A meta-analytic review of two modes of learning and the description-experience gap.

Abstract

People can learn about the probabilistic consequences of their actions in two ways: One is by consulting descriptions of an action's consequences and probabilities (e.g., reading up on a medication's side effects). The other is by personally experiencing the probabilistic consequences of an action (e.g., beta testing software). In principle, people taking each route can reach analogous states of knowledge and consequently make analogous decisions. In the last dozen years, however, research has demonstrated systematic discrepancies between description- and experienced-based choices. This description-experience gap has been attributed to factors including reliance on a small set of experience, the impact of recency, and different weighting of probability information in the two decision types. In this meta-analysis focusing on studies using the sampling paradigm of decisions from experience, we evaluated these and other determinants of the decision-experience gap by reference to more than 70,000 choices made by more than 6,000 participants. We found, first, a robust description-experience gap but also a key moderator, namely, problem structure. Second, the largest determinant of the gap was reliance on small samples and the associated sampling error: free to terminate search, individuals explored too little to experience all possible outcomes. Third, the gap persisted when sampling error was basically eliminated, suggesting other determinants. Fourth, the occurrence of recency was contingent on decision makers' autonomy to terminate search, consistent with the notion of optional stopping. Finally, we found indications of different probability weighting in decisions from experience versus decisions from description when the problem structure involved a risky and a safe option. (PsycINFO Database Record

The experience‐based format of probability improves probability estimates: The moderating role of individual differences in numeracy

“…Our experience‐based probability format is inspired by the decision from experience method (Ashby, ; Barron & Erev, ; Hertwig, Barron, Weber, & Erev, ; Traczyk et al, ; Wulff, Mergenthaler‐Canseco, & Hertwig, ) in which people can freely explore the environment and learn its properties (e.g., probabilities and outcomes). 1 However, this line of research focused on choices and decision‐making processes rather than communication of probability.…”

The Attraction Effect in Experience‐based Decisions

“…For example, when consumers choose between investments or grocers, they need to trade off investment returns (or discount magnitude) with investment risks (or discount frequency), or when they choose between medical treatments, they need to trade off the positive (partial or full treatment) and negative outcomes (side effects) of each treatment with the likelihood of these events (Saporta‐Sorozon, Danziger, & Sloman, ). Second, much of the literature examining differences between description‐based and experience‐based choice examined choice between gambles (Barron & Erev, ; Hertwig, ; Hertwig et al, ; Wulff, Mergenthaler Canseco, & Hertwig, in press).…”

Switch rates do not influence weighting of rare events in decisions from experience, but optional stopping does

“…Third, underweighting is moderated by the structure of the decision problems. Wulff et al () found that underweighting is greater when the rare outcome is extremely rare, when one option is risky (has more than one possible outcome) while the other is safe (has only one outcome), and when the prospects contain losses.…”

“…We now focus on the second question regarding optional stopping. Optional stopping refers to situations in which participants decide how much data to collect in a sequential manner, which can be influenced by many factors (Fried & Peterson, ; Gonzalez & Dutt, , ; Markant, Pleskac, Diederich, Pachur, & Hertwig, ; Wulff et al, ).…”