New Perspectives in Science Education

Biochemistry remains one of the most conceptually demanding disciplines in the life sciences. Metabolic biochemistry requires students to integrate complex pathways and interpret outcomes when regulation fails—tasks that are particularly challenging for multilingual learners. Traditional didactic delivery and recall-based assessment often promote surface learning rather than conceptual transfer [1]. To address this challenge, this project reconceptualises assessment as an experiential learning process. Through AI-assisted infographic design, students visualise enzyme defects, metabolic imbalances, and therapeutic strategies, iteratively refining prompts to integrate scientific accuracy with creative representation. Learning is evaluated using a rubric assessing conceptual understanding, visual communication, and reflective insight, while reflection logs capture how understanding develops through prompt revision and feedback. Guided by Kolb’s Experiential Learning Cycle, students engage in concrete experience, reflective observation, conceptual abstraction, and active experimentation [2]. Grounded in social constructivism and connectivism, the approach positions AI as a collaborative learning partner and emphasises knowledge co-construction through dialogue and reflection [3]. Building on evidence for visualising complex metabolic networks [4] and for active and flipped learning in medical biochemistry [5], this project presents a sustainable, research-informed model that transforms assessment into active, reflective, and measurable learning.