The International Journal of Management Education 19 (2021) 100555
Contents lists available at ScienceDirect
The International Journal of Management Education
journal homepage: www.elsevier.com/locate/ijme
Roles of gender, study major, and origins in accounting learning: A
case in Thailand
Muhammad Syukur
School of Management, Mae Fah Luang University, Chiang Rai, Thailand
A R T I C L E I N F O
A B S T R A C T
Keywords:
Learning performance
Management students
Accounting education
Gender
Study major
Origins
Management students are required to pass several quantitative subjects, such as Accounting,
Business Finance, and Mathematics, during their study at the undergraduate level. There are
limited studies conducted in Thailand that explored students’ learning achievement in accounting
courses. This paper explored the learning achievement of undergraduate management students in
the introductory accounting course at a public university in Thailand. It examined whether the
achievement differs across the students’ gender, study major, and origins. Data from 906 man­
agement students were taken as samples. This study relied on the independent samples t-test and
one-way ANOVA to analyze the data. The results suggested that the performance of undergrad­
uate management students in the accounting course differs significantly across genders, majors,
and origins of the students.
1. Introduction
Business schools worldwide require their undergraduate students to complete several quantitative courses before graduation, such
as accounting. Researchers in different disciplines in developed and developing countries have paid considerable attention to students’
academic performance in higher education and the determinants of students’ academic success.
Students’ performance in learning will contribute to their success in their future workplace. Therefore it is critical to discuss their
learning performance. The factors influencing students’ performance when learning accounting subjects are a lot and diverse. Ac­
counting education scholars have examined several factors that influence students’ performance in learning accounting, such as
gender, age, major, nationality, and high school GPA (Al-Rashed, 2001; Al-Twaijry, 2010; Bealing et al., 2009; Hijazi et al., 2008;
Mohrweis, 2010; Nelson et al., 2008; Paisey & Paisey, 2004; Papageorgiou & Halabi, 2014; Yousef, 2013, 2019). However, there are
only a few studies conducted on non-accounting students for an accounting subject. This idea needs to be studied more as
non-accounting students have negative attitudes toward accounting courses (Lucas & Meyer, 2005).
This study explores the learning performance in the introductory accounting course of non-accounting students from a School of
Management. We consider it critical to observe in order to design the best teaching techniques and approaches in this young university.
As it is an international university, the research population will include national and international students. The study examines
whether learning performance differs across genders, study majors, and origins.
The rest of the paper is structured as the Literature Review of previous research related to the present study. Then, it is followed by a
presentation of the Research Methodology, which includes the variable measurement, the process of data collection, and research
tools. The section Results and Discussion are then presented. The paper is concluded with contributions, limitations, and suggestions
E-mail addresses: muhammad.syu@mfu.ac.th, msyukurmail@gmail.com.
https://doi.org/10.1016/j.ijme.2021.100555
Received 24 April 2020; Received in revised form 27 June 2021; Accepted 31 August 2021
Available online 3 September 2021
1472-8117/© 2021 Elsevier Ltd. All rights reserved.
The International Journal of Management Education 19 (2021) 100555
M. Syukur
for future researchers.
2. Literature review and hypothesis development
Students of a business school are required to learn introductory quantitative courses, including Accounting. Understanding ac­
counting skills help students to understand the nature of the business, and accounting itself is the language of business. Therefore, an
introductory accounting course is a mandatory subject for all business students.
Students’ performance in learning Accounting varies according to the measure and across variables. The measurement can be based
on raw scores or CGPA. Many researchers were curious to find as many variables as possible to find the most influencing factors. At last,
research around the world found varied results, which conclude inconsistent findings.
Previous works of literature have elaborated on several variables, such as examination format (Arthur & Everaert, 2012; Nourayi,
1994), job placement (Grace & Black, 2011), nationality (Alanzi, 2015), age (Alanzi & Alfraih, 2017; Alhajraf & Alasfour, 2014),
gender (AL-Mutairi, 2011; Alanzi, 2018), perceptions and the role of technology (Madah Marzuki et al., 2019), language (Yang &
Farley, 2019), emotional intelligence (Ahmed et al., 2019), course delivery mode (McCarthy et al., 2019) and social networking
(Alaslani & Alandejani, 2020). However, in this paper, we operationalize three selected variables that are appropriate to the situation
in the investigated institution. The variables that differentiate students’ performance in learning Accounting are students’ gender,
study majors, and origins.
2.1. Gender and student’s performance
Gender research in education has been generously published to check patterns in male/female learning results. Previous studies
have recognized the importance of gender in Management education literature (Alanzi, 2015; Du, 2011; Fallan & Opstad, 2014;
Nguyen et al., 2005; Sheard, 2009). However, only a few have attempted to compare learning performance between male and female
students.
In Nigeria, Okafor and Egbon (2011) found that male and female students’ performance is equal. The research does not tell that the
country is free of gender issues, but it is the opposite. It was explained that the females in Nigeria usually are responsible for housework
in their family; at the same time, they also need to perform well in their class. The males are independent and free yet perform as much
as their female counterparts. Guney (2009) also proved that both male and female students perform similarly.
Nouri and Domingo (2019) argued that male and female students performed unequally. Older manuscripts, such as from Lipe
(1989), found that males performed better than females in Accounting courses. Koh and Koh (1999) summarized from Mutchler et al.
(1987) that male students in western countries had dominated accounting fields.
However, later studies found that females outperformed their male counterparts (Gammie et al., 2003; Kaighobadi & Allen, 2008;
Kara et al., 2009). The effect of gender on student performance remains inconclusive. This condition could be due to some factors,
including investigated institutions, country settings, research methodologies, or different learning strategies (De Lange & Mavondo,
2004). As follows from these arguments, the first hypothesis is:
H1. There is a different level of understanding in learning Accounting between male and female students.
2.2. Study majors and students’ performance
Researchers have primarily agreed that students perform differently in class according to their study major and their previous study
background. Business students with math skills perform better in overall learning courses than students without the skill (Erdem et al.,
2007; Garkaz et al., 2011). Alfan and Othman (2005) also agreed that prior knowledge about quantitative subjects such as mathematics
would help students undertake their studies. Maksy and Zheng (2008) implied that students should always be eager to earn good
grades because cumulative abilities will help them learn courses the next semester.
Students from a specific major can perform better among others. The study plan tells what subjects are required to pass before
taking another and implicitly shows the expectation of the graduates after finishing their study. A study plan with fewer quantitative
subjects entitles students to have fewer skills in calculation or numerical logics. This condition can influence the problem-solving skills
of graduates in the business situation.
Accounting demands adequate quantitative skills (Koh & Koh, 1999), so students with mathematics or economics knowledge
Table 1
Details on quantitative credit hours for all majors.
Major
Quantitative Subjects
Aviation Business Management
Business Administration
Economics
Hospitality Industry Management
Logistics & Supply Chain Management
Tourism Management
2
Credit hours
Percentage
36/132
27/135
42/123
15/131
49/129
12/126
27.27
20.00
34.10
11.45
37.98
9.52
The International Journal of Management Education 19 (2021) 100555
M. Syukur
usually perform satisfactorily in the course (Tho, 1994). Table 1 summarizes the numbers of credit hours of quantitative courses in the
school of management. It is extracted from the full-version study plan and discussed with lecturers and heads in the programs.
The table explains that Business Administration, Tourism, and Hospitality students have less exposure to numbers. Contrarily, other
students have more than 20 per cent of their study hours to be with quantitative courses. The gap in quantitative courses between these
groups is substantial.
Previous research explored the impact of study major or experience on the performance in a particular subject or course. Kaigh­
obadi and Allen (2008) found that choosing a major is a significant indicator of students’ success in classes. Also, Tickell and Smyrnios
(2005) said that students’ performance in university is best impacted by their prior performance in the same discipline, supported by
Halabi (2009). Yousef (2009) also specifically proved a significant performance difference in learning a research course between
students majoring in art and science. Considering these matters, the second hypothesis is:
H2. There is a different level of understanding in learning Accounting among study majors.
2.3. Student’s origins and learning performance
Very little academic research has attempted to investigate students’ nationality on their learning performance. Harb and
El-shaarawi (2007) found that non-national students coming from countries with a better education system and learning styles perform
better than local students.
The human development index and the educational index of Thailand vary across the four regions, as shown in Table 2. Based on
the Global Data Lab (globaldatalab.org) published by the Institute for Management Research, Radboud University, northern Thailand
has an HDI index of 0.755 and an educational index of 0.635 in 2018, the lowest in the country. Those indices are greatly different
compared to those of the central region. This condition causes gaps in education quality among the regions. For this reason, the third
hypothesis would be:
H3. There is a different level of understanding in learning Accounting according to the students’ origins.
3. Methodology
3.1. Population
The School of Management in the observed university requires all students to learn Fundamentals of Accounting. Each major is
assigned to a different semester, so the only two available lecturers can handle the classes. Students of Economics, Business Admin­
istration, and Aviation Business Management learned Fundamentals of Accounting in the odd semester, and the rest in the even se­
mester of the academic year 2018. Table 3 shows the samples of this study in details.
3.2. Data collection technique
The data is technically and carefully collected. The data, which is the raw scores of students, is coming from the results of the
midterm examination and final examination. In both exams, students solved multiple-choice questions, and the question sets were
repeatedly used for the odd and even semesters in the same academic year. The question paper could be reusable several times because
students could not take the exam paper out of the exam room.
In the observed institution, the Fundamentals of Accounting course opens three to four sections, handled by two lecturers, every
semester. An individual lecturer handles one section. Each lecturer independently arranged assignments and quizzes without any fixed
timetables, making those two assessments customizable and subjective. That is why the scores from assignments and quizzes are not
taken as data for this study. Whereas the other two types of assessment were arranged in a single-mode arrangement, one question set
jointly made by the lecturers. Table 4 shows the proportion of the assessment system for the course.
The first two assessment methods of the course were Assignments and Quizzes, which were arranged in customizable manners. At
the same time, the other methods were a midterm exam and a final exam which were arranged at an appointed time. Therefore, the
score (data) used to measure students’ learning achievement was only 60 points instead of 100 points.
After the author collected the scores (data), the data were categorized into several categories based on the student’s attributes, such
Table 2
Subnational human development index (HDI) and educational index.
Regions
National
North
Northeast
Central
Bangkok
South
HDI
Educational index
0.772
0.755
0.755
0.776
0.815
0.762
0.677
0.635
0.634
0.689
0.791
0.657
Source: globaldatalab.org (accessed on June 9, 2021)
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The International Journal of Management Education 19 (2021) 100555
M. Syukur
Table 3
Samples.
Major
Aviation Business Management
Business Administration
Economics
Hospitality Industry Management
Logistics & Supply Chain Management
Tourism Management
Total
Semester 1
Semester 2
Total
237
142
27
0
0
10
416
5
8
0
64
164
249
490
242
150
27
64
164
259
906
Table 4
Assessment system.
No.
Assessment
1
2
3
4
Assignments
Quizzes
Midterm exam
Final exam
Total
Percentage
Remark
20%
20%
30%
30%
100%
Customizable
Customizable
Single-mode
Single-mode
-
as gender, study major, and origins (four regions of Thailand and international).
3.3. Data groups and data analysis method
This paper aims to check whether student’s study performance can differ according to their gender, study major, and origins in
learning Fundamentals of Accounting. The performance was measured by scores, which combined the midterm exam and final exam
results, with 60 points as the full scores. Table 5 shows the variable and codes used in this study.
The data were grouped based on gender (male and female), the six study majors, and origins. The origins are the four regions of
Thailand and international. We tested all hypotheses by the comparison of means tests, such as the independent sample t-test and the
ANOVA test. Fig. 1 shows the details on the variables and the tests we employed.
Finding evidence through statistical test results is needed to get approval or acceptance towards hypotheses. In this study, the tests
were the independent sample t-test and ANOVA. The author also conducted a post hoc test to identify which differences between pairs
of means are significant. This test must be run after the ANOVA result is showing a p-score below 0.05.
4. Results and discussion
Before testing the three hypotheses, the author compared students’ learning performance based on who taught the course (Lecturer
A and Lecturer B) and when the students enrolled in the course (odd semester and even semester). The result shows that students who
studied accounting with Lecturer A were not better than students with Lecturer B. It approves that students performed in class at a
similar level regardless of who teaches the subject. It can also explain that the teachers had similar qualifications to deliver the course.
The finding also confirms that students enrolling in the odd semester were not better than those in the even semester. No matter in
Table 5
Data pairs and groups.
Variable
Description
Codification
Remarks
Learning performance
average score from the combination of the midterm exam and final exam result
Gender
Male
Male students
1
–
Female
Female students
2
–
Study major
Economics
31202
The codification is based on the program code in the observed school.
Business Administration
31203
Tourism Management
31205
Hospitality industry management
31207
Logistics and Supply Chain Management
31209
Aviation Business Management
31210
Origin
N
Northern region
1
–
NE
Northeastern region
2
–
C
Central region
3
–
S
Southern region
4
–
Int
International
5
–
4
The International Journal of Management Education 19 (2021) 100555
M. Syukur
Fig. 1. Data analysis method.
which semester students take the subject, their level of understanding was the same. Lecturers usually do not apply new teaching
methods to improve students’ knowledge acquisition in the following semester. The approximate level of students’ understanding in
the prior semester is not different compared to that of students in the current semester.
4.1. Is there any gender issue in the learning?
Table 6 shows the composition of the population in genders and the mean score for each gender. The population consists of 296
male and 610 female students, which means that only one-third of the samples are men.
Male and female are biologically born so different that much research has been done to analyze whether student’s learning per­
formance is different across gender. The author proves the acceptance of hypothesis 1 that male and female achieve understanding at a
different level in learning introductory accounting, as shown in Table 7.
The learning performance of male students is significantly smaller than that of female students, as shown in Table 7. This result is
supported by Alanzi (2015), Arthur and Everaert (2012), Gammie et al. (2003), Harb and El-shaarawi (2007), and Nouri and Domingo
(2019). This result summarizes that female is better than male learners at numbers and calculation, suggesting the acceptance of
hypothesis one.
In countries where gender equality in learning is still an issue, a performance imbalance between males and females will remain.
Many cultures stereotype a son to be physically active and a daughter to involve in passive activities, such as reading novels and
writing blogs. Especially in a conservative society, male students have more freedom and independence than female students, which
gives female students more time to study (Harb & El-shaarawi, 2007).
Both genders are not only different in learning style but also in the level of motivation. Miglietti (2020) found that female students
are active in asking questions when they face obstacles in understanding an accounting topic. The researcher commented that female
students also give positive reactions when teachers motivate students by giving bonus scores.
Students sometimes face difficulties during class since there is anxiety in learning among students (Malgwi, 2004). Teachers have a
critical role in helping the students reduce their anxiety to increase their success in studying (Mondéjar-Jiménez & Vargas-Vargas,
2010). Success in learning can contribute to job performance in the future.
4.2. Which students did perform the best in learning accounting?
Nine hundred six non-accounting students from the School of Management learned the introductory Accounting course in 2018.
Table 6
Frequencies and descriptive statistics – male vs female.
Frequencies
Valid
Descriptive statistics
Gender
Frequency
Valid Percent
male
female
Total
296
610
906
32.7
67.3
100.0
Total score
5
gender
N
Mean
male
female
Total
296
610
906
30.54
32.38
The International Journal of Management Education 19 (2021) 100555
M. Syukur
Table 7
Independent sample T-test for hypothesis 1.
Levene’s Test for Equality of Variances
total
Equal variances assumed
Equal variances not assumed
t-test for Equality of Means
F
Sig.
t
df
8.636
.003
− 3.071
− 3.198
904
649.845
Sig. (2-tailed)
Mean Difference
Std. Error Difference
.002
.001
− 1.83413
− 1.83413
.59728
.57347
Table 8
Data frequencies and descriptive statistics – among majors.
Frequency
Aviation Business Management
Business Administration
Economics
Hospitality Industry Management
Logistics & Supply Chain Management
Tourism Management
Total
Descriptive statistics
Frequency
Per cent
Mean
Minimum
Maximum
242
150
27
64
164
259
906
26.71
16.57
2.98
7.06
18.10
28.59
100.0
34.54
30.47
33.98
27.90
33.60
29.53
31.78
18.10
14.90
17.50
13.50
14.30
13.70
13.50
56.60
49.60
51.00
49.60
56.30
53.20
56.60
Table 9
ANOVA test result across majors.
Sum of Squares
df
Mean Square
F
Sig.
5046.563
59895.189
64941.752
5
900
905
1009.313
66.550
15.166
.000
Between Groups
Within Groups
Total
Table 10
Multiple comparisons based on students’ study major.
(I) Major
(J) Major
Economics
Business Administration
Tourism Management
Hospitality Industry Management
Logistics & Supply Chain Management
Aviation Business Management
Economics
Tourism Management
Hospitality Industry Management
Logistics & Supply Chain Management
Aviation Business Management
Economics
Business Administration
Hospitality Industry Management
Logistics & Supply Chain Management
Aviation Business Management
Economics
Business Administration
Tourism Management
Logistics & Supply Chain Management
Aviation Business Management
Economics
Business Administration
Tourism Management
Hospitality Industry Management
Aviation Business Management
Economics
Business Administration
Tourism Management
Hospitality Industry Management
Logistics & Supply Chain Management
Business Administration
Tourism Management
Hospitality Industry Management
Logistics & Supply Chain Management
Aviation Business Management
a
The mean difference is significant at the 0.05 level.
6
Mean Difference (I-J)
Sig.
3.51148
4.44982
6.08617a
.37721
-.55401
− 3.51148
.93834
2.57469
− 3.13427a
− 4.06550a
− 4.44982
-.93834
1.63635
− 4.07261a
− 5.00384a
− 6.08617a
− 2.57469
− 1.63635
− 5.70896a
− 6.64018a
-.37721
3.13427a
4.07261a
5.70896a
-.93123
.55401
4.06550a
5.00384a
6.64018a
.93123
.310
.077
.015
1.000
.999
.310
.873
.281
.009
.000
.077
.873
.704
.000
.000
.015
.281
.704
.000
.000
1.000
.009
.000
.000
.869
.999
.000
.000
.000
.869
The International Journal of Management Education 19 (2021) 100555
M. Syukur
Most students come from the Tourism department with 259 students, and the least is Economics with only 27 students.
The approximate score of the students reached 31.78 points. Students majoring in Business Administration, Tourism, and Hos­
pitality perform less than the average. At the same time, those who are from Aviation Business, Economics, and Logistics & Supply
Chain are better than the mean score. In this case, Aviation Business students are the top scorer among all, and Hospitality students
perform at the lowest level. Table 8 shows the descriptive statistics according to students’ major.
Hypothesis two, the level of understanding in learning Accounting is different among study majors, is accepted (p-score of 0.000).
This result is relevant to Yousef (2011), saying that the performance of business students in quantitative courses differed across
business majors. Since the homogeneity of variances is met, and the ANOVA test is significant with a p-value of 0.000 (see Table 9), the
Tukey HSD test can be run to test which study group is better in learning Accounting.
Table 10 shows that students from Economics, Logistics & Supply Chain, and Aviation Business majors performed better at the
accounting subject than students from Business Administration, Tourism, and Hospitality. However, hospitality students got the lowest
mean score compared to others, shown by the negative sign for Hospitality’s Mean Difference column in Table 10. The hospitality
students had only around 11% of quantitative courses in their study plan. They were not expected to graduate with a high level of the
numerical quotient as they were more into service-minded skills. Since the hospitality students’ learning performance level was not
significantly different to students’ from Business Administration and Tourism, all of these students should have been placed together in
one classroom or used the same approach to learn the Accounting course.
4.3. Where do the best students come from among the population?
This study was conducted in a university located in Chiang Rai province, the northernmost of Thailand. The country has four
political regions, namely north, northeast, central, and south. Thailand shares borders with Myanmar (north), Laos (northeast),
Cambodia (Central-southwest), and Malaysia (south).
Despite the distance, students of the school were coming from all parts of Thailand. Most of the students come from Chiang Rai,
Bangkok, Chiang Mai, Phuket, and Nonthaburi. The international students were only 5% and mostly came from Yunnan province of
China and Shan state of Myanmar. Fig. 2 Shows the distribution of Thai students’ origins in the observed school (the darker area is
where most students come from).
The population was students from the school of management enrolling in the Accounting course in 2018. Out of 906 population,
860 were domestic students. Out of this number, more than 35% was coming from northern Thailand. The farthest location to the
university is the southern region, but it still sent more students than the northeast did.
Students from the south performed the best (33.93/60.00 points), while students from the north are the lowest (30.74/60.00
points). However, the highest score was achieved at least by one student from the central part of Thailand, followed by at least a
student from the north. Fig. 3 shows the line graph of mean scores according to the students’ origin.
Students from the south are the highest performers, while the northern people are the lowest. The performance of northeastern and
central students was almost equal. Hypothesis 3, there is a different level of understanding in learning Accounting according to the
students’ origins, is accepted since the ANOVA result proves that the difference between groups is significant with a p-value of 0.009
(shown by Table 11).
Fig. 2. Distribution of Thai students’ origins in the observed school.
7
The International Journal of Management Education 19 (2021) 100555
M. Syukur
Fig. 3. Mean of the total of the observation.
Table 12 is the posthoc test result comparing the learning performance of students grouped according to their origin. The only
significant difference was found between students from the north and the south of Thailand. The students from the south obtained
almost 3.2 points higher than students from the north. There was no significant difference in learning performance among other groups
of students.
The southern region is well-known for its natural beauty that attracts many foreign tourists. The region is where Phuket and Krabi
are situated. It makes people from the south are more exposed to foreign languages, such as English. Conversely, the Chiang Rai
province does not yet provide numerous tourist destinations to attract international visitors. The southern region of Thailand also
shares land borders with Malaysia. Many of the students finished their secondary education in Malaysia, whose education system (the
World Bank rank-2017) and English proficiency level (the EF English Proficiency Index-2019) were far much better than Thailand. This
fact made the students from the south of Thailand could perform better than others. Another reason why students from the south
performed better is that usually, students coming from the geographically distant region usually showed his/her best efforts in
studying. Even though there is no supporting literature yet, this finding claims that students’ origin (their home address) positively
correlates with their learning performance.
The international students in this study were not the best performers because most of them are originally from China and Myanmar,
where English is still a foreign language. However, this finding contradicts the finding from Heng (2018), saying that Chinese students
did not find language difficulties in English-speaking countries. According to Harb and El-shaarawi (2007), the most important factor
affecting students’ performance was their competence in English communication. People who have linguistic difficulties, e.g. English
unproficiency, will face hardship in their study due to cognitive load problems (Yang & Farley, 2019), which refer to the constraints
that can buffer the information processes (Sweller, 1988).
5. Conclusion
This study aims to compare the performance of management students in learning Accounting across different variables. There are
three variables taken: gender, major, and region. The result confirms that female students perform better in the Accounting subject
than the male ones. Also, it reveals that students who get fewer quantitative credit hours in their study plan are unfavored in learning
Accounting. Additionally, it also shows that students from the south of Thailand could get the highest score in accounting learning
among students from other regions in Thailand and International.
This case study is applied to a population of more than 900 management students. The results can be beneficial for readers from
8
The International Journal of Management Education 19 (2021) 100555
M. Syukur
Table 11
ANOVA test result across students’ origin.
Sum of Squares
Between Groups
Within Groups
Total
df
959.823
63981.929
64941.752
Mean Square
4
901
905
239.956
71.012
F
Sig.
3.379
.009
Table 12
Multiple comparisons based on students’ origin.
(I) region
Northern
Northeastern
Central
Southern
International
a
(J) region
Mean Difference (I-J)
Northeastern
Central
Southern
International
Northern
Central
Southern
International
Northern
Northeastern
Southern
International
Northern
Northeastern
Central
International
Northern
Northeastern
Central
Southern
Std. Error
− 1.31157
− 1.33431
− 3.18797a
-.46746
1.31157
-.02274
− 1.87640
.84411
1.33431
.02274
− 1.85366
.86685
3.18797a
1.87640
1.85366
2.72051
.46746
-.84411
-.86685
− 2.72051
1.05894
.64216
.95644
1.26839
1.05894
1.08265
1.29404
1.53902
.64216
1.08265
.98262
1.28825
.95644
1.29404
.98262
1.47037
1.26839
1.53902
1.28825
1.47037
Sig.
.729
.231
.009
.996
.729
1.000
.596
.982
.231
1.000
.328
.962
.009
.596
.328
.351
.996
.982
.962
.351
95% Confidence Interval
Lower Bound
Upper Bound
4.2474
3.0909
5.8236
4.0380
1.6243
3.0224
5.4424
3.4306
-.4223
2.9750
4.5590
2.7529
.5523
1.6896
-.8517
1.3679
3.1031
5.1188
4.4866
6.8089
1.6243
.4223
-.5523
3.1031
4.2474
2.9750
1.6896
5.1188
3.0909
3.0204
.8517
4.4866
5.8236
5.4424
4.5590
6.8089
4.0380
3.4306
2.7529
1.3679
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
The mean difference is significant at the 0.05 level.
various parties. Some recommendations can be addressed from the research results of this paper. They are as follows:
1. The head of the accounting department in universities should design a special syllabus for a major like Business Administration,
Tourism Management, and Hospitality Industry Management. Also, the head can consider the gender balance for lecturers teaching
in the institution.
2. Accounting lecturers should give different teaching approaches for students who have less exposure to numbers.
3. Universities in non-English speaking countries should add English language subjects or courses so that students can understand
English-delivered lecturers better. Increasing the entry requirement for English proficiency is not advisable.
4. Future academicians can fill the research gap by employing more student attributes that can influence students’ performance in
learning Accounting, especially across non-Accounting students.
During the research process, the author faced some limitations that future researchers can improve. The limitations and the
suggestions would be:
1. This research is limited to management (non-Accounting) students enrolling in an Accounting course in 2018. Future researchers
should expand the time series and compare whether each batch also performs differently.
2. Variables in this research are limited to gender, study majors, and origins. Future researchers might comprehend the variables by
adding high school major and GPA, English proficiency, and university admission rank or score.
3. The analysis is only limited to the test of comparison of means. Researchers in the future might add more tests, such as multiple
regression.
4. In the observed institution, the teachers are all males. Future researchers might want to see if students perform better if the teachers
are from the opposite gender.
Author statement
Muhammad Syukur: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project
administration; Resources; Software; Supervision; Validation; Visualization; Roles/Writing - original draft; Writing - review & editing.
9
The International Journal of Management Education 19 (2021) 100555
M. Syukur
Acknowledgement
The author would like to thank the Registrar Division staffs and colleagues in the School of Management for their support.
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