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Journal of International Education in Business Factors influencing academic performance in quantitative courses among undergraduate business students of a public higher education institution Darwish Abdulrahamn Yousef,

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Article information: To cite this document: Darwish Abdulrahamn Yousef, (2017) "Factors influencing academic performance in quantitative courses among undergraduate business students of a public higher education institution", Journal of International Education in Business, Vol. 10 Issue: 01, pp.12-30, https://doi.org/10.1108/ JIEB-07-2016-0016 Permanent link to this document: https://doi.org/10.1108/JIEB-07-2016-0016 Downloaded on: 13 June 2017, At: 23:15 (PT) References: this document contains references to 59 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 112 times since 2017*

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JIEB 10,1

12 Received 14 July 2016 Revised 13 November 2016 Accepted 13 January 2017

Factors influencing academic performance in quantitative courses among undergraduate business students of a public higher education institution Darwish Abdulrahamn Yousef

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Department of Business Administration, UAE University, Al Ain, UAE

Abstract Purpose – This paper aims to investigate the impacts of teaching style, English language and communication and assessment methods on the academic performance of undergraduate business students in introductory quantitative courses such as Statistics for Business 1 and 2, Quantitative Methods for Business, Operations and Production Management and Operations Research in a non-Western setting. Design/methodology/approach – Data was collected from 750 undergraduate business students in third- and fourth-year classes at the UAE University (UAEU). Descriptive statistics were used to gain some insights into the demographic and educational characteristics of respondents and their opinions regarding the importance of the three factors of concern to their understanding of quantitative courses material, along with multiple regression analysis that was used to test the hypotheses of the study. Findings – The results of the present study indicate the importance of the teaching style in terms of the way the lecturer speaks and the pace of presenting the material, in addition to the structure of the lecture in understanding quantitative course material. Additionally, availability and contents of the material on the course website play an important role in helping undergraduate business students understand the subjects of quantitative courses. The study revealed that the UAEU undergraduate business students are, to some extent, uncomfortable in reading printed textbooks and writing reports on quantitative topics in English. The results of multiple regression analysis revealed that both teaching style and English language and communication have a great influence on the academic performance of UAEU undergraduate business students. Research limitations/implications – The paper has a number of limitations. For instance, the sample was taken only from students in a single university. Moreover, this study focuses on the business students and in turn, it excludes students of other colleges. On the other hand, it has a number of implications for administrators, instructors and researchers. Administrators should pay special attention when setting admission standards. Instructors teaching quantitative courses should prepare well-structured lectures and deliver them at a reasonable pace to allow students the time to understand them. They should also pay attention to the way they speak. For researchers, this study will indicate the need for further research to confirm or refute the results of the present study. Originality/value – The present study is the first attempt to investigate the impacts of the three factors of concern on the academic performance of undergraduate business students in introductory quantitative courses in a public university setting in the UAE context.

Keywords Business education, Higher education, Academic performance, Quantitative courses Paper type Research paper Journal of International Education in Business Vol. 10 No. 1, 2017 pp. 12-30 © Emerald Publishing Limited 2046-469X DOI 10.1108/JIEB-07-2016-0016

Introduction According to the accreditation standards of the Association to Advance Collegiate of Schools of Business (AACSB), business schools’ curricula should contain a significant

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number of quantitative courses such as decision sciences, management science and statistics (AACSB International, 2016). The AACSB-accredited College of Business and Economics (CBE) of the United Arab Emirates University (UAEU) incorporates quantitative courses such as Statistics for Business 1 and 2, Quantitative Methods for Business, Operations and Production Management and Operations Research is a mandatory requirement of the Bachelor in Business Administration (BBA) degree. English is being used as the primary language for teaching and class communication. Moreover, the adopted learning resources and materials for the business programme such as textbooks and case studies are in English, which largely reflect the Western intellectual experiences and cultures in the management domains. However, the majority of UAEU business students are Arabic native speakers, and the very few non-Arab students (mainly Africans and Asians) use English as a second language. On the other hand, many scholarly studies argued that business students generally consider the quantitative subjects as challenging and the most difficult core courses of the business curricula (Naik, 2009, Blaylock and Hollandsworth, 2008, Brookshire and Palocsay, 2005, Mukherjee, 2000). This negative attitude towards the quantitative courses usually results in enormous adverse consequences for students, educators and administrators. Despite the significant impact of the teaching style, English language and communication and assessment methods on the academic performance in business courses, in particular quantitative courses, an extensive literature review reveals that this area of research has received little attention in the developing countries in general and in the UAE in particular. The aim of this study is to investigate the potential impact of three categories of factors found in the conceptual framework developed by Lebcir et al. (2008), namely, teaching style, English language and communication and assessment methods, on the academic performance of non-native English undergraduate business students in introductory quantitative courses (Statistics for Business 1 and 2, Quantitative Methods for Business, Operations & Production Management and Operations Research) at the UAEU CBE. A handful of UAE-based studies have been conducted. However, none of these studies investigated the impact of the three factors of concern together on business students’ academic performance in quantitative courses in a public university setting. For example, the study of Harb and El-Shaarawi (2007), although using a sample of UAEU students, investigated only the impact of English language on students’ academic performance in general business courses. On the other hand, although the study of Yousef (2012) investigated the impact of the three factors of concern together on business students’ academic performance in quantitative courses, it used a sample drawn from a private university. However, the population of the present study is statistically different from that of Yousef’s (2012) study in terms of age groups ( x 2 = 18.453, df = 2, p = 0.000), gender ( x 2 = 11.098, df = 1, p = 0.001), nationality ( x 2 = 145.774, df = 1, p = 0.000), high school majors ( x 2 = 10.825, df = 1, p = 0.001) and type of high school ( x 2 = 122.98, df = 1, p = 0.000). Therefore, the findings of the present study will be used to confirm or contradict the findings of Yousef (2012). Literature review A conceptual framework was proposed by Lebcir et al. (2008), which includes three categories of factors, namely, teaching style, English language and communication, and assessment methods believed to influence the academic performance of international students. The authors tested this framework through the design and statistical analysis of a questionnaire sent to international students who completed project management

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modules in a post-1992 British University. The results revealed that level of details given in lectures, speed of lectures, academic internet sources, English language skills, group or individual assessment and qualitative/quantitative content of assessment are important predictors of the academic performance of international students in project management courses. Figure 1 exhibits the conceptual framework.

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Teaching style Teaching style, as a hot research topic in education, has received different definitions given by many scholars. It is concerned with the way an instructor handles a learning task (Davis et al., 1994), or as a preference towards the teaching behaviour and the congruence between the teaching behaviour and teaching beliefs of the educator (Heimlich and Norland, 1994). Moreover, some teaching styles are specified as a label associated with the various identifiable sets of classroom teaching behaviours, which are consistent with the taught content even though such content may be subject to change (Conti and Welborn, 1986), whereas Spoon and Schell (1998) argue that the style may refer to the person’s pervasive instructional qualities that persist even though the situational conditions may be subject to change. However, the common attributes derived from these definitions are the teaching behaviour and learning process. Previous research has found that active teaching approach may have a greater positive influence on student learning rather than passive teaching approach in some contexts (Michel et al., 2009). Kang’ahi et al. (2012) found that lecturers’ teaching styles have a positive influence on students’ academic achievements. Ganyaupfu (2013) concluded that teaching methods have a significant positive influence on undergraduate students’ academic achievements in quantitative business courses. Yet, many researchers have demonstrated that the student learning behaviour is enhanced when the instructors present information using particular styles that the students prefer (Keller, 1987, Miller, 1998, Laight, 2004). Many researchers in the field argue that a match between the preferred teaching style of the instructor and the preferred learning style of the students could significantly produce higher final exam scores and course grades (Tulbure, 2011, Canfield, 1992, Miglietti, 1994, Matthews, 1995), improve the motivation and achievement of the students (Cafferty, 1980, Wetzel et al., 1982, Welborn, 1986, Miller, 2001,Stitt-Gohdes, 2003) and create a productive learning environment (Claxton and Murrell, 1987). Apparently, none of the reviewed studies have particularly investigated the impact of teaching style on the academic performance in the introductory quantitative courses among undergraduate business students.

Figure 1. Conceptual framework

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English language and communication English competency (i.e. reading, writing and speaking) is found to have a great impact as an instructional language on the academic functioning of the UAEU students in the general business courses (Harb and El-Shaarawi, 2007). Likewise, English language skills are found to be among the important predictors of the academic performance of the international students in the project management courses at a British University (Lebcir et al., 2008) and that of non-native English undergraduate business students in introductory quantitative courses (Yousef, 2012). The existing relationship between English proficiency, as measured by International English Language Testing System (IELTS) scores and academic performance as measured by the Grade Point Average (GPA) is likely significant and positive (Feast, 2002). Many other researchers have also reported a positive and significant correlation between academic success and language proficiency as measured by TOEFL grades, but low in magnitude (Abadzi, 1984, Burgess and Greis, 1984, Heil and Aleamoni, 1974, Riggs, 1982, Vinke and Jochems, 1993). English proficiency was reported as a second strong predictor of overall performance after GMAT scores (Peiperl and Trevelyan, 1997). Ho and Spinks (1985) recorded that English language skills had the most predictive value, accounting for about 10 per cent of the variance of the performance measures. Assessment methods Undoubtedly, many assessment methods have been found to have a significant impact on student learning and academic achievements. For instance, classroom evaluation may guide students to judge which of which is important to be learned according to their motivation and self-perceptions of competence (Crooks, 1988). This in turn might structure and affect their approaches to, and timing of a personal study to consolidate further learning and to develop continuing learning strategies and skills. The adopted assessment method has been recorded to influence the various learning approaches of the students (Scouller, 1998), whereas the students’ perceptions about the assessment method significantly influence their approaches to learning and studying (Struyven et al., 2005). The formative assessment strategy was found to affect student achievements in a Web-based learning environment (Wang et al., 2006). Group or individual assessment and the qualitative/quantitative content of assessment are important predictors of the academic performance of international students in the project management courses (Lebcir et al., 2008). Yousef (2012) concluded that assessment methods influence non-native English undergraduate business students’ academic performance in introductory quantitative courses. Demographic and academic factors The impact of demographic and academic factors on the academic performance of business students in quantitative courses has been the subject of a sizable number of papers. An empirical study has examined the effects of students’ performance in the Operations Research (OR) course at the UAEU of the demographic factors such as students’ age, gender and nationality, as well as the academic factors such as GPA (excluding the OR course), major track (Science or Art) and scores at high school, completing prerequisites prior to taking the OR course, grades in the prerequisite, field of study, in addition to other factors. The results suggested that the major track at the high school, high school scores, taking the prerequisites, grades in prerequisite and the field of the study affect students’ performance in the OR course (Yousef, 1991). The investigation of the attitudes of the students of the UAEU Faculty of Business and Economics towards quantitative courses showed that the major track at the high

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school (Science vs Art), the fields of study (accounting, business administration, economics, finance and insurance), GPA and high school scores have a significant impact on students’ attitudes towards the quantitative courses (Yousef, 1993). On the other hand, the investigation on the factors that might contribute to the success in an introductory OR course at the UAEU showed that significant correlations existed between OR grade and GPA, maths I grades, maths II grades and stat 105 grades. The results also showed that there was a statistically significant difference between the performance, measured by grade, in the OR of male and female students, where females performed better than males (Yousef, 2009). There was also a statistically significant difference in performance in OR between students majoring in Art and those majoring in Science at high school. The regression analysis indicated that the GPA was the most significant predictor of students’ performance in the OR course (Yousef, 2009). The academic performance (measured by quality points) of business students in quantitative courses at the UAEU CBE has been studied to explore the impact of a number of factors on the academic performance of business students in these courses. The results indicated that the academic performance of the business students in quantitative courses differs across the fields of study (accounting, economics, finance, management, marketing, MIS and statistics), the nationality (Emirati vs non-Emirati), the type of high school (private vs public), the major track in high school (Science vs Art), the gender (except for Business Stat 1 and Principles of Operations Management courses) and the age, except for Quantitative Methods for Business and OR courses (Yousef, 2011). The impact of demographic and academic characteristics on the academic performance of statistics major at the UAEU has been investigated. The results showed that only high school tracks and high school scores have a significant impact on the academic performance of statistics’ majors (Yousef, 2016). The only UAE-based study which investigates the influence of teaching style, English language and communication and assessment methods of business students’ academic performance in quantitative courses has been probed in a private university setting. The results indicated that academic performance of business students in quantitative courses is influenced by the teaching style, English language and communication and assessment methods (Yousef, 2012). Furthermore, the self-expectation of examination results, English as a teaching language, along with certificate grades in English and mathematics at the high school, personality type, intention to obtain a business degree and previous knowledge of accounting were found as significant predictors of student performance in the introductory accounting class at the Chinese University in Hong Kong (Gul and Fong, 1993). A model developed by Tho (1994) was used to identify the factors involved in the examination results of the business students in the first-level tertiary accounting course at the University of Malaya; the model revealed that the study and grades in accounting, mathematics and economics at the high school have significantly explained 66 percent of the variation in the performance. In contrast, the socio-demographic variables such as gender and residential location did not contribute significantly to performance variations. Moreover, some new empirical evidence on the determinants of student performance in a Principles of Accounting course at the Palestinian Birzeit University, shows that gender, age, grades in English and mathematics and the type of school (public/private) attended did not significantly impact on student performance (Nasser and Peel, 1998). In contrast, the university faculty originally attended (which may proxy for motivation and/or educational attributes) was significantly associated with examination performance. The study also showed that the perceptions of the students towards the factors associated with class size,

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lecturer’s delivery and complexity of the course were found to be associated with student performance in a first-level Principles of Accounting course. A sample of students at Singapore Nanyang Business School were randomly selected for conducting an investigation of six variables, namely, gender, prior accounting knowledge, academic aptitude, mathematics background, previous working experience and age with their influence on the performance of students in a three-year accountancy degree programme. The results showed that males and those with previous working experience, better academic aptitude and mathematics background, as well as younger students, performed significantly better in the accountancy degree programme (Koh and Koh, 1999). Academic performance and the associated influential factors were investigated using a sample of the undergraduate students in the Faculty of Business and Accountancy at the University of Malaya, Malaysia. The results revealed that the demographic profile, entry qualifications and subjects taken by the students in the pre-university level explained the variance in the students’ final Cumulative Grade Point Average (CGPA). The authors also found that knowledge prior to entering the university such as that in subjects such as economics, mathematics and accounting was crucial in assisting the students in undertaking courses in both business and accounting programmes. Furthermore, it was found that female students perform better than male students, whilst Chinese students perform better than Malay and Indian students (Alfan and Othman, 2005). Alhajraf and Alasfour (2014) explored students’ demographic and academic characteristics that are associated with students’ academic performance during their undergraduate studies. Results showed that student’s age, gender, high school major and high school GPA are significantly related to business students’ academic performance. The factors influencing students’ performance in quantitative courses have been reported in a number of previous studies. An investigation on the factors contributing to success in a management science course using a sample of 310 students in an American university was carried out by Brookshire and Palcosay (2005) to reveal that the GPA was the strongest predictive factor of students’ performance in this course. Rochelle and Dotterweich (2007) examined the factors that affect the academic performance of business majors at a mid-size regional state university using a sample of 93 students enrolled in four sections of Business Statistics course taught by the same instructor. The results showed that three factors, namely, class attendance, previous performance in algebra and differential calculus, and overall GPA were significantly related to student performance in business statistics courses. The potential factors that may influence the performance of students in the introductory management science course were investigated with around 300 students from the business and other related majors at Hampton University. The results recorded that the current class grade point average (GPA), average homework score, course utilization ratio and completion of pre-calculus prerequisite influence the performance of students in the introductory management science course (D'Souza and Maheshwari, 2010). Mondejar-Jemenaz and Vargas-Vargas (2010) tested the covariance structure of the affective (degree of interest in the subject and degree of anxiety and nervousness when studying the subject) and evaluative (utility students perceive for their current studies and the utility for their future professional career) factors that influence students’ attitude towards statistics using a sample of 408 (122 males and 286 females) full-time students from the University of Castilla-La Mancha (Spain). These students enrolled in a unit with statistical content for the first time during their university studies. The results indicated that no significant difference exists between male and female students in the relation between the evaluative variables and interest.

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On the other hand, the results showed that a highly significant difference exists between male and female students in the relation between utility in studies and anxiety. The response is much stronger for male students. A significant difference also exists between male and female students for the relation between the level of interest in the subject and the level of anxiety. The response is much stronger for female students. Finally, a significant difference also exists between male and female students for the relation between utility in the career and utility in the studies. The response is much stronger for male students. Ganyaupfu (2013) examined factors influencing academic achievement in quantitative courses among business students of private higher education institutions in South Africa. Results indicated that lecturer competence, teaching methods and quality of learning materials have a positive influence on business students’ academic achievements in quantitative business courses. Research hypotheses Based on the previous discussion, the present study attempts to test the following hypotheses: H1. The academic performance of UAEU undergraduate business students in introductory quantitative courses is influenced by teaching style. H2. The academic performance of UAEU undergraduate business students in introductory quantitative courses is influenced by English language and communication. H3. The academic performance of UAEU undergraduate business students in introductory quantitative courses is influenced by assessment methods. Method Population and sample The population of this study consists of all third- and fourth-year business students at the UAEU CBE. The total number of third- and fourth-year business students as of Fall 2012 was 1,000. The reason for choosing third- and fourth-year students is that those students have already completed the required quantitative courses. Data were collected from 750 business students at the College of Business and Economics, UAEU. Students were asked to complete hard copies of the questionnaire. Out of the 750 questionnaires distributed by the author and his assistants to students in classes after taking instructors’ permission, only 600 questionnaires were returned (80 per cent response rate), of which 581 questionnaires were usable. The remaining questionnaires were unusable due to missing data. Data collection To gather the required data, a questionnaire was designed by the author. The questionnaire consists of three parts. In the first part, respondents were asked to indicate which quantitative courses they had already completed successfully and the grades they achieved in these courses. The second part is the scale developed by Lebcir et al. (2008). It consists of 16 statements which measure teaching style (Statements 1 to 5), English language and communication (Statements 6 to 11) and assessment methods (Statements 12 to 16). Respondents were asked to rank each statement on a scale from one to five (1 = strongly disagree and 5 = strongly agree). A copy of the questionnaire is presented in the Appendix.

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A number of changes were introduced by Lebcir et al. (2008) to suit the purpose of this study. Changes introduced include combining Statements 2 and 3 in Lebcir’s scale in one statement (Statement 2) in the present study. Additionally, the term “project management” in Lebcir’s scale has been changed to “quantitative courses” in the present study; the word “module” has been changed to “course”; and the word “associates” has been changed to “colleagues”. The third part consists of general information such as business majors (accounting, economics, finance, management, marketing, MIS and statistics), major track at the high school (Science vs Art), age, nationality (Emirati vs. non-Emirati), gender, GPA and type of the high school (private vs public). With respect to coding, for the first part, “Yes” was coded 1 and “No” was coded 0, and for the grades, the letters A, Bþ, B, etc. were converted to quality points 4, 3.5, 3, etc. The second part, “Strongly Agree” was coded 5, “Agree” was coded 4 and so on. The third part, field of specialization “Accounting” was coded 1, “Finance” was coded 2, “Management” was coded 3 and so on. High school major, “Science” was coded 1 and “Art” was coded 0. Nationality, “National” was coded 1 and “Non-National” was coded 0. Age, “Less than 20 years” was coded 1, “20 years to Less than 22 years” was coded 2 and “22 years and Above” was coded 3. Gender, “Male” was coded 1 and “Female” was coded 0. Ownership of high school, “Private” was coded 1 and “Public” was coded 0. The author measured the reliability of the second part of the questionnaire using Cronbach’s alpha, which was 0.65 for teaching style, 0.69 for English language and communication and 0.70 for assessment methods. The overall was 0.78. It is worth noting that 0.70 would be an acceptable reliability coefficient; however, lower coefficients are sometimes used in some literature (Nunnaly, 1978).

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Measures Quality points (QP) were used in this study to measure the academic performance of UAEU undergraduate business students in introductory quantitative courses (the dependent variable in the regression model). Table I show quality points awarded for each grade. Lebcir et al.’s (2008) scale was used to measure teaching style, English language and communication and assessment methods (the independent variables in the regression model). Analysis Descriptive statistics such as frequencies and percentages were used to present the demographic and educational characteristics of respondents. Furthermore, means

Grade A Bþ B Cþ C Dþ D

Quality points 4 3.5 3 2.5 2 1.5 1.0

Table I. Quality points equivalent to letter grades

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and standard deviations were used to present respondents’ opinions regarding the importance of the three factors of concern to their understanding of the subjects of the qualitative courses. Multiple regression analysis was used to test the hypotheses of the study. Academic performance (measured by quality points) was the dependent variable in the regression model. The average score for each teaching style, English language and communication and assessment methods was calculated and then used as an independent variable in the model. Variance inflation factor (VIF) was calculated to find whether multicollinearity among the predictors exists or not.

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Results Respondents’ demographic and educational characteristics Table II presents respondents’ demographic and educational characteristics. The results show that 68 per cent of respondents were female, 58 per cent had science as their majors in high school and 80 per cent are Emiratis. About 90 per cent attended public high schools, 69 per cent had GPA between 2.5 and 3.5, about 26 per cent had finance as business major and 58 per cent are between 20 and 22 years old.

Table II. Respondents’ demographic and educational characteristics

Characteristics

Frequency

(%)

Business majors Accounting Finance Management Marketing MIS Economics Statistics

130 151 130 38 54 47 31

22 26 22 7 9 8 6

High school majors Art Science

244 337

42 58

Nationality Emiratis Non-Emiratis

466 115

80 20

Age Less than 20 20- less than 22 22 and over

15 334 232

2 58 40

Gender Male Female

188 393

32 68

GPA Less than 2.5 2.5- less than 3.5 3.5-4.0

106 399 76

18 69 13

Type of high school Public Private

525 56

90 10

Respondents’ opinion regarding the importance of the three factors to their understanding of introductory quantitative courses material Table III shows the means and standard deviations for the sixteen statements, which measure the respondents’ opinion regarding the importance of the three factors of concern to their understanding of the introductory quantitative courses material.

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21 Teaching style As shown in Table III, the way the lecturer presents the lecture material, the pace of presenting the material, the structure of the lecture and availability and contents of the material on the course website are important factors in students’ understanding of the subjects of quantitative courses. This was indicated by the mean scores for those statements, which were above 3. English language and communication The results in Table III also indicate that UAEU undergraduate business students have some difficulty in reading quantitative textbooks and writing reports in the English language. They favour using their first language for discussion of quantitative course material with their colleagues and for reading about quantitative courses. The mean scores for those statements were above 3. Additionally, UAEU undergraduate business students have some problems with understanding technical words in quantitative courses. The mean score for this statement was close to 3. No. Statement Teaching style 1 The way the lecturer speaks is important in understanding the lecture 2 The pace (speed) of delivery of the teaching is reasonable 3 It is difficult to understand what is explained if there is no clear link between the different parts of the lecture 4 I find that information posted by the lecturer on the course website (Blackboard) always give the answers to any questions I have after a lecture 5 I have difficulty with class discussions on quantitative courses

Mean SD 4.27 1.24 3.70 1.04 3.78 1.20 3.32 1.15 2.76 1.24

English language and communication 6 I find reading quantitative course textbooks difficult 7 I find writing reports and essays difficult for quantitative courses 8 The use of some technical words in quantitative courses makes them harder to understand 9 I find it difficult to express my thoughts in spoken English 10 I discuss quantitative course materials in my first language with my colleagues 11 I would like to read about quantitative courses in my first language.

2.62 1.25 3.24 1.26 3.13 1.31

Assessment methods 12 Examination questions in quantitative courses are difficult to answer 13 The quantitative course assignments are difficult to understand 14 I prefer to work in a team for assignment work 15 I prefer to work on my own for assignment work 16 I am happy with questions which are mathematically based

2.89 2.91 3.61 2.84 3.65

3.09 1.24 3.11 1.23 2.98 1.16

1.24 1.24 1.41 1.43 1.27

Table III. Mean and standard deviation for the 16 statements

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Assessment methods It is apparent from Table III that UAEU undergraduate business students have some difficulty in answering exam questions and in understanding assignments in quantitative courses. This was indicated by the mean scores for those statements, which were close to 3. Furthermore, undergraduate business students strongly favour mathematically based questions and group assignments. Again, this was supported by the mean scores for those statements, which were well above 3.

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Hypotheses testing Three research hypotheses were tested to identify the influence of teaching style (H1), English language and communication (H2) and assessment methods (H3) on UAEU undergraduate business students’ academic performance in introductory quantitative courses (measured by quality points). A multiple regression analysis was conducted. The results of the regression analysis are presented in Table IV. As shown in Table IV, VIF scores indicate that the independent variables are not correlated (VIF % 1). Therefore, multicollinearity does not exist. H1 proposes that teaching style influences UAEU undergraduate business students’ academic performance in introductory quantitative courses. Table IV reveals that teaching style influences UAEU undergraduate business students’ academic performance in introductory quantitative courses (p-value = 0.000). Hence, H1 is accepted. H2 posits that English language and communication influence UAEU undergraduate business students’ academic performance in quantitative courses. The results in Table IV reveal that English language and communication influence UAEU business students’ academic performance in quantitative courses (p-value = 0.0000). Thus, H2 is accepted. H3 postulates that assessment methods influence UAEU undergraduate business students’ academic performance in introductory quantitative courses. As shown in Table IV, assessment methods do not influence UAEU undergraduate business students’ academic performance in introductory quantitative courses (p-value = 0.599). Accordingly, H3 is rejected. Discussion The results of the present study indicate the importance of teaching style in terms of the way the lecturer speaks and the pace of presenting the material in addition to the structure of the lecture in understanding quantitative course material. Additionally, the availability and contents of the material on the course website play an important role in helping undergraduate business students understand the subjects of quantitative courses. As pointed out by Lebcir et al. (2008), this might be due to the weakness of students in English language, subsequently leading them to rely heavily on the lecturer and the material posted on the course website. Ganyaupfu (2013) argues that quality of learning materials has a

Results of regression analysis

Table IV. Regression analysis

Teaching style English language Assessment methods

B

Standard error

b

t-Value

p-Value

VIF

1.094 0.191 0.036

0.106 0.052 0.068

0.556 0.218 0.032

10.361 3.638 0.526

0.000 0.000 0.599

1.393 1.565 1.596

Notes: R2 = 0.44; Adjusted R2 = 0.42; F-value = 16.341 (p-value = 0.000)

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significant positive influence on undergraduate business students’ academic achievements in quantitative business courses. The results that UAEU undergraduate business students are somewhat uncomfortable in reading quantitative textbooks and writing reports in the English language might be attributed also to lack of English language skills. This indicates that attention needs to be paid to the selection of textbooks, which are written in a simple style and clear language. Furthermore, efforts should be devoted to enhancing students’ report-writing skills. The UAEU undergraduate business students prefer using their first language for discussion of quantitative courses material with their colleagues, and when reading about quantitative courses. This might be due in part to lack of English language skills, and be because of human nature, where the preference is usually given to one’s first language. On the other hand, UAEU undergraduate business students have some trouble with understanding technical words in quantitative courses. This might be due to the complexity of the presentation of the technical information in the quantitative course textbooks and to a lack of English language proficiency of business students as well. The results also uncovered that UAEU undergraduate business students have some difficulties with understanding exam questions and assignments in quantitative courses. Obviously, such difficulties are attributed to language barriers. The fact that UAEU undergraduate business students strongly favour mathematically based questions is because quantitative questions usually require less English expertise. UAEU undergraduate business students prefer group assignments because the effort required from each member of the group is less than the effort required for individual assignments. Furthermore, the weaknesses of one member of the group are offset by the strengths of the other members. Previous research studies have shown that, regardless of subjects, students who work in groups achieve better results and are more satisfied with their learning experiences than those who do not work in collaborative groups (Gross, 1993, Springer et al., 1999). Although the majority of participants had science majors in the high school and their GPA at the university was high, as shown in Table II, most of them graduated from public high schools where most of the courses are taught in Arabic; therefore, they were having trouble with quantitative courses due to poor command of English. The result which revealed that teaching style influences the academic performance of the UAEU undergraduate business students is consistent with that of a number of previous studies, which suggest that teaching style influences students’ academic performance (Yousef, 2012, Michel et al., 2009, Lebcir et al., 2008, Stitt-Gohdes, 2003, Johnson, 1996, Felder, 1993). Previous research has shown that the match between the preferred teaching style of the instructor and preferred learning style of the students usually lead to enhance students’ learning behaviour (Keller, 1987, Miller, 1998, Laight, 2004). Lebcir et al. (2008) argue that the level of detail given in lectures, speed of lectures and academic internet sources as components of teaching style are important drivers of the academic performance of international students in quantitative courses such as project management course. Yousef (2012) concludes that teaching style adopted by the instructor significantly influences the academic performance of undergraduate business students in introductory quantitative courses. Ganyaupfu (2013) argues that teaching methods have a significant positive influence on undergraduate business students’ achievements in quantitative business courses. The result that English language and communication influence UAEU undergraduate business students’ academic performance is consistent with that of a number of earlier

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studies which found that English language proficiency influences students’ academic performance (Yousef, 2012, Lebcir et al., 2008, Harb and El-Shaarawi, 2007). For instance, Yousef (2012) concludes that English language and communication influence the academic performance of undergraduate business students in introductory quantitative courses. Similarly, Lebcir et al. (2008) argue that English language skills are important drivers of the academic performance of international students in project management courses. Harb and El-Shaarawi (2007) assert that competence in English is the most important factor that affects students’ performance. Surprisingly the result that the UAEU undergraduate business students’ academic performance is not influenced by assessment methods is in contrast to prior studies which found that assessment methods influence students’ academic performance (Yousef, 2012, Lebcir et al., 2008, Wang et al., 2006, Struyven et al., 2005). The difference between the result of this study and that of Yousef (2012) in particular, might be due to the fact that the present study uses a sample of students from a public higher education institution, whereas Yousef’s (2012) study used a sample of students from a private higher education institution. Regression analysis results have shown, as pointed out earlier, that teaching style and English language and communication influence UAEU business students’ academic performance, whereas assessment methods do not influence students’ academic performance. Therefore, instructors teaching introductory quantitative courses should take into account teaching style and English language and communication when preparing course materials and when delivering these materials to their students. Moreover, although the results of this study have shown that the assessment methods do not influence students’ academic performance, instructors should pay attention to the assessment methods they use to assess their students’ performance, as prior studies have shown that assessment methods influence students’ academic performance. Conclusion The aim of the present study is to investigate the influence of three categories of factors: teaching style, English language and communication and assessment methods included in the conceptual framework developed by Lebcir et al. (2008) on the undergraduate business students’ academic performance in introductory quantitative courses at the UAEU CBE. This study has certain limitations. First, the sample was taken only from students in a single university. Nonetheless, because the UAEU is the flagship university in the UAE, which enrols the largest number of Emiratis and foreign students, one would expect that this sample would be representative of other UAE-based universities. Second, this study focuses on the business students, and in turn, it excludes students of other colleges (e.g. engineering) who also take quantitative courses, and might have different experiences. Third, it is based mainly on a questionnaire as a tool of collecting the required data. As it is known, the questionnaire has a number of drawbacks, which might affect the generated results of the study. The current study has a number of implications for administrators, educator and researchers. Administrators should pay special attention when setting admission standards, which emphasize that students must possess the necessary degree of proficiency in English before accepting them into the CBE. Moreover, students admitted into the CBE should be provided with adequate English language support and this support should continue throughout their period of study. Such support should focus on enhancing students’ oral and written communication skills. Students should also be made aware that English is the major mode of business communication globally. Additionally, they should be aware that for them to be global business players, they need to enhance their knowledge of the English language.

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Educators teaching quantitative courses should prepare well-structured lectures and deliver them at a reasonable pace to allow students the time to understand them. They should also pay attention to the way they speak. However, educators should realize that delivering lectures at a reasonable pace does not mean that the pace is to be slowed down. Because if the pace is to be slowed down, then more time may have to be devoted to these courses. This in turn may require students to spend more time in college prior to graduation. Moreover, this may result in more economic resources being devoted to such courses. Educators should also engage students through class discussions and encourage them to participate in these discussions. Furthermore, they should make a good use of the Web learning platform. In addition, they should pay special attention when selecting textbooks for quantitative courses. With respect to exams and assignments, there should be a balance between quantitative and qualitative components. Results have shown that teaching style has a significant impact on students’ academic performance. Therefore, educators should pay special attention to their teaching styles and ensure that their teaching styles match the learning styles of the majority of their students. This will enhance students’ academic performance. For researchers, this study indicates the need for further research to confirm or disconfirm the results of the present study. Furthermore, this study serves as a base for more comprehensive and analytical studies. Based on the analysis of this study, a number of future studies are suggested. For instance, there is a need to replicate this study in other universities in the UAE and in other Gulf Cooperation Council countries to enhance the generalizability of its findings. A study, which uses a sample of non-business students, would be valuable. Furthermore, a comparison between business and non-business students would be worthwhile. A study which uses a sample of students drawn from other countries in Africa, Europe and North America would be of value. References AACSB International (2016), Eligibility Procedures and Accreditation Standards for Business Accreditation, The Association to Advance Collegiate Schools of Business, Tampa, FL, p. 9, p. 31. Abadzi, J. (1984), “Evaluation of foreign students’ admission procedures used at the university of Alabama”, in Hale, G., Stansfield, C. and Duran, R. (Eds), Summaries of Studies Involving the Test of English as a Foreign Language, 1963-1982, Educational Testing Service, Princeton, NJ. Alfan, E. and Othman, M.N. (2005), “Undergraduate students’ performance: the case of university of Malaya”, Quality Assurance in Education, Vol. 13 No. 4, pp. 329-343. Alhajraf, N.M. and Alasfour, A.M. (2014), “The impact of demographic and academic characteristics on academic performance”, International Business Research, Vol. 7 No. 4, pp. 92-100. Blaylock, B. and Hollandsworth, R. (2008), “Improving the impact of classroom student engagement on out-of-class mental focus in quantitative courses”, The Journal of Learning in Higher Education, Vol. 4 No. 2, pp. 37-44. Brookshire, R.G. and Palocsay, S.W. (2005), “Factors contributing to the success of undergraduate business students in management science courses”, Decision Sciences Journal of Innovative Education, Vol. 3 No. 1, pp. 99-108. Burgess, T. and Greis, N. (1984), “English language proficiency and academic achievement among students of English as a second language at the college level”, in Hale, G., Startsfield, C. and Duran, R. (Eds), Summaries of Studies Involving the Test of English as a Foreign Language, 1963-1982, Educational Testing Service, Princeton, NJ.

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Appendix

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Corresponding author Darwish Abdulrahamn Yousef can be contacted at: [email protected]

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