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An Application-Oriented Study of Diagnostic Language Assessment in College English Listening Instruction: The Case of the UDig System

Author(s)

Xiaoxiao Yang

Affiliation(s)

Department of Humanity and Law, Fuzhou Technology and Business University, China

Abstract

With the increasing integration of artificial intelligence (AI) and educational digitalization, diagnostic language assessment (DLA) has gained attention as a formative approach that supports learning-oriented instruction. Unlike summative testing, DLA focuses on identifying learners' strengths and weaknesses in specific language subskills and providing actionable feedback for pedagogical decision-making. This paper examines the application of diagnostic language assessment in undergraduate College English listening instruction, taking the AI-assisted UDig system as an illustrative case. Drawing on theories of diagnostic assessment and learning-oriented assessment (LOA), the paper proposes an assessment - instruction interaction framework that embeds diagnostic feedback into listening teaching, remedial support, and learner autonomy development. By reviewing representative diagnostic assessment systems and listening-related research, the study discusses the pedagogical value, implementation pathways, and challenges of applying AI-supported diagnostic assessment in university-level English listening instruction. The paper aims to provide a theoretically grounded and practically feasible reference for integrating diagnostic language assessment into College English teaching in digitally enhanced learning environments.

Keywords

Diagnostic Language Assessment; English Listening; Learning-Oriented Assessment; AI-Assisted Assessment; College English

References

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