Scaffolding active learning with AI tools: an instructional design approach in teaching and learning

The integration of digital tools into education continues to reshape how teaching and learning are delivered, yet many educators struggle to adopt effective approaches that balance technology and pedagogy. This paper presents the design and evaluation of a micro-module to strengthen active learning practices among teachers and lecturers. The module was structured using instructional design frameworks, including SOLO taxonomy, the Zone of Proximal Development (ZPD), and cognitive alignment theory, to ensure clear learning objectives, scaffolded activities, and appropriate assessment methods. Training sessions introduced participants to tools such as Canva and ChatGPT, as well as ready-to-use templates to support lesson preparation. A mixed-methods approach was used, combining survey data with interviews to capture both outcomes and participants’ experiences. Quantitative results showed high ratings for content suitability, instructional strategies, and delivery format, with mean scores above 4.5 on a five-point scale. Interview findings indicated that participants gained confidence in applying active learning techniques and valued the practicality of the resources provided. However, limited prior exposure to certain tools and challenges related to time and infrastructure was noted. The findings suggest that a structured instructional design approach, when combined with accessible e-learning resources, can provide educators with both the confidence and the practical means to apply active learning in their classrooms. This study presents a replicable model for professional development and highlights best practices to support educators in adopting technology-enhanced active learning.