The Effectiveness of the Algo-Art Module Based on Computational Thinking for Learning Painting Art Expression in Secondary Schools

Abstract

The integration of computational thinking elements in Visual Arts Education is a teaching and learning approach that incorporates computational thinking into Visual Arts Education. This study aims to identify the effectiveness of integrating computational thinking elements in the Visual Arts Education subjects specifically for the Form Four painting expression topic. This research employs a quantitative methodology with a quasi-experimental design. The research location is a national secondary school in the Petaling Perdana district, Selangor. A total of 70 students were selected as research samples through purposive sampling, with 35 students assigned to the control group and the remaining 35 students assigned to the treatment group. Data collection was conducted through tests administered twice: a pre-test and a post-test. The research instrument was based specifically a painting practical assessment using the Malaysian Certificate of Education (SPM) examination format. The Independent Samples t- test at the pre-test stage showed no significant difference in mean scores between the control group and the treatment group. However, at the post-test stage, the Independent Samples t- test found that the mean score of the treatment group was significantly higher than the control group. These findings demonstrate the effectiveness of the computational thinking- based ALGO-ART module in enhancing painting expression skills among secondary school students. Consequently, the ALGO-ART module has brought innovation to visual arts teaching and learning methods by integrating computational thinking elements.