extended · article · 2026

Does Rating Time Predict Illusory Halo? A Mixture Rasch Facets Analysis of Halo Effects in Onscreen Assessments

Kuan-Yu Jin; Thomas Eckes

Halo effects refer to a persistent rater error posing a significant threat to the validity and fairness of assessments involving human raters. This research introduces a novel approach to analyzing halo effects by considering rating times recorded automatically in technology-based, online, or onscreen assessments as an additional data source. For this purpose, we propose the mixture Rasch facets model for halo with rating time. Utilizing Bayesian parameter estimation methods, we applied the model to a real dataset from a large-scale Chinese writing assessment. We found that rating time predicted illusory halo, such that longer rating times were associated with a greater likelihood of observing halo effects. Compared to traditional models, considering rating time as an additional variable resulted in better data–model fit and preserved the integrity of the latent scale, maintaining the in...