


































Frontiers of Contemporary Education 
ISSN 2690-3520 (Print) ISSN 2690-3539 (Online) 

Vol. 1, No. 1, 2020 

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17 
 

Original Paper 

Determinants of Student Absenteeism/Presenteeism in Qatar: A 

Path Analysis 

Abdel Latif Sellami
1*

, Rima Charbaji El-Kassem
1
, Haneen B. K. Alqassass

1
 & Ahmed Al-Emadi

2
 

1
 Social and Economic Survey Research Institute (SESRI), Qatar University, Qatar 

2
 College of Education, Qatar University, Qatar 

* 
Abdel Latif Sellami, E-mail: asellami@qu.edu.qa

 

 

Received: April 30, 2020          Accepted: May 14, 2020        Online Published: June 2, 2020 

doi:10.22158/fce.v1n1p17                 URL: http://dx.doi.org/10.22158/fce.v1n1p17 

 

Abstract 

The current study sought to investigate the perceptions of school teachers regarding student 

absenteeism and presenteeism in the State of Qatar. Drawing on the existing relevant literature in the 

field and based on a survey research method, the study was carried out during the first term (Fall 

semester) in 2015. The study involved preparatory (middle) and secondary (high) school teachers at 

both public (Independent) and private (International) schools in Qatar. To attain this goal, a causal 

model was used to examine the causes that shape teachers’ perceptions of absenteeism and 

presenteeism. The data required for the present research was collected from a sample of 495 teachers 

at Independent and International schools. Based on factor analysis, the findings concluded from the 

study indicated that seven valid dimensions were extracted. In addition, three determinant factors that 

influence the perceptions of preparatory and secondary school teachers with regard to students’ 

absentee and presentee behaviours were identified. These factors are: (a) reviewing curriculum content, 

(b) the teaching load, and (c) the expected rate of student graduations. The study concludes by offering 

some important recommendations for education practitioners and policy makers as well as some useful 

suggestions for future research and practice. 

Keywords 

Causal path analysis, teachers’ perceptions, student absenteeism, student presenteeism, Qatar  

 

 

 

 

 



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1. Introduction  

In today’s dynamic and highly competitive world, student engagement and motivation are key to 

success. Many educational institutions are plagued with student idleness, non-attentiveness, unrest, and 

indiscipline that undermine the quality of education. International research shows that with many 

students turning into unmotivated and apathetic individuals, increased student absenteeism, lethargy, 

and boredom are a concern for schools and families alikeas more and more students fail to perform 

well at school. Other research, however, confirms that student disengagement leads to absenteeism 

(Archambault, Janosz, Fallu, & Pagani, 2009). 

Because attendance constitutes the first step toward students’ educational success, students, families, 

school practitioners, and the larger community all need to gain a better understanding and more 

appropriately address the challenges associated with absenteeism and presenteeism within schools in 

our communities. No two would disagree that attendance is a key indicator of successful school results, 

as well as productive life outcomes. Students who frequently miss school classes are at a much greater 

risk of poor self-concept, poor school performance, retention, and dropping out (Picklo & Christenson, 

2005). 

Interest in the reasons that drive students to miss classes has prompted researchers to investigate their 

motivation and commitment at school. Examining and understanding the factors influencing students’ 

desire to attend school and actively engage in their learning can be an arduous undertaking and a 

daunting task but will certainly aid in shedding important light on student absenteeism/presenteeism.  

 

2. Background  

Realising major social and economic changes are required to transform their societies from reliance on 

hydrocarbon resources to knowledge-based economies, the six Gulf Cooperation Council countries 

(Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, the UAE) introduced a wave of long-term strategic 

―national vision‖ initiatives often drafted by foreign firms and consultants (Al-Kuwārī, 2012). In Qatar, 

for example, the Qatar National Vision 2030 (QNV), which the leaders articulated in 2008, rests on 

four pillars: (a) human, (b) social, (c) economic, and (d) environmental development (Abduljawad, 

2015). 

Central to QNV 2030 is the need to modernise the country’s education system. To achieve this goal, 

Qatar commissioned the RAND Corporation, to overhaul its entire education system from elementary 

school to higher education (Powell, 2012; Rubin, 2012). The education reform, referred to as Education 

for a New Era, was initiated in 2002 to decentralise education and introduce the principles of autonomy, 

accountability, variety, and choice within the system (Al-Maadheed, 2017). This resulted in the 

creation of independent schools, which replaced government schools, and the establishment of new 

curriculum standards and teacher and leadership professional development (Nasser, 2017). A visible 

consequence of these changes is increased pressure on teachers struggling to juggle many 

responsibilities, especially managing heavy workloads. 



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At the heart of the education reform in Qatar is the call for enhancing student motivation and positive 

engagement in class and other academic environments (Nasser, 2017; QGSDP, 2011). Low student 

attendance rates and lack of student motivation were identified as real challenges in Qatar (Lee, 2016). 

Both issues are persistent chronic problems characterising Qatar’s school system (Alfadala, 2015; 

Badri & Khaili, 2014). There is therefore a pressing need to develop students’ positive attitudes 

towards learning, and to deepen their appreciation of the importance of class attendance (Clump, Bauer, 

& Whiteleather, 2003).  

 

3. Absenteeism/Presenteeism Defined 

Defined as the failure to show up for work as required (Johns, 2009), absenteeism entails missing ten 

per cent or more of total days missed in a school year (Balfanz & Byrnes, 2012). Current research 

indicates consensus amongst scholars that absenteeism is an area for concern (Hocking, 2008). With 

reference to the school environment, there is ample evidence of work done on the reasons and 

consequences of student absenteeism in particular, including studies proposing a myriad of factors that 

distract students from school and hence non-attendance. Discussion of these causes and effects is 

beyond the scope of this paper. Suffice it to say here that personal (Bridgeland, DiIulio, & Morison, 

2006), contextual (Hartnett, 2007) and health (Kearney & Bensaheb, 2006) influences are prime 

reasons why students skip school. Student underperformance remains a major consequence of 

absenteeism (Gottfried, 2010). 

A concept related to absenteeism is presenteeism, a problem many researchers have investigated in 

organisational behaviour and human resources management fields. Presenteeism is defined as the 

condition of being physically present at work but not fully functional, productive or engaged, due to 

health problems (Gerich, 2016). According to Johns (2009, p. 8), ―On a continuum, presenteeism 

stands between full work engagement and absenteeism‖. In this study, presenteeism refers to the 

behaviour or condition whereby students are physically present in class during scheduled class time but 

do not operate to their full potential, thus resulting in loss of productivity.  

 

4. Review of Literature  

While research has documented absenteeism in academic settings (Arulampalam, Naylor, & Smith, 

2012; Chen & Lin, 2008; Credé, Roch, & Kieszczynka, 2010; Schmulian & Coetzee, 2011), very little 

is known about presenteeism in educational contexts (Macfarlane, 2012). Admittedly, research on this 

subject is needed, especially regarding the factors that are likely to cause K–12 student presenteeism 

behaviour and its effect in hindering academic performance (Law, 2007; Macfarlane, 2015; Schalge & 

Soga, 2008). 

 

 

 



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4.1 Presenteeism in the School Context 

Although the subject of presenteeism in the workplace is well-researched, only a handful of isolated 

research efforts have investigated presenteeism in educational settings. Consequently, not enough 

work has been done to study this phenomenon in academic contexts, especially at K-12 levels. Limited 

as it is, the recent expansion of presenteeism from its widely acknowledged use in the workplace to the 

realm of education has brought about a fresh perspective on this topic. Viewing student presenteeism 

as a loss of academic performance due to illness, Ferritto (2016) measured the concept based on five 

behavioural facets that normally support student academic achievement: (a) paying attention in class; 

(b) class participation; (c) class attendance; (d) arriving on time for classes; and (e) note-taking. 

Pioneering work explicitly addressing the problem of presenteeism and academic performance loss 

among students—albeit very limited—has only recently begun to emerge (Ferritto, 2016; Ja úregui et 

al., 2009; Macfarlane, 2012). Scanty as they are, these studies on student presenteeism have 

concentrated exclusively on post-secondary (university) settings, including research undertaken in the 

US (Hysenbegasi, Hass, & Rowland, 2005), Hong Kong (Macfarlane, 2015, 2016, 2017) and Japan 

(Mikami et al., 2013). Although these studies provide insights into presenteeism in academic 

environments, other aspects of presenteeism have received limited attention, including its impact on 

learners’ achievement and measures required to curb the problem.  

In a study involving university students in Japan, Matsushita et al. (2011) developed a Presenteeism 

Scale to assess the existence of presenteeism among participants. First-year students in four universities 

were given a survey on presenteeism and a questionnaire on mental health and eating behavior. The 

study revealed students with emotional problems had higher levels of presenteeism compared to those 

with other health problems and that student presenteeism was associated with health problems (allergy, 

back or neck pain, menstruation, chronic headaches, depression, and anxiety, etc.). In another study, 

Ferritto (2016) designed the Presenteeism and Perceived Academic Performance Scale to measure 

student presenteeism by employing a series of student behavioral traits shown to be supportive of 

academic performance, including paying attention and participation in class, class attendance, tardiness, 

and note taking.  

What prompted this study is lack of information on student absenteeism/presenteeism in Qatar and the 

Arab region. In trying to decipher teachers’ perceptions of student absenteeism/presenteeism in 

preparatory and secondary school levels in Qatar, this study aims to bridge this gap and contribute to 

scholarly knowledge regarding absences and disengagement in pre-college education. Additionally, 

whereas previous work has looked at students’ perspectives (Lee, 2016; Massingham & Herrington, 

2006), teachers’ viewpoints on the topic have been neglected. The present study explores how the latter 

perceive student absenteeism and presenteeism.  

 

 

 



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4.2 Research Questions 

This study sought to examine the factors influencing preparatory (8
th

 and 9
th 

grades) and secondary 

(11
th

 and 12
th

 grades) school teachers’ perceptions of absenteeism/presenteeism in Qatar. In so doing, 

we studied the relationship of three constructs to teachers’ perceptions: (a) reviewing curriculum 

content, (b) teaching load, and (c) student graduation rates. The purpose was to see if there are any 

significant relationships between reported teachers’ perceptions and those three variables.  

The overarching question this study addressed is: What factors shape teachers’ perceptions of student 

absenteeism/presenteeism in Qatar? In particular specifically, answers were solicited to the following 

questions: 

– How do teachers perceive students’ absenteeism/presenteeism?   

– What are the factors that influence teachers’ perceptions of student absenteeism/presenteeism? 

– How are teachers’ perceptions associated with students’ absenteeism/presenteeism? 

 

5. Research Method 

5.1 Research Deign 

This research used a survey research method based on an instrument designed by the Social and 

Economic Survey Research Institute (SESRI), Qatar University. The instrument consists of 98 

statements measuring different dimensions related to teachers’ perception of student 

absenteeism/presenteeism and uses a five-point Likert type scale ranging from 1 (Strongly Agree) to 5 

(Strongly Disagree). 

5.2 Research Sample 

This study involved teachers who teach in preparatory (middle) and secondary (high) school teachers at 

both government-funded (Independent) and private (International) schools in Qatar.1200 teachers from 

the selected schools were surveyed by SESRI fieldworkers using Computer-Assisted Personal 

Interviewing. The data was collected by SESRI during the fall of 2015, with a response rate of 41%. 

The study involved teachers (n=495) at preparatory (grades 8=31.1% and 9=20.6%) and secondary 

(grades 11=27.5% and 12=20.8%) Independent and International schools (see Table 1). Overall, the age 

of participants was distributed with an average of approximately 42 years. Of the 495 questionnaires that 

were returned, 410 were complete and valid for multivariate analysis. Moreover, only 54 of the 495 

teachers who responded are Qatari (10.9%) and 279 are female teachers (56.4%).  

 

 

 

 

 

 

 



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Table 1. Teachers’ Distribution by Nationality, Gender and Grade Level 

Subgroup Frequency Percentage 

Gender   

Male 216 43.6% 

Female 279 56.4% 

Gradelevel   

Grade 8 154 31.1% 

Grade 9 102 20.6 

Grade 11 136 27.5 

Grade 12 103 20.8 

Total 495 100% 

 

5.3 Research Procedure 

After data collection was completed, responses were entered manually into Blaise, a computer-assisted 

interviewing system and survey processing tool. The dataset was then cleaned, coded and saved in 

SPSS format. After weighting the final responses, the data were analysed using SPSS. The survey 

involved a two-stage probability school sample of teachers. The sampling frame was based on a 

comprehensive list of public and private schools provided by Qatar’s Ministry of Education. 

The first stage sample was a proportionate sample of schools according to school size, school type (i.e., 

Independent, International), gender (male, female or co-ed) and grade (8
th

, 9
th

, 11
th

, or 12
th

). Schools 

were randomly selected within each of these subgroups (type, gender, and grade) so that the school size 

selected from each strata was relative to its incidence in the entire sampling frame. In stage two, one 

class from each school grade was randomly selected and teachers of the classes selected were included 

in the survey. 

After getting relevant approvals from the Ministry of Education and Qatar University’s Internal Review 

Board, official letters requesting permission to implement the study were sent to the schools. Teachers 

were informed in advance about the purpose of the research project and were told participation in the 

survey was voluntary and that their responses would be kept strictly confidential.  

43 schools were sampled, with four refusing to participate, resulting in a 90.7% response rate at the 

school level. Classrooms were randomly selected in 39 schools and teachers in selected classrooms 

participated in the survey. However, we do not have information on the actual class sizes to calculate a 

response rate at the classroom level. This design resulted in 495 teachers. Teachers’ response rate was 

82.8% and the maximum sampling error was calculated at +/–2 percentage points, showing this study’s 

instrument has internal reliability and construct validity.  

 

 



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5.4 Measures 

Dependent variable 

Teachers’ perception of student absenteeism presenteeism in Qatar. In the teacher questionnaire, 

teachers were asked: ―To what extent is each of the following a problem in your classes?‖ and were 

instructed to check all that were applicable: (a) Student tardiness is a problem in your classes; (b) 

Student absenteeism is a problem in your class; (c) Student apathy is a problem in your classes; and (d) 

Student unpreparedness to learn is a problem in year class.  

In this study, absenteeism includes ―Student absenteeism is a problem in your class‖ and presenteeism 

comprises ―Student tardiness is a problem in your classes‖, ―Student apathy is a problem in your 

classes‖, and ―Student unpreparedness to learn is a problem in year class‖ as will be seen in the results 

section below.   

Independent variables 

Teaching load: 

Teachers were also asked: ―Currently, how many hours do you teach per week?‖ followed by the 

following options: ―I don’t know‖ and ―refused‖. 

Reviewing curriculum content:  

Teachers were also asked: ―In a typical term (semester), how often do you review curriculum content 

with (a) Fellow teachers in your school and (b) Subject coordinator in your school? Would you say 

once a term (semester), twice a term (semester), three times a term (semester), more than three times a 

term (semester) or never?‖  

Graduation rate:  

Teachers were asked: ―About what percentage of the students in your class do you expect to graduate?‖  

Construct validity and reliability 

Factor analysis was conducted as a data reduction technique and a test of validity of the 98 statements in 

the questionnaire. Two statistical tests were performed to determine the suitability of factor analysis. 

First, the Kaisers-Meyer-Olkin (KMO) measure of sampling adequacy score of 0.679 was well above the 

recommended level of 0.50. Second, the Bartless test of sphericity was significant (Chi 

Square=2689.22, P<0.00), indicating there were adequate inter-correlations between the items which 

allow the use of factor analysis. Moreover, principal axis factoring was utilised as an extraction method 

and oblique rotation was used as a rotation method.  

 

 

 

 

 

 

 



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6. Results  

6.1 Factor Analysis 

Factor analysis resulted in deleting eighty statements with Factor Loadings below 0.70. Accordingly, 

eighteen valid five-point Likert type scale statements yielded seven factors with Eigen value greater than 

1.0 and factor loadings higher than 0.7 (see Table 2). The seven-factor solution accounted for 74.816 per 

cent of the total variance.  

 

Table 2. Structure Matrix 

 Component 

 1 2 3 4 5 6 7 

Q95. Student absenteeism is a problem in your classes .855 .008 .127 -.022 -.199 -.022 .039 

Q96. Student apathy is a problem in your classes .842 -.014 .189 .144 -.167 .264 .063 

Q94. Student tardiness is a problem in your classes .806 .065 .053 .006 -.148 -.039 .044 

Q97. Student unprepared to learn is a problem in your classes .797 .043 .150 .140 -.132 .289 .049 

Q44. Discuss using multimedia in class with fellow teachers .106 .903 -.144 .022 .203 .120 -.128 

Q46. Discuss using multimedia in class with subject coordinator .037 .899 -.146 .021 .196 .051 -.093 

Q45. Discuss using multimedia in class with school management -.032 .856 -.157 -.016 .076 -.001 -.054 

Q55. This school management respects teachers .163 -.163 .877 -.003 -.064 -.103 -.012 

Q52. Teachers are treated well in this school .125 -.102 .853 .024 -.046 -.123 .012 

Q54. Teachers and administration work as a team in this school .070 -.171 .833 .054 -.068 -.144 .083 

Q13. In a typical semester, how often do you consult or seek advice 

on teaching matt 
.013 -.012 .024 .866 .014 -.052 .109 

Q14. In a typical semester, how often do you consult or seek advice 

on teaching matt 
.087 .022 .029 .854 -.035 -.088 .154 

Q4. In a typical semester, how often do you review curriculum 

content with Fellow teachers in your school 
-.147 .116 -.015 -.022 .894 -.075 -.068 

Q6. In a typical semester, how often do you review curriculum 

content with Subject coordinator in your school 
-.195 .196 -.118 -.001 .881 -.028 -.097 

Q1. How satisfied are you with curriculum standards? -.161 -.097 .159 -.004 .062 -.870 .091 

Q3. How satisfied are you with the curriculum content for the 

subject you teach? 
-.035 -.026 .138 .153 .040 -.834 -.070 

Q19. How often do you use teaching materials prepared by yourself .067 -.114 .045 .066 -.085 .020 .846 

Q20. How often do you use teaching materials prepared by yourself 

with your fellow teachers in your school 
.035 -.050 .014 .188 -.073 -.022 .835 

Extraction Method: Principal Component Analysis.  

Rotation Method: Oblimin with Kaiser Normalization. 



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The range of the Cronbach’s alpha reliability coefficients for the factors was between 0.714 and 0.829 

and these factors were labelled according to their factor loadings as follows: 

– Factor 1: Teachers’ perception of student absenteeism and presenteeism in Qatar 

– Factor 2: Discussing how to use multimedia in class 

– Factor 3: Treating teachers as professionals 

– Factor 4: School teacher-teacher consultation 

– Factor 5: Teachers’ satisfaction with the curriculum 

– Factor 6: Preparing teaching materials 

– Factor 7: Reviewing curriculum content 

Based on factor analysis, it is clear that absenteeism/presenteeism were loaded under Factor 1 and will 

be treated as one variable in the discussion of the results. 

Testing the relative importance of the independent variables to the dependent variable 

In regressing factor one (teachers’ perception of student absenteeism/presenteeism in Qatar) on the 

other six factors, alongside two other questions, namely (1) teaching load (i.e., Currently, how many 

hours do you teach per week?) and (2) expected graduation rate (i.e., About what percentage of the 

students in your class do you expect to graduate?), only three are significant in explaining the variation 

(teaching load: 0.000; expected graduation rate: 0.023; reviewing curriculum content: 0.045) and hence 

in predicting teachers’ reported perception of student absenteeism/presenteeism in Qatar (Table 3). 

These variables were used in path analysis. 

 

Table 3. Coefficients 

Model 

Unstandardized 

Coefficients 

Standardized 

Coefficients t Sig. 

B Std. Error Beta 

1 (Constant) -1.153 .207  -5.566 .000 

Discuss How to Use Multimedia in Class .032 .047 .032 .679 .498 

Treating teachers as professionals .074 .048 .074 1.551 .122 

School Teacher–Teacher Consultation .055 .046 .055 1.208 .228 

Reviewing Curriculum Content -.095 .047 -.095 -2.008 .045 

Teachers' Job satisfaction .061 .046 .061 1.306 .192 

Preparation of Teaching Materials .016 .046 .016 .343 .732 

Expected Graduation Rate (Student Success) .005 .002 .105 2.280 .023 

Teaching Load .048 .008 .312 6.307 .000 

Note. a. Dependent Variable: Teachers’ perceptions of student absenteeism and presenteeism in Qatar. 

 

 



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Conceptual framework 

Regressing the dependent variable (teachers’ perception of student absenteeism/presenteeism) on the 

explanatory variables ―reviewing curriculum content‖, ―teaching load‖, and the ―expected graduation 

rate‖ and using a stepwise multiple regression equation produced a highly significant F value. Path 

analysis results showed that the teaching load has the highest direct effect. Reviewing curriculum 

content and the expected graduation rate received the second and third highest direct effects, 

respectively. Figure 1 shows the conceptual causal framework for the selected factors that interact to 

influence teachers’ perception of student absenteeism/presenteeism in Qatar. The true direct effect is 

shown between parentheses while the other numbers represent zero-order relations. 

 

 

 

Figure 1. Predictors of Student Absenteeism and Presenteeism in Qatar: A Pathway Analysis 

Chart 

 

7. Discussion 

This study draws on previous research to identify contextual (school-related) variables likely to 

influence teachers’ perceptions regarding students’ absentee/presentee behavior. Looked at from the 

perspectives of teachers, three variables were found to influence student absenteeism/presenteeism: 

teaching load, reviewing the content of the curriculum, and the expected rate of student graduation. The 

data analysis points to a positive causal relationship between teachers’ reported perceptions of student 

absenteeism/presenteeism and their teaching load. Against our expectations, a path analysis revealed 

the heavier the teachers’ workload is, the more likely they are to report student 



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absenteeism/presenteeim in school. This may be taken to mean that heavy or excessive teaching load 

affects student attendance, interest and engagement. These findings are in line with previous studies 

indicating that school-related factors influence the likelihood a student will skip or attend school 

regularly. More specifically, instructional and classroom factors are strong predictors of student 

attendance or absence (Marks, 2000). For instance, workload is shown to affect students’ school 

engagement and their academic achievement (Salmela-Aro & Upadyaya, 2014).  

Evidence shows teachers’ workload (including instruction, assessment, materials development, tutoring, 

advising, etc.) influences student attitudes towards learning. For example, Salley and Shaw (2015) 

noted a heavy teaching load affects both teacher effectiveness and student learning outcomes. Thus, 

students’ overall satisfaction with their course is significantly affected by how they perceive workload. 

Demanding course loads can be a source of stress and may cause student burnout due to feelings of 

exhaustion and stress and student burnout can in turn trigger high levels of absenteeism, low motivation 

and engagement, and reduced productivity (Meier & Schmeck, 1985). However, evidence remains 

inconsistent since other research shows workload has little to do with burnout (Jacobs & Dodd, 2003).  

Our results could also be interpreted in the context of easy access to information and the availability of 

alternative study materials, which may account for student absences (Massingham & Herrington, 2006). 

Evidence shows technology and the Internet have multiple benefits for education where it is being 

utilised as a convenient educational tool (Dogruer, Eyyam, & Menevis, 2011). Dissimilar to traditional 

classes, the Internet is oftentimes employed by students as a convenient tool to complete homework 

assignments (Cranmer, 2006). One could argue the Internet in particular makes it possible for some 

students with extended absences to make up for their missed lectures.  

The results also yielded a negative relationship between teachers’ perceptions of student 

absenteeism/presenteeim and curriculum content reviewing. Could this imply that the more the 

curriculum content is reviewed, the less likely teachers are to perceive student absentee/presentee 

behaviour? Moreover, could this signify that reviewing the existing curriculum helps spark student 

interest, motivation and engagement? This study’s findings reinforce results from past research and 

emphasise the importance of curriculum revision in motivating students. The current study also shows 

reviewing curriculum content helps to lessen boredom and reduce absences from school.  

Curriculum development and renewal are important components of any educational reform. Research 

unveils a recent surge of interest in the impact of curriculum reforms on educational outcomes (Allais, 

2012; Souto-Otero, 2012). Common to many reform initiatives is a growing interest in the influence of 

curriculum materials on classroom instruction (Moyer, Cai, Wang, & Nie, 2011). With the focus on 

outcomes as a force driving curriculum design and development, student attendance and engagement 

are viewed as critical for academic success (Chang & Romero, 2008). Documented research 

consistently shows that curriculum review and revision aid in enhancing student engagement and 

academic performance (Vander Jagt, 2013). When curriculum practices (teaching materials, instruction 

and assessment) are revised, students tend to demonstrate successful learning and achievement. 



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These findings support the results of other studies by underscoring the role of the curriculum in 

enhancing student attendance and triggering active involvement in class (Kousalya, Ravindranath, & 

Vizayakumar, 2006). The key role of the curriculum and curriculum revision in engaging students in 

learning is documented in a recent study by Mills, Krouse, Rossi-Schwartz, and Klein (2017) and 

previous work by Windham (2005). Curriculum revision significantly influences student success and 

remains an option that can help to curtail absenteeism among students (Kumar & Giri, 2012). For 

Schalge and Soga (2008), dissatisfaction with the curriculum causes boredom and the structure of the 

curriculum, coupled with good teacher-student communication concerning curriculum content, is a key 

to curbing student absences. No doubt, an engaging pedagogy and an engaging curriculum instigate 

active student engagement (Parsons & Taylor, 2011). 

Against our expectations, our results reveal a positive relationship between teachers’ perception of 

students’ absenteeism/presenteeism, and their expected graduation rate. Surprisingly, the data suggest 

that the more teachers expect their students to graduate, the more likely they are to perceive student 

absenteeism/presenteeism. Empirical evidence demonstrates that attendance does matter for students to 

graduate on time and that chronic absenteeism puts them off-track to graduation (Allensworth, Gwynne, 

Moore, & de la Torre, 2014). However, this contrasts with our results, which point to the opposite, 

indicating absentee/presentee behaviours tend to be associated with graduation from school, as reported 

by teachers. It needs to be noted that in the absence of attendance record data and data regarding 

graduation rates in Qatar, it is difficult to clarify the likely effect of absence or attendance on student 

success and achievement. It is unfortunate that access to such valuable information is not readily made 

available to the public. 

A drop in attendance rates is a predictor of course failure, thus setting students off-track to graduation. 

Prior research shows consistent links between student attendance and being on the path toward eventual 

graduation. Hence, attendance is a predictor of whether students are on-track to graduation from school 

and absence from classes puts students at high risks of not graduating at all (Allensworth, Gwynne, 

Moore, & de la Torre, 2014; Kieffer & Marinell, 2012). In Qatar, anecdotal reports increasingly point 

to a prevalent absenteeism/presenteeism epidemic amongst the student population at all levels of 

schooling. This situation has not improved despite multiple K=12 education reforms initiated over the 

past two decades (Brewer et al., 2007). The public also has been largely unaware of the gravity of the 

problem of absenteeism/presenteeism. Unfortunately, the difficulty of obtaining access to accurate and 

reliable empirical data on the scope and extent of this phenomenon in Qatar makes it difficult to paint a 

clear picture of the scale and scope of student absentee and presentee behaviour.  

Whereas we acknowledge the missing link between students’ absences and their graduation prospects 

in our study, previous documented research that shows associations between graduation and 

absenteeism is lacking. A tentative explanation for our observation above, and the paradox it alludes to, 

lies in contemplating the global expansion of private tutoring in recent years, with private lessons 

increasingly perceived as an alternative to regular schooling (Bray & Kwo, 2014). Due to weak formal 



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education, private tutoring is turning into a supplement, and even a substitute—to mainstream public 

schools (Ali, 2013), as evidenced by findings from Silova and Bray’s research (2006). In Qatar, the 

prevalence of tutoring for secondary, and even primary-level students is vivid and has turned into a 

convenient means of compensating for missed classes (Stepney, 2016). 

 

8. Conclusion and Recommendations 

Absenteeism and presenteeism flourish when students realise the risk of being penalised for their 

behaviour is minimal or non-existent, eventually making absences and disengagement a gateway to 

dropping out of school altogether. Since poor student attendance and presenteeism have far-reaching 

consequences on students, schools, and society, the solution to this problem requires a 

multidimensional approach involving the interaction and interplay between personal, scholastic and 

socio-cultural factors. As key players in children’s education, school leaders, teachers, families, and the 

community all have a share of responsibility in raising awareness of the importance of school 

attendance and active engagement starting at the pre-school level. 

In the interest of effective management of the problem, strategies for scaling down chronic 

absence/absenteeism should start within school sites. Teachers and school officials need to understand 

and monitor attendance and disengagement behaviour. Early identification of absenteeism/presenteeism 

patterns will provide opportunities for early intervention to engage students and families before these 

patterns become chronic. Similarly, a strict school attendance policy must be adopted and maintained 

and an early-warning system implemented. Stressing that regular attendance is a priority, along with 

continued recognition of and rewards to students with good and improved attendance records, is 

important. Students and their families need to be aware of the positive impact of good attendance and 

active participation in class. Motivation and positive engagement with the curriculum are critical 

requisites for them to be on-track to graduation. 

Presenteeism is a relatively new field and very little is known about this phenomenon within school 

environments. Lack of scholarship on this topic makes it hard to identify relevant characteristics that 

can easily be measured empirically. Therefore, any attempt that seeks to quantify presenteeism is 

fraught with difficulty. Investigating different factors that are at play in order to establish the validity of 

self-reports of class disengagement is useful to inform our understanding of the impact of presenteeism 

on the individual learner, the school and society at large. 

While this study focused on a few school-related variables affecting teachers’ perceptions of 

absenteeism/presenteeism, it would benefit from also looking at other important influences. By 

analysing personal variables (attitudes, beliefs, motivation, etc.) and contextual factors (demographic, 

social, cultural, etc.), research stands to gain fresh insights into the nature and impact of absenteeism 

and, more specifically, presenteeism. A limitation of this study lies in its use of a survey method 

confined to a sample of teachers. Employing qualitative research methods that include the perspectives 

of teachers, students and school officials would help to explore, in depth, the levels of concern of these 



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different groups, and the supports required to deal with student absences and disengagement. 

Further research is required to expand participant recruitment to comprise other K-12 grade levels, 

including primary and preparatory levels of schooling. Expanding the study would allow comparisons 

within and across different student groups and thus provide rich and robust data; it would also help to 

identify the grades at which absentee/presentee behaviour is more or less visible. We recognise 

problematic behaviours may alter with age and will vary from one school to another depending on 

different contextual factors. However, understanding the factors that shape absentee/presentee 

behaviours can be very useful in gaining deeper insights regarding this problematic behaviour and ways 

of support planning.  

 

Acknowledgement 

This study was supported by the Social and Economic Survey Research Institute, Qatar University. The 

authors would like to thank all the students and teachers who took part in the 2015 Qatar Education 

Study. The authors would also like to thank SESRI’s Research, Survey Operations, Survey 

Programming and Development, and Information Technology Projects teams for giving so generously 

of their time at various stages of the data collection and data entry.  

 

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