Digital Prompting in Education: A Design Framework and Bibliometric Analysis

Abstract Digital prompts are brief instructional cues designed to guide student learning. The variety of ways in which prompts are designed and labelled across education result in conceptual and terminological inconsistencies that make it difficult to integrate research findings. Furthermore, artificial intelligence (AI) has introduced a new dominant meaning of the term “prompt” that complicates the discoverability of relevant literature. To address these challenges, we propose a guiding framework that conceptualizes digital prompts as dynamic scaffolds and characterizes their instructional design through a typology of content, function, presentation, and source. Using a bibliometric approach, we analyzed 1,238 publications to examine how well this framework captures the structure of the field. We identified 283 distinct prompt labels, most of which were used in only one publication. The mapping of these labels onto the proposed typology led to a refined understanding of prompt design characteristics. Furthermore, we examined co-occurrences between labels and identified research topics and citation practices. The resulting patterns revealed two major research clusters centered on metacognitive and self-explanation prompts, which structure much of the literature. However, these two clusters lack integration. We show how these separate research traditions can be integrated into our framework of dynamic scaffolding through prompts. Finally, we demonstrate how our typology of prompt types can foster greater terminological coherence and improve search strategies in the age of AI.