The article dubbed Am I missing something. The effect of absence from class on student performance authored by Wiji Arulampalam, Robin A. Naylor, and Jeremy Smith investigates the relationship between absenteeism and class performance. The primary focus of the article is on the effect that student absenteeism has on the performance of the students. Secondarily, the article goes forth to investigate the effect that this school absenteeism has on the labour market earnings. The paper approaches the subject of school absenteeism as a determinant of the success for individuals and whole economies.
Moreover, the article also attempts to analyze other determinants of class absenteeism. Different remedial measures are proposed to counter the negative trend in class attendance. The class attendance between strong and weak students is also compared (Arulampalam, Naylor, and Robin 364). The article goes further to establish the relationship between amount of tuition fees paid and class attendance. In this regard, certain proposals are made by policy makers with an aim of inspiring students to attend classes.
Policy makers appreciate the negative effect that class absenteeism has on the economy of the country. The policy makers are concerned because government expenditure on education surpasses the returns they receive from the graduates. The whole economy tends to suffer when students miss classes. The design of the education system is such that students receive educational instructions in two settings i.e. lecture halls and class settings (Arulampalam, Naylor, and Robin 364). The lecture rooms accommodate large group of students, and this is supplemented by smaller classroom sessions. Classroom attendance is considered compulsory while lectures are optional. These two modes of education delivery are used to maximize on the allocation of scarce resources.
The data used in the article has been obtained from the economic department of a university in the UK. The data was collected from three successive groups of students. The data collected is used to study the underlying relationship between class absenteeism and student performance. The sample size (n) for this particular experimentation is pegged at 444. The participants in this study are drawn from 2nd year students who are admitted to the economics’ department of the varsity to pursue their undergraduate degree courses, which commence in October and runs for three years. The data is obtained for students that were admitted into the program. Staff allocation in this study is split as 15% for lectures and 85% for classroom sessions (Arulampalam et al 365)
The study sample has been taken from 2nd year students exclusively because it is at 2nd year that students work on maximizing their final scores per course taken. The second reason lies in the fact that by 2nd year of university studies the students have already established their preferred learning strategies. Thirdly, 3rd year students are exempt from the study because unlike the 2nd year students they are not obliged to take compulsory courses (Arulampalam et al 365).
The absence data is collected by the tutors of each class before they begin their sessions. The information collected is stored electronically. The students’ attendances are recorded accurately and these are used to determine the frequency of class attendance. The tutors understand the importance of taking and recording student attendance accurately as this is used to impose punishment to those found to absent frequently. The department counterchecks the class attendance information fed into the system ensuring that it is accurate. The careful monitoring of the data by the economics department renders the information reliable (Arulampalam et al 365).
From the frequency data collected and used in the article, it is apparent that the data is relatively reliable as the curves obtained by plotting the data gives the characteristic s-shaped curve that suggests that students miss classes despite the fact that the classes are compulsory. I feel that the sample is representative and as thus good.
Figure 1 reports on the absence rate observed per student taking three core courses. Figure 2 shows the cumulative distribution of class absenteeism over 142 classes that offered the three core courses. The two figures differ on the unit of their observation with Fig 1 having the total absences as the unit of observation and fig 2 having the class as the unit of observation (Arulampalam et al 365). The summary statistics reveal that fewer than 5% of classes had a zero absence rate. The highest absence rate is recorded at 9 a.m. and on Wednesdays. The author has represented and explained the figures adequately.
In table 1 the students are divided into four groups. The table presents summary statistics is taken for 444 students taking three core courses. The observations are broken down according to the total class absences and are broken down into four groups or band categories that are defined by intervals such as 0-4%), (4-8%), (8-15%), and (15% and over). In overall, 34% of the students are female and are less likely to record high class absenteeism (Arulampalam et al 366).
In table 1 the students cohorts used in the analysis are those of female students and students that were paying from overseas as well as male students and home students. The female students record the lowest absence rate compared to their male counterparts. Overseas paying students also reported higher absentee rate compared to home based students. The cohort size varies with the size of intake per intake year with some years admitting more students than the others. Cohort dummies are included in the analysis to boost uniformity of data.
The lowest core course average score is recorded by overseas student and cohort of students admitted between 04/05. There is a glaring relationship between student absence and average score results. It happens that the lowest average score is recorded on the same group that records the highest-class absentee rates. Table 1 reveals a monotonic relationship between performance and absence in the 2nd year. Additionally, the statistics tabulated in table 1 reveal a monotonic relationship between prior performance and absence indicating that the previous scores are correlated to the students’ attendance records (Arulampalam et al 367).
From the information given on the table, it is apparent that there exists an underlying causal relationship between class attendance and performance. From the statistics tabulated, we see overseas students as recording the lowest in average scores and hold the highest absentee records. This goes to show that performance is dependent on attendance. Class absentees are perform poorly because they miss important class material shared by the tutors during class sessions. As a matter of conclusion, the poor performance by the overseas students can be rectified by the varsity taking punitive measures that will deter students from skipping classes.
Wiji Arulampalam, Robin A. Naylor, and Jeremy Smith. “Am I missing something. The effect of absence from class on student performance . Economics of Education Review. 31(2012) 363-375. [Attached pdf]
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