Enhancing Students’ Motivation in Algorithm Learning through Web-Based Visual Diagramming Tools: An ARCS Model Analysis

Abstract

Learning algorithms and flowchart design in secondary informatics education often lack engaging instructional strategies that effectively foster students’ learning motivation. However, limited studies have examined how web-based visual diagramming tools influence students’ motivational dimensions in algorithm learning within the ARCS framework. This study provides empirical evidence on how web-based diagramming tools enhance motivational engagement in algorithm learning. A qualitative descriptive design was employed involving 36 tenth-grade students. The findings reveal that visual interaction through draw.io significantly increased students’ attention and engagement, improved contextual relevance of learning tasks, strengthened learners’ confidence in constructing flowcharts independently, and generated positive learning satisfaction. These findings extend the application of the ARCS model within web-based informatics instruction and highlight the potential of digital visual tools to enhance affective learning outcomes. Integrating digital visual media into informatics instruction can serve as an effective strategy to enhance students’ motivation and engagement in computational learning