Decision-making under risk often deviates from normative benchmarks due to cognitive limitations and difficulties in processing probabilistic information. This study investigates the effectiveness of Information Processing Guidance (IPG) in enhancing decision-making performance and examines how task difficulty shapes both decision quality and the impact of guidance.

Using a controlled laboratory experiment, we test whether IPG reduces deviations from Bayesian-optimal choices in repeated investment tasks. Participants were randomly assigned to one of three between-subjects treatments—a Baseline condition without guidance, a continuous IPG condition, and a withdrawn guidance condition (IPG-W)—and completed 32 decision rounds involving tasks of varying difficulty.

The results show that IPG significantly improves decision quality, with guided participants committing fewer errors relative to those in the Baseline. Meanwhile, decision performance in the withdrawn guidance condition lies between the Baseline and continuous IPG conditions and is not statistically distinguishable from either. Although higher task difficulty leads to more decision errors overall, the performance-enhancing effect of IPG remains stable across difficulty levels. This study contributes to the literature on decision support and learning under risk by demonstrating that information processing guidance can durably improve decision-making quality, even in cognitively demanding tasks.