Work

Dr. Scratch 2.0 (CT4ALL): Advanced modes and rubrics for assessing computational thinking in Scratch projects

Year: 2025

Type: software-paper

Abstract: Dr. Scratch 2.0 (CT4ALL) is a web-based service designed to analyze and assess Computational Thinking (CT) in Scratch projects. It employs a client-server architecture with Python’s Django framework and a user friendly interface. Under the CT4ALL project, we have extended the original and widely-used Dr. Scratch to offer four new functionalities (or modes). The Personalized Rubric mode allows customizing CT rubrics. The Batch Assessment mode assesses multiple Scratch projects simultaneously, delivering detailed reports via email. The Comparison mode analyzes and compares CT score in two or more Scratch projects. Finally, the Recommender Assistant guides users in resolving coding issues (or Bad Smells). Together, these modes enable personalizing CT rubrics and identifying coding issues—all with the purpose to help Scratch users in advancing their CT.

Source: SoftwareX

DOI: 10.1016/j.softx.2025.102359

Authors: Gregorio Robles, Guillermo Pons, Daniel Escobar-Morales, Casper Harteveld, Giovanni M. Troiano

Institutions: Universidad Rey Juan Carlos, Northeastern University

Language: English

Topic: Teaching and Learning Programming

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,200

Funders: National Science Foundation, National Sleep Foundation, Ministerio de Ciencia, Innovación y Universidades