Exploring Elementary Teachers' Perceptions of Data Science and Curriculum Design through Professional Development

Autor/inn/en	Herro, Danielle; Madison, Matthew; Arastoopour Irgens, Golnaz; Hirsch, Shanna; Abimbade, Oluwadara; Adisa, Oluwajoba
Titel	Exploring Elementary Teachers' Perceptions of Data Science and Curriculum Design through Professional Development
Quelle	In: Journal of Technology and Teacher Education, 30 (2022) 4, S.493-525 (33 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1059-7069
Schlagwörter	Elementary School Teachers; Data Science; Curriculum Design; Faculty Development; Teacher Improvement; STEM Education; Multiple Literacies; Teacher Attitudes; Rural Schools; Self Efficacy; Teacher Collaboration; Cooperative Planning; Thinking Skills; Theory Practice Relationship; Educational Research; Partnerships in Education + Suchen Sie Ihr Suchwort? Elementary school; Teacher; Teachers; Grundschule; Volksschule; Lehrer; Lehrerin; Lehrende; Lehrplangestaltung; STEM; Lehrerverhalten; Rural area; Rural areas; School; Schools; Ländlicher Raum; Schule; Schulen; Self-efficacy; Selbstwirksamkeit; Lehrerkooperation; Denkfähigkeit; Theorie-Praxis-Beziehung; Bildungsforschung; Pädagogische Forschung; Hochschulpartnerschaft
Abstract	Data science and computational thinking (CT) skills are important STEM literacies necessary to make informed daily decisions. In elementary schools, particularly in rural areas, there is little instruction and limited research towards understanding and developing these literacies. Using a Research-Practice Partnership model (RPP; Coburn & Penuel, 2016) we conducted multimethod research investigating nine elementary teachers' perceptions of data science and related curriculum design during professional development (PD). Connected Learning theory, enhanced with Universal Design for Learning, guided ways we assisted teachers in designing the data science curriculum. Findings suggest teachers maintained high levels of interest in data science instruction and CT before and after the PD and increased their self-efficacy towards teaching data science. A thematic analysis revealed how a data science framework guided curriculum design and assisted teachers in defining, understanding, and co-creating the curriculum. During curriculum design, teachers shared the workload among partners, made collaborative design choices, integrated differentiation strategies, and felt confidence towards teaching data science. Identified challenges included locating data sets and the complexity of understanding data science and related software. This study addresses the research gap in data science education for elementary teachers and assists with successful strategies for data science PD and curricular design. (As Provided).
Anmerkungen	Association for the Advancement of Computing in Education. P.O. Box 719, Waynesville, NC 28786. Tel: 828-246-9558; Fax: 828-246-9557; e-mail: info@aace.org; Web site: http://www.aace.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01