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Many language proficiency tests include group oral assessments involving peer interaction. In such an assessment, examinees have to discuss a common topic with others. Human raters score each examinee's spoken performance on specially designed criteria. However, measurement models for analyzing group assessment data usually assume local person independence and thus fail to consider the impact of peer interaction on the assessment outcomes. This research advances an extended Rasch facets model for group assessment (RFM-GA), accounting for local person dependence. We used a real dataset to illustrate the efficiency of the new model. The discussion focuses on the model’s usefulness for measuring oral language proficiency, practical implications, and future research perspectives.