Enhance the Attractiveness of Studies in Science and Technology WP 6: Formal Hinders

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Enhance the Attractiveness of Studies in Science
and Technology WP 6 Formal Hinders

• Kevin Kelly
• Trinity College Dublin
• WP 6 Co-ordinator

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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

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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)

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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

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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

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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

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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

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Comparison Framework Sample of preliminary data

• Overview of partner universities

University Type National ranking Core Funding sources Undergrad students (F/T) Undergrad engineering students Postgrad students (F/T) Postgrad engineering students
Trinity College General ?1 Government - 66 Student fees 24 Other 10 11,290 700 (6 of total) 3,335 460 (14 of total postgrads)
Aalto University Multi-disciplinary n/a Government - 71 Private donations - 29 17,020 4,289 (25 of total) 2,496 657 (26 of total postgrads)
KTH Technical ?5 Government - 79.8 Private donations 12.9 Other 7.3 13,000 1,500
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Comparison Framework Sample of preliminary data

• of second-level students by type of
  school/curriculum

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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)

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• Student exposure to STEM subjects over time

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• Career Guidance

Standardised Counselling System? Qualifications required to become a Guidance Counsellor Operational Bias? Primary background
Ireland No (currently under review) Primary degree One year postgraduate studies Yes - CG training provided in parallel with religion, PE etc - No specific training given based on CG trainees academic background Humanities
Sweden No Social Science program in upper secondary school BA arts Work experience - -
Finland Yes Qualified teacher with additional studies in CG OR Masters degree in Education Yes Humanities
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• University Admissions

Centralised Admissions (Y/N) Does the university have power over student selection? General admission requirements Additional requirements for STEM courses of potential applicants who meet STEM requirements Alternative entry routes of students who enter via alternative routes
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 Real Skills evaluation Scholastic Aptitude Test
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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?

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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

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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
  y1/(1exp(-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.

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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

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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

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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

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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)

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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.

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Thank You