The Effectiveness of the ARAI-Land (AR-AI for Wetland Ecosystem) e-Module to Improve Students’ 6 C Skills in Chemistry Learning

Abstract High school chemistry learning increasingly requires instructional designs that support both conceptual understanding and 21st-century competencies. This study examined the effectiveness of ARAI-Land, an augmented reality and artificial intelligence-based e-module contextualized within wetland ecosystems, for teaching reaction rates and developing students’ 6 C skills: critical thinking, creativity, collaboration, communication, character, and citizenship. The study employed an Educational Design Research approach, followed the ADDIE development model, and used a convergent mixed-methods design. The intervention involved 192 Grade 11 students from three public senior high schools in South Kalimantan, Indonesia, representing urban, semi-urban, and rural school contexts. Three classes used ARAI-Land through the SCCrT-STEAM approach, while three control classes received conventional instruction aligned with the same learning objectives. Quantitative data were collected through a reaction-rate learning outcome test and a 6 C skills instrument, while qualitative data were obtained from classroom observations, student reflections, and teacher interviews. The results showed that ARAI-Land significantly improved students’ reaction-rate learning outcomes, with high N-Gain scores and large effect sizes. The e-module also supported the development of 6 C skills, particularly character and citizenship, through ecological contextualization, collaborative inquiry, and reflective learning tasks. The findings suggest that the effectiveness of ARAI-Land lies not merely in the use of AR and AI, but in the pedagogical integration of visualization, adaptive feedback, SCCrT-STEAM activities, and locally meaningful wetland contexts. This study contributes to science education and technology by offering an Eco-Contextualized TPACK model for sustainability-oriented chemistry learning.