Towards Adaptive Support for Anticipatory Thinking

Abstract

Adaptive training and support technologies have been used to improve training and performance in a number of domains. However, limited work on adaptive training has examined anticipatory thinking, which is the deliberate, divergent exploration and analysis of relevant futures to avoid surprise. Anticipatory thinking engages the process of imagining how uncertainties impact the future, helps identify leading indicators and causal dependencies of future scenarios, and complements forecasting, which focuses on assessing the likelihood of outcomes. It is particularly important for intelligence analysis, mission planning, and strategic forecasting, wherein practitioners apply prospective sense-making, scenario planning, and other methodologies to identify possible options and their effects during decision making processes. However, there is currently no underlying cognitive theory supporting specific anticipatory thinking methodologies, no adaptive technologies to support their training, and no existing measures to assess their efficacy.We are engaged in an ongoing effort to design adaptive technologies to support the acquisition and measurement of anticipatory thinking. As a first step toward adaptive environments that support the acquisition and application of anticipatory thinking competencies, we have developed a task to measure anticipatory thinking in which participants explore uncertainties and the impacts on the future given a particular topic. We present preliminary results from a study to examine the validity of this measure and discuss multiple factors that affect anticipatory thinking including attention, inhibitory control, need for cognition, need for closure, convergent thinking, and divergent thinking. We then introduce design principles for supporting training, application, and assessment of anticipatory thinking.