Evidence map›Paper›PMID 38624739›Full record

ArticleDisciplinary and interdisciplinary science education research2021

Measuring the long-term effects of informal science education experiences: challenges and potential solutions.

Nancy L Staus, John H Falk, Aaron Price, Robert H Tai, Lynn D Dierking

Abstract read
In one paragraph

Article in Disciplinary and interdisciplinary science education research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Learning science with YouTube videos and the impacts of Covid-19.Disciplinary and interdisciplinary science education research · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nancy L StausSTEM Research Center, Oregon State University, Corvallis, OR USA.ORCID 0000-0001-8415-1006
John H FalkInstitute for Learning Innovation, Portland, OR USA.
Aaron PriceMuseum of Science and Industry, Chicago, IL USA.
Robert H TaiUniversity of Virginia School of Education and Human Development, Charlottesville, VA USA.
Lynn D DierkingCollege of Education, Oregon State University, Corvallis, OR USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the fact that most science learning takes place outside of school, little is known about how engagement in informal science learning (ISL) experiences affects learners' knowledge, skill development, interest, or identities over long periods of time. Although substantial ISL research has documented short-term outcomes such as the learning that takes place during a science center visit, research suggests that the genuine benefits of informal experiences are long-term transformations in learners as they pursue a "cascade" of experiences subsequent to the initial educational event. However, a number of major methodological challenges have limited longitudinal research projects investigating the long-term effects of ISL experiences. In this paper we identify and address four key issues surrounding the critical but challenging area of how to study and measure the long-term effects or impacts of ISL experiences: attribution, attrition, data collection, and analytic approaches. Our objective is to provide guidance to ISL researchers wishing to engage in long-term investigations of learner outcomes and to begin a dialogue about how best to address the numerous challenges involved in this work.

Indexed as

Analytic approachAttributionAttritionInformal science learningLongitudinalMethodologyPerson-centeredProspectiveRetrospectiveVariable-centered

Identifiers

PMID38624739
PMCPMC8090518

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.