AI-supported assessment in online learning: a Chinese- and English-language systematic scoping review and evidence map of computational approaches, assessment-use impact, and technical validation

A systematic scoping review and evidence map examined the application of Artificial Intelligence (AI) in online learning assessments across both Chinese- and English-language publications. The review focused on computational approaches, the impact of AI on assessment use, and technical validation. It highlights that while AI can support feedback, diagnosis, prediction, intervention, and scoring, its technical performance does not inherently define how AI-generated outputs should be interpreted or utilized as assessment evidence.

This review underscores the increasing integration of AI into educational assessment systems, particularly in online learning environments. It is critical for organizations to understand the current state of AI application in this domain, acknowledging that technical performance alone is insufficient for establishing the evidentiary value or interpretability of AI-generated assessments.

AI is actively employed in online learning to facilitate various assessment functions, including providing feedback, diagnosing learning gaps, predicting performance, intervening with support, and automated scoring.

Forward consideration, not a verified fact.