Using HLM to Determine a STEM Programs Impact on Middle School Academic Achievement

Autor/inn/en	Chine, Danielle R.; Larwin, Karen H.
Titel	Using HLM to Determine a STEM Programs Impact on Middle School Academic Achievement
Quelle	In: International Journal of Research in Education and Science, 8 (2022) 1, S.1-17 (18 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Chine, Danielle R.) ORCID (Larwin, Karen H.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2148-9955
Schlagwörter	Middle Schools; STEM Education; Instructional Effectiveness; Program Development; Hierarchical Linear Modeling; Outcomes of Education; Measurement; Grade 5; Grade 6; Grade 7; Grade 8; Middle School Teachers; State Policy; Achievement Tests; Ohio + Suchen Sie Ihr Suchwort? Middle school; Mittelschule; Mittelstufenschule; STEM; Unterrichtserfolg; Programmplanung; Lernleistung; Schulerfolg; Messverfahren; School year 05; 5. Schuljahr; Schuljahr 05; School year 06; 6. Schuljahr; Schuljahr 06; School year 07; 7. Schuljahr; Schuljahr 07; School year 08; 8. Schuljahr; Schuljahr 08; Middle schools; Teacher; Teachers; Lehrer; Lehrerin; Lehrende; Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen
Abstract	Hierarchical linear modeling (HLM) has become an increasingly popular multilevel method of analyzing data among nested datasets, in particular, the effect of specialized academic programming within schools. The purpose of this methodological study is to demonstrate the use of HLM to determine the effectiveness of STEM programming in an Ohio middle school. This longitudinal study analyzes potential moderators of gender, socioeconomic status, student race, and attendance rate along with state test scores to quantify achievement. HLM determined integrated STEM education had a significant, positive effect on achievement in math and science combined (students scoring 31.8 points higher on average) and science achievement (students scoring 38.2 points higher on average) compared to traditional education students, respectively. There were little to no interaction effects determined between STEM participation and student factors. This demonstrates HLM as a powerful statistical tool for quantifying the impact of academic programming on student achievement. (As Provided).
Anmerkungen	International Society for Technology, Education, and Science. e-mail: ijresoffice@gmail.com; Web site: https://www.ijres.net/index.php/ijres
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01