Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Dream jobs? - Teenagers' career aspirations and the future of work

36,057 views

Published on

Every day, teenagers make important decisions that are relevant to their future. The time and energy they dedicate to learning and the fields of study where they place their greatest efforts profoundly shape the opportunities they will have throughout their lives. A key source of motivation for students to study hard is to realise their dreams for work and life. Those dreams and aspirations, in turn, do not just depend on students’ talents, but they can be hugely influenced by the personal background of students and their families as well as by the depth and breadth of their knowledge about the world of work. In a nutshell, students cannot be what they cannot see. With young people staying in education longer than ever and the labour market automating with unprecedented speed, students need help to make sense of the world of work. In 2018, the OECD Programme for International Student Assessment (PISA), the world’s largest dataset on young people’s educational experiences, collected firstof- its kind data on this, making it possible to explore how much the career dreams of young people have changed over the past 20 years, how closely they are related to actual labour demand, and how closely aspirations are shaped by social background and gender.

Published in: Education

Dream jobs? - Teenagers' career aspirations and the future of work

  1. 1. 2020 World Economic Forum Andreas Schleicher
  2. 2. PISA 2018 but also responded to questions about their aspirations for their future careers, and from where they learn about the world of work
  3. 3. Participating countries 2018 – 79 participating
  4. 4. With the labour market undergoing rapid, fundamental change – decision-making is more important, but also more difficult. 4 Nedelkoska, L. and Quintini, G. 2018. Automation, Skills Use and Training. Paris: OECD
  5. 5. Skills and the risk of automation Australia Austria Canada Chile Cyprus¹ Czech Republic Denmark Ecuador England (UK) Estonia Flanders (Belgium) France Germany Greece Hungary Ireland Israel Italy Japan Kazakhstan Korea Lithuania Mexico Netherlands Northern Ireland (UK) OECD average Peru Poland Russian Federation² Singapore Slovak Republic Slovenia Spain Sweden Turkey United States 2012/2014 United States 2017 R² = 0.273 170 190 210 230 250 270 290 310 35 40 45 50 55 60 65 70 Risk of automation Skills(PIAACNumeracy)
  6. 6. Every day, teenagers make important decisions that shape their future …but young people’s career aspirations are often narrow, unrealistic and distorted by gender and social background
  7. 7. 8 4 0 4 8 12 16 Doctors Teachers Businessmanagers Engineers Lawyers Policeofficers ICTprofessionals Nursingandmidwives Designers Psychologists Architects Veterinarians Actors Motorvehiclemechanics Musicalperformers Girls 2018 Boys 2018 Girls 2000 Boys 2000 % The fifteen most common occupational expectations among 15-year-olds
  8. 8. Many teenagers aspire to jobs that are at high risk of automation 0% 10% 20% 30% 40% 50% 60% Australia UnitedKingdom Ireland NewZealand UnitedStates Finland Norway Canada Singapore Israel Sweden ECD-SampleAverage Belgium Denmark Korea Chile Austria Netherlands Italy Spain Estonia France CzechRepublic Poland Slovenia Cyprus Greece Germany Japan Lithuania SlovakRepublic Advantaged Disadvantaged
  9. 9. While the world of work has undergone major changes since 2000… …career expectations of youths have changed little but became more concentrated
  10. 10. 40 42 44 46 48 50 52 54 2000 2006 2015 2018 % Girls Boys Total Concentration of occupational expectations between 2000 and 2018 Percentage of students naming 10 most popular occupations Source: PISA databases. Countries reporting career expectations in PISA 2000, 2003, 2006, 2015 and 2018.
  11. 11. 0 10 20 30 40 50 60 70 Indonesia Brazil Thailand Mexico Korea Russia Greece Canada Portugal UnitedStates Ireland Spain Norway HongKong… Iceland Sweden Latvia Belgium Denmark Finland Poland NewZealand Australia Italy Austria Germany Switzerland Hungary Czech… France Concentration of occupational expectations by country Percentage of students naming 10 most popular occupations % Over half of Indonesian girls anticipate being either a business manager, a doctor or a teacher when they are 30. In Germany and Switzerland much lower levels of concentration are seen.
  12. 12. Labour market signals are failing to reach young people Job title Projected growth (%) Student preference rank* Median annual salary (2018) Accessibility Risk of automation United States Physical therapist assistants 33.10% #29 $58,040 High – associate degree Lower than average Occupational therapy assistants 27.10% #71 $60,220 High – associate degree Lower than average Computer user support specialist 10.60% #229 $50,980 High – associate degree Lower than average Canada Nurse aides and patient service associate 24.50% #33 $ 40,715 High – associate degree Lower than average Veterinary technician 21.50% #32 $ 41,804 High – associate degree Lower than average User support technician & Information systems testing technician 13.70% #158 $ 55,290 High – associate degree Lower than average *Rank is based on ISCO occupation count of 543.
  13. 13. High performers with low expectations “Across OECD countries, approximately one in three disadvantaged teenagers who perform well on the PISA tests does not expect to pursue tertiary education or work in a university-level profession
  14. 14. 0 5 10 15 20 25 30 35 Disadvantaged student Advantaged student Girl Boy to complete tertiary education to be professionals or managers Do not expect: % High performers in PISA who do not have high expectations for their future Percentage of students who do not expect to complete tertiary education amongst high performers (OECD average) Source: PISA 2018 database Notes: High performers are students who attained at least minimum proficiency (Level 2) in the three core PISA subjects and are high performers (Level 4) in at least one subject.
  15. 15. 0 10 20 30 40 50 60 70 80 Thailand UnitedStates Mexico Korea Turkey Singapore Greece Serbia Ireland Canada BosniaandHerzegovina UnitedArabEmirates Qatar Chile Romania Portugal Lithuania Montenegro Brazil B-S-J-Z(China) Argentina Belarus ChineseTaipei Albania NorthMacedonia CzechRepublic SlovakRepublic HongKong(China) Sweden Jordan Belgium Australia Malaysia Spain Norway Japan Bulgaria Kazakhstan France Hungary Macao(China) OECDaverage Estonia UnitedKingdom BruneiDarussalam Slovenia Poland Malta Latvia Netherlands Israel Russia Baku(Azerbaijan) Moldova Uruguay Ukraine Italy NewZealand Denmark Croatia Finland Luxembourg Iceland Switzerland Austria Germany % Percentage of students amongst those who have attained at least minimum proficiency (Level 2) in the three core PISA subjects and are high performers (Level 4) in at least one subject Disadvantaged students Advantaged students High performers who do not expect to complete higher education
  16. 16. 0 10 20 30 40 50 60 Philippines CzechRepublic Japan Switzerland Baku(Azerbaijan) Finland Germany Hungary Latvia Austria Netherlands Thailand Poland Norway Sweden Italy Moldova Turkey Estonia Korea France ChineseTaipei Croatia Belarus Iceland Kazakhstan OECDaverage Montenegro Romania SaudiArabia Denmark UnitedStates HongKong(China) Russia Bulgaria NewZealand Australia Greece B-S-J-Z(China) Lithuania Macao(China) Singapore Slovenia Canada Portugal BruneiDarussalam UnitedKingdom Luxembourg Spain Albania UnitedArabEmirates Chile Belgium VietNam Ireland SlovakRepublic Malaysia NorthMacedonia Israel Malta Uruguay Brazil Qatar Serbia Ukraine Jordan BosniaandHerzegovina Lebanon Colombia Georgia CostaRica Mexico Argentina Indonesia Disadvantaged students Advantaged students% High performers who do not expect to be professionals or managers Source: PISA 2018 database
  17. 17. 0 5 10 15 20 25 30 35 40 45 50 Argentina Lebanon Greece Albania Chile Qatar Turkey Sweden Brazil UnitedKingdom NorthMacedonia Australia BruneiDarussalam Montenegro Serbia France Denmark Ireland Hungary Croatia Belgium UnitedArabEmirates Israel Estonia Portugal Malaysia Malta Luxembourg Slovenia Thailand NewZealand OECDaverage-36 Kazakhstan Iceland Canada Lithuania Baku(Azerbaijan) Italy Germany Russia Latvia Singapore Poland Norway Bulgaria Romania Switzerland Jordan Moldova Belarus SlovakRepublic UnitedStates B-S-J-Z(China) Finland Austria ChineseTaipei Netherlands CzechRepublic Macao(China) Korea HongKong(China) Ukraine Indonesia Japan Percentageoftopperformerswhoexpectacareerinthefield Expect to work as science or engineering professionals Top performers among all students Girls Boys Gender gap in career expectations amongst top performers High performers in mathematics and/or science who aspire to science and engineering professionals
  18. 18. Do teenagers know what they need to do to fulfil their career expectations? One in five young people across the PISA 2018 countries underestimate the levels of education typically required to secure the professional or managerial occupational positions they aspire to
  19. 19. 0 5 10 15 20 25 30 35 40 All students Disadvantaged students Advantaged students % Students with professional or managerial occupational expectations, but not planning to complete tertiary education Source: PISA 2018 database High performing young people from the most disadvantaged backgrounds are, on average, nearly four times less likely to hold high aspirations than similarly performing peers from the most privileged social backgrounds
  20. 20. 0 10 20 30 40 50 60 70 80 Germany Moldova Hungary Austria Morocco Poland Switzerland Latvia Jordan Romania Lebanon Kazakhstan Russia Croatia Italy Uruguay Philippines Luxembourg Belgium(FrenchCommunity) Slovenia NewZealand Iceland VietNam BruneiDarussalam Portugal* Kosovo Malta UnitedKingdom SaudiArabia Denmark Netherlands* Baku(Azerbaijan) Albania NorthMacedonia Bulgaria OECDaverage Japan CzechRepublic Argentina Thailand Greece SlovakRepublic Finland BosniaandHerzegovina Estonia HongKong(China)* ChineseTaipei Lithuania Indonesia Israel Malaysia Sweden Colombia Macao(China) Norway Australia B-S-J-Z(China) DominicanRepublic France Spain UnitedArabEmirates Qatar Belarus Georgia Brazil Ireland Panama Mexico Montenegro Cyprus CostaRica Peru Serbia Korea Chile Turkey UnitedStates* Canada Singapore Ukraine Disadvantaged students Advantaged students % Misalignment: Students with professional or managerial occupational expectations, but not planning to complete tertiary education Source: PISA 2018 database
  21. 21. Effective career guidance encourages students to reflect on who they are and who they want to become… …and to think critically about the relationships between their educational choices and future life
  22. 22. 0 10 20 30 40 50 60 70 80 Iresearchedtheinternetfor informationaboutcareers Icompletedaquestionnaireto findoutaboutmyinterests andabilities. Iresearchedtheinternetfor informationaboutISCED3-5 programmes. Ispoketoacareeradvisorat myschool Iwenttoanorganisedtourin anISCED3-5institution. Iattendedajobshadowingor work-sitevisit Ivisitedajobfair Ididaninternship Ispoketocareeradvisora outsideofmyschool Disadvantaged student Advantaged student% Participation in career development activities OECD average * Source: PISA 2018 database.
  23. 23. 1 1.02 1.04 1.06 1.08 1.1 1.12 1.14 1.16 1.18 1.2 Did an internship I attended a job shadowing or work-site visit I visited a job fair I spoke to a career advisor at my school Odds ratio Effect of participation in career development on positive attitudes towards school Odds ratio of the likelihood of students agreeing with the statement "Trying hard at school will help me get a good job” Source: PISA 2018 database Note: Odds ratio are adjusted for gender, socio-economic status, school type (private/public,class size, urban/rural,staff/student ratio), immigrant background, motivational factors (whether students skipped classes or days) and cognitive potential (whether students repeated a year of study).
  24. 24. 39 40 41 42 43 44 45 46 Ididaninternship* Ispoketocareeradvisora outsideofmyschool* Iattendedajobshadowing orwork-sitevisit* Ivisitedajobfair* Ispoketoacareeradvisor atmyschool* Iwenttoanorganisedtour inanISCED3-5institution Icompleteda questionnairetofindout aboutmyinterestsand abilities* Iresearchedtheinternet forinformationabout careers* Iresearchedtheinternet forinformationabout ISCED3-5programmes* Participated in this activity Did not participate% Concentration of occupational expectations by participation in career development activities * Difference is statistically significant
  25. 25. What to do now
  26. 26. Experimental and quasi-experimental studies published in English in OECD countries (1996-2016) Largely positive Mixed outcomes Largely negative Economic (adult employment & earnings) – 27 studies 67% 33% 0% Educational (academic achievement) – 47 studies 58% 40% 2% Social (well-being, self-esteem, career management skills) – 25 studies 67% 33% 0% Economic, educational and social outcomes linked to career guidance (Hughes et al. 2016). 37
  27. 27. • Starts early (primary) and intensifies around key decision points • Connects classroom learning with future economic lives • Provides easy access to trustworthy labour market information and advice/guidance from well-trained and impartial professionals • Addresses information asymmetries about specific professions and challenges stereotyping • Broadens understanding of the labour market – focusing in particular occupations which are poorly understood and of strategic importance • Targets young people from disadvantaged backgrounds for the greatest levels of intervention • Is experiential with rich and plentiful engagement from the world of work Effective career guidance … 38
  28. 28. • authentic - enabling first-hand encounters • commonplace – volume of encounters matters • valued (relevant) – by young people themselves • varied - different activities can be associated with different outcomes for different types of students • contextualised - by effective career guidance • personalised – in recognition of existing work-related networks and aspirations • begun young – addressing attitudes and expectations from primary schooling Employer engagement to boost young people’s understanding of jobs and careers needs to be… 39 Source: Mann et al. 2018. Employer engagement in Education. EEF.
  29. 29. Find out more about our work at www.oecd.org/pisa  PISA 2018: Insights and Implications  PISA 2018 Results (Volume I): What Students Know and Can Do  PISA 2018 Results (Volume II): Where All Students Can Succeed  PISA 2018 Results (Volume III): What School Life Means for Students’ Lives Take the test: www.oecd.org/pisa/test FAQs: www.oecd.org/pisa/pisafaq PISA indicators on Education GPS: http://gpseducation.oecd.org PISA Data Explorer: www.oecd.org/pisa/data Email: Andreas.Schleicher@OECD.org Thank you

×