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The ability to recognize key causal models across situations is associated with expertise. The acquisition of schema-governed category knowledge of key causal models may underlie this ability. In an experimental study ( n = 183), we investigated the effects of promoting the construction of schema-governed categories and how an enhanced ability to recognize the key causal models relates to performance in complex problem-solving tasks that are based on the key causal models. In a 2 × 2 design, we tested the effects of an adapted version of an intervention designed to build abstract mental representations of the key causal models and a tutorial designed to convey conceptual understanding of the key causal models and procedural knowledge. Participants who were enabled to recognize the underlying key causal models across situations as a result of the intervention and the tutorial (i.e., causal sorters) outperformed non-causal sorters in the subsequent complex problem-solving task. Causal sorters outperformed the control group, except for the subtask knowledge application in the experimental group that did not receive the tutorial and, hence, did not have the opportunity to elaborate their conceptual understanding of the key causal models. The findings highlight that being able to categorize novel situations according to their underlying key causal model alone is insufficient for enhancing the transfer of the according concept. Instead, for successful application, conceptual and procedural knowledge also seem to be necessary. By using a complex problem-solving task as the dependent variable for transfer, we extended the scope of the results to dynamic tasks that reflect some of the typical challenges of the 21st century.

As a component of many intelligence test batteries, figural matrices tests are an effective way to assess reasoning, which is considered a core ability of intelligence. Traditionally, the sum of correct items is used as a performance indicator (total solution procedure). However, recent advances in the development of computer-based figural matrices tests allow additional indicators to be considered for scoring. In two studies, we focused on the added value of a partial solution procedure employing log file analyses from a computer-based figural matrices test. In the first study ( n = 198), we explored the internal validity of this procedure by applying both an exploratory bottom-up approach (using sequence analyses) and a complementary top-down approach (using rule jumps, an indicator taken from relevant studies). Both approaches confirmed that higher scores in the partial solution procedure were associated with higher structuredness in participants' response behavior. In the second study ( n = 169), we examined the external validity by correlating the partial solution procedure in addition to the total solution procedure with a Grade Point Average (GPA) criterion. The partial solution procedure showed an advantage over the total solution procedure in predicting GPA, especially at lower ability levels. The implications of the results and their applicability to other tests are discussed.

The development of a vaccine marks a breakthrough in the fight against infectious diseases. However, to eradicate highly infectious diseases globally, the immunization of large parts of the population is needed. Otherwise, diseases, such as polio, measles, or more recently COVID-19, will repeatedly flare-up, with devastating effects on individuals and, in the worst case, on significant shares of the world population. For example, polio has been almost eradicated over the past three decades through an unprecedented global effort, but complete immunization has not yet been achieved. In this article, we use polio as an example to show how the global effort of developing and administering a vaccine can be understood as solving a complex problem since it involves cultural, political, and geographical barriers that demand solutions in dynamically changing and highly versatile environments. Referring to the literature on problem-solving, higher-order thinking, and complex reasoning, we demonstrate how the ability to deal with real-world environments that are complex and dynamically changing, adapting initial solutions to new circumstances and collaborate efficiently with others, has been essential for this endeavor. We argue that problem-solving abilities form one basis for solving consequential world problems.