Integrating Scratch and Canva to Foster Digital Literacy in Junior-Secondary Science: A Feasibility Study in Indonesia
Abstract
This study investigated the feasibility of integrating Scratch (block-based programming) and Canva (visual design) to cultivate digital literacy within a junior-secondary science lesson on the human circulatory system in Indonesia. Using a descriptive, cross-sectional design, one intact Grade VIII class (n = 12) at an MTs participated in a single-period implementation that combined brief teacher input with a make-and-explain sequence: students authored a simple Scratch mini-project to externalize mechanism and then produced a concise Canva infographic to communicate key ideas. Data were collected via structured classroom observations, a brief post-lesson teacher interview, and a four-item student questionnaire (binary Yes/No) capturing satisfaction, perceived difficulty, prior exposure to similar media, and perceived improvement in digital literacy; analysis focused on counts and percentages. Results showed high acceptability and usability: 11/12 students (91.7%) reported satisfaction, none reported difficulty (0/12), 8/12 (66.7%) indicated prior exposure, and 11/12 (91.7%) perceived improved digital literacy; observations corroborated sustained on-task behavior, successful navigation of core interface actions, and productive peer support. These patterns suggest that a low-threshold, creation-centered workflow is implementable under ordinary school conditions and pedagogically consistent with active, student-generated learning. The study concludes that explicitly coupling executable modeling (Scratch) with audience-ready visual explanation (Canva) is a promising approach for classroom-level digital-literacy development, while noting limitations of a small, single-class sample and reliance on brief self-reports. Teachers can package lessons as short inputs → templated production → micro-publication to strengthen digital literacy without heavy infrastructure; future research should adopt larger, pre–post or quasi-experimental designs with validated multi-item scales, content assessments, fidelity checks, and comparisons of integrated versus single-tool conditions.
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