This essay tackles about the usefulness and
relevance of the Tinto Model to the retention issue in Irish Higher Education.
On the first part, the Vincent Tinto model was introduced. Its key features,
strengths, and its limitations are identified to give the reader enough
background as to what the model is all about. On the second part, it addresses
the characteristics of the retention in the Irish educational system. The
model’s application, usefulness and relevance to the Irish system were presented
on the last part for the writer’s final discussion.
The Problem of Student Attrition
Dropout is known to be the greatest problem
facing the institutions of higher education. The reason behind this is that
attendance in higher education is voluntary. That is why there are a plethora of
reasons why people may choose, or be forced, to withdraw. Whereas in primary and
secondary education, attendance is compulsory, up to age sixteen.
Generally speaking, enrolment in higher
education continues to expand. In the United States of America, enrolment in
degree granting institutions increased by about nine percent between the years
1989 and 1999 (Snyder and Hoffman, 2002). As the figure of the enrollment in
tertiary education rises, so does the number of students who will be affected by
dropout. There is major discrepancy in the estimated figures for dropout from
higher education, depending on both the nature of the institution(s) concerned
and also with the definition of attrition or dropout used. In general, the rates
of students withdrawing from tertiary education voluntarily are around twenty
three percent (Rovai, 2002). On the other hand, the usual figure for attrition,
as well as academic dismissal, has been fairly consistent to be fifty percent
for most of the last century (Leys, 1999) (Tinto, 1983).
In attrition, there is a significant financial
cost associated with it. Students who do not complete their studies already have
had substantial amounts of money invested in their education, through both
resources distributed to them and time spent teaching them. It is practically
clear that the universities would prefer to spend this money on students who
will guarantee the completion of their degree course.
Non-financial costs are also associated with
attrition. The dropout or academic failure of students has a negative effect on
the educational achievement and development of other students. This is possible
through the damaging of their morale or making them question their own
commitment to their course or educational institution (Tinto, 1975).
Normally, it is very rare for the least able
students to dropout from their studies, perhaps counter intuitively. Instead,
the case turns out to be that the students who are often more academically able
are the ones who dropout from higher education, compared to those who stay (Tinto,
1982). That being the case, the result is a graduating class who are less
academically able than the one that enrolled in first year. That is all due to
the process of attrition.
Given the costs, financial and otherwise, that
are connected with attrition, it is evident for most colleges and universities
to better understand the forces driving it. If universities and colleges would
be more aware of the students’ reasons of their withdrawal from higher
education, they would make an effort on the amendments. This would include their
selection policies or the way they deal with their students, with a view of
reducing their rates of attrition. The most significant model of attrition from
higher education was perhaps, the one proposed by Vincent Tinto in 1975.
Student Integration Model (SIM) of Vincent Tinto
Vincent Tinto’s 1975 Student Integration Model (SIM)
of attrition was intended to offer a longitudinal model which would explain all
of the aspects and processes that influenced an individual’s decision to leave
college or university. The model also tells how these processes interact on the
production of attrition.
Upon designing the model, Tinto aimed on doing
several things. Initially, he intends on making a distinction among the diverse
types of leaving behavior. This is important as there are a number of different
ways in which a student may choose, or be forced, to leave college. In
anticipation of the publishing of Tinto’s paper, these different learning
behaviors were often grouped under the rubric of dropout. Among the different
types of leaving behavior that Tinto identified are academic failure, voluntary
withdrawal, permanent dropout, temporary dropout and transfer.
The basis of Tinto’s model was Durkheim’s theory
of suicide. This theory supports the statement that the probability of an
individual’s commitment to suicide is predicted by the level of their
integration into the society’s foundation. To a large extent, Durkheim argued
that if an individual has an ample social support network and sufficient
integration on morals, the likelihood of one’s execution of suicide will be
lessened. Tinto also asserted that the act of committing suicide was essentially
the willful withdrawal of an individual from existence. Therefore, he relates it
to the student’s dropout from higher education. In this situation, it is the
willful isolation of an individual (student) from one aspect of his society.
In Durkheim’s model of suicide, the individual’s
insufficient integration into the society is the drive that pushes him into
committing suicide. While for Tinto, he asserts that dropout occurs because the
individual is inadequately integrated into the different aspects of college or
university life.
He identified the two most important systems at
college as academic and social. He also contended that a lack of integration in
either or both of these systems could initiate the occurrence of student
dropout. But, on the other hand, an extreme integration in either the academic
or social systems at college, as indicated by Tinto, would probably be likely to
cause problems in the other system. For example, a student who spent the vast
majority of his time studying would have little time to spend in his social
activity. Similarly, if a student spent his maximum amount of time on his
engagement into social activity, his academic performance would probably suffer.
Tinto’s model of attrition was not exclusively
based on Durkheim’s model of suicide. He (Tinto) even admitted that this model
had one enormous shortcoming. It is the failure of the model to take account of
individual psychological characteristics that incline some individuals into
suicide. Any model of dropout from higher education that was based solely on
Durkheim’s model would be subject to the same kind of limitations. It would fall
short of paying enough attention to the individual characteristics of a person
that would make him more likely to dropout of higher education than their peers.
Tinto understood this and his work included assessing the degree to which
individual characteristics affected attrition.
The Student Integration Model (SIM)
Tinto’s Student Integration Model had certain
key features. At the heart of the model is the degree to which the individual is
integrated into the social and academic aspects of the university. Also of
central importance are both the degree to which the student is committed to
their goal (i.e. degree attainment) and the extent to which he is committed to
the university.
In his model, various types of individual
characteristic affected the student’s pre enrolment commitment to both their
goal (i.e. degree attainment) and the institution they were going to attend. The
characteristics that Tinto highlights as being important in influencing the
individual’s goal and institutional commitment are their individual attributes,
pre-college experiences and family background.
Individual attributes covers variables such as
race, sex and academic ability. Pre-college experiences include social and
academic experiences like school grade point average, as well as academic and
social attainments. Family background, on the other hand, is comprised of the
factors like social status, value climates and expectational climates.
In addition to this, Tinto also asserted that an
individual’s educational expectations have effects on their likelihood of
attrition. Specifically, this is how long the student intended to attend the
educational institution and the importance that the student placed upon the
specific institution in which they plan to attend.
There is said to be a significant variance in
how committed the individual students are to their specific educational
institution. Some students view the college they attend as pivotal to their
chances of future employment. Other students may be as happy in another college
as they are in the one they attend. Obviously, those students who place a great
deal of importance on the college they attend are significantly more likely to
persist at the college they are presently in, despite the problems on academic
or social issues.
In terms of the effect of socio economic class
on institutional commitment, Tinto basically thought that individuals from
higher socioeconomic class are more likely to persist at college. According to
Tinto, the exact nature of the relationship is more complex than that. He
asserts that while academic dismissals tend to be among those of lower social
status, lower aptitude and lower levels of intellectual development than those
who persist, voluntary withdrawals seem to be of comparable. Or higher social
class exhibit higher levels of intellectual development than persisters.
Tinto also stresses that while these individual
characteristics, and the individual’s social and academic integration thereafter
are the most important determinants in whether or not a student persists in
higher education, it is the interaction between the students’ individual
commitment to the goal of college completion and their commitment to the
specific educational institution, that finally determines whether or not they
drop out.
The students’ view of their own higher education
experience is obviously all important in their decision to drop out. Tinto
thinks that students assess their own higher education experience in terms of a
cost benefit analysis. And if they feel they could get greater benefit at equal
or less cost out-with the college, it is likely to provoke dropout.
Dropout can also be influenced by aspects of the
individual’s personality. Dropouts tend to display certain personality traits.
Greater impulsivity, and less emotional commitment to education, are unable to
profit as much from past experience, more unstable, more anxious and are overly
active and restless.
As previously mentioned, the sex of the student
has an influence on college persistence. But its influence is not entirely clear
cut. Males are more likely to finish their college course. But of those females
who drop out, a higher proportion of them are voluntary withdrawals. Tinto
emphasizes that dropout is the result of longitudinal processes of interactions
between the individual and the educational institution they attend.
Tinto stresses the importance of the students’
view of their own academic integration and details how he thinks they assess
this. According to Tinto, the student views their academic integration as being
a combination of two other factors; their grade performance and their
intellectual development. Again, according to Tinto, grade performance functions
as a kind of extrinsic reward while intellectual development is more of an
intrinsic reward.
The sex of the student also influences the
importance that they place upon grade performance. Grade performance appears to
be particularly important for males. Also, according to, Tinto, intellectual
development appears to be more important in determining persistence for females
than for males.
Tinto also asserts that for those who persist,
they view the education process differently from non-persisters. While non-persisters
view education as more of a process of vocational development, persisters (those
who persist) see it as more to do with gaining knowledge and appreciating ideas.
Tinto highlighted the importance of determining
the different types of social integration and their possible consequences. He
stated that social integration in college was “directly related” to persistence
and while the lack of social integration would lead to attrition, it would be
more likely to cause voluntary withdrawal than it would dismissal.
Tinto also indicates that while as already
indicated, very high levels of social integration may lead to deficits in
academic performance; it may not lead to attrition. As long as it is provided
that the integration has occurred with a support group who has “strong academic
orientations”.
Aside from the fact that it is important to the
integration of students who are well motivated, with respect to academic work,
Tinto also highlights the potential importance of social integration within the
faculty itself. It is important as it not only increases the student’s level of
social integration. It also increases their level of academic integration.
The student integration model also illustrates
Tinto’s affirmation to the fact that academic and social integration, together
with goal and institutional commitment, are not separate and distinct. Rather,
they have a distinct, influential relationship upon each other. According to
Tinto, academic integration directly influences the students’ goal commitment
while social integration directly influences his commitment to the specific
institution. Also goal and institution commitment may not both be necessary in
order for someone to persist. According to Tinto, as long as a student has
sufficient goal commitment, he may remain in an institution that they may have
little commitment to.
Limitations of Tinto’s Student Integration Model
According to its Criticisms
While Tinto’s Student Integration Model of
persistence has been the dominant model of student attrition for over
twenty-five years, it is far from universal acknowledgement. There have been
several criticisms made regarding the said model.
Criticism 1: The Student Integration Model is
inadequate in Modeling Student
Attrition.
Whilst the vast majority of studies into the
Student Integration Model have been generally supportive, it has been contended
that the Tinto model is globally flawed and fails to explain the majority of
attrition behavior.
For example, Vivenne Brunsden, Mark Davies, Mark
Shevlin and Maeve Bracken carried out a statistical analysis on a questionnaire
administered to two hundred sixty four first year University students in order
to assess the key features of Tinto’s model (Brunsden, Davies, Shevlin and
Bracken, 2000).
These first year students had enrolled in one of
two different courses at two different universities, one which is BA Computer
Studies course at an English University, and another one in BA Psychology course
at a Scottish University.
Brunsden et al then noted their participants’
enrolment status a year later, noting voluntary dropouts, involuntary dropouts
and persisters. Brunsden assessed each of the participants with their own
questionnaire and with proven psychometrically verified valid tests. This
includes the Eysenck Personality Inventory (EPI), Rosenberg Self-Esteem Scale
(SES) and the Satisfaction with Life Scale (SWLS). The questionnaire items that
Brunsden et al used to construct their own questionnaire have high face
validity. Brunsden et al tested a conceptualization of Tinto’s 1975 Model
constructed using LISREL8 software in a way that ensured it was statistically
testable.
Brunsden et al found that their conceptualism of
Tinto’s model did not adequately explain the data they obtained. None of the
criteria for fit supported the model and the global assessment of the model
proved it to be so inadequate that assessment of the individual components was
impossible.
Brunsden et al do however admit that there may
have been serious shortcomings in their study that contributed to their results.
First, they did not actually assess social or academic integration. What they
actually did is to assess only the potential of academic and social integration.
As the assessment of potential is open to subjective interpretation, it is
possible that the level for potential integration and the level of actual
integration for any student didn’t actually line up.
Another conceivable weakness in this study is
that it was not exactly Tinto’s actual model that was assessed. In order to
carry out an effective statistical test of Tinto’s model they had to create
their own testable conceptualization of it. The possibility of the
conceptualization being different from the actual model in key ways means that
their results are potentially invalid.
Brunsden et al also criticize Tinto’s model for
having its origins in Durkheim’s model of suicide. Their argument is effective
that even supposing that Durkheim’s original model was an accurate and effective
model of suicide, there remains serious doubt over the extent to which the
relationship of dropout and suicide can truly be seen as analogous.
They also contend that although Tinto himself
was keen to separate the different forms of attrition behavior, that by basing
his model upon one of suicide, he is effectively acknowledging that attrition is
a negative process. It ignores the possibility of it to be a positive experience
for others. For example, on changing courses, having decided that one is now the
preferred option compared to another.
Also, while Tinto acknowledged that the
important thing is the individual’s own perceptions of the constructs in his
model (i.e. their social and academic integration), instead of the degree to
which each construct is expressed in an individual, his model entirely fails to
take account of this.
Criticism 2: The Student Integration Model is
only applicable to “Traditional” Students.
One of the most reliable criticisms made of
Tinto’s model is that it is only applicable to a traditional residential type of
students. Basically, it has been proposed that the Tinto model is not
generalisable beyond students who are resident on, or near, campus and who enter
university or college directly after leaving school.
What evidence is there to support this idea?
Alfred Rovai published a paper which discussed the extent to which Tinto’s model
would generalize to students engaged in distance learning programmes (Rovai,
2002). He comments that previous authors have noted that Tinto’s model is of
limited applicability in the study of non traditional students as it is based
around the analysis of how traditional undergraduate students fit into to the
institution of higher education which they attend.
He points to the work of Bean and Metzner who
proposed their own model of student attrition (the student attrition model or
S.A.M.). Bean and Metzner’s model also contended that Tinto’s model did not
explain attrition in students who were over twenty four, who did not live on
campus or were not in full time education. In addition, it also does not fully
account for those students who do not particularly wish to become involved in
the social aspects of student life and for whom the greatest concern about the
university they attend is what it can offer them, academically speaking.
The argument behind this way of thinking is that
the classmates, flat mates etc. that non-traditional students have, are a
potentially very different form of support network, compared to those fairly
common form of support network most students have. For example, mature students
are likely to have an extensive, well established network of friends and family
in place out with the university. And owing to this, there is less likely the
need of intra-university social and academic integration, the kind identified by
Tinto.
Similarly, it is unusual for those who are
engaged in distance learning for their higher education, to demonstrate similar
patterns of attrition, compared to those traditional students. This is due to
their differences in levels and types of their social and academic integration.
While these criticisms may be valid up to a
point (i.e. the Tinto Student Integration Model may not generalize beyond
traditional full time undergraduate students), there is a very simple reason for
this. The Tinto model is very ambitious in its scope; one model to explain the
full range of student attrition behavior. It was fundamentally designed to
describe the factors that cause students to leave higher education and is fairly
successful in doing so. But because of the ambitious nature of its design, it
was almost inevitable that it would fail to address attrition behavior of some
student populations. It was simply because of the nature of the difference of
their entire experience of the higher education process to that of the
traditional students. It is unlikely that any one model could account for every
conceivable reason that every single departing student had for leaving higher
education and one that can effectively describe that the attrition behavior of
the traditional student type will still have been a remarkable success.
Criticism 3: Academic
integration is not an important predictor of student attrition in
traditional student populations.
Evidence suggests that academic integration may
not be an important predictor of student attrition in the case of
non-traditional student groups. At the same time, some researchers also have
suggested that it is invalid generally in modeling student attrition.
An example is the office of Institutional
Retention at Bowling Green State University. They produced its own analysis of
student retention and attrition. Through the administration of its
self-constructed questionnaire to the two thousand eight hundred twenty nine
students entering first year, they assessed which of these students will return
for their second year.
This questionnaire was designed to test a number
of variables drawn from the Tinto model. Among them are Academic Integration,
Institutional Perception, Social Integration, Goal Commitment, Institutional
Commitment, their plans to return and whether or not they did. A path analysis
was carried out on the results of the questionnaire.
As a result, they obtained forty one percent of
the explanations of the variance in student retention through the said
questionnaire. It was said to be based on Tinto’s Student Integration Model. It
was also found that Institutional Commitment, Grade point average and Social
Integration were amongst the most important variables in the explanation of
attrition.
However, they did not find a significant amount
of the attrition behavior described by academic integration. Obviously, care
must be taken in the interpretation of these results. This was due to the fact
that this is a privately carried out study that has not been published and as
such has not undergone peer review.
The size of the sample used in this experiment
is perhaps its only strength. It represents one hundred percent sample and
previous researchers have contended that it is only through the use of a sample
this big that Tinto’s model can truly be assessed (Draper, 2002).
The exact nature of some of the questionnaire
items are not detailed, nor are they available in appendices of the paper. As
such, it is impossible to judge their questionnaire items’ accuracy or validity,
in terms of assessing attrition via a SIM-type model. And this is potentially
the biggest shortcoming of this study.
All the data that has been obtained in this
study is based upon self- report questionnaire. And as such, it is open to
subjective interpretation. The lack of effect from the academic integration
variable could be a function of the students, who answers the questionnaire with
a view to their self image. They don’t perceive the traits that constitute
academic integration as socially desirable.
It could also be the case that the exact items
that constitute the academic integration in this questionnaire are invalid.
Academic integration, as Tinto understood it, could indeed be responsible for a
great deal of attrition/retention behavior. But the items on this questionnaire
are invalid and do not correctly measure this.
Obviously, if caution is being exercised in the
interpretation of the lack of effect seen for academic integration, caution will
also be needed in giving too much importance to the significant effect observed
for the other SIM based items.
Due to the lack of scientific rigor demonstrated
by those who carried out this study, it is possible that the effects observed,
due to the other variables, may have been caused by the nature of the
questionnaire items or on how they were administered.
There have been several well controlled studies
that have investigated the importance of academic integration and whose results
have been consistent with its role in the SIM. Of particular note, due to the
rigor with which it was constructed, was carried out by Ernest Pascarella and
Patrick Terenzini in 1977.
Pascarella and Terenzini tested the effect of
the level of student-faculty interaction on student attrition in a traditional
student population. Their experiment was designed to determine whether the
amount of non-classroom interaction with academic staff that a student had was
predictive of their attrition or retention. This non-classroom interaction with
members of faculty staff is potentially important as it raises not only the
level of that individual’s academic integration but also their social
integration.
Pascarella and Terenzini examined a sample of
one thousand and eight students from the incoming freshman (first year) class at
Syracuse University in New York. These students were sent a detailed
questionnaire. Of the one thousand and eight questionnaires they sent out, they
obtained usable answers from seven hundred sixty six students, all of whom had
also supplied the university with completed Activity Indices AI (10) which is a
measure of personality on a twelve dimension scale and all of whom had available
scores on the verbal and quantitative scores from the Scholastic Aptitude Test
(SAT) which give an indication of academic capability. They then tested their
sample again in March the following year.
Their original sample of seven hundred sixty six
was sent further test items. As a result, they received usable responses from
five hundred thirty six students. Of these responses, one hundred ninety two had
to be discounted. It was either they had incomplete AI or SAT scores, or were
academic withdrawals, or had left the institution before the end of the first
semester.
The final experimental sample was, therefore
three hundred forty four students. This sample of students was shown, through
analysis via a Chi-squared, to be representative of the student freshman
population of Syracuse University. This was in terms of sex and college of
enrolment.
The sample was assessed one more time, at the
enrolment for the following academic year. At that time, it was determined that
fifty five subjects have voluntarily withdrawn. The frequency and nature of
non-classroom interaction that each student had with the faculty was assessed
through a series of questionnaire items administered to the students in March of
their first term. Only contacts that lasted for ten to fifteen minutes or more
were counted.
Pascarella and Terenzini analyzed the data
obtained from their questionnaires in order to see the effect of faculty contact
on attrition behavior, while controlling for possible effects of sex, academic
aptitude and personality characteristics. Pascarella and Terenzini found that
the amount of informal contact with the faculty was found to discriminate
significantly between those students who chose to leave the university and those
who chose to persist.
Pascarella and Terenzini's findings indicate
that some students who have certain personality traits and needs are more likely
to seek non-classroom contact with members of faculty staff. And as a result of
this contact, they are likely to attain higher levels of both social and
academic integration. In conclusion, they are now more likely to persist at
university. However, the results of this experiment indicate that the individual
student characteristics do not totally account for the difference in frequency
of faculty contact for different students.
The said experiment is potentially important. It
provides fairly convincing evidence of the usefulness of some of the most
important aspects of Tinto’s Student Integration Model in predicting student
attrition in a traditional student body. It is also important as it offers an
interactive longitudinal examination of student attrition.
Whereas most studies measure the students’
characteristics once, then assess dropout at a later date, Terenzini and
Pascarella assessed the students at three time points which gives a better
understanding of the nature of the interaction between different factors of the
Student Integration Model.
Retention in the Irish Higher Educational
System
The universities identified retention,
completion and student withdrawal as important issues to be addressed.
Particularly over the last three years, they have received rising attention
within the Irish university sector. A wide range of interventions across the
sector has been focusing on the challenge of preventing underperformance among
university students. These have been supported by targeted initiatives funding
from the Higher Education Authority, increased intra-institutional awareness,
and the establishment of the Irish Inter-University Retention Network.
Background of the Irish Retention
Overall figures on student completion of
university courses in Ireland indicate that an average of 83.2% of students
complete the university courses on which they originally enroll. A recent study
on completion, made by the Higher Education Authority, indicates that student
completion rates are higher in Ireland compared to other European countries. In
spite of this, certain areas of study and student groups depicted higher
non-completion rates than what is reflected by the average figure, as the case
is elsewhere.
The following have all been found to decrease
the likelihood of course completion among university students: under
preparedness in Mathematics, lack of adequate interaction with the career
guidance services in their secondary school, socio-economic background,
motivation to avail of student support, mismatched expectations, and poor
adjustment to the challenges of third-level learning environments.
The Issue on Non-Completion of Higher Education
in Ireland
In 1994, the Higher Education
Authority obtained progression data on students who had entered full-time
undergraduate courses in the years 1985-1986 in six universities: Dublin City
University, St. Patrick’s College Maynooth, Trinity College Dublin (TCD),
University College Cork (UCC), University College Dublin, and the University of
Limerick. Data were not available from University College Galway. The
information obtained are related to (i) the number of male and female students
entering each course in that year, (ii) the number of students who proceeded to
successive years of each course, and (iii) the number of students graduating or
not completing in each course. The data were subsequently analyzed at the
Educational Research Center (1997).
In all institutions, high rates of
non-completion were found. With one exception (UCC), each institution registered
at least one course with a non-completion rate in excess of one-third of
commencing students. The highest non-completion rate for UCC was a quarter.
Furthermore, all institutions had courses where twenty percent or more students
did not complete.
At the other end of the spectrum,
all institutions had at least one course for which non-completion rate was less
than ten percent. Furthermore, there were a number of courses (three in TCD and
one in Limerick) in which all students completed their course. But this was the
exception rather than the rule. Although courses with high, medium, and low
rates of completion were found in all institutions, differences in the patterns
of completion rates suggest that institutions vary in their capacity to retain
students.
The data of Higher Education
Authority also provided the opportunity of examining whether completion or
non-completion was associated with certain courses, irrespective of institution.
There were some indications that this was the case. Medicine, Law, and Dentistry
had low non-completion rates in all institutions, while rates for Science and
Arts tended to be relatively high. However, several subject areas differed in
their completion rates, depending on the institution in which they were offered
(for example, Engineering and Business Studies).
The report also identified a number
of problems in the data. These, in turn, indicate the need of exercising caution
in the interpretation of the findings. For example, institutions defined courses
in different ways when providing data, creating comparability problems. In the
case of one institution, it was not possible to determine for many courses the
extent of repetition, or indeed if there had been any repetition at all.
In a more recent study, the
predictive validity of the relationship between performance in the Leaving
Certificate Examination and performance at graduation by 1998 for students who
had entered third-level colleges in 1992 was examined (Commission on the Points
System, 1998). While the overall figure for graduation in this study was found
to be seventy four percent, twenty one percent did not receive any qualification
for the course for which they had first enrolled (divided equally among those
who passed first year exams and withdrew; failed first year exams and withdrew;
and did not sit first year exams). While the remaining five percent were in the
system (three percent were still attending and two percent had failed final year
exams).
While the results indicate that there was a
relationship between performance on the Leaving Certificate Examination and the
final year performance, it was far from perfect. The Leaving Certificate Grade
Point Average (LCGPA) of students who were awarded a first class honors or
distinction was slightly below than of those who were awarded upper second class
honors. While it was marginally lower points at entry for those who graduated
with third class honors, as compared to those who failed. And perhaps, of
greatest interest, is the fact that students who passed first year and then
withdrew, had a LCGPA that was much higher than that of students in the third
class honors degree. This was comparable to the LCGPA of those who had received
a lower second class honors and of those who were still attending.
These findings suggest that factors
other than those assessed in the Leaving Certificate Examination, affect
performance in higher education. One of these factors, field of study, was
explored in a further study for the Commission on the Points System. In here,
all third-level institutions have provided either data of first and final year
examination, or a sample of four hundred forty nine students who had commenced
college in 1992.
Students with the same Leaving Certificate
grades were found to have a higher probability of being awarded a top grade in
some disciplines than in others. They also had a higher possibility of not
completing in some fields compared to others.
While humanities had a non-completion rate of
only six percent, the corresponding figure for science was twenty percent.
Another interesting point is the relationships between LCGPA score, grade, and
field of study related to the Leaving Certificate scores of students who passed
first year and then withdrew. Remarkably, such students in the humanities and
science had a substantially better Leaving Certificate scores than for students
who graduated. Likewise, the case also applies even for those who obtained first
class honors. This pattern was broadly related in other fields of study
(business, technologies).
When non-completion rates were
analyzed by field of study, it was found that students who had not completed
their courses were more likely to have withdrawn after passing first year
examinations (38%) than to be still attending (29%). In addition, twenty six
percent are likely to have withdrawn after passing first year, while the
remaining seven percent belongs to those who have left before taking their first
year examinations.
Passing first year and then withdrawing
afterwards was the most common factor associated with non-completion among
business and humanities students (44% and 71% respectively). While almost
one-third (31%) of science students passed and withdrew, a higher percentage of
science students (48%) failed and then withdrew (12% for humanities and 29% for
business). The inability to provide more detailed analyses by courses of study
limits the usefulness of this study. This was due to the small sample size.
A non-completion study was also carried out in
three Institutes of Technology. The study is of particular interest in obtaining
individual student data in its attempt on finding reasons for non-completion. It
was reported here that non-completion rate was roughly around thirty seven
percent among first year students. Analyses also indicated that a number of
factors were associated to non-completion. Among them are low grades in the
Leaving Certificate Examination, unclear career aspirations, lack of
information, guidance on course and career options, unsuitable course choices,
difficulties with some or all of the subjects taken, as well as financial and
work-related problems. Institutional factors also played a role, particularly
the lack of facilities and support services, along with poor communication
between the staff and its students.
Relevance of the Tinto Model to the Irish Higher
Educational System
Tinto’s model did not focus directly
on individual characteristics. Instead, he looked at it in the way that they
interfaced with the central aspects of his model, which were the academic and
social systems of the educational systems of the educational institutions they
attended. Rather than focusing on the possible effects of a myriad of individual
characteristics, he focused on a few key characteristics. They are the grade
point average, family background, sex, etc. He then incorporated these into a
model which focused more directly on the impact of the institution itself on the
attrition behavior of it students.
He also acknowledged the adequate
notice of his model on the role of student finance in their decision to drop out
or persist. Although it was fairly obvious that financial concerns had a great
impact on decisions regarding a student’s drop-out, for him, it is only
longitudinal and indirect. It is because financial implications may determine
which university the individual chooses to attend and this may, in turn, affect
the likelihood of dropping out. Once at college or university, Tinto maintains
that the role of finance is not a pivotal one for the majority of the students.
It will be a key factor affecting the drop out behavior of only the most
economically disadvantaged students.
For Tinto, although there is little
chance of reducing attrition rates globally, there is the possibility that these
rates may be reduced in certain subgroups of the population. This can be made
possible through the increasing of the support or resources given to some
students. Another possibility is on the alteration of the selection methods in
order to select students that Tinto’s model shows.
Specifically, it is important for
universities and colleges to increase the amount of non-classroom contact
between the faculty and the students. Tinto feels that such contact directly
affects the likelihood of a person’s persistence in continuing higher education.
And as such, such contact should be regular and structured. Tinto also points to
one possible indirect way to reduce attrition. That is for universities and
colleges to advertise the social and academic aspects of their institutions more
realistically. By doing so, he asserts that it would reduce the number of
students entering an institution with an unrealistic image of what it will be
like. This should in turn minimize attrition, as there would be fewer students
dropping out or transferring from institutions that they had found to have less
social activity or less academic opportunity than they were led to believe.
