Determinants of Adult Education and Training Participation in the United States: A Machine Learning Approach

Abstract

In response to recent shifts in the global economy, there has been a growing academic interest in adult education and training (AET), enabling adults to meet the ever-changing demands of the workforce. However, empirical findings offer nuanced evidence on the most influential factors among various aspects. This study aims to reexamine the previously highlighted determinants of job-related AET participation using the random forest classifiers technique. The data is drawn from the 2017 U.S. Program for the International Assessment of Adult Competencies, where we selected 1,334 respondents with work experience in the last 12 months. Our findings suggest that age and skills use at work were found to be the most important factors for formal AET, whereas skills use at work and organization size were the most significant factors for nonformal AET. Our results emphasize the critical role of skills utilization and organizational support in working adults’ participation in AET.

Keywords

adult education and training participation working adults machine learning random forest classifiers PIAAC

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References

AIR PIAAC Team. (2019). What you need to consider before working with PIAAC data . http://piaacgateway.com/s/WorkingWithPIAACData_updated-092816.pdf

Aspin

D. N.

Chapman

Y. D.

(2007). Values education and lifelong learning: Principles, policies, programmes. Springer.

Billett

(2010). The perils of confusing lifelong learning with lifelong education. International Journal of Lifelong Education, 29(4), 401–413. https://doi.org/10.1080/02601370.2010.488803

Boeren

Nicaise

Baert

(2010). Theoretical models of participation in adult education: The need for an integrated model. International Journal of Lifelong Learning, 29(1), 45–61. https://doi.org/10.1080/02601370903471270

Breiman

(2001). Random forests. Machine Learning, 45(1), 5–32. https://doi.org/10.1023/A:1010933404324

Brown

Bimrose

(2018). Drivers of learning for the low-skilled. International Journal of Lifelong Education, 37(2), 151–167. https://doi.org/10.1080/02601370.2017.1378934

CEC. (2000). A memorandum on lifelong learning (Commission Staff Working Paper). European Commission.

CEDEFOP. (2016). Unequal access to job-related learning: Evidence from the adult education survey (Research Paper No. 52). Publications Office of the European Union. https://data.europa.eu/doi/10.2801/219228.

Choi

Robinson

Maulik

Wehde

(2020). What matters the most? Understanding individual tornado preparedness using machine learning. Natural Hazards, 103, 1183–1200. https://doi.org/10.1007/s11069-020-04029-1

10.

Clochard

Westerman

(2020). Understanding the incumbent worker’s decision to train: The challenges facing less-educated workers (MIT Work of the Future Working Paper 9-2020). MIT Industrial Performance Center.

11.

Cummins

P. A.

Yamashita

Arbogast

(2018). An examination of PIAAC data for unemployed adults aged 45–74 . https://piaac.squarespace.com/s/CumminsYamashita-Arbogast_2018.pdf

12.

Desjardins

(2015). Participation in adult education opportunities: Evidence from PIAAC and policy trends in selected countries (Background paper for EFA Global Monitoring Report 2015). UNESCO.

13.

Desjardins

(2019). The labor market benefits of adult education from a global perspective. International Review of Education, 65, 955–973. https://doi.org/10.1007/s11159-019-09813-1

14.

Desjardins

Rubenson

(2011). An analysis of skill mismatch using direct measures of skills (OECD Education Working Papers No. 63). OECD Publishing. https://doi.org/10.1787/5kg3nh9h52g5-en.

15.

Dibra

Kashahu

Bushati

Priku

(2014). Learning among adults. European Scientific Journal, 10(13), 498–506. https://doi.org/10.19044/esj.2014.v10n13p%25p

16.

Egglestone

Stevens

Jones

Aldridge

(2018). Adult participation in learning survey 2017 (Learning and Work Institute Report). UK Department of Education.

17.

Eurostat. (2016). Classification of learning activities (CLA): Manual. Publications Office of the European Union.

18.

Findsen

Formosa

(2016). International perspectives on older adult education: Research, policy and practice. Springer. https://doi.org/10.1007/978-3-319-24939-1.

19.

Fouarge

Schils

(2009). The effect of early retirement incentives on the training participation of older workers. Review of Labour Economics and Industrial Relations, 23(1), 85–109. https://doi.org/10.1111/j.1467-9914.2008.00441.x

20.

Grinyer

P. H.

Yasai-Ardekani

(1981). Strategy, structure, size and bureaucracy. Academy of Management Journal, 24(3), 471–486. https://doi.org/10.5465/255569

21.

Ioannidou

Parma

(2022). Risk of job automation and participation in adult education and training: Do welfare regimes matter? Adult Education Quarterly, 72(1), 84–109. https://doi.org/10.1177/07417136211026635

22.

Jarvis

(2010). Adult education and lifelong learning: Theory and practice (4th ed.). Routledge. https://doi.org/10.4324/9780203718100.

23.

Kalenda

Kočvarová

Vaculíková

(2020). Determinants of participation in nonformal education in the Czech Republic. Adult Education Quarterly, 70(2), 99–118. https://doi.org/10.1177/0741713619878391

24.

Krenzke

VanDeKerckhove

Thornton

Diaz-Hoffmann

Hogan

Mohadjer

Yamamoto

Khorramdel

Ali

(2019). U.S. Program for the International Assessment of Adult Competencies (PIAAC) 2012/2014/2017: Main study, national supplement, and PIAAC 2017 technical report (NCES 2020-224). U.S. Department of Education. National Center for Education Statistics.

25.

Massing

Gauly

(2017). Training participation and gender: Analyzing individual barriers across different welfare state regimes. Adult Education Quarterly, 67(4), 266–285. https://doi.org/10.1177/0741713617715706

26.

Melacarne

Nicolaides

(2019). Developing professional capability: Growing capacity and competencies to meet complex workplace demands. New Directions for Adult and Continuing Education, 163, 37–51. https://doi.org/10.1002/ace.20340

27.

OECD. (2013). OECD skills outlook 2013: First results from the survey of adult skills. OECD Publishing. http://dx.https://doi.org/10.1787/9789264204256-en

28.

OECD. (2016). Skills matter: Further results from the survey of adult skills. OECD Publishing. http://dx.https://doi.org/10.1787/9789264258051-en

29.

OECD. (2019). Getting skills right: Future-ready adult learning systems. OECD Publishing. https://doi.org/10.1787/9789264311756-en

30.

Pedregosa

Varoquaux

Gramfort

Michel

Thirion

Grisel

Blondel

Prettenhofer

Weiss

Dubourg

Vanderplas

Passos

Cournapeau

Brucher

Perrot

Duchesnay

(2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12(85), 2825–2830. http://jmlr.org/papers/v12/pedregosa11a.html

31.

Prasad

A. M.

Iverson

L. R.

Liaw

(2006). Newer classification and regression tree techniques: Bagging and random forests for ecological prediction. Ecosystems, 9, 181–199. https://doi.org/10.1007/s10021-005-0054-1

32.

Punksungka

Yamashita

Helsinger

Karam

Cummins

Kramer

(2021). Re-examining adult education and training participation by education, literacy, gender, and race/ethnicity in the U.S. Journal of Adult and Continuing Education, 28(2), 634–657. https://doi.org/10.1177/14779714211049261

33.

Roosmaa

E.-L.

Saar

(2017). Adults who do not want to participate in learning: A cross-national European analysis of their perceived barriers. International Journal of Lifelong Education, 36(3), 254–277. https://doi.org/10.1080/02601370.2016.1246485

34.

Ross-Gordon

J. M.

Rose

A. D.

Kasworm

C. E.

(2017). Foundations of adult and continuing education. Jossey-Bass.

35.

Rubenson

(2011). Adult learning and education. Elsevier.

36.

Rubenson

Desjardins

(2009). The impact of welfare state regimes on barriers to participation in adult education: A bounded agency model. Adult Education Quarterly, 59(3), 187–207. https://doi.org/10.1177/0741713609331548

37.

Schmidt

S. W.

(2007). The relationship between satisfaction with workplace training and overall job satisfaction. Human Resource Development Quarterly, 18(4), 481–498. https://doi.org/10.1002/hrdq.1216

38.

Tikkanen

Nissinen

(2018). Drivers of job-related learning among low-educated employees in the Nordic countries. International Journal of Lifelong Education, 37(5), 615–632. https://doi.org/10.1080/02601370.2018.1554720

39.

Watkins

K. E.

Marsick

V. J.

(2014). Adult education and human resource development: Overlapping and disparate fields. New Horizons in Adult Education and Human Resource Development, 26(1), 42–54. https://doi.org/10.1002/nha3.20052

40.

White

(2012). Modelling the ‘learning divide’: Predicting participation in adult learning and future learning intentions 2002 to 2010. British Educational Research Journal, 38(1), 153–175. https://doi.org/10.1080/01411926.2010.529871

41.

Widany

Christ

Gauly

Massing

Hoffmann

(2019). The quality of data on participation in adult education and training: An analysis of varying participation rates and patterns under consideration of survey design and measurement effects. Frontiers in Sociology, 4(71), 1–18. https://doi.org/10.3389/fsoc.2019.00071

42.

Yamashita

Cummins

P. A.

Millar

R. J.

Sahoo

Smith

T. J.

(2019). Associations between motivation to learn, basic skills, and adult education and training participation among older adults in the USA. International Journal of Lifelong Education, 38(5), 538–552. https://doi.org/10.1080/02601370.2019.1666927