Abstract
This paper unpacks the factors likely to influence students’ use of supplementary private tutoring in Qatar. Drawing on insights from Ajzen’s theory of planned behavior (TPB), the current study seeks to understand the main predictors of private tutoring usage in the context of Qatar. This study used survey questionnaire data to ascertain key predictors of participation in private tutoring, as perceived by students in preparatory schools (grades 8 and 9) and secondary schools (grades 11 and 12). The regression analysis revealed that upper-grade students were more likely to use private tutoring than their lower-grade counterparts. Additionally, parental attributes, particularly their educational levels, employment status, and involvement in their children’s schooling, were strong determinants of household decisions to hire private tutors. The results also indicated that the demand for private tutoring is strongly associated with the quality of teaching. The paper offers relevant recommendations for policymaking and calls for future study and research.
Introduction
Until recently, public (government-funded) education systems have been the main, and often the sole, providers of schooling suited to students’ desires, talents, and capabilities. With the changing dynamics of the educational landscape, other educational alternatives have emerged and are operating in full swing. Private supplementary tutoring is an analogous—and potentially rival—form of education running parallel to official mainstream education. Also referred to as shadow education (Aurini et al., 2013; Bray, 1999, 2006; Y. C. Kim & Jung, 2021), private tutoring has become a global phenomenon (Zhang & Bray, 2021).
In this study, private tutoring is viewed as a practice that involves using additional supplementary instruction outside regular school hours (Bray et al., 2014; Bray & Lykins, 2012; Brehm & Silova, 2014; J. Lee, 2013). Despite its growing importance in scale and intensity, private tutoring has not received sufficient attention in the literature (Zhang & Bray, 2020). While the nature and the scope of private tutoring vary from one country to another (Bray, 2021; J. Lee, 2007; Silova & Bray, 2006), available research has focused on the spread of this phenomenon in specific world regions, specifically in East Asia (Bray & Lykins, 2012; S. Kim & Lee, 2010) and several other areas. Within the Arab world, research in this area is starting to emerge (Ali, 2013; Bray & Hajar, 2022; Hartmann, 2013; Sobhy, 2012), policy briefs and working papers (Al Sumaiti, 2012; Farah, 2011; Stepney, 2016), which provide sketchy overviews of the extent, drivers and impact of private tutoring in the region.
Throughout the Arab world, many students enrolled in mainstream education concurrently attended a certain form of private tutoring classes. The statistics about students reporting having private tutoring worldwide vary. The OECD suggests the average is roughly 28% (Al Sumaiti, 2012; Farah, 2011). Southgate’s (2009)“shadow education” analysis of cross-border factors surveyed 250,000 students from 36 countries, including 21 European states, the United Kingdom, Australia, Canada, Brazil, and Uruguay. It was reported that there are tutors in all countries surveyed. School student participation rates range from 8% to 74%.
Private tutoring in some Arab countries reported being in the upper range, such as Egypt at 69% (Central Agency for Public Mobilization and Statistics [CAPMS], 2016), UAE students at 65% (Farah, 2011), Jordan ranging from 66.2% to 83.2%, depending on the region of the country (MOE, Educational Statistical Report 2010–2011). Although private tutoring in Qatar is estimated to be around 36% of all secondary students, Stepney (2016) reports a modest increase over the past years.
The purpose of this current study was two-fold. Firstly, it sought to unpack the main drivers likely to shape students’ decisions to receive private tutoring in Qatar. Secondly, by providing an Arab perspective, the study aimed to inform education policy and decision-making in Qatar and the wider Arab region. The study will offer insights into the factors that influence the demand for and use of private tutoring in the Arabian Gulf State of Qatar. The topic of private tutoring in Qatar and the broader Gulf Cooperation Council (GCC) region is largely under-studied and deserves more attention. Therefore, this research will contribute to private tutoring research and policy literature.
In Qatar, private tutoring is prohibited by law (Law 23 of 2015), and stiff fines are imposed on educational providers who function externally of ministry oversight (Stepney, 2016). In 2010, the Ministry of Education and Higher Education (MEHE) launched measures aiming to crack down on illegal private tutoring in the country (Raslan, 2020). Stepney (2016) argues that Qatar hosts an unregulated tutor “shadow education” system. Tutors often engage in private non-contracted work at student homes. Private Education Centers that offer educational services that meet the standards of the MEHE and are granted educational and training center licenses are legal in Qatar (Ministry of Education and Higher Education, n.d.).
However, despite the ban imposed by Qatar’s government to regulate the practice of using private tutors outside regular schooling, the demand for private tutors is intensifying and this phenomenon shows no sign of abating. Because private tutoring is viewed as a tool for advancing a child’s academic performance and achievement, demand for it will not cease to exist (Rao, 2017). Findings derived from the Qatar Education Study 2018 (A. L. Sellami, 2019) demonstrate that 40% of students use private tutoring. The results further reveal that parents spend a monthly average of 1,400 Qatari Riyals (approximately $400) on private tutoring. Considering the average Qatari household, comprising roughly eight or nine people earns 72,700 Qatari Riyals tax-free per month (approximately $19,917) (Sergon, 2022) or 2% of monthly wages.
The present research draws on the Qatar Education Study (QES), which comprises four surveys conducted by the Social and Economic Survey Research Institute (SESRI) in October–November 2018: student, parent, teacher, and school administrator surveys. For this research, we focused on students and used a few items from the teacher questionnaire to inform the findings from student surveys. Using data from the QES study offers one of the first analyses of the determinants shaping private tutoring with data from schools representing the full spectrum of public and private educational offerings in Qatar. Particular emphasis is placed on public (government-funded) and international schools.
This paper is organized as follows. The first section offers background information contextualizing the study’s research problem. Section two critically reviews the literature on private tutoring and highlights salient gaps in the relevant scholarship. Section three describes the methodology employed in this study, including the design, participants, and measures used in the research. Section four outlines the mode and the techniques used in analyzing the study’s data. The results of the study are presented and discussed in Sections five and six, respectively. Finally, the paper concludes with a discussion of the findings and provides several recommendations.
Context of the Study
Qatar is a small Arabian Gulf state that is part of the Arab States, consisting of 22 Arab countries and members of the Arab League inhabiting much of the Middle East and North Africa. Seib (2005) argues that there is no generally accepted definition of the “Arab world,” but the ties that connect the Arabs are ethnic, linguistic, cultural, historical, and nationalist. It is geographical, political, and often associated with religious and cultural identities (Deng, 1995). In Arab countries, the government uses standard Arabic. Qatar is a political and economic union of Arab countries adjacent to the Arabian Gulf, gathered within the Gulf Cooperation Council Countries (GCC). These include the United Arab Emirates, Saudi Arabia, Qatar, Oman, Kuwait, and Bahrain. Since the discovery of oil, the GCC region has undergone significant transformation and is now home to some of the fastest-growing economies in the world. The GCC countries have similar cultures, similar language(s), religion, history, norms, and values, as well as “…similarities in the development of their socio-economic and political structures, so much so that they together constitute a societal type particular to this oil-rich region” (Khalaf & Alkobaisi, 1999, p. 271).
With a demographic imbalance where nationals are largely under-represented, Qatar is over-reliant on migrant workers from foreign countries to compensate for its sharp workforce deficit in various sectors ranging from financial services to education, healthcare, tourism, and construction. Qatari nationals accounted for less than 15% of the country’s total population. The population also includes other Arab nationalities (13%), Indian (24%), Nepali (16%), Filipino (11%), Bangladesh and Sri Lankan (5% each), US (1.25%), UK (0.7%), and Canada (0.3%)) Also, there are approximately 250,000 Filipinos in the country, making them the third-largest group of expatriates (Online Qatar, 2019; World Population Review, 2022). Thus, a challenge facing Qatar’s target of transitioning into a knowledge society is the lack of national professionals possessing the skill sets in demand in various knowledge economy fields (Barnett, 2015; Organisation for Economic CoOperation and Development [OECD], 2014; Wiseman et al., 2016).
With this demographic composition, the job market in Qatar is highly segmented, with a strong presence of Qataris working in the public sector, matched with a vivid density of expatriates in the private sector (Kabbani & Mimoune, 2020; World Bank, 2013). Historically, the government in Qatar has always been a key employer of nationals who have a strong penchant for public sector jobs (Momani, 2017). Overall, the choice of public sector jobs stems from a range of factors, such as highly competitive salaries, job security, low expected productivity, and favorable work conditions, including shorter working hours (Golkowska, 2014; Johnsen, 2015).
Qatar’s leaders deployed the wealth generated from ample natural gas and oil resources to revamp the education system and advance the country’s educational profile. In line with Qatar’s National Vision 2030, successive governments have taken important steps to modernize K-12 schooling in Qatar. A conspicuous example is the Education for a New Era (EFNE) reform, an initiative launched in 2002 to overhaul K-12 education in Qatar (Brewer et al., 2007). At the same time, significant investments have been channeled toward turning the country into a regional hub of higher education, resulting in the establishment of several international branch campuses housed in Education City (Al-Ali Mustafa et al., 2018).
Qatar’s school system is composed of the following school categories: (1) public (government-funded), (2) private international, (3) private Arabic, and (4) community schools. Public schools, which are all free for Qatari citizens, are a favorite destination for most Qatari students (Ministry of Development Planning and Statistics [MDPS], 2017). Education level in Qatar’s government schools is as follows, “Primary education from grades 1 to 6 (age group of 6 to 11 years), Preparatory education from grades 7 to 9 (age group of 12–14 years), Secondary education for grades 10 to 12 (age group of 15–17 years)” (Qatar Development Bank, 2020, p. 14). As of the 2018–2019 school year, government schools comprised 54% Qatari and 46% non-Qatari students from various Arab and non-Arab countries (Qatar Development Bank, 2020). These are single-gender, with separate schools for boys and girls, emphasizing Arabic and Islamic education subjects. International schools offer tuition for English-speaking Western expatriates, but some local and resident families enroll their children in these schools. Comprised within this type are American, British, and Canadian schools. Community schools use the languages and curricula of specific countries and admit students from those countries based in Qatar; these include Egyptian, Filipino, Indian, Pakistani, and Turkish schools, for example.
Jaafar (2011) points out that government schools in Qatar apply a performance-based accountability system using the Qatar Comprehensive Educational Assessments (QCEA) final exam grades 4 to 11 are administered in four subject areas: Arabic, English, Mathematics, and Science. Also, the Overall Senior School Scores (QSSC) exam includes a sequence of four final exams given at the end of the final semester for Year 12 students taken in a single time frame that covers the same areas as the QCEA exam.
There are concerns about the growth of tutors in Qatar. Stepney (2016) suggests a link between tutoring and school absenteeism and that regular access to tutoring correlates with increased absenteeism. The concern is that reliance on a tutor can lead to indifference and discouragement, leading to student absenteeism. As a result, MEHE has defined and implemented attendance policies at schools in Qatar, which has brought tangible improvements to student attendance. The spread of tutoring practices in the country has become a “convenient way to make up for absent lessons” (Stepney, 2016, p. 3).
Research Problem
Drawing on past research on private tutoring in other world regions, this study sought to investigate the factors that impact students’ likelihood of using private tutoring in Qatar. It is anticipated that a correlation would be observed between students’ individual and household characteristics and private tutoring. Contextual (school) factors were also expected to be associated with private tutoring. Two specific questions guided the current study:
(a) What are the factors that influence students’ use of private tutoring in Qatar?
(b) Are there any significant relationships between individual, household, and school factors and private tutoring?
Review of Literature
Ajzen’s (1991) theory of planned behavior (TPB) provided a framework for the present study and insights into the factors that shape familial decisions to use private tutoring. As Ajzen (1991) explains, TPB predicts and explains the intent of an individual to engage in the behavior at a particular time and place. The theory postulates that individuals’ intentions to engage in various behaviors can be forecasted with a high level of accuracy based on attitudes toward the behavior, subjective norms, and perceived behavioral control.
These intentions, coupled with perceptions of behavioral control, account for considerable variance in actual behavior (Ajzen, 1991). TPB posits that behavioral intent represents a person’s motivation, conscious plan, or decision to perform a particular behavior. Second, TPB addresses the personal attitudes toward the behavior, the extent to which the person has positive or negative emotions toward the behavior of interest, and the consequences of performing the behavior. Next, subjective norms or beliefs about how others are important to the performance of an individual’s behavior. This is related to the social environment surrounding behavior. Finally, Ajzen (1991) views behavioral control as an individual’s perception of how easy or difficult it is to perform a behavior (Ajzen, 1991). TPB has received widespread empirical support for explaining individual behavior and behavior in institutional settings (Morris et al., 2005).
For this research study that examines tutoring, TPB suggests that students’ decisions to receive private tutoring are jointly influenced by behavioral intent, such as students’ aspirations, individual’s attitude toward the behavior, such as being bored at schools, and subjective norms or the social environment surrounding behavior such as parents. The survey in this study does not provide data regarding behavior control. This study also built on TPB to see if private tutoring was associated with student, household, and school characteristics.
Private Tutoring
As a fee-based profit-making business, private tutoring is delivered by private individuals (e.g., teachers and senior or advanced students) and centers or institutes that teach various academic subjects. Addressing tutoring in Hong Kong, Yung and Bray (2017) discuss three major features that characterize private tutoring. First, “privateness” specifies tutoring provided in return for a fee. Secondly, “supplementation” indicates that private tutoring supplements the public education system and takes place outside school hours. Third, “academic subjects” refers to the core school subjects and excludes those studied for “leisure and/or personal development such as music, art and sports.” (p. 96).
An important step in understanding the volume, intensity, and complexity of private tutoring lies in identifying why households invest extra time and money in hiring a private tutor. Current research points to a host of predictors of the likelihood of hiring a private tutor by a household. Many studies have used a combination of macro and micro variables to explain why students attend private tutoring (Bray & Lykins, 2012; S. Kim & Lee, 2010; J. Lee, 2013). For example, examining 23 developing and developed countries, literature Dang and Rogers (2008) report that national cultural values, the level of competition for top universities, the characteristics of educational systems, and the labor market are among the macro-level factors identified. On the other hand, micro-level factors are wide-ranging and encompass student factors and household characteristics of tutoring in Korea (S. Kim & Lee, 2006; J. H. Kim & Park, 2010) and Hon Kong (Zhan et al., 2013).
Teaching
Ineffective classroom teaching, too much reliance on academic performance, lack of individualized student attention, and standardized examinations have been identified in the literature as strong determinants of participation in private tutoring globally (Bray, 2023) and specifically in Turkey (Atalmis et al., 2016). Other research demonstrates that the desire to secure admission to elite and renowned higher education institutions is a predictor of enrollment in private tutoring, including studies conducted by Das and Das (2013) in India and Berberoğlu and Tansel (2014) and Turkey. For example, in a study conducted in Korea, where the level of participation in private tutoring is very high, S. Kim and Lee (2010) found that households with higher levels of wealth spend more on hiring private tutors and that parents’ level of education—particularly the mother’s—has a strong effect on the use of private tutoring. The researchers further concluded that whether the mother works outside the home does not significantly impact their use of private tutoring. In another study, Tansel and Bircan (2006) noted that households in urban areas in Turkey spend significantly more on private tutoring than those in rural areas.
Parents
Documented research has shown that parents’ involvement in their children’s schooling in Arab societies is limited (Faour, 2012; Khasawneh & Alsagheer, 2007). Rocha and Hamed (2018) studied teaching in the UAE and reported that the most common reason parents hire tutors was to improve exam scores or learn the material better. Furthermore, they categorized reasons for hiring private tutors into three areas. First, the academic requirements are very high. For example, the school curriculum is very demanding, and the semester has too many exams. Tutors can help children with homework. Second, there are concerns over education quality where parents believe that although the quality of the school is good, providing tutoring will provide the child with an academic advantage. Also, if the school quality is viewed as poor, the tutoring will make up for the poor education. Parents also hired tutors if they believed that teacher(s) were of poor quality. Finally, Rocha and Hamed (2018) suggest parents comply with external influences such as peer pressure from other parents who hire tutors and the fear that their child would fall behind or be left out. Another reason was that the principal or one of their child’s teachers encouraged tutoring outside regular school hours.
The bulk of scholarship has concentrated on the factors likely to influence the use of private tutoring, shedding light on some fundamental dynamics, workings, and ways of operation of this phenomenon. However, little is known about how private tutoring boosts students’ academic achievement. The studies reporting on student achievement are mixed. For example, Berberoğlu and Tansel (2014) studied private tutoring in Turkey and reported that tutoring positively impacted math and Turkish academic performance but not in the natural sciences. Sohn et al. (2010) reported a positive relationship between the time spent on tutoring and the student’s achievement in China. In the GCC region, few studies investigate tutoring a student’s achievement. Faour (2012) reported that in Kuwait, Qatar, and Saudi Arabia, there was no significant relationship between achievement due to private tutoring. Much less work has been done to investigate whether private tutoring enhances students’ learning engagement and motivation.
The present study looks at this line of research in Qatar. Within the context of Qatar, there is a dearth of documented information about private tutoring despite the importance it may have for educational policy planning and decision-making in the country. Other than a study investigating the drivers shaping parental use of private tutoring (A. Sellami & Le Trung, 2020), only three studies have investigated this phenomenon, and in a rather sketchy manner: the Qatar Education Study 2012 (Jardina & Johnston, 2013), the Qatar Education Study 2015 (Al-Emadi et al., 2016) and the Qatar Education Study 2018 (A. L. Sellami, 2019). The three studies were carried out by SESRI based at Qatar University.
Method
Research Design
The data used in this research originates from a paper-and-pencil survey conducted by the Social and Economic Survey Research Institute (SESRI) at Qatar University. The main objective of the QES was to examine the perceptions of students, parents, teachers, and school administrators about diverse aspects of K-12 education. This present study focuses on data from the student questionnaires using Likert and other measurement scales. For this study, the questionnaire was designed based on models developed and validated by Bray et al. (2014, 2015). The questionnaire instrument was available in both English and Arabic. Originally, questionnaires were designed in English and then translated into Arabic by professional translators. Then, bilingual staff at SESRI checked the equivalence of the instruments. A pre-test was conducted in four randomly selected schools, leading to the final questionnaire revision.
After receiving the appropriate IRB approval, official letters were sent to the relevant schools requesting permission to conduct the study. Students and their parents/guardians were informed in advance about the purpose of the research, that participation in the survey was voluntary, and that their responses would be kept strictly confidential. Consent forms for both students and parents/guardians were handed to students to take home and return.
Participants
The target population of the QES 2018 comprised students in preparatory (8th and 9th grades) and secondary (grades 11th and 12th) schools. The choice of these grade levels stems from the fact that these are preparatory (grades 8 and 9) and secondary (grades 11 and 12) exit levels and may rely on a private tutor to pass their exit exams. The sampling frame was a list the Ministry of Education and Higher Education provided, including public, private, and community schools in Qatar. The schools were classified according to the school system (public, private international, private Arabic, and community), school gender (male, female, or coed), and school level (preparatory or secondary).
Proportionate sample allocation was implemented to ensure that the number of students in each stratum was proportionately similar between the frame and sample. In each stratum, schools were randomly selected using a two-stage sampling procedure. In the first stage, schools were randomly selected with probability proportionate to their size (PPS). In the second stage, one class for each grade (8, 9, 11, and 12) was randomly selected, and all students completed the survey. To ensure unbiased estimates, weights were created to account for selection probability. Weight trimming was also used to avoid undesirable variability in the estimates.
In total, 37 schools and 1,803 students participated in the survey, yielding a response rate of approximately 81%. Following data cleaning and editing, this article is based on a sample of 1,138 students who indicated they took private tutoring. The remaining students were, therefore, included in the analyses. The final sample included 67% from public schools and 33% from international schools.
Students from Community schools and Arabic private schools were excluded from the analysis due to their small number. A total of 45.4% of the students are male and 54.6% female. A total of 38.2% of the students are Qatari citizens, while 61.8% are non-Qatari (expatriates). The grade distribution of the students is 22.8% in 8th grade, 24.3% in 9th grade, 26% in 11th grade, and 26.8% in 12th grade.
Measures
The following paragraphs describe the measures used in the analyses to address the study’s research questions. Descriptive statistics for the measures, both for the total sample and for Qatari and non-Qatari students, are provided in Table 1.
Sample Characteristics.
Private Tutoring
This is the dependent variable for the analyses. The students were asked: “Do you hire a private tutor?” with “Yes” and “No” response alternatives. A dummy variable was used in the analyses, with a value of 1 representing the use of private tutoring.
Students’ Characteristics
Gender, grade, attitudes toward school, and students’ aspirations were included in the models as student characteristics. Regarding
Bored at School
Students were asked: “How often do you feel bored when you are at school?” and were offered three response options: (1) Most of the time, (2) Once in a while, and (3) Never. To highlight differences, responses of “Once in a while” and “Never” were collapsed, meaning that this variable was included in the models as dichotomous (1 = Most of the time, and 0 = Once in a while + Never).
Likely Going to College
Students were asked: “How likely is it that you would go to college after you leave secondary/high school?” and the following response options were presented: (1) Very likely; (2) Somewhat likely; (3) Somewhat unlikely; (4) Very unlikely; and (8) I don’t know. Responses were collapsed to create two categories: 1 = Very likely, and 0 = Don’t know + Somewhat likely + Somewhat unlikely + Very unlikely. To highlight differences, responses for “Bored at school” and “Likely to go to college” were dichotomized in this article, a practice uncommon in analyzing data. It is important to distinguish between continuous and categorical variables. Existing studies, past and recent, have similarly dichotomized variables (see MacCallum et al., 2002; Ragland, 1992; Rucker et al., 2015).
Parent characteristics such as education level and occupation were included in the models as household characteristics. Students’ perceptions of parent involvement in school homework assignments were also included.
Father’s and Mother’s (Male or Female Guardian’s) Highest Education Level
Students were asked: “What is your father/male and mother/female guardian’s highest education degree or certificate?” and the following response options were provided: (1) Never joined school; (2) Elementary; (3) Preparatory; (4) Secondary; (5) Post-secondary diploma; (6) Bachelor’s degree; (7) Master’s degree; and (8) Ph.D. Categories were collapsed to form a dichotomous variable, where 1 = Bachelor’s degree (B.A.) or more, and 0 = Less than B.A.
Father’s and Mother’s Current Employment Status
This question was asked of the students: “What is your father’s and Mother’s current employment status?” with the following response options: (1) Full-time employee; (2) Part-time employee; (3) Unemployed, seeking a job; (4) Unemployed, not seeking a job; (5) Retired; (6) Unable to work; and (7) Other. Categories were collapsed to form a dichotomous variable, where 1 = Father not at home (Full-time employee + Part-time employee), and 0 = Mother at home (Unemployed, seeking a job + Unemployed, not seeking a job + Retired + Unable to work + Other). In total, 63 responses were imputed.
Discussing Subjects With Parents
Students were asked: “In the past four week, how often did you discuss the subjects studied in class with either one or both of your parents/guardians?” and the response options were: (1) Never; (2) Once; (3) Twice; (4) Three times; (5) Four times or more; and (6) I do not remember. Categories were regrouped to create a binary variable, where 1 = Four times or more in the past 4 weeks (Four times or more), and 0 = Less than four times in the past 4 weeks (Never + Once + Twice + Three times). Responses “I do not remember” were coded as missing values.
Parents’/Guardians’ Help With Homework
Students were asked: “In a typical week, how often do your parents, guardians, or others at home help you with your homework assignments?” and the response alternatives were: (1) Not at all; (2) Once; (3) Twice; (4) Three times, and (5) Every day. Categories were collapsed to create a dichotomous variable: 1 = Once + Twice + Three times + Every day in a typical week, and 0 = Not at all in a typical week.
Contextual (School) Characteristics
Questions regarding teacher’s performance and school-level variables are included in the models as contextual characteristics.
Teaching
Students were asked: “To what extent would you agree or disagree with each of the following statements in relation to your current school?” with the following response options: (1) I enjoy going to this school; (2) Students get along well with teachers; (3) Behavior rules are strict at school; (4) Discipline is fair at school; (5) Teaching is good; (6) Teachers care about students; (7) When I work hard on schoolwork, my teachers praise my effort; (8) In class, I often feel “put down” by my teachers; (9) Most of my teachers listen to what I’m trying to say; (10) I don’t feel safe at this school; (11) Disruptions by some students get in the way of my learning; (12) Misbehaving students get away with it; (13) Students’ efforts are reflected in their grades; (14) Teachers do not make enough effort; (15) The curriculum is well prepared; and (16) I do not make my maximum effort in studying. Response options were: (1) Strongly agree; (2) Somewhat agree; (3) Somewhat disagree; and (4) Strongly disagree. After collapsing the categories, a binary variable was created, where 1 = Strongly agree + Somewhat agree, and 0 = Strongly disagree + Somewhat disagree.
School Type
This variable is an administrative variable obtained from the sampling frame and has four categories: (1) government, (2) international, (3) community, and (4) Arabic private. However, only the first two school types were used for the statistical analysis due to the low number of cases in the last two. These categories were coded as 1 = Government and 0 = International.
Nationality and Time Living in Qatar
This measure was created using two questions included in the students’ questionnaire. The first one asked: “What is your nationality?” and response alternatives were: (1) Qatari and (2) non-Qatari. The second question used was: “How long have you lived in Qatar?” and response options were: (1) Less than six months; (2) 6 months to 1 year; (3) More than 1 year to 2 years; (4) More than 2 years to 5 years; (5) More than 5 years to 10 years; (6) More than 10 years to 20 years; (7) More than 20 years; and (8) All my life/I was born in Qatar. A categorical variable was created, where 1 = Qatari; 2 = non-Qatari living no more than 10 years in Qatar, and 3 = non-Qatari living more than 10 years in Qatar. The second category of this new variable was used as a reference group in the models.
Data Analysis
To study the determinants of private tutoring, logistic regressions were performed. As with other types of regression models, logistic regression’s main objective is to describe the relationship between a dependent variable (or outcome variable) and independent variables, which are usually referred to as predictors, explanatory variables, or covariates (Hosmer et al., 2013). However, the dependent variable in logistic regression is binary or dichotomous, meaning it has only two possible values, commonly coded as 1 and 0, where 1 represents the “success” and 0 “failure.”
This type of technique allows for predicting the odds ratio of being in group 1. The odds ratio tells us how the presence or absence of property influences the outcome variable. This research aims to study how likely a student is to use private tutoring depending on different covariates presented at three levels: students, household, and contextual. STATA 14 was used for the statistical analysis. The study used the
Three logistic models were performed, one for the full population of students, another for the subpopulation of Qatari students and the last for the subpopulation of non-Qatari students. Model diagnostic and goodness-of-fit were conducted to ensure no violations of logistic regression assumptions and to guarantee that the model fit the data well. To facilitate the interpretation of the results, this paper shows the estimated odds ratios instead of the estimated regression coefficients.
Results
The following section addresses the two research questions that center on the factors that influence students’ use of private tutoring in Qatar and any significant relationships between individual, household and school factors, and private tutoring.
The variable “Bored at school” similarly affects grade level. In general, students who feel bored at school most of the time have an odd of taking private tutoring 75.8% higher than students who occasionally or never feel bored at school. As happened with the variable “grade,” no matter the citizenship, students who are bored at school most of the time are more likely to hire private tutors. As is shown in Model 3, Qatari students who are bored at school most of the time have an odd of being enrolled in private classes 98% higher than Qatari students who don’t get bored very often. Similarly, non-Qatari students who frequently get bored at school have odds of taking private classes 62.9% higher than non-Qatari students who frequently get bored at school.
Even though being in 12th grade significantly explains why students take private tutoring, expectations about going to college are not significant. This means that with respect to taking private classes, there is no difference between students who feel they are very likely to go to college and those who do not. Table 2 shows the independent variables’ estimated odds ratios and the standard error between parentheses. Percentages illustrated in Table 2 represent the highest category. The three models included in Table 2 present the results of the analyses to explain taking private tutoring for the following three groups: (1) Model 1 is for all students; (2) Model 2 includes only non-Qatari students; and (3) Model 3 includes only Qatari students.
Estimates of Odds Ratios for Private Tutoring.
Household Characteristics
The parents’ education level is also significantly related to private tutoring, but for different subgroups. Qatari students are more likely to use private tutoring if their fathers/male guardians have at least Bachelor’s degrees. Their odds are 91.8% higher than for Qatari students whose father/male guardian does not have a Bachelor’s degree. However, the father’s education is not significant in the model for non-Qatari students (Model 2). In contrast, mothers’ education is a significant predictor of the use of private tutoring for non-Qatari students but not for Qatari students. The results show that non-Qatari students whose mother has at least a Bachelor’s degree have an odds ratio of using private tutoring 30.7% lower than non-Qatari students whose mother does not complete a Bachelor’s degree.
The mother’s current employment status is also significantly related to the likelihood that students will use private tutoring. Overall, if the mother is not at home, it is more likely the student will use private tutoring, with students whose mother is not at home having an odd of using private classes, which is 29.7% higher than students whose mother is at home most of the time. However, there is no significant effect of the variable when we move to the two models for Qatari and non-Qatari students.
Students who discuss subjects with their parents are more likely to take private tutoring than those who do not discuss subjects with them. Particularly, students who discuss subjects with their parents four times or more during the week have an odds ratio of hiring a private tutor, which is 29.8% higher than students who discuss subjects with their parents less often. Parental help with homework is significant in all three models. In general, students who received help with homework have an odd of using private tutoring, 58.1% higher than students who do not receive help. For Qatari students that received support, the odds are 53.5% higher, and for non-Qatari students, they are 57.5% higher.
Contextual (School) Characteristics
Three contextual variables affect private tutoring, but they are not consistent across the models. Qatari students who strongly agree with the statement “Teaching is good” are less likely to enroll in private tutoring classes. The odds are 46.8% lower than Qatari students who do not strongly agree with the statement. Qatari students are more likely to use private classes than non-Qatari students in the model for all students, with an odds ratio 220% higher.
Discussion
This study’s results reveal that students’ characteristics, behavioral determined personal attitudes, subjective norms, or beliefs are important predictors of their enrollment in private tutoring. Specifically, results show that upper-level (grade 12) students are more likely to enroll in private tutoring in Qatar than their peers in lower grade levels. The high rates of private tutoring among upper-grade college-going students, especially those about to exit high school, may be indicative of their desire to perform well in exams and exit/high stakes standardized exams. This interpretation not only aligns with Mandikiana (2021), who reported that Qataris and non-Qataris mostly use private tutoring to pass exams. Additionally, this study contributes to the existing body of research by demonstrating that various parental characteristics, such as their educational attainment, employment status, and level of engagement in their children’s education, significantly influence the household’s choice to hire private tutors. Not surprisingly, tutoring in the upper grades may be attributed to parents’ willingness to enhance their children’s chances of admission to the more selective colleges and universities. The results corroborate similar findings in other contexts, demonstrating that private tutoring is most common among students in the final stages of secondary school (Silova, 2010; Smyth, 2009; Zhan et al., 2013). However, the results of this investigation add to the literature by indicating that private tutoring is predominantly prevalent among students in the advanced phases of secondary education in Qatar.
TPB suggests that personal attitudes toward the behavior could be associated with tutoring. The results derived from this study add to this knowledge by revealing that boredom and, to a lesser extent, lack of motivation at school appear to be associated with students’ use of private tutoring. Could this imply that additional tutoring outside formal schooling increases students’ motivation and thus become more inattentive in their regular classes, thus mirroring previous research by Guill and Bos (2014)? Evidence suggests that using private tutoring undermines the likelihood that students will attend their regular classes at school and increases the rate of student absenteeism (Bhorkar & Bray, 2018; Liu & Bray, 2020; Zhang & Bray, 2017). Reporting research by Ali (2013) and Silova and Bray’s (2006) study, A. Sellami and Le Trung (2020) argue that in the context of Qatar, private tutoring is gradually replacing mainstream schooling. Concerns are that reliance on private tutors may increase students’ drive to feel bored and become apathetic and unmotivated, thus leading to absenteeism. This is in addition to the potential risk of failing to perform well academically at school. Although fostering students’ motivation to learn and engage with schooling is central to Qatar’s recent education reforms (Nasser, 2017), students’ meager attendance rates and lack of motivation are still chronic problems in the country (S. Lee, 2016).
Subjective beliefs about how others view an individual’s performance can influence behavior. For example, household characteristics, particularly parents’ level of education and employment, also emerged as factors shaping students’ use of private tutoring in Qatar. These results align with findings from past research confirming correlations between the father/mother’s level of education and type of occupation and their child’s enrollment in private tutoring (J. S. Kim & Bang, 2017; Zhang & Bray, 2018). Looking at parental education, the results reveal that parents with at least a Bachelor’s degree are more likely to employ a private tutor for their children.
Whereas existing research has shown that highly educated parents are more likely to have higher expectations for their children and thus hire a private tutor (Entrich, 2017; A. L. Sellami, 2019), not enough is known about how and when low-income, less educated families choose private tutoring.
Parents’ employment status also emerged as a significant factor influencing decisions to hire a private tutor. More specifically, the results of this study suggest that students whose mothers are in full-time employment are more likely to hire a private tutor, which echoes similar conclusions arrived at in past research by Park et al. (2011). In a study conducted by Tansel and Bircan (2006), for example, children in households with working mothers, not surprisingly, appear “more likely to receive tutoring, not only because working mothers have less time to supervise their children but also because family incomes are likely to be higher.” (p. 310). These discoveries can now be utilized within the specific circumstances of Qatar. Finally, contextual (school) characteristics also emerged as significantly associated with using private tutoring.
More specifically, this study’s results revealed that the quality of instruction appears to be a strong determinant that influences decisions to hire a private tutor in this study. These results echo previously reported findings confirming the impact that the quality of teaching wields on families’ reliance on private tutoring to make up for possible shortcomings of teaching in regular mainstream classrooms (Paviot et al., 2008; Rocha & Hamed, 2018. In this study, the quality of instruction also emerged as a factor influencing students’ decision to engage in private tutoring. This discovery provides additional corroboration for the findings of Mandikiana (2021) in Qatar, which suggest that inadequate or substandard teaching has a bearing on individuals’ inclination to pursue private tutoring options.
However, while the quality of education is acknowledged as impacting enrollment in private tutoring, empirical evidence indicating the effectiveness of private tutoring appears contradictory and inconclusive (Guill et al., 2020). For example, research conducted by Berberoğlu and Tansel (2014) in Turkey and Ireson and Rushforth (2005) in the UK point to positive effects on students’ achievement. By contrast, other research implemented by Park et al. (2016) and Ryu and Kang (2013) in Korea reveals no or minor effects. Here, caution needs to be taken when looking at the “quality of teaching,” this study’s participants may perceive the term differently according to their age, gender, and grade level. Equally important, the effect of social desirability may also come into play.
Applying the theory of planned behavior to this study evokes that household factors and contextual (school) characteristics jointly influence students’ decisions to receive private tutoring. The findings from this study indicated that parental attributes, including their educational level, employment status, involvement in their children’s education, and teaching quality, are salient predictors of students’ private tutoring usage in Qatar.
Limitations of This Study
This study had several limitations. A constraint of this study is its exclusive dependence on a survey questionnaire as the primary method for collecting data. The data collected in the study relied on self-reports, indicating that the accuracy of some responses could be compromised. This is particularly plausible when participants were queried about subjective notions, such as their attitudes toward school or their level of boredom in a school setting. The study would benefit from replicating the current research using a qualitative approach to enhance the data’s richness and comprehensiveness and expand the scope of the current investigation by adding supplementary data and knowledge. An additional limitation of this investigation lies in its sole concentration on students’ viewpoints. Analyzing the views of parents, teachers, and potentially private tutors would greatly enhance the rigor and comprehensiveness of the data and subsequent data analysis.
Conclusions and Recommendations
When it is unregulated, shadow education can undermine the public good. It runs against the principle of equity, where all children, rich and poor, should be accorded equal educational opportunities. The cost of private tuition can exacerbate social inequalities and may worsen financial burdens on students and their families, particularly those from low-income backgrounds.
This has led to a situation where the use of private tutoring may deny those with no or less exposure to a private tutor opportunity for improved academic performance at school, as is shown in research conducted in Croatia and Bosnia & Herzegovina (Jokić et al., 2013), Japan (Kariya, 2011), South Korea (S. Kim & Lee, 2010), and Turkey (Tansel, 2013) among others.
The findings concluded from this study offer some valuable insights for policymakers and educators in Qatar. The results call attention to the need for concerted efforts to address the issue of shadow education in the country. If checked and adequately regulated, private tutoring may contribute positively to education provision as it can provide enrichment or remedial assistance to at-risk students struggling academically. While there is no one-size-fits-all approach to solving the issue of private tutoring, this study recommends systematically monitoring this problem. The onus rests with governments to impose and especially enforce laws that regulate this phenomenon to ensure it doesn’t undermine mainstream education.
Because private tutoring entails investment in time and money, it is incumbent on all concerned to contribute to managing supplementary education. For example, in collaboration with other government entities, education authorities may encourage the establishment of regulated tutoring centers along with enrichment and remedial after-school tutorials that cater to students’ individual needs. A few of these centers currently operate in Qatar, including Kumon, New Horizons, Geometric Centre, Study Plus, and Berlitz, but existing demand surpasses supply.
Similarly, the Ministry of Education and Higher Education should liaise with primary, preparatory, and secondary schools to help students gain from using and avert misusing supplementary education. Consultations between officials at the Ministry of Education and Higher Education and school principals, parents or guardians, teachers, academic advisors, and school counselors can be crucial in guiding students. Parents should, in turn, encourage their children to emphasize their schoolwork, both inside and outside school walls, rather than readily avail themselves of private options.
Future research is required to extend the existing literature and establish, in more detail, household and other context-specific factors that underlie the use of private tutoring within the context of Qatar and the broader Arab region. Looking at parental perspectives on this phenomenon will also help better understand the educational, economic, and social implications for individuals, families, the education system, and society.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Data Availability Statement
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study