Research Topics: Relevance Of Valuation Models

The relevance of these valuation models

Chapter V CONCLUSION   The relevance of these valuation models depends, therefore, on the assertion that the business landscape has fundamentally changed: that traditional rules of business success have been modified by technological developments in two key ways. First, barriers to entry are much more substantial than in old-economy businesses. Second, the beneficiaries of these barriers to entry will be existing but recently-established firms, even though their scale of operations is very small relative to the potential size of the market. First-mover advantages are far more significant than in old-economy businesses. These are different but related claims and both propositions are considered in the following section on business strategy. For the moment, however, I note that doubts had set in by 2001, and Amazon’s market value had fallen to .7 billion at 31 March, 2001.   The valuation of stock markets as a whole is discussed in an earlier review article (Wadhwani, 1999).[1] In 1996, when Mr Greenspan famously talked of “irrational exuberance”, the US stock market was priced, relative to corporate earnings, at levels on a par with 1929 and ahead of the two other peaks of valuation in the twentieth century, 1901 and 1966 (Shiller, 2000).[2] Thereafter, the headline Dow-Jones index rose from 6437.1 (5 December, 1996) to an all-time high of 11722.98 (14 January, 2000).   The argument here also is that traditional valuation criteria, such as price-earnings ratios, have been made obsolete by the new economy. Alternative views of appropriate market levels centre round applications of the dividend growth model.   It begins from the risk-free bond rate, adding a premium for the additional risk associated with investment in equities Glassman and Hassett (1999).[3] The anticipated growth of dividends has three components. In the long run, we might expect the growth of corporate earnings and the dividend stream from them to follow study examined the intraday and interday dynamics of both the level of and the rate of growth of national income.   This changes in the FTSE (Financial Times-Stock Exchange) 100 index. Like numerous previous studies, there was a find significant evidence of mean reversion and hence predictability in pricing changes measured over high (minute-by-minute) and low (daily) frequencies. For low-frequency data, predictability is driven neither by arbitrage activity nor by microstructure effects. Rather, it is a statistical illusion that is the result of overdifferencing a trend-stationary series.     [1] Wadhwani, S. (1999), ‘The US stock market and the global economic crisis’, National Institute Economic Review, 67, January, pp. 86-105.   [2] Shiller, R.J. (2000), Irrational Exuberance, Princeton N.J., University Press.   [3] Supra Glassman and Hassett Credit:ivythesis.typepad.com

The relevance of these valuation models

Chapter V CONCLUSION The relevance of these valuation models depends, therefore, on the assertion that the business landscape has fundam...

The Usefulness and Relevance of the Tinto Model to the Retention in Irish Higher Education”

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.   Credit:ivythesis.typepad.com

The Usefulness and Relevance of the Tinto Model to the Retention in Irish Higher Education”

This essay tackles about the usefulness and relevance of the Tinto Model to the retention issue in Irish Higher Education. On the first p...

The Usefulness and Relevance of the Tinto Model to the Retention in Irish Higher Education”

The Usefulness and Relevance of the Tinto Model to the Retention in Irish Higher Education”

This essay tackles about the usefulness and relevance of the Tinto Model to the retention issue in Irish Higher Education. On the first p...