Katalog Plus
Bibliothek der Frankfurt UAS
Bald neuer Katalog: sichern Sie sich schon vorab Ihre persönlichen Merklisten im Nutzerkonto: Anleitung.
Dieses Ergebnis aus ERIC kann Gästen nicht angezeigt werden.  Login für vollen Zugriff.

A Generalized Estimating Equations Approach to Investigate Predictors of Teacher Candidates' Views of Coding

Title: A Generalized Estimating Equations Approach to Investigate Predictors of Teacher Candidates' Views of Coding
Language: English
Authors: Belland, Brian R. (ORCID 0000-0002-8925-9152); Kim, Chanmin (ORCID 0000-0001-9383-8846); Zhang, Anna Y. (ORCID 0000-0003-0609-4741); Lee, Eunseo (ORCID 0000-0003-2948-3328)
Source: ACM Transactions on Computing Education. Jun 2023 23(2).
Availability: Association for Computing Machinery. 2 Penn Plaza Suite 701, New York, NY 10121. Tel: 800-342-6626; Tel: 212-626-0500; Fax: 212-944-1318; e-mail: acmhelp@acm.org; Web site: http://toce.acm.org/
Peer Reviewed: Y
Page Count: 23
Publication Date: 2023
Sponsoring Agency: National Science Foundation (NSF)
Document Type: Journal Articles; Reports - Evaluative
Education Level: Higher Education; Postsecondary Education; Early Childhood Education
Descriptors: Predictor Variables; Preservice Teachers; Student Attitudes; Programming; Early Childhood Teachers; Technology Integration; Computer Science Education; Robotics; Prior Learning; Statistical Analysis
DOI: 10.1145/3587163
ISSN: 1946-6226
Abstract: This article reports the analysis of data from five different studies to identify predictors of preservice, early childhood teachers' views of (a) the nature of coding, (b) integration of coding into preschool classrooms, and (c) relation of coding to fields other than computer science (CS). Significant changes in views of coding were predicted by time, prior robot programming experience, and perceptions of the value of coding. Notably, prior programming knowledge and positive perceptions of mathematics predicted decreases in views of coding from pre- to post-survey.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1393216
Database: ERIC