Digital reading comprehension assessment in English language education: a systematic review

Swift progress in information technology has aroused more interest in reading texts on digital platforms. A range of research has explored comprehension processes across print and digital formats, along with the distinct features of each medium. However, no prior systematic effort has synthesized and evaluated the tools used to measure English learners’ digital reading comprehension (DRC), a crucial competency in today’s AI-driven workforce. This systematic literature review investigates how DRC is assessed in English language education, synthesizing theoretical frameworks, types of assessment instruments, and presentation modalities found in digital texts. Twenty-four (N = 24) English-language peer-reviewed publications (2015–2025) within the educational technology context, indexed in Web of Science and Scopus, were included. The analysis revealed four theoretical categories: cognitive processing models, cognitive load theories, interactive technology-integrated models, and multidimensional frameworks, with Kintsch’s Construction-Integration model being the most prominent. Assessment instruments comprise both objective measurements (e.g. reading comprehension tests) and subjective measurements (e.g. self-assessments). Multimodal presentations are prevalent, incorporating annotations, highlights, and hyperlinks. The findings underscore the need for cohesive theoretical frameworks and process-oriented assessment instruments that move beyond traditional testing. Digital literacy training for educators is essential to meet the varied needs of English language learners in digital contexts.