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Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
Attract Project - Formal Barriers
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Attract Project - Formal Barriers

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To facilitate maximally open access to engineering higher education …

To facilitate maximally open access to engineering higher education
without compromising standards or unfairly exposing unequipped students.

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  • 1. Enhance the Attractiveness of Studies in Science and Technology WP 6: Formal Barriers Kevin Kelly Trinity College Dublin WP 6 Co-ordinator
  • 2. WP 6: Formal Barriers Aim of the Work Package:• To examine the formal barriers to engineering education at third-level• To document & recommend measures to facilitate maximally open access to engineering higher education without compromising standards or unfairly exposing unequipped students
  • 3. WP6 Key DeliverablesThree phases of work:• Survey of education systems in partner countries• Comparison Framework• Report on formal barriers to engineering higher education
  • 4. Status of Deliverables 1: Survey of Education SystemsCurrent Status: Completed• Extensive questionnaire developed and distributed to all partners• Questions investigated national education systems from primary level to university entry, regarding provision of science, engineering & technology (SET) subjects• Survey data gathered was used to inform other WP 6 deliverables
  • 5. Status of Deliverables 2: Comparison FrameworkCurrent Status: Completed (pending final contributions)• Aim is to provide ‘at a glance’ information to compare partner countries under key headings, relevant to all work packages• Provides necessary context to enable conclusions to be drawn between national structures with significant variations• Combination of graphs, tables and textual information used
  • 6. Status of Deliverables 3: Report on Formal BarriersCurrent Status: Finalising reportThe report documents:• main factors restricting access to engineering higher education• research illustrating the impact of these barriers on access to engineering• data analysis of the relationship between entry barriers and subsequent student progression 14.4.2011 6
  • 7. Report on Formal BarriersMain categories of barriers identified:• Entry requirements for engineering courses• Structures within the school system – such as streams which force students to choose at an early age between academic or vocational pathways• Socio-economic factors – engineering programmes in several countries appear to be less diverse in socio-economic terms than other programmes
  • 8. 1. Entry RequirementsKey points:• No subject requirements set for entry in Italy andBelgium• Mathematics required in all other countries, plusPhysics and Chemistry in most• Limited students eligible for entry as a result – max 12% eligible in Sweden and Ireland
  • 9. 1. Entry Requirements (cont’d)Do entry requirements serve the intended purpose?• Evidence found in some partner countries of a linkbetween achievement in the subjects required for entry,and subsequent performance in engineering universityprogrammes – e.g. in IST students who have grades lower than those now required have significant difficulty in successfully completing the programme
  • 10. 1. Entry Requirements (cont’d)Alternatives to standard entry requirements• Alternative entry routes exist in most partner countries• Function: To facilitate access to university for non- traditional students & those not meeting standard entry requirements• Proportion of students entering via these means varies from 0% (Italy) to 29% (Sweden)
  • 11. 2. High School SystemStructural Factors:• Separation between academic and vocational branches of high school in most countries• This impacts on options for higher education  vocational students may not be eligible for academic study at university• Subject specialisation creates further restrictions – students who don’t specialise in science/technology may be ineligible for engineering programmes
  • 12. 2. High School System (cont’d)Gender and subject specialisation:• Persistent gender differences in uptake of engineering-relevant subjects, especially Physics• In Ireland some technology-related subjects are not taught in all-girls schools• Research suggests causal relationship between lower % of girls specialising in Physics, Chemistry and Mathematics in high school and low numbers of female students entering engineering programmes at university
  • 13. 3. Socio-economic Factors• Engineering courses in many countries are less accessible to students from lower socio-economic backgrounds than other fields (Eurostudent IV)• This is reflected in several ATTRACT countries – in Ireland, Sweden and Italy engineering programmes tend to be less socio-economically diverse than other programmes• In Ireland, PISA mathematics scores were significantly higher among students designated as ‘high socio- economic status’ than among others
  • 14. Aalto Trinity KU Leuven PoliTo IST KTH Uppsala University College Country Belgium Finland Ireland Italy Portugal Sweden Sweden Multi- Multi-University Type General General Technical Technical Technical disciplinary disciplinaryNational Ranking #1 n/a #1 #2 #2 #4 #3 Government: Government: Government: Government: Government: Government: Governmen 75% 71% 66% 45% 41% 80% t: 80% Student fees: 10% Core Funding Private Student fees: Student fees: Private Sources Private Public sources/contrac 24% 9% sources: donations: 29% funds: 8% t research: 15% Research 13% income: 43% Private Other (own Other: 10% Other: 10% Other: 2% Other: 7% sources: income): 50% 12% # of students studying to 36,820 17,020 11,290 18,792 9,445 14,000 20,000degree/accreditedprofessional level 9% 25% 6% 75% 94% 100% 12%· % studying (4,124 (4,289 (14,053 (8,832 (14,000 (2,300 engineering (700 students) students) students) students) students) students) students)# of advanced or 4,454 2,496 3,335 1,135 1,500 2,000doctoral students 21% 26% 14% n/a 69% 100% 5%· % studying (1,500 (100 engineering (964 students) (657 students) (460 students) (779 students) students) students)
  • 15. Comparison of high school systems Belgium Ireland Portugal Sweden Finland ItalyTracks(e.g. N N Y Y Y Yliterature,science)Higherand lower N Y N N N NlevelsCore Y N Y Y Y YsubjectsStudentchoice Y N N Y Y Noverquantity
  • 16. Structure of Education Systems
  • 17. Structure of Education Systems
  • 18. Contact Time in Schools
  • 19. Exposure to Mathematics
  • 20. Finland Ireland Italy Portugal Sweden School certificate Yes Yes Yes Yes No exams and/or - - and/or - Ongoing Yes No No Yes Yes performance at second-level General and/or - - and/or - admissionrequirements Entrance exams Yes No No No No (Managed by institution) - - - and/or and Other n/a n/a n/a Yes† Yes‡
  • 21. Portuga Finland Ireland Italy Sweden l Yes* Yes – No Yesˠ Yes Maths 55% + Physics Yes* No Yesˠ Yes Approx.Additional admission Yes* 10% of No Yesˠ Yes requirements for Chemistry coursesEngineering courses No require one No No Required Biology science in certain subject courses Advanced 12% n/a 38% 11% mathematics: % of students who meet STEM 42% requirements Physics/ Chemistry: 17%
  • 22. Purpose of Barriers1. Identification of student ability2. Pre-requisite knowledge (i.e. university does not need to teach this!)
  • 23. Appropriateness & Effectiveness• Reasons (historical) for design and implementation of barriers• Evidence of whether (appropriate) and how well (effective) these barriers work • Pre-requisite knowledge – by definition it is effective. Appropriate is more difficult to say! • Students who pass barriers should do better than those who don’t. – Those who don’t pass barriers aren’t let in! – Use excess of performance over barriers to measure how well these metrics capture ability to progress
  • 24. Barrier Effectiveness – ItalyNumber of students who took a low note at the entry 250 200 150 test 100 50 0 0 8 10 16 18 20 26 28 30 36 38 46 number of credits passed the first year
  • 25. Barrier Effectiveness – ItalyNumber of students who took a high note at the entry 200 180 160 140 120 100 test 80 60 40 20 0 0 8 10 16 18 20 26 28 30 36 38 46 number of credits passed the first year
  • 26. Barrier Effectiveness – Portugal• the variables of parental education level and stage of admission were not significant;• the variables regarding the academic background proved all significant, in particular the impact of the grade obtained in the secondary education in the academic achievement (40% performance improvement for every 10 points) and the frequency of Physics in Secondary (72% increase in the probability of success, compared to those who had not);
  • 27. Barrier Effectiveness – Portugal• in the socio-economic status and family income dimension, the variables gender and household income level were significant, showing that women have a higher probability of success than men (+10%) and the level of household income below the national average increases by 8% school performance;• regarding the motivations and expectations, it appears that if the student doesn’t access his/her first choice of programme (-16%) and if he/she student did not anticipate to engage in all subjects expecting a good average (-9%) there is a negative impact on academic achievement. The early choice of the course (prior to the year of admission) has a positive impact on the success rate (+22%);
  • 28. Barrier Effectiveness – Portugal• academic achievement. The early choice of the course (prior to the year of admission) has a positive impact on the success rate (+22%);• contextually it is observed that the fact that a student is away from his/her usual residence exerts a negative effect on their academic performance (there is a 17% decrease in academic performance demonstrated by students who are away from residence) and that the travel time is also reflected negatively (a student who takes more than 1h in each travel to IST decreases 10% in academic performance).
  • 29. Factors Analysed - Ireland• Inputs – Whether a student took a particular subject (binary) – Mark achieved in each subject (0-100) – Degree (one of two available) programme chosen (binary) – Gender (binary) – Year (have things changed over 10 year period) (1-10) – CAO mark (cumulative grade in best 6 subjects) (0-600) – Living at home (binary)• Outputs – Had to take second exam sessions (Binary) – Progressed to 2nd year (Binary)
  • 30. Key questions• Can we identify those entrants less likely to progress• How accurately can we do this – i.e. what is the balance between correctly identifying those with difficulties and incorrectly identifying those who won’t
  • 31. 128 Students
  • 32. 15 Students on average will fail their exams (~12%) – 113 passed
  • 33. We can select these using various strategies – e.g. random, ortargeting certain individuals
  • 34. Here for example we are selecting 24 students (we’ll assume wehave some strategy!)In terms of effective detection/identification, we could measure itas:4/15 failing students were correctly identified. This is a TruePositive Rate of 27%20/113 passing students were incorrectly identified. This is a FalsePositive Rate of 17%
  • 35. A system with perfect discrimination could identify all those failingstudents correctly, AND have no students incorrectly identifiedMost practical systems will involve some compromise betweenincorrectly identifying some students, versus correctly identifyingthose who will failGraphically this tradeoff can be plotted on something called areceiver operating characteristic
  • 36. Receiver Operating Characteristic - Progression 1 0.9 0.8 0.7True Positive Rate 0.6 All Factors 0.5 Random 0.4 CAO CAO + Maths 0.3 0.2 0.1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 False Positive Rate
  • 37. Receiver Operating Characteristic - First Sitting 1 0.9 0.8 0.7True Positive Rate 0.6 All Factors 0.5 Random 0.4 CAO CAO + Maths 0.3 0.2 0.1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 False Positive Rate
  • 38. Exam Mark versus Effect Size0.20.1 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100-0.1 Accounting-0.2-0.3-0.4
  • 39. Logistic Analysis of Performance Input Weighted Logistic ProbabilityVariables Sum Function [0 / 1] [- ∞, + ∞] [0 - 1][0 - 100]
  • 40. Probability of succesful completion of exams 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0-4 -3 -2 -1 0 1 2 3 4 Weighted sum of input factors
  • 41. Previous work in Ireland CAO Maths English Student A High B High C Low D High E High F Low G Low H I High J High K Low L Low M High N Low O Low P
  • 42. Previous work in Ireland0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0%ABCDEFGHIJKLMNOP
  • 43. 100.00% Gender Uptake of Various Subjects90.00%80.00%70.00%60.00% Female Male50.00%40.00%30.00%20.00%10.00% 0.00%
  • 44. 10.00% Relative Subject Difficulty 5.00% 0.00% -5.00%-10.00% Male Female-15.00%
  • 45. PISA – maths, science & GDP Finland Ireland USA Sweden Belgium Italy Portugal
  • 46. PISA – top students in maths & science“the number of students reaching level 5 or 6 inmathematics and science will be particularlyimportant for countries wishing to create a pool ofworkers able to advance the frontiers of scientificand technological knowledge in the future andcompete in the global economy”– OECD Report – PISA 2009 Results Vol. 1
  • 47. Percentages of Students at Level 5(6) in Maths and ScienceCountry Maths ScienceShanghai 24(26) 20(4)Finland 16(6) 15(4)Belgium 14(5) 8(2)OECD average 9(3) 7(2)Sweden 8(3) 7(1)Portugal 7(3) 3(1)Italy 7(2) 5(1)Ireland 5(1) 8(1)
  • 48. RecommendationsThree categories:a. Changes to admission requirementsb. Structural Changes to Education Systemc. Socio-economic and cultural issuesRelative difficulty of implementation• Easy, moderate or difficult
  • 49. Recommendations (a) Changes to admission requirementsMathematicsPhysics and/or Chemistry
  • 50. Recommendations (b)Structural changes to education systemHigher level of preparation in STEMLater ‘tracking’ of studentsHigher core STEM content for all students
  • 51. Recommendations (c) Socio-economic and cultural issuesNeed to show relevance of STEM to real lifeEncourage more girlsIncrease participation from marginal socio-economicgroups

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