From comic panels to clinical practice: data comics as a learning analytics tool in nursing simulation

Abstract In healthcare education, it is important for nursing students to be able to reflect on their performance in high-fidelity clinical simulations in order to develop key skills. Learning Analytics (LA) offers opportunities for data-driven reflection by providing visual representations of educational experiences. While many LA tools rely on data visualisations to communicate insights, these are often difficult for students to interpret, limiting their effectiveness. Despite these challenges, there is limited research exploring alternative and potentially more accessible formats—such as data comics, a narrative visualisation technique that integrates data with the structure of traditional comic strips—to represent and communicate insights from learner data in a more engaging way. This study addresses that gap through a qualitative analysis of nursing students’ perceptions of data comics as reflective tools, focusing on: (i) support for student reflection, (ii) advantages and limitations, and (iii) concerns about their use in healthcare education. Third-year nursing students who participated in a simulation were interviewed and asked to reflect on personalised data comic prototypes generated from their multimodal data using a mix of human input and AI methods. The results indicated that while data comics present an engaging and accessible form of reflective visualisation, considerations need to be made regarding the designs to ensure that they are appropriate for the target audience and do not oversimplify the simulation experience. These findings indicate that data comics should not act as a replacement for conventional visualisations but rather serve as supplementary material to communicate contextual information or aid in interpretation of visualisations.