Contributing Factors of Computer Science and IT Students’ Attrition Rate

Aniceto B. Naval and Julian S. Setosta

St. Michael’s College of Iligan City Quezon Avenue, Iligan City 9200, Philippines

Abstract. This study endeavors to seek and assess the contributory factors affecting computer science and information technology students’ attrition rate. A total of 64 students under the College of Engineering and Computer Studies (CECS) of St. Michael’s College who officially withdrew their classes were included as the subjects of the study. Determining these contributory factors were based from their reasons indicated from the official withdrawal form filed by these students. Findings revealed that attrition rate was caused mainly by financial reasons, followed by students’ health reasons and parents’ related reasons. Furthermore, the study showed that female students are more vulnerable of withdrawing a course when faced a financial adversities than male students. Likewise, first year and second year students taking up BS Information Technology would likely drop or withdraw a course.

Keywords: Attrition rate, dropout rate, computer science, information technology, retention rate.

Introduction

Students who drop out of college often suffer personal disappointments, financial setbacks,

and a lowering of career and life goals. Concern about the student has led to much research on

college student attrition and retention. Attrition in computing disciplines is generally accepted as

a critical issue that needs supplementary examination (Beaubouef & Mason, 2005; Lasserre &

Szostak, 2011). The attrition rate of computer science degrees is higher than average attrition rate

in other disciplines, by quite a margin (Beaubouef & Mason, 2005; Lasserre & Szostak, 2011).

In the past few years, recognition of the imminent leveling off and decline of the number

of students of college-going age has lent a certain sense of institutional urgency not only to the

understanding of which students drop out and why, but also to influencing them to stay. In addition

to its role in describing a societal ill, the research on the causes of attrition has now taken on the

dimension of an urgent administrative necessity to keep students. Private higher education

institutions (HEIs) are aware of the importance of student retention issue because students’

experience is a tangible demonstration of the validity and meaning of institutional mission

(Scholder and Maguire, 2009).

Hence, soliciting feedbacks from students is necessary to assess retention factors about

specifics areas of the institution like value, resources, academics, faculty, advising/supporting

services, social life, extracurricular activities, educational goals and preparation for the future. At

the same time, a new movement for student consumer rights has developed. This movement has

challenged long-accepted practices and assumptions about higher education. One assumption that

has been challenged is that it is always in the best interest of the student to continue his or her

education without interruption. Many students question the placement of any stigma on dropping

or stopping out of college. They say that information about options other than four consecutive

years of college education should be made available to them, and that administrative procedures

for delayed entry after high school, for withdrawal, and for re-entry should be made as clear and

efficient as possible. This position is consistent with the view of education as a life-long learning

process. Thus, while colleges are concerned about what they think are high dropout rates and are

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gearing to combat this phenomenon, it is clear that any subtle societal stigma will no longer be

effective in retaining students.

But college concern about attrition and students' concern about their rights as consumers

are really congruous. Although a great deal of sophisticated research has described the reasons for

dropping out, with the exception of the very few students who leave due to circumstances beyond

their control, the student reasons all stem from dissatisfaction with (or lack of sufficient perceived

benefits from) the academic or social life of the institution. For some, this dissatisfaction would

be present regardless of the educational service that is provided: they did not really want to go to

college, the time is right for a break in their formal education, or their talents could be better used

elsewhere. For others, their original college choice was an error, and their dissatisfaction could be

eliminated by transfer. For still others, a better, more complete educational service offered by their

college may have prevented or reduced the source of their dissatisfaction, may have changed their

perception of long-range college benefits, and may have resulted in retention. For the benefit of

this latter group, and for the benefit of the perhaps larger group of dissatisfied students who would

not consider withdrawal as an option, a college can deal with its dropout problem by doing

everything it can to upgrade the educational service, in its broadest sense, that it provides its

students. Such an attack on the root causes that contribute to attrition would benefit all students

and would be an excellent recruitment tactic for future classes. Therefore, what is important is to

look into specific reasons or factors (herein called attrition/delay factors) why computer science

and information technology students are not able to finish and/or take a long time to finish.

The main objective of the present study is to uncover institutional, programmatic and

personal factors that represent hurdles in successfully finishing degree. Hence this study was

conducted by the researchers to find out and assess the contributory factors affecting the high

attrition rates of Computer Science and IT students of the College of Engineering and Computer

Studies (CECS) of St. Michael’s College. The results of this study will serve as the springboard

of the College program that will seek to address these daunting challenges of every higher

education institution, the students’ high attrition rates.

Review of Literature and Empirical Background

Student attrition may be more specifically defined within a particular field, it is generally

characterized as the departure from or delay in successful completion of program requirements.

Student attrition tends to be a systematic concern for many types of higher education programs such

as computer related studies (Levy, 2007). In fact computer science and other computer related

programs have a history of problems both in recruiting and keeping students of every higher

institutions around the globe offering the said program.

In the study of Lasserre and Szostak (2011) of University of British Columbia-Okanagan

attrition rate in computer science, specifically the introductory courses has been found to be 30%‐

50% and between 30% and 40% according to Beaubouef and Mason (2005) of Southern Louisiana

University. Beaubouef and Mason (2005) further noted that their personal observations have

attrition rates as high as 60% per academic school year.

Several confounding factors had been established as the root causes of the students’

attrition rate. According to Cuseo (2010) students’ attrition rate can be attributed to academic,

motivational, psychosocial, and financial root causes. Attrition stemming from students being

inadequately prepared to accommodate the academic demands of college and meet minimal

academic standards, that is, attrition due to academic failure or dismissal. Motivational root causes

are related to students’ low level of commitment to college in general or the specific college

attended and perceived irrelevance of the college experience. Meanwhile, students’ departure

related to social factors and emotional issues are psychosocial root causes. This attrition

attributable to poor institutional or departmental “fit” which stems from a mismatch between the

student’s expectations, interests, or values and those of the prevailing community. Finally,

financial roots are student attrition related to inability (or perceived inability) to afford the total

cost of college and a perception that the cost of college outweighs its benefits.

The main reason of the relatively high attrition rates in the Philippines was the financial

root causes. In fact, Philippines ranked the topmost five countries with high dropouts (Inocencio,

2014). Dropouts has been a perennial problem of every learning institutions whether private or

public as retention among students has become a challenging concern for the academic

community. Waning number of students returning to school usually results in larger financial loss

and a lower graduation rate for institution and might affect the perception of the parents, students,

stakeholders, legislators’ vision of the institution (Zerna, Cruz, & V.Nuqui, 2014).

Private higher education institutions (HEIs) are aware of the importance of student

retention issue because students’ experience is a tangible demonstration of the validity and

meaning of institutional mission (Scholder & Maguire, 2009). Hence, soliciting feedbacks from

students is necessary to assess retention factors about specifics areas of the institution like value,

resources, academics, faculty, advising/supporting services, social life, extracurricular activities,

educational goals and preparation for the future.

The aforementioned reasons showed how challenging was attrition rate be addressed.

Tinto (1975) is credited with developing one of the first models for studying student attrition and

persistence in higher education. This study is anchored on his Student Integration Model as shown

in Figure 1, he defined student attrition as “a longitudinal process of interactions between the

individual and the academic and social systems of the college during which a person’s experiences

in those systems which continually modify his goals and institutional commitments in ways which

lead to persistence and/or to varying forms of dropout”. Tinto’s definition demonstrates how

student attrition can involve many interrelated factors which made attrition a more complex

process. Furthermore, he claimed that these factors are important in determining whether an

individual will become integrated socially and academically.

These include demographical profile such as sex, race, age, social status, and etc. These

characteristics interact with the student’s goals (e.g. to complete and successfully pass a

course/degree) and commitments (to the course and to the institution) to influence integration.

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Figure 1: A conceptual schema for university persistence (redrawn from Tinto, 1975)

This in turn, combined with the influence of any contextual factors (e.g. accommodation,

employment and family commitments, finances), and factors particular to the university (e.g.

timetable, teaching environment, curriculum) impacts the subsequent re-evaluation of goals and

commitment, which is the primary determinant of persistence (Tinto, 1985).

Objectives of the Study

The general purpose of this study was to determine and assess the contributing factors of

the computer science and information technology students’ attrition rate. Specifically, this study

sought to answer the following queries: (1) what are the background variables of the students? (2)

what are the different factors that contribute the attrition rates? and how do students’ background

variables contributes the attrition rate?

METHODOLOGY

Research Design

The descriptive quantitative resign design was employed to gather the data and to answer

the posed questions in the study. The data were qualitative in nature, however interpreted and

analyzed through quantitative analysis.

Participants

A total of 64 computer science and information technology students of the College of

Engineering and Computer Studies of St. Michael’s College of Iligan City who officially

withdrew, abandoned, or dropped their enrolled subjects during academic years 2009 – 2010 to

2012 – 2013 were included as respondents of this study.

Background

Variables -Student’s Profile

Goal and

Institution

Commitments

SOCIAL AND

ACADEMIC

INTEGRATION

Contextual

Factors e.g. finance,

accommodation

University

Factors e.g. curriculum,

timetable

Later

Commitment PERSISTENCE

Procedures

Determining and assessing contributory factors affecting attrition rates were solely based

from the reasons indicated from their withdrawal form filed by these students through the

Registrar’s Office. There reasons were tallied accordingly and analysed quantitatively.

Results and Discussion

The results of the analysis are shown on the following tables.

Table 1. Distribution of the Respondents by Gender

Gender Frequency Percent

Female 25 39.1

Male 39 60.9

Total 64 100.0

Table 1 showed that most of the students who officially withdrew, dropped, or abandoned

their classes were male with 39 out of 64 respondents or 60.9% incident. This relatively high

occurrence of attrition rate of male students than female students is proportionate to the number

of officially enrolled male students in the College of Engineering and Computer Studies (CECS).

It can be noted that the college is dominated mostly by male students. This can be attributed to the

fact that courses offered under CECS are engineering and computer related studies where women

would less likely take these courses (Coger, 2012). Furthermore, the result supported the claim

that male students were more likely than female students to drop out classes due to several factors

such as peer influence, laziness, and unpreparedness (Paulynice, 2013).

Table 2. Distribution of the Respondents by Course

Course Frequency Percent

Computer Science 11 17.2

Information Technology 53 82.8

Total 64 100.0

Table 2 showed that more incidents of attrition occurred in the field of information

technology with 53 out of 64 or 82.8%. This result again can be attributed to the fact that more

students took up BS Information Technology than BS Computer Science. This can be implied

otherwise by proportion, that IT students are more likely to drop or withdraw their classes than

CS students because they outnumbered the latter in terms of population in the department. Hence,

as expected by proportion there would be more attrition incidents will occur under this group of

students.

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Table 3. Distribution of Respondents by Year Level

Year Level Frequency Percent

First Year 24 37.5

Second Year 23 35.9

Third Year 10 15.6

Fourth Year 7 10.9

Total 64 100.0

Table 3 revealed that more freshmen and sophomore students would likely to withdraw,

drop or abandon their classes with 24 out of 64 or 37.5% and 23 out 64 or 35.9% occurrences.

This result agreed the studies of Hall, Smith, and Boeckman (2010) and Kennelly and Monrad

(2012) that freshman students are more vulnerable of dropping or quitting their courses than senior

students because of several reasons such as unpreparedness in college life and academic life

adjustment in college. They pointed out that adjustment of the students life from high school to

college is the most crucial phase to persist academically. Some of the students cannot meet the

academic standards as one of the requirement in completing a college degree (Paulynice, 2013).

This is further supported by Cuseo (2010) that attrition is a result from new students having

trouble coping with the initial changes, demands or stressors that accompany his transition into

the college and/or departmental culture.

Table 4. Reasons for Withdrawing from a Course

Reasons Cited Frequency Percent

Financial reasons 21 32.8

Not attending the class 7 10.9

Family problems/reasons 9 14.1

Health reasons 13 20.3

Withdrawn/dropped for employment 4 6.2

Transfer to other school 4 6.2

Going abroad 3 4.7

No reasons cited 3 4.7

Total 64 100.0

Table 4 showed the reasons of withdrawing or dropping their course as indicated in their

withdrawal form. Most of them indicated that they withdrew their course because of financial

reasons with 21 out of 64 or 32.8% incidents. As cited by Cuseo (2010) that one of the causes of

the attrition rate is financial roots, an inability or even an inability perception of students to afford

college influence them to withdraw their course, causing them in the delay of completing their

course within 4 years. This being followed by their health as 13 out 64 or 20.3% cited several

reasons in relation to their health as the main cause of quitting or dropping. This perhaps can be

attributed that some of these students were working through on-line job at night and having their

class at day. Hence, they don’t have enough time to rest at day as exhausted workload by

disrupting one’s biological clock (not sleeping at night) creates lifetime health vulnerabilities

(Johnson, 2011).

Thirdly, they withdrew or dropped because of family problems or reasons with 9 out 64 or

14.1% incidents. As cited from their withdrawal form some of these students their parents or

relatives encountered or involved in a clan conflict forced them to withdraw or dropped their

course immediately for their safety. This followed by not attending classes anymore with 7 out 64

or 10.9% incidents leading them to withdraw. Finally, few incidents were cited such as

withdrawing because of transferring to other school, going abroad, and seeking for employment

instead of finishing their course.

It can be observed that these results revealed more first year and second year male students

taking up BS Information Technology who greatly contributed on the relatively high attrition rate

due to financial reasons. In order to determine whether these variables are associated to each other,

further analyses were conducted through Fisher’s Exact Test and their relative risk ratio. The

results were shown in the next succeeding tables.

Table 5. Relationship of the Students’ Gender and Their Reasons for Withdrawing

Gender Reasons for Withdrawing

Relative Risk Chi-square

value p-value

Financial reasons Others

Female 13 (52.0) 12 (48.0) 2.535 6.851 .014*

Male 8 (20.5) 31(79.5) .604

* Significant at 0.05 level

Table 5 showed the frequency and percentage distribution of the students’ reasons for

withdrawing a course when analysed by gender. It can be noted in the table that more female

students withdrawn their course because of financial reasons (13 or 52.0%) than male (8 or

20.5%). On the other hand, aside from financial reasons, more male students had withdrawn (31

or 79.5%) than female students (12 or 48.0%). These differences are supported statistically with

𝜒2 = 6.851 and p-value = .014 less than .05 level of significance. Hence, these differences can be

attributed to their gender. In fact, it can be gleaned that female students had a relative risk of 2.535

of withdrawing a course because financial reason than the male students with only .604. In other

words, the risk of female students that would likely to withdraw when facing financial problem is

more than twice than male students under the same conditions. This can be inferred that female

students facing this adversity is more prone to withdraw than male students.

This result contradicts in the recent study abroad that more men than women who dropout

college because men are much less willing to take significant debt to finance their education

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(Schwyzer, 2013). Furthermore, in Philippine settings male students were most likely to drop than

female students when faced in this adversity, mainly financial constraints (Rosero, 2012).

Table 6. Relationship of the Students’ Course and Their Reasons for Withdrawing

Course

Reasons for Withdrawing Relative

Risk

Chi-

square

value

p-value Financial reasons Others

Computer Science 2 (18.2) 9 (81.8) .507

1.290 0.314 Information

Technology 19 (35.8) 34 (64.2) 1.275

Table 6 showed the frequency and percentage distribution of the students’ reasons for

withdrawing a course when analysed according to their course taken. As shown, only 2 out 11

computer science students or 18.2% of the total students who withdrew because of financial

reasons while there were only 19 out of 53 information technology students or 35.8% of the total

students who withdrew on the same reason. This can be inferred that the rate incidents of computer

science to withdraw due to financial reason is lower than the over-all rate of 32.8% to withdraw

on the same reason. On the hand, information technology students’ incident rate 35.8% is a little

bit higher than the over-all rate. However, these differences are not supported statistically with 𝜒2

= 1.290 and p-value = .314 less than .05 level of significance.

Hence, these differences cannot be attributed to their chosen course. This can be further

implied that their chosen course is not directly associated to their reasons for withdrawing a

course. Although computer science students faced with financial adversities showed a relative risk

of .507 of withdrawing a course than information technology students. This simply implies that

the relative risk of students took up information technology to withdrew under this circumstances

is almost twice as the relative risk of computer science students. Hence, the probability of

withdrawing due to financial reasons are more likely on the information technology students.

Though this result did not show strong evidence to support this claim at 0.05 level of significance.

Table 7. Relationship of the Students’ Year Level and Their Reasons for Withdrawing

Year Level

Reasons for Withdrawing Relative

Risk

Chi-

square

value

p-value Financial reasons Others

1st year and 2nd year 14 (29.8) 33 (70.2) .723 .735 .574

3rd year and 4th year 7 (41.2) 10 (58.8) 1.194

Table 7 showed the frequency and percentage distribution of the students’ reasons for

withdrawing a course when analyzed according to their year level. As revealed, there was a high

rate of incident on withdrawing due to financial adversities among junior and senior students

(41.2%) than freshmen and sophomore students (29.8%). The incident rate among 3rd year and 4th

year students is greater than the over-all rate of withdrawing when students confronted financial

problems.

However, these observed differences are not supported statistically with 𝜒2 = .735, as p-

value = .574 less than .05 level of significance. Hence, the occurrence of withdrawing a course

due to financial reasons or among other reasons is statistically related to year level of students.

Though 3rd year and 4th year students exhibited a lower relative risk of withdrawing due to

financial reason than 1st year and 2nd year students. Perhaps this relationship was indeed true to

some students under these circumstances, however, by chance, the probability is high (57.4%) that

this result is not true.

Conclusion

The empirical investigations have revealed that several reasons can be attributed as

contributory factors that affect attrition rate of the students taking up computer science and

information technology of the College of Engineering and Computer Studies (CECS) of St.

Michael’ College. In this study findings revealed that financial adversities is the number one root

causes that contributes the relatively high attrition rate of the students. Furthermore, gender of the

respondents somehow interacts the contributory factors such as financial problem that compelled

them to withdraw a course. This claim is supported as findings revealed a significant high relative

risk among female students who would likely to withdraw under this circumstances. Minor

findings were also exhibited in this study such as first year and second year students taking up

Bachelor of Science in Information Technology (BSIT) have a higher probability of not

continuing or competing this degree on time when faced adversities such as financial problems.

Though these results were not supported statistically.

Recommendation

Based on the findings and conclusions, the researchers recommend the following:

1. There should be an intervention program that will address this attrition rate such as

scholarship program for deserving students.

2. Consistent monitoring of the students’ attendance must be closely monitored by the

concern teachers and a developmental academic advising of the students who are

frequently absent from their classes must be religiously conducted.

3. A thorough research study to be conducted to understand clearly the underlying factors

that influence the attrition rate of the students by using evaluative instrument.

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Action Plan Taken

Based from the aforementioned findings, conclusions, and recommendations of this study

the following measures as intervention program have been implemented to address the relatively

high attrition rate of CECS students:

1. Skolar ni Miguel. This scholarship program seek to address students facing financial

adversities. Through this program students were able to finish their study.

2. Academic Advising Program. This program serve as an academic counseling program

design for students with academic deficiencies and other academic related problems.

Through this program students’ academic performance will be closely monitored.

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