The Benefits of Longitudinal Data and Multilevel Modeling to Measure Change in Adventure Education Research

Autor/inn/en	Shirilla, Paul; Solid, Craig; Graham, Suzanne E.
Titel	The Benefits of Longitudinal Data and Multilevel Modeling to Measure Change in Adventure Education Research
Quelle	In: Journal of Experiential Education, 45 (2022) 1, S.88-109 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Shirilla, Paul)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1053-8259
DOI	10.1177/10538259211027595
Schlagwörter	Longitudinal Studies; Hierarchical Linear Modeling; Adventure Education; Educational Research; Research Methodology; Research Design; Urban Schools; Middle School Students; Interpersonal Competence; Skill Development; Change; Social Skills Rating System + Suchen Sie Ihr Suchwort? Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Adventure pedagogics; Abenteuerpädagogik; Erlebnispädagogik; Bildungsforschung; Pädagogische Forschung; Research method; Forschungsmethode; Forschungsdesign; Urban area; Urban areas; School; Schools; Stadtregion; Stadt; Schule; Middle school; Middle schools; Student; Students; Mittelschule; Mittelstufenschule; Schüler; Schülerin; Interpersonale Kompetenz; Kompetenzentwicklung; Qualifikationsentwicklung; Wandel
Abstract	Background: A common critique of adventure education research methodology is the overreliance on pre-/post-study designs to measure change. Purpose: This paper compares and contrasts two methods of data analysis on the same adventure education data set to show how these distinct approaches provide starkly different results and interpretation. Methodology/Approach: Using secondary data analysis, we employ a longitudinal data set of the social skill development of urban middle school students who participated in an adventure education program over the course of three academic years. First, change was assessed using a pre-/post-design by a traditional analysis of variance (ANOVA). Next, change was assessed with a six-wave, longitudinal design using multilevel modeling. Findings/Conclusions: Results show that the multilevel modeling approach revealed nonlinear change in the social skill development of middle school students, resulting in more accurate, nuanced estimation of change in social skill development than the ANOVA approach. Implications: The use of longitudinal data and multilevel modeling can be a useful methodological approach and statistical tool for adventure education researchers to not only address the criticisms of quantitative research in adventure education, but more importantly, provide a more thorough understanding of the impact of adventure education on human development. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01