The Use of AI, Canva, and Wayground in Diagnostic Assessment for Differentiated Learning in Elementary Schools: A Literature Review

Abstract

This study aims to analyze how AI (Artificial Intelligence), Canva, and Wayground (formerly known as Quizizz) are utilized in diagnostic assessment to support differentiated learning in elementary schools. Using a literature review method, ten relevant studies published between 2023 and 2026 were analyzed and compared to identify differences in research focus, methodology, and findings. These findings were then integrated with theories of assessment and differentiated learning to develop a new synthesis. The comparative analysis revealed that AI is primarily utilized by teachers to generate diverse cognitive diagnostic assessment items and to accelerate the analysis of students' learning difficulties. Canva is employed as a visual medium to identify students' interests and learning styles through non-cognitive creative products such as posters and infographics. Meanwhile, Wayground is used to administer gamified cognitive diagnostic quizzes with real-time data analytics, enabling differentiated student grouping on the same day. In conclusion, the integration of AI, Canva, and Wayground offers a promising strategy for enhancing the quality and responsiveness of diagnostic assessment as a foundation for differentiated learning in elementary schools.