Supplementary Materials for: Digital Prompting in Education: A Design Framework and Bibliometric Analysis

Digital prompts are a widely used instructional method to support student learning. However, the diversity of research topics and the variety of ways in which prompts are designed and labeled result in terminological inconsistencies (e.g., jingle-jangle fallacies) and make it difficult to integrate similar research. Additionally, the rise of artificial intelligence has introduced new meanings to the term “prompt,” threatening the discoverability of research on digital prompting interventions. An updated analysis of recent records showed that in 2025, 19% of all publications using the term “prompt” referred to AI-related contexts. Therefore, this bibliometric analysis of 1,238 publications provides a systematic overview of how digital prompts are labeled and how well the research field is integrated. We identified 283 distinct prompt labels, either referring to the content of the prompt or its presentation format. Our findings highlight that a few prompt types such as metacognitive prompts, self-explanation prompts, and question prompts dominate the field, while the majority is used inconsistently or idiosyncratically. Network analyses revealed limited integration across the field, with metacognitive prompting emerging as a central research area. We provide concrete recommendations to improve the visibility and integration of this research field, including the use of standardized terminology in metadata, multi-level labeling practices, and engagement with conceptually similar prompting interventions.

Prompting is a prominent type of instructional intervention used to support student learning. Prompts are brief hints, questions, or requests that are integrated into the learning context to help students recall and execute their knowledge, strategies, and skills. An advanced way to deliver prompts is through digital technology. Commentators have noted the great variety in the way prompts are designed and labeled, but a comprehensive overview and understanding of the diversity of the field remains limited. To address this issue, the present study aims to map the research field on digital prompting interventions, with a focus on providing an overview of how the term prompting is used in the context of digital (educational) interventions and how the field is integrated.

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.