An Analysis of Non-Progression Rates in Irish Higher Education Institutions – Overview and Key Findings
(April 2022)
Background
Background
This report examines progression in Irish Higher Education Institutions and follows on from previous (print/pdf) reports on progression in Higher Education 1. The purpose of this report is to identify the overall rate of non-progression of students from their first year into the following academic year and more particularly, to enable identification of particular cohorts of students with a high risk of non-progression.
This report consists of four themed sections allowing users to view descriptive statistics, complemented by a logistic regression analysis which presents a like-for-like analysis of students across institutions:
- Introduction and Methodology
- Executive Summary of Key Findings including summary tables (This page, below)
- Interactive Tables: A set of interactive visualisations allowing the user to view and analyse non-progression rates of New Entrants 2015/16 to 2019/20
- Interactive Tables: Logistic Regression analysis of non-progression rates of new entrants 2017/18, 2018/19 and 2019/20
The most recent publication focused on the non-progression rates of entrants in 2015/16 and 2016/17. This section presents a summary of the key findings of the analysis of the non-progression rates of entrants to higher education in 2017/18, 2018/19 and 2019/20. Note that the 2019/20 cohort was the first cohort to be impacted by the covid-19 pandemic.
Non-Progression in Higher Education - Executive Summary and Key Findings
Key Points:
- Non-progression rates are trending slowly downwards overall, from 16% (2010/11 entrants) to 12% (2018/19 entrants). The non-progression rate of new entrants in 2019/20 was 9%.
- While the overall non-progression rate improved in 2019/20, the non-progression rates for new entrants at Level 6 and 7 is at least double that for entrants to Level 8 courses (16% and 18% at Levels 6 and 7 respectively, compared to 8% at Level 8).
- As in recent years, the highest overall non-progression rate was in the Services field of study (16% for 2019/20 entrants), closely followed by ICT (15%) and Engineering, Manufacturing & Construction (13%). The field of study with the lowest rate continues to be Education (3%).
- Males have a higher non-progression rate than females, particularly at L6 and L7. In 2018/19 the non-progression rates were 26 and 27% respectively for males, 18% each for females. The gap was narrower at Level 8, at 8% for females and 11% for males. This pattern has continued in 2019/20, with overall rates for males at 11% but at 7% for females.
- Mature entrants have a higher non-progression rate than non-mature entrants at Level 8; however, mature entrants have a lower rate of non-progression at Level 6 while there was no difference between the two age groupings at Level 7 (2019/20 entrants).
- Students entering Level 8 courses through the DARE and HEAR schemes have slightly better non-progression rates than the overall average for Level 8 entrants. However, students entering from other “non-traditional” routes (i.e., not on the basis of Leaving Certificate points) have in general higher than average non-progression rates across all NFQ levels.
- Where data is available, a very strong association between Leaving Certificate points at entry and non-progression rates is evidenced. Entrants with lower Leaving Certificate points have much higher-than-average non-progression rates, particularly at Levels 6 and 7. By contrast, students entering Level 8 courses with high points have the lowest non-progression rates, between 4 and 7% (2018/19 entrants) and as low as 3% (2019/20 entrants).
- Variation in headline non-progression rates across HEIs can be seen before controls are applied. Comparing like-for-like students however, the difference in non-progression rates by HEI is significantly reduced.
- Leaving Certificate Points are an important predictor of non-progression rates. Despite comparing like-for-like students, those with less than 200 points have a predicted non-progression rate of 25%, compared to just 4% for those with over 500 points.
- Students from disadvantaged backgrounds are more likely to not progress than affluent students. However, after controlling for Leaving Certificate Points, no clear relationship exists between Deprivation Index Scores and non-progression rates.
- Disparities in non-progression rates exist across gender and Leaving Certificate Points. For example, the gap in in non-progression rates between males and females with 200 Leaving Certificate Points is 11 percentage points, despite comparing like-for-like students. This gap diminishes for students with higher Leaving Certificate Points.
Non-Progression in Higher Education - NFQ and Field of Study (2017/18, 2018/19 and 2019/20 Entrants)
Table 1: Non-Progression Rates by NFQ Level
NFQ Level | 2017/18 | 2018/19 | 2019/20 |
---|---|---|---|
Level 6 | 22% | 22% | 16% |
Level 7 | 26% | 24% | 18% |
Level 8 | 11% | 10% | 8% |
All Levels | 13% | 12% | 9% |
Table 2: Non-progression Rates by Field of Study
Field of Study (ISCED) | 2017/2018 | 2018/2019 | 2019/2020 |
---|---|---|---|
Education | 4% | 4% | 3% |
Arts and humanities | 15% | 13% | 11% |
Social sciences, journalism and information | 9% | 10% | 6% |
Business, administration and law | 12% | 11% | 8% |
Natural sciences, mathematics and statistics | 12% | 11% | 7% |
Information and Communication Technologies (ICTs) | 20% | 17% | 15% |
Engineering, manufacturing and construction | 17% | 15% | 13% |
Agriculture, forestry, fisheries and veterinary | 8% | 8% | 5% |
Health and Welfare | 9% | 8% | 6% |
Services | 21% | 22% | 16% |
Total | 13% | 12% | 9% |
The user can view non-progression rates by NFQ and Field of Study and by individual HEI in interactive format in the next section of this report.
Non-Progression in Higher Education - Student Characteristics (2017/18, 2018/19 and 2019/20 Entrants)
Table 3: Non-progression rates by gender
Gender | 2017/2018 | 2018/2019 | 2019/2020 |
---|---|---|---|
Female | 11% | 9% | 7% |
Male | 16% | 14% | 11% |
Total | 13% | 12% | 9% |
Table 4: Non-progression rates by Domiciliary of Origin
Domiciliary of Origin | 2017/2018 | 2018/2019 | 2019/2020 |
---|---|---|---|
Irish | 13% | 12% | 9% |
Non-Irish | 15% | 11% | 13% |
Total | 13% | 12% | 9% |
Table 5: Non-progression rates by Age Group
Age grouping | 2017/2018 | 2018/2019 | 2019/2020 |
---|---|---|---|
Under 23 (Non-mature entrant) | 13% | 11% | 9% |
23+ (Mature entrant) | 18% | 16% | 13% |
Total | 13% | 12% | 9% |
Non-progression rates by Deprivation Index Score
Table 6.1: 2018/19 Non-progression rates by Deprivation Index Score category (Irish Domicile only, excluding Unknowns)
DIS Category | Level 6 | Level 7 | Level 8 | All Levels |
---|---|---|---|---|
Affluent | 16% | 24% | 8% | 10% |
Marginally Above Average | 18% | 22% | 9% | 11% |
Marginally Below Average | 25% | 24% | 10% | 13% |
Disadvantaged | 28% | 30% | 13% | 17% |
Grand Total | 22% | 24% | 10% | 12% |
Table 6.2: 2019/20 Non-progression rates by Deprivation Index Score category (Irish Domicile only, excluding Unknowns)
DIS Category | Level 6 | Level 7 | Level 8 | All Levels |
---|---|---|---|---|
Affluent | 14% | 16% | 6% | 7% |
Marginally Above Average | 17% | 18% | 7% | 9% |
Marginally Below Average | 15% | 18% | 7% | 9% |
Disadvantaged | 16% | 21% | 10% | 12% |
Grand Total | 15% | 18% | 7% | 9% |
Non-Progression in Higher Education - Entry Routes and Prior Educational Attainment (2017/18, 2018/19 and 2019/20 Entrants)
Since the 2018/19 academic year, the HEA has collected data on the entry basis of students. The majority of new entrants to Higher Education come directly from school and are admitted to their course on the basis of school leaving examinations (75% of entrants in 2019/20). Smaller numbers gain entry via access routes targeting underrepresented groups (primarily students with disabilities, students from disadvantaged social backgrounds and mature students), while others gain entry on the basis of other qualifications, such as a further education award.
The following table shows the non-progression rates of students by entry basis and NFQ level.
Table 7.1: Non-progression by Entry Basis (2018/19 Entrants)
Entry Basis | Level 6 | Level 7 | Level 8 | Total |
---|---|---|---|---|
2nd level school leaving exams | 23% | 24% | 9% | 11% |
DARE | 19% | 17% | 9% | 10% |
HEAR | ^ 5% | 28% | 8% | 8% |
Access/Foundation & Other Access | ^ 17% | 35% | 15% | 18% |
Mature Years | 24% | 19% | 15% | 16% |
Direct Entry | 23% | 15% | 11% | 11% |
Further Education Award | 25% | 25% | 13% | 16% |
Other | 10% | 14% | 12% | 12% |
Total | 22% | 24% | 10% | 12% |
Note: ^ indicates number of entrants in cohort is less than 25.
Table 7.2: Non-progression by Entry Basis (2019/20 Entrants)
Entry Basis | Level 6 | Level 7 | Level 8 | Total |
---|---|---|---|---|
2nd level school leaving exams | 17% | 19% | 7% | 8% |
DARE | 13% | 16% | 6% | 7% |
HEAR | 11% | 16% | 8% | 9% |
Access/Foundation & Other Access | ^ 10% | 12% | 15% | 15% |
Mature Years | 18% | 18% | 11% | 12% |
Direct Entry | 25% | 21% | 10% | 12% |
Further Education Award | 17% | 18% | 11% | 12% |
Other | 4% | 3% | 10% | 9% |
Total | 16% | 18% | 8% | 9% |
Note: ^ indicates number of entrants in cohort is less than 25.
Non-progression rates by Leaving Certificate Points Range
The following tables show the non-progression rate by Leaving Certificate Points range (where available) for students entering solely on the basis of 2nd level school leaving exams.
Table 8.1: 2018/19 Entrants – Non-progression rates by Leaving Certificate Points Range
LC Points Range | Level 6 | Level 7 | Level 8 | All Levels |
---|---|---|---|---|
150 to 199 | 28% | 39% | ^ 20% | 34% |
200 to 249 | 32% | 37% | 39% | 36% |
250 to 299 | 26% | 27% | 23% | 26% |
300 to 349 | 13% | 19% | 16% | 17% |
350 to 399 | 5% | 12% | 12% | 12% |
400 to 449 | 13% | 9% | 8% | 8% |
450 to 499 | ^20% | 15% | 6% | 6% |
500 to 549 | ^ 14% | 4% | 4% | |
550 to 599 | 4% | 4% | ||
600 to 625 | 4% | 4% | ||
Total | 21% | 25% | 9% | 11% |
Note: ^ indicates number of entrants in cohort is less than 25.
Table 8.2: 2019/20 Entrants – Non-progression rates by Leaving Certificate Points Range
Based on Leaving Certificate Points where available for students entering solely on the basis of Leaving Certificate Points
LC Points Range | Level 6 | Level 7 | Level 8 | All Levels |
---|---|---|---|---|
150 to 199 | 38% | 28% | ^ 0% | 31% |
200 to 249 | 18% | 30% | 29% | 28% |
250 to 299 | 15% | 19% | 19% | 19% |
300 to 349 | 9% | 14% | 13% | 13% |
350 to 399 | 11% | 9% | 9% | 9% |
400 to 449 | 4% | 6% | 5% | 5% |
450 to 499 | ^0% | 2% | 4% | 4% |
500 to 549 | ^0% | ^0% | 3% | 3% |
550 to 599 | ^0% | ^0% | 3% | 3% |
600 to 625 | 3% | 3% | ||
Total | 15% | 18% | 6% | 8% |
Note: ^ indicates number of entrants in cohort is less than 25.
Methodology and Demographic Profile of New Entrant Population
Methodology
The study is purely quantitative in nature, drawing on data returned from HEA funded institutions to the HEA’s Student Record System database (SRS2) to identify first year new entrants who do not progress to the following academic year. The datasets on which these analyses are based were extracted from the SRS by tracking the student IDs within institutions and from the year of entry to the following academic year. A student is deemed to have progressed if they are present in the same institution in the following academic year. The majority of these students who progress do so into the second year of their course, but students who repeat or who transfer to a different course, level/programme type or mode of study are also treated as having progressed. It is those students who are not present in the academic year following the year of entry that are considered as non-progressed and who are therefore the focus of this study.
The non-progression rates described in this section, and in the three following sections, reflect the number of students that did not progress expressed as a percentage of the total number of new entrants for the relevant cohort. Non-progression rates are influenced by various factors. As such, comparisons of unadjusted non-progression rates across institutes may be confounded by differences in individual and institutional factors. To further understand the key drivers of non-progression, richly specified regression models are employed to control for student characteristics such as leaving certificate points, age, gender, socio-economic background, domicile, school type, and entry basis. In terms of institutional level characteristics, institute, NFQ level and course of study are included as explanatory variables in our models. This chapter attempts to disentangle the effects of these factors and model non-progression rates across several variables by comparing like-for-like individuals. These “full model” estimates compare like-for-like students, in an attempt to isolate the impact of the selected variable on non-progression.
Limitations of this analysis
Students who transfer to another institution, or who take a year out between their first year and second year (or who take a year out before returning to repeat or commence a different course) are not recorded as progressed for the purposes of this study. Students who leave their institution early in the academic year, prior to the census dates in the base year (01 March) may not be included in the base year cohort. The report does not consider differing progression practices across institutions, for example, where some institutions may allow a student to progress carrying failed modules while others do not.
Most importantly, this study is purely quantitative in nature: It does not provide any insight on the motivation for enrolling in Higher Education, the financial well-being of students, study patterns, student views on teaching methodologies and staff, the effect (good or bad) of participation in extra-curricular activities as well as the work practices of non-progressing students. Rather, these analyses should be viewed as providing quantitative data to underpin constructive and collective engagement on the challenges faced by the system in ensuring progression and successful completion for undergraduate students.
Student Demographics
Student Characteristics: Profile of New Entrants
It is important that the user be aware of the demographic profile of the new entrant cohort. In particular, the user should be cautious when drawing conclusions based on cohorts of students with small numbers of new entrants. The following tables are a profile of the new entrant cohort in terms of gender, domiciliary, age grouping and socio-economic status (as measured by Deprivation Index Score Category).
The following is a profile of the New Entrant cohorts 2017/18 and 2018/19 used for this analysis.
Table 9: Gender Breakdown of New EntrantsGender 2017/2018 2018/2019 2019/2020 Female 52% 52% 53% Male 48% 48% 47% Less than 1% of the new entrants in 2018/19 or 2019/20 identified as neither Male or Female
Table 10: Domiciliary Breakdown of New Entrants
Domiciliary of Origin 2017/2018 2018/2019 2019/2020 Irish 94% 94% 95% Non-Irish 6% 6% 5% Table 11: Age Breakdown of New Entrants
Age Group 2017/2018 2018/2019 2019/2020 Under 23 (Non-mature entrant) 92% 93% 93% 23+ (Mature entrant) 8% 7% 7% Note: Mature in this context refers to person’s age (i.e. 23 or over) on entry into higher education. They may not have entered on the basis of mature student entry routes.
Table 12: Socio-economic profile of New Entrants
DIS Category 2017/2018 2018/2019 2019/2020 Affluent 16% 16% 15% Marginally Above Average 38% 38% 38% Marginally Below Average 29% 28% 28% Disadvantaged 10% 10% 10% Unknown 7% 8% 10%
Go to next Section: Non-Progression by NFQ, Field of Study and Higher Education Institution
Notes:
[1] links to previous progression reports can be found on our progression archive page.
[2] The Student Record System (SRS), the HEA’s in-house database. The SRS contains an individual record for each student enrolment and graduation in all HEA-funded Institutions. The SRS has gathered student data from the University and College sector since the 2004/05 academic year and from the Institute of Technology (and subsequently Technological University) sector since the 2007/08 academic year. Please visit this page for an overview of the HEA data collection and analyis methodology
[3]Science, technology, engineering, and mathematics
[4] For further reading on the use of Deprivation Index Scores for socio-economic profiling, please see HEA (2019) A Spatial & Socio-Economic Profile of Higher Education Institutions in Ireland
. Previous reports used responses from the Equal Access Survey to identify the socio-economic group of entrants. The equal access survey no longer collects this data and DIS analysis is now the method used to identify the socio-economic profile of student cohorts for studies such as this.