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ERIC Number: EJ1298619
Record Type: Journal
Publication Date: 2021
Pages: 28
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0899 3408
EISSN: N/A
Design and Validation of Learning Trajectory-Based Assessments for Computational Thinking in Upper Elementary Grades
Gane, Brian D.; Israel, Maya; Elagha, Noor; Yan, Wei; Luo, Feiya; Pellegrino, James W.
Computer Science Education, v31 n2 p141-168 2021
Background & Context: We describe the rationale, design, and initial validation of computational thinking (CT) assessments to pair with curricular lessons that integrate fractions and CT. Objective: We used cognitive models of CT (learning trajectories; LTs) to design assessments and obtained evidence to support a validity argument. Method: We used the LTs and evidence-centered design to develop assessments that 144 Grade 3 and Grade 4 elementary students completed following the integrated instruction. We analyzed data using multiple psychometric approaches. Findings: The design approach and data analysis suggest that the assessments are well-suited to evaluate students' CT knowledge, skills and abilities across multiple LTs. Implications: We show how to use LTs to design assessments that can yield valid inferences about students' CT competencies; these methods can be adopted and extended by others to create additional assessments that can advance computer science education.
Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Research
Education Level: Elementary Education; Early Childhood Education; Grade 3; Primary Education; Grade 4; Intermediate Grades
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Grant or Contract Numbers: 1932920