis of ELTLS revealed a four-factor model using varimax rotation. These factors were teacher cognition and belief, teacher emotion, teacher motivation, and contextual realities.The EFA approach applied to determine the psychometric features of the scale showed that the four-factor structure of ELTLS is a reliable and valid scale that can be used across disciplines and cultures. The ELTLS could also be used to assess pharmacy teachers’ attitude towards language learning in the field of pharmacy. The results of the study further revealed that the scale could be used for assessing the attitude of both male and female teachers about the importance of language and its application in pharmacy. Pharmacy teachers may also use this scale to modify the pharmacy education programs across the countries for the improvement of effective language use among the pharmacy students. 

Future Direction

Based on the findings of the present, it is recommended that further research should test the psychometrics of the current scale in other fields and contexts. Future studies could be conducted using confirmatory factor analysis in order to test the hypothesized model of the present four-factor structure. The results of this research study are surely hoped to encourage language researchers to conduct further studies and teachers of English language for considering the scale for enhancing language skills of pharmacy students. Since the results of the present research were representative of a smaller group of public sector higher education institutions based on a convenience sample approach. Hence, the results have limited generalizability which requires more robust studies in the future. The findings of the current study support the usefulness of ELTLS as a reliable and valid scale. It is also a psychometrically sound measure for assessing language learning among pharmacy students. A stronger four-factor model emerged in the context of Pakistani pharmaceutical field. Based on EFA testing for the four factors dimensional scale, it is suggested that the results of this study may be tested in another educational fieldd to further improve the psychometric features of the scale. 

References

• Adrian, J. A. L., Zeszotarski, P., & Ma, C. (2015). Developing pharmacy student communication skills through role-playing and active learning. American journal of pharmaceutical education, 79(3).
• Al-Sobhi, B. M. S., & Preece, A. S. (2018). Teaching English speaking skills to the Arab students in the Saudi school in Kuala Lumpur: Problems and solutions. International Journal of Education and Literacy Studies, 6(1), 1-11.
• Aliakbari, M., & Malmir, B. (2017). Development and validation of an English language teacher learning scale. Cogent Education, 4(1), 1292613.
• Bradshaw, M., Tomany-Korman, S., & Flores, G. (2007). Language barriers to prescriptions for patients with limited English proficiency: a survey of pharmacies. Pediatrics, 120(2), e225-e235.
• Breaugh, J. A., & Colihan, J. P. (1994). Measuring facets of job ambiguity: Construct validity evidence. Journal of applied psychology, 79(2), 191
• Cameron, A. J., & MacKeigan, L. D. (2012). Development and pilot testing of a multiple mini-interview for admission to a pharmacy degree program. American journal of pharmaceutical education, 76(1).
• Cook, V. (2016). Second language learning and language teaching: Routledge.
• Coroban, C. (2019). Teaching English to Pharmacy students: resources, importance and applications. Analele Universităţii Ovidius din ConstanÅ£a. Seria Filologie, 30(1), 44-56.
• Crutzen, R., & Peters, G.-J. Y. (2017). Scale quality: alpha is an inadequate estim,ate and factor-analytic evidence is needed first of all. Health psychology review, 11(3), 242-247.
• Dang, Y., Truong, H.-A., & Wade, L. (2019). Assessment of First-Year Student Pharmacists' Intercultural Competency Skills Using a Validated Scale and International Scenarios. American journal of pharmaceutical education, 83(5).
• Das, K. R., & Imon, A. (2016). A brief review of tests for normality. American Journal of Theoretical and Applied Statistics, 5(1), 5-12.
• Delgado-Ballester, E., Munuera-Aleman, J. L., & Yague-Guillen, M. J. (2003). Development and validation of a brand trust scale. International journal of market research, 45(1), 35-54.
• Dilworth, T. J., Mott, D., & Young, H. (2009). Pharmacists' communication with Spanish-speaking patients: a review of the literature to establish an agenda for future research. Research in Social and Administrative Pharmacy, 5(2), 108-120.
• Doherty, M., Mitchell, E. A., & O'Neill, S. (2011). Attitudes of healthcare workers towards older people in a rural population: A survey using the Kogan Scale. Nursing research and practice, 2011.
• Echeverri, M., Brookover, C., & Kennedy, K. (2013). Assessing pharmacy students' self-perception of cultural competence. Journal of health care for the poor and underserved, 24(1 0), 64.
• Gagné, M., Forest, J., Gilbert, M.-H., Aubé, C., Morin, E., & Malorni, A. (2010). The motivation at work scale: Validation evidence in two languages. Educational and psychological measurement, 70(4), 628-646.
• Grabowski, Ł. (2015). Keywords and lexical bundles within English pharmaceutical discourse: A corpus-driven description. English for Specific Purposes, 38, 23-33.
• Hartmann, C., & Siegrist, M. (2018). Development and validation of the Food Disgust Scale. Food Quality and Preference, 63, 38-50.
• Hulme, C., Snowling, M. J., West, G., LervÃ¥g, A., & Melby-LervÃ¥g, M. (2020). Children's language skills can be improved: lessons from psychological science for educational policy. Current Directions in Psychological Science, 29(4), 372-377.
• Kimberlin, C. L. (2006). Communicating with patients: skills assessment in US colleges of pharmacy. American journal of pharmaceutical education, 70(3), 67.
• Lee, J. S., & Drajati, N. A. (2019). Willingness to communicate in digital and non-digital EFL contexts: Scale development and psychometric testing. Computer Assisted Language Learning, 1-20.
• Luiz Adrian, J. A., Zeszotarski, P., & Ma, C. (2015). Developing pharmacy student communication skills through role-playing and active learning. American journal of pharmaceutical education, 79(3), 44.
• Mesquita, A. R., Lyra Jr, D. P., Brito, G. C., Balisa-Rocha, B. J., Aguiar, P. M., & de Almeida Neto, A. C. (2010). Developing communication skills in pharmacy: a systematic review of the use of simulated patient methods. Patient Education and Counseling, 78(2), 143-148.
• Oxford, R. L., & Burry-Stock, J. A. (1995). Assessing the use of language learning strategies worldwide with the ESL/EFL version of the Strategy Inventory for Language Learning (SILL). System, 23(1), 1-23.
• Schwappach, D. L., Massetti, C. M., & Gehring, K. (2012). Communication barriers in counselling foreignlanguage patients in public pharmacies: threats to patient safety? International journal of clinical pharmacy, 34(5), 765-772.
• Silva, A. D., do Céu Taveira, M., Marques, C., & Gouveia, V. V. (2015). Satisfaction with life scale among adolescents and young adults in Portugal: Extending evidence of construct validity. Social Indicators Research, 120(1), 309-318.
• Stanley, P., & Murray, N. (2013). 'Qualified'? A framework for comparing ELT teacher preparation courses. Australian Review of Applied Linguistics, 36(1), 102-115.
• Syakur, A., Junining, E., & Mubarok, M. K. (2020). Developing English for Specific Purposes (ESP) Textbook for Pharmacy Students Using On-Line Learning in Higher Education. Britain International of Linguistics Arts and Education (BIoLAE) Journal, 2(1), 467-474.
• Syakur, A., Zainuddin, H., & Hasan, M. A. (2020). Needs Analysis English For Specific Purposes (ESP) For Vocational Pharmacy Students. Budapest International Research and Critics in Linguistics and Education (BirLE) Journal, 3(2), 724-733.
• Tenney, J. W., Paiva, M., & Wang, Q. (2020). Assessment of English language performance scores and academic performance in an English-based curriculum for pharmacy students with English as a second language. Currents in Pharmacy Teaching and Learning, 12(4), 423-428.
• Wallman, A., Vaudan, C., & Sporrong, S. K. (2013). Communications training in pharmacy education, 1995- 2010. American journal of pharmaceutical education, 77(2), 36.
• White, C. J. (2003). Emotions, gender and destination visitation intentions. Paper presented at the 12th International Tourism and Leisure Symposium, Barcelona.