Design and validation of learning trajectory-based assessments for computational thinking in upper elementary grades. Issue 2 (3rd April 2021)

• Record Type: Journal Article
• Authors: Gane, Brian D.; Israel, Maya; Elagha, Noor; Yan, Wei; Luo, Feiya; Pellegrino, James W.
• Is Part Of: Computer science education. Volume 31:Issue 2(2021)
• Page Start: 141
• Page End: 168
• Publication Date: 2021-04-03
• Subjects: Learning trajectories -- assessment -- computational thinking -- evidence-centered design -- validity -- elementary; Computer science -- Study and teaching -- Periodicals; 004
• DOI: 10.1080/08993408.2021.1874221
• Languages: English
• ISSNs: 0899-3408

Abstract

ABSTRACT: 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.