Describing and explaining age, period, and cohort trends in Americans’ vocabulary knowledge

Liying Luo, John Robert Warren

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

For a quarter of a century researchers have been documenting and trying to explain trends in Americans’ vocabulary knowledge using data from the General Social Survey (GSS) and its WORDSUM test. Trends in Americans’ vocabulary knowledge have important practical implications—for example, for educational policy and practice—and speak to the American workforce’s competitiveness in the global knowledge economy. We contribute to this debate by analyzing 1978–2018 GSS data using an improved analytical approach that is consistent with theoretical notions of cohort effects and that permits simultaneously estimating inter-cohort average differences and intra-cohort life-course changes. We find that WORDSUM scores peak around age 35 and gradually decline in older ages; the scores were significantly lower in the 1980s and higher in the late 2000s and 2010s; and the 1940–1954 birth cohorts and the 1965 and later birth cohorts had notably higher and lower scores, respectively, than the expectation based on age and period main effects. We provide new evidence that such cohort differences tend to persist over the life course. Interestingly, the effects of increasing educational attainment and decreasing reading behaviors seemed to cancel out, leading to a relatively flat overall period trend. Trends in television viewing and word obsolescence did not appear to affect age, period, or cohort trends in WORDSUM scores.

Original languageEnglish (US)
Article number31
JournalPopulation Research and Policy Review
Volume42
Issue number3
DOIs
StatePublished - Jun 2023

Bibliographical note

Funding Information:
An earlier version of this paper was presented at the 2014 meetings of the Population Association of America in Boston. We are grateful to James Hodges, participants in Sociology 8090 at the University of Minnesota in Spring 2020, and several anonymous reviewers for providing helpful comments and suggestions. We thank Tom Smith and Jaesok Son at NORC for providing access to the words contained on the General Social Survey’s WORDSUM test battery. Liying Luo acknowledges funding from the National Institutes of Health (R03AG070812). Support for this project has also come from the Minnesota Population Center (University of Minnesota) and the Population Research Institute (Pennsylvania State University), which each receive core funding (P2C HD041023 at Minnesota, P2C HD041025 at Pennsylvania State) from the Eunice Kennedy Shriver National Institute for Child Health and Human Development. However, errors and omissions are the responsibility of the authors. Please direct correspondence to Liying Luo at liyingluo@psu.edu.

Funding Information:
An earlier version of this paper was presented at the 2014 meetings of the Population Association of America in Boston. We are grateful to James Hodges, participants in Sociology 8090 at the University of Minnesota in Spring 2020, and several anonymous reviewers for providing helpful comments and suggestions. We thank Tom Smith and Jaesok Son at NORC for providing access to the words contained on the General Social Survey’s WORDSUM test battery. Liying Luo acknowledges funding from the National Institutes of Health (R03AG070812). Support for this project has also come from the Minnesota Population Center (University of Minnesota) and the Population Research Institute (Pennsylvania State University), which each receive core funding (P2C HD041023 at Minnesota, P2C HD041025 at Pennsylvania State) from the Eunice Kennedy Shriver National Institute for Child Health and Human Development. However, errors and omissions are the responsibility of the authors. Please direct correspondence to Liying Luo at liyingluo@psu.edu.

Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature B.V.

Keywords

  • Age-period-cohort model
  • Cohort pattern
  • Life-course dynamics
  • Vocabulary knowledge
  • WORDSUM

PubMed: MeSH publication types

  • Journal Article

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