Information-Reduction Ability Assessment in the Context of Complex Problem-Solving

In this era with an increasing overabundance of information, the ability to distill relevant information, i.e., "information reduction", is becoming more crucial to daily functioning. However, the fact that information reduction is most prominent in complex situations poses challenges for measuring and quantifying this ability. Existing assessments tend to suffer from either too little complexity, compromising ecological validity, or too much complexity, which makes distinguishing and measuring information-reduction behavior difficult. To address this gap in the literature, our study developed a novel assessment tool, the Little Monster Clinic (LMC), designed to capture the information-reduction process within complex problem-solving scenarios. Following the classic complex problem-solving (CPS) framework, LMC simulates real-world medical situations and provides a sufficiently complex task for assessing information-reduction ability. We recruited 303 students to validate our tool and identified six key indicators for information reduction, which demonstrated a high degree of internal consistency (α = 0.83). Structural validity from the confirmatory factor analysis (CFA) supported a one-factor model of information reduction based on the extracted indicators (χ2 = 14.872, df = 5, χ2/df = 2.774, CFI = 0.989, TLI = 0.967, RMSEA = 0.077, SRMR = 0.024). The significant correlation (r = 0.43, p < 0.01) between LMC and Genetics Lab demonstrated its criterion-related validity. Furthermore, exploratory analysis highlighted the importance of identifying key relevant information during the process of information reduction. These findings lend support to both the theoretical foundation and practical applications of information-reduction assessment.