G-P17 · TOPIC · lifelong-learningGCRI dossier · service level R0
GCRIFuture of Work and SkillsIn development
Topic dossier · Future of Work and Skills

Lifelong learning

As work changes, people need to learn throughout their working lives, not only at the start. Yet participation in adult learning is lowest among those who need it most: lower-skilled workers, older workers and those in small firms. This page sets out how lifelong learning systems work, who they reach, how participation and outcomes are measured, and what evidence serves the governments, employers and training providers involved.

Systems · around this subjectDesign, not a record

Skills and exposure console

Lifelong learning · Labour market A · Year 2

Gap in data rolesGCRI · Future of Work and Skills

Occupations by exposure

Clerical support86,7660.7SubstituteData operations
Machine operators47,0320.4MixedRobot maintenance
Care workers19,4550.1ComplementUpskill
Analysts27,3290.4ComplementUpskill

Vacancies by skill

050100vacancies per 100 jobseekersDataCareTradesGreenAdmin

Reskilling pathway

  1. Assessskills profile
  2. Matchtarget role
  3. Train20 weeks
  4. Placeemployer
  5. Follow up6 months
Skills and exposure console: the screen's structure, terms and states for Lifelong learning.Placeholder names and illustrative values; a design, not a record or a live system.

Fig.Skills and exposure console. Design wireframe with placeholder names and illustrative values, not a record or a live system.

01In brief

The short answer.

Lifelong learning is learning throughout life in formal, non-formal and informal settings to keep skills current as work changes. Participation is lowest among those who need it most, time and cost are barriers, recognition makes learning count, and training funds and agreements widen access.

02Geography

People and exposure in Southeast Asia.

For lifelong learning, in GCRI's spatial-intelligence reading, the map opens on population density, night lights and true-colour imagery with true colour from NASA GIBS, framed on Southeast Asia; every other NASA layer, live feed and forecast waits in the layer list.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

People and exposure, for this page

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

For lifelong learning, in GCRI's spatial-intelligence reading, the map opens on population density, night lights and true-colour imagery with true colour from NASA GIBS, framed on Southeast Asia; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · GDACS · Copernicus Sentinel-2 L2A · NASA HLS S30Sources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). CC BY 4.0
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Live: GDACS (EC JRC / UN OCHA) Events are indicative, not official warnings.
  • Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer
  • Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • Optional layers (35 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
  • Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026

03The question

Lifelong learning: how the risk develops.

Mid-career transitions and skill maintenance. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

Those who need it least get most

Highly educated workers in large firms receive most training, while lower-skilled and older workers, and those in small firms, receive least.

Mechanism

Time and money are barriers

Adults face costs, lost earnings, caring duties and lack of time, which keep them from training.

Mechanism

Recognition makes learning count

Learning is more valuable when it leads to recognised qualifications or credentials that employers trust.

Mechanism

Employers and unions shape access

Training funds, paid learning leave and collective agreements expand access to learning where they exist and are used.

04Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

TermDefinition
Adult learningEducation and training undertaken by adults after they have left initial education.
Recognition of prior learningAssessing and certifying skills that people have gained outside formal education, such as at work.
Micro-credentialA record of learning outcomes from a short, assessed course of study.
05Indicators

What is measured, and how well.

Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.

IndicatorUnitCadenceSource typeLabel
Adult participation in learningpercent of adults in the last twelve monthsper surveyAdult education surveysREPORTED
Participation gap by skill levelpercentage point differenceper surveyAdult education surveysREPORTED
Adult literacy and numeracy proficiencyscoreper assessmentAdult skills surveysOBSERVED
Public spending on adult learningpercent of GDPannualBudget dataOFFICIAL
Workers with paid training leave rightspercent of employeesper assessmentLabour law and agreementsDECLARED
Micro-credentials recognised in qualification frameworkscountper assessmentQualification authority recordsOFFICIAL
06Canvas

From sources to decisions.

The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.

Pipeline canvas · Lifelong learning as a run graphDesign, not a record
Lifelong learning: from task exposure to reskilling pathwaysOccupations are broken into tasks and scored for exposure; skill gaps are found against vacancies; training pathways are designed with employers; placement and social protection support the transition. Design of the process, not a record of a run.

Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.

07Sources

Where the evidence comes from.

Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.

SourceWhat it givesLicence class
OECD Survey of Adult Skills (PIAAC)Adult literacy, numeracy and problem-solvingPublic results, OECD terms
Eurostat Adult Education SurveyParticipation in adult learningOpen, Eurostat reuse policy
UNESCO Institute for Lifelong Learning Global Report on Adult Learning and EducationGlobal adult learning policy and participationPublic, UNESCO terms
Cedefop skills and training dataVocational training and skills in EuropePublic, EU terms
National qualification framework registersRecognised qualificationsPublic records, licence per authority
08Decisions

Who decides, and what the evidence serves.

Future of Work and Skills prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Who decidesThe questionEvidence this page serves
Education and labour ministriesHow to fund and target adult learningGap analyses; evaluations
Employers and sector bodiesWhich training to provide and co-fundSkills and participation evidence
Qualification authoritiesHow to recognise short courses and prior learningCredential reviews

Outputs this topic produces

  • Participation and access gap analyses
  • Evaluation designs for adult learning programmes
  • Recognition and credential reviews
  • Evidence notes for skills strategies
09Core questions

What researchers ask about adult learning.

  • Who takes part in adult learning, and who does not?
  • Which forms of training lead to better jobs and earnings?
  • How transferable are skills between occupations?
  • How can learning be fitted around work, care and other obligations?
10Mechanisms

Why adult learning is hard.

Skills depreciate when unused and become obsolete when technology changes. Adults face barriers that young students do not: lost earnings while training, care responsibilities, uncertainty about which skills will pay off and, often, past negative experiences of education. Employers under-invest in general skills that workers could take elsewhere.

As a result, participation in adult learning tends to be highest among people who are already well educated and in good jobs, and lowest among those most exposed to change. Training that is short, close to real work and linked to actual vacancies tends to show better results than generic courses.

11Methods and data

Evidence on learning and transitions.

  1. 01

    Programme evaluation

    Comparing outcomes of participants and similar non-participants, using econometrics. Selection into training is hard to control for.

  2. 02

    Skills taxonomies

    Mapping skills between occupations to identify feasible transitions, using economics and development economics. Taxonomies simplify real skills.

  3. 03

    Longitudinal surveys

    Following adults over time to see how learning relates to careers, with social and behavioural science. Such surveys are costly and rare.

  4. 04

    Recognition of prior learning

    Methods for assessing skills gained outside formal education. Recognition must be trusted by employers to matter.

12Methods

How it is studied, and what the methods cannot say.

13Questions

Questions and answers.

What is lifelong learning?
Learning that takes place throughout life, in formal, non-formal and informal settings, to improve knowledge, skills and competences.
Why do lower-skilled adults train less?
Because of costs, lack of time, fewer employer-provided opportunities, past negative experiences of education and lack of information.
What are micro-credentials?
Records of learning outcomes from short courses, which can be stacked or recognised within qualification systems.
Does training help displaced workers?
Some programmes do, especially those linked to employer demand and real vacancies. Many generic programmes show small or no effects. Design matters.
Why do those most at risk train least?
Cost, time, care duties, uncertainty about returns and past experiences of education all weigh more heavily on them, and employers invest less in their training.
Are learning pathways from the platform qualifications?
No. They are research outputs showing feasible skill transitions. Qualifications are awarded by competent education and professional bodies.
What are individual learning accounts?
Schemes that give individuals funds or entitlements to spend on training. Evidence on their effectiveness is mixed and depends on guidance and quality control.
Future of Work and Skills

Bring your expertise to this field.

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