Academic Achievement and Employment Status - Paper Example

College students are engaged in many activities which consume their study time. Some of these activities include work, leisure, socialization, and sports (Finlay, Ram, Maggs, & Caldwell, 2012). They, therefore, have to strike a balance between these activities and learning or their studies. In trying to achieve this balance, it seems that students employment come at the expense of other critical academic activities. If employed students significantly reduce the time spent on learning, negative consequences on their academic progress (such as low GPAs, increased dropout rates, and decreased graduation rates) may be realized. There exist evidence that the time spent studying has a significant effect on academic achievement (Nonis & Hudson, 2006). Because of this, the current study will seek to establish if there is a relationship between academic achievement and employment status among college students. It is believed that working while learning leads to decreased academic performance because of reduced time spent on studying. The following research questions will guide the proposed study:

Are student employment and academic success related?

Why do students seek employment?

What are the perceived effects of employment on academic success among the students?

How do characteristics of students who are employed compare to those of students who do not work?

What supports do employed students rely on in finishing their studies?

Literature Review

Student Employment and Academic Success

Student employment is increasing globally. In European countries, New Zealand, United States, Australia, and China, the practice is widespread and has attracted researchers attention (Kosi, Nastav, and Sustersic, 2013). Most researchers are keen to investigate the impact of students employment or work while studying on academic performance or academic achievement as measured by grade point averages (GPA). Most of these studies involve college students and learners in other higher educational institutions where the phenomenon is widespread. Few of the studies focus on high school students.

A recent study conducted by Kosi et al. (2013) examined the characteristics of student employment in Slovenia and estimated the effect of student work on successful completion of an academic year. For the study, the researchers obtained data from two employment databases derived from the largest Slovenian student employment service. One of the databases had aggregate monthly data for four years (2005-2008). The variables of interest in the first database included the total number of hours the students worked per month and the total value of students work done the employment period. The numbers of hours of work completed by students were categorized according to the students level of education, nature of the study (full or part-time) and the specific college or high school. Analysis of the employment data per level of education showed that 30 percent of the students work was performed by high school students while 70% of the work was carried out by students with tertiary education levels.

The second database comprised of a sample of data at the level of individual student work referral. In each of the four years (2005-2008), the investigators randomly sampled 1500 tertiary-level students for the study. Individual student demographic data, number of hours worked, and related wages, type of employment, and educational information of the participants were gathered. The sample for the study was representative because the participants were randomly sampled. Also, large sample size and high market share of the employment service that provided the data ensured representativeness (Kosi et al., 2013).

Using undergraduate students data, the researchers analyzed the total number of work hours completed per student per week in order to find out if students employment leaves students enough time to study. Additionally, the investigators classified the type of employment in which the students were enrolled. This enabled the researchers to find out if there is a relationship between the type of employment and their fields of study. Consequently, this helped the researchers to establish the effect of employment on academic performance. Finally, the researchers developed a model used to estimate if students employment affects students progress to the next level of study. Data analysis revealed that college students worked for 428 hours annually or an average of 8.2 hours per week. The students were engaged in either physical work (20.4%), non-demanding work (44.5%), moderately demanding work (10.9%), or very demanding work (15.0%). Lastly, analysis of the impact of students work on academic performance revealed that students work negatively affected academic performance thus reducing the probability of progressing to the next year of studies (Kosi et al., 2013).

In a related study, Blicblau, Nelson, and Dini (2016) investigated the effect of two types of work experiences, short term and long- term on academic achievement as measured by grades, over a period of two years. The sample for the study comprised of 240 undergraduate mechanical engineering students who were in their final year of study. The students academic grades were analyzed over a period of two years. These grades were a combination of summative and formative assessment. In the first year of the study, all the students completed their first-year projects while in their final year, they completed their capstone project. Industry Based Learning (IBL) students completed their placement after two and a half years of the study while Short Term Placement (STP) students completed their 3-month placement at any stage of their course. Data on academic performance (the grades) of IBL and STP were collected over a period of two years.

To determine whether work placement influenced academic performance, data were analyzed using ex-post facto design. Data analysis involved collation of participants GPA, their GPA in the capstone project, and their participation in either IBL or STP. Out of the original 240 participants, data were gathered from 159 students who completed IBL or STP. Data analysis explored the impact of IBL process on the academic performance of the students in subjects taken after completion of IBL. Results of the analysis showed that work placement program resulted in increased academic achievement as indicated by a statistically significant increase in average grades from before IBL to after IBL.

In a recent study, Sprietsma (2015) also investigated the effect of students employment during the semester on students academic performance of full-time students. The sample for the study was obtained from the student cohort of the National Education Panel Study (NEPS). NEPS contains students employment data (such as the number of hours worked and the type of student employment), an educational biography of the students, and academic achievement data. Analysis of employment data showed that 48% of the students worked for at least one hour on a weekly basis during the semester under study. The average number of students working hours were 12 hours per week. Data analysis also revealed that employed students had a higher monthly income compared to their nonworking counterparts. On average, working students income exceeded non-employed students income by 100 Euros. Approximately 15% of the students derived their income exclusively from employment while 30% of them were involved in employment related to their fields of studies.

Further analysis revealed that students employment resulted in better grades at the final examination compared to students who did not work. However, the positive relationship between students work and academic achievement was found to be significant up to 15 hours per week. In students who worked for more than 15 hours per week, there was no statistically significant association between grades and employment. Employed students were also less likely to be recipients of governments financial aid. Therefore, employment of these students seems to have been motivated by financial constraints. Additionally, working students were found to spend less time studying by themselves. Specifically, they spent approximately half an hour less reading and attending lectures compared to non-working students (Sprietsma, 2015).

Gleason (1993) examined the relationship between student employment, grades, and dropping out. It also investigated whether or not work affected the length of stay in school, employability, and wages. The sample for the study was obtained from High School and Beyond Survey (HSB). The sample for the study comprised of 4,068 students who attended four-year colleges. Findings of the study showed no statistically significant difference in academic achievement of employed and non-employed students, as measured by grades attained at the end of the semesters. The mean GPA of employed students was higher (2.72) compared to those of non-employed students whose GPA was found to be 2.69. However, among the working students, a negative relationship between the number of hours per week worked and GPA was reported. Specifically, students who worked for between 1 and 10 hours per week had a mean GPA of 2.94 while those who worked for 31-40 hours per week had a mean GPA of 2.63. Except for students who work for long number of hours, employment was reported not to affect GPA negatively.

Andemariam, Tsegai, Andre, Dhumal, and Tessemas (2015) study aimed at investigating the impact of student employment on GPA treated students employment as both homogeneous and heterogeneous experience/category. Unlike previous studies which used a single GPA (such as first-year GPA) as a measure of academic achievement, the current study senior students cumulative GPA. Additionally, unlike past studies, this study controlled for confounding variables such as students prior academic achievement and demographic variables which could moderate students employment. The sample for the study consisted of 5,223 students. Data analysis revealed that as the number of students working hours increased, GPA declined. That is, the number of students working hours had a statistically significant effect on students academic performance. Additionally, independent t-test analysis conducted to find out if the difference in GPA of employed and non-employed students existed showed that there is a significant difference between the GPA of working and non-working students (t4846=3.75, p<001). Specifically, the mean GPA of employed students was lower (mean GPA= 3.29) than those of non-employed students (mean GPA=3.35).

Andemariam et al.s (2015) study also revealed that students academic performance was influenced by the number of working hours. An ANOVA t-test revealed statistically significant differences in GPA of five categories of students (F (4, 4846) =27.167, p<0.001). The five categories were: students who worked for 0 hours (unemployed), 1 to 10 hours, 11 to 15 hours, 16 to 20 hours, 21 to 30 hours, and 31 hours and over. Students who worked for the least number of hours were found to have the highest GPA. Overall, GPA declined with an increased number of working hours. Students who worked for between 1 and 10 hours had a mean GPA of 3.39 while those who were engaged in more than 31 hours of employment had the lowest GPA of 3.24. On the other hand, unemployed students had a mean GPA of 3.34. This implies that a moderate number of working hours boost students GPA. Moreover, results of the study showed that male students worked longer than female students. Also, students from families of low socioeconomic status were reported to work for more hours per week.

Some studies have not reported a negative or a positive relationship between stu...