Enhance the Attractiveness of Studies in Science and
Technology
WP 6: Formal Hinders
Kevin Kelly
Trinity College Dublin
WP 6 Co-ordinator
WP 6: Formal Barriers
Origins of WP6: Are there students who want to study
engineering at third-level but who are prevented from
doing so? What are the barriers in their way?
Aim: To examine the formal barriers to engineering
education at third-level
For example:
•University admission requirements
•School systems which compel students to choose a particular path
early on
•Financial circumstances and access issues
Development of the Work Package
• Expanding the focus of WP6
– Formal barriers only part of the issue
– Needed to examine the subtle factors that can have a significant
impact
• Examination of the pre-university education system
– What are the structural factors that contribute to a student choosing
engineering?
– Assessment of formal barriers AND influencing factors (e.g.
exposure to STEM subjects, career guidance, etc)
Actions performed so far
• Formulation of documentation template for circulation
to partners
• Documentation of education systems in partner
countries
• Preliminary analysis of results
• Comparison framework for national results
Documentation of education systems in
partner countries
Aim: To collect data on key aspects of the primary and
secondary education systems, and university
admissions practices, in all partner countries
Example of topics covered:
•
Structure of school system
•
•
STEM subjects taught
Teacher training
Devised: April – June 2010
Revision and Agreement: June - October 2010
Sent to all ATTRACT partners: October 2010
Consolidation commenced: February 2011
Comparison Framework
Aim: To provide a framework for readily comparing the
education systems in partner countries under key
headings – required in each work package
Current status:
•Preliminary model devised to present comparison data
•Combination of charts, tables and textual info used
•Detailed information from each partner country will be
added
Comparison Framework
Categories for comparisons:
•General information about partner universities
•Pre-university education in each partner country
•Career Guidance provision for school students
•University admissions practices
•Financial situation for third-level students
Comparison Framework – Sample of
preliminary data
Overview of partner universities
Trinity
College
University
Type
National Core Funding
ranking sources
General
1
Aalto
MultiUniversity disciplinary
n/a
KTH
5
Technical
Government 66%
Student fees –
24%
Other – 10%
Government 71%
Private
donations 29%
Government 79.8%
Private
donations –
12.9%
Other – 7.3%
Undergrad
students
(F/T)
11,290
Undergrad
engineering
students
700 (6% of
total)
Postgrad
students
(F/T)
3,335
Postgrad
engineering
students
460 (14% of
total
postgrads)
17,020
4,289 (25%
of total)
2,496
657 (26% of
total
postgrads)
13,000
1,500
Comparison Framework – Sample of
preliminary data
% of second-level students by type of
school/curriculum
Comparison Framework:
Exposure to STEM subjects over time
Purpose: To document the progressive hours of student
exposure to engineering-relevant STEM subjects
throughout the primary and secondary education cycles
STEM Subjects covered:
• Maths (incl. Applied Maths)
• Physics
• Chemistry
•Other STEM (ICT, technical graphics, construction
studies, etc)
Student exposure to STEM subjects over time
4000
3000
2000
Finland
1000
Ireland
0
1
3
Number of hours
Maximum Maths
5000
5000
4000
3000
2000
Finland
1000
Ireland
0
1
5 7 9 11 13 15 17
Student age (years)
3
5 7 9 11 13 15 17
Student age (years)
Average Maths
4500
Number of hours
Number of hours
Minimum Maths
3500
2500
Finland
1500
Ireland
500
-500 1
3
5 7 9 11 13 15 17
Student age (years)
Career Guidance
Standardised
Counselling
System?
Qualifications
Operational Bias?
required to become
a Guidance
Counsellor
Primary
background
Ireland
No (currently
under review)
-
Primary degree
One year
postgraduate
studies
Yes
Humanities
- CG training provided in
parallel with religion, PE etc
- No specific training given
based on CG trainees academic
background
Sweden
No
-
Social & Science
program in upper
secondary school
BA arts
Work experience
-
Qualified teacher
with additional
studies in CG
OR
Masters degree in
Education
Yes
Finland
Yes *
-
-
-
Humanities
University Admissions
Centralised
Admissions
(Y/N)
Does the
General
university
admission
have power requirements
over student
selection?
Ireland
Y
No

State exams
State exams: Maths
55%+ at higher
level
 Mature
Student entry
 University
Access
Programmes
Finland
N
Yes

Entrance
exam
State exam
Entrance exams:
weighting for
Mathematics &
Physics/Chemistry
results
Open
Universities
access
programmes

Sweden
Y
Additional
requirements
for STEM
courses
% of potential
applicants
who meet
STEM
requirements
Alternative
entry routes
 Real Skills
evaluation
 Scholastic
Aptitude Test
% of
students
who enter
via
alternative
routes
Statistical Analysis
Aim: To examine factors affecting student success at
summer exams, in the context of the formal barriers to
third-level education assessed within WP 6
Point of Enquiry: What factors in the pre-third level
education system impact on success at third level?
Statistical Analysis
Background: HEA Study (October 2010)
• Examined factors affecting student progression,
including:
–
–
–
–
–
Prior attainment in Maths
Prior attainment in English
Overall prior educational attainment
Field of study
Student characteristics (e.g. gender, age, socio-economic
background)
• Findings:
− Prior attainment in Maths was single strongest
predictor of successful progression in higher education
Statistical Analysis: TCD
Data Examined:
• 2008-09 entrants through CAO and leaving certificate
• 2078 students
• Of these, 168 were engineering students
Data Analysis:
• Logistic regression was used to examine the following
variables:
–
–
–
–
–
–
CAO points
Gender
CAO score in English
CAO score in Maths
Average of CAO scores in Maths and Physics
Average of CAO scores in Maths and Applied Maths
The logistic model was of the form y=1/(1+exp(-u)) where u is a linear combination of the
independent variables. The output of the regression therefore is the value of the weighting
coefficients for u.
Results of Statistical Analysis: TCD
Main findings:
• CAO results overall had a significant predictive power
• Results in Maths and English had no additional predictive
capability
• Gender has a substantial impact on success at first year exams
across Trinity College as a whole
• Applied Maths may have some predictive power, but more data
is needed to confirm this
Findings when considering engineering students only:
• Gender has no impact
• Further examination of CAO results in English may be
worthwhile as there is a suggestion of some predictive power
Challenges and obstacles
•
•
•
•
Definition of scope of comparison
Formulation of headings for comparison
Acquisition of data
Distillation of data into coherent summary
• Difficulty in comparing very different education
systems
Involvement of stakeholders
• Why & what typology
– Missing data/more data
– Other headings/metrics
– Effectiveness/appropriateness of barriers
• In what way (activities and expectations)
– Determined at project level
– Circulation of draft documents
– Comment/feedback process
Next Steps
• Gathering of outstanding data (late May 2011)
• Completion of comparison framework (early June
2011)
• Gathering evidence of effectiveness of current
barriers (September 2011)
• Analysis of results & preliminary conclusions (end
September 2011)
• Drafting of WP 6 final report (January 2012)
Final comments
The number of formal barriers is not particularly high but
the underlying systems are so different as to make
comparison extremely difficult. This is a recurring theme
in the project as a whole.
The effectiveness and appropriateness of barriers
depends crucially on the structure of the education
system.
Thank You