Explanation generation: Questions direct exploration in semantic space

In everyday reasoning and scientific inquiry, explanations help people make sense of their experiences and observations. We investigate how people generate new possible explanations. Specifically, we study how the phrasing of "why" questions shapes exploration of the space of possible explanations. We hypothesized that rephrasing a question comparing two keywords to make one or the other more focal would guide people toward explanations that are more closely related to the focal word. Using a pre-trained machine learning model, we measured how closely each explanation aligned with the comparison words. In Study 1, we manipulated the order of the two keywords and found that explanations aligned more strongly with the earlier words. However, this design did not distinguish whether the effect was driven by the primacy of the words or the pragmatics of the question. In Study 2, we then independently manipulated which word appeared first and which word served as the grammatical subject, and found that participants were more likely to generate explanations related to the subject. These findings highlight how the phrasing of a question can shape explanation generation, demonstrating that pragmatic understanding influences how people explore a conceptual space.

Authors

Institutions

Publication Details

Journal
Cognition
Published
2026-09-08
DOI
https://doi.org/10.1016/j.cognition.2026.106689
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Explanation generation: Questions direct exploration in semantic space

Russell Golman, Kara Kedrick
Cognition
Explainable Artificial Intelligence (XAI)
article

Explanation generation: Questions direct exploration in semantic space

Russell Golman, Kara Kedrick
article en

Abstract

In everyday reasoning and scientific inquiry, explanations help people make sense of their experiences and observations. We investigate how people generate new possible explanations. Specifically, we study how the phrasing of "why" questions shapes exploration of the space of possible explanations. We hypothesized that rephrasing a question comparing two keywords to make one or the other more focal would guide people toward explanations that are more closely related to the focal word. Using a pre-trained machine learning model, we measured how closely each explanation aligned with the comparison words. In Study 1, we manipulated the order of the two keywords and found that explanations aligned more strongly with the earlier words. However, this design did not distinguish whether the effect was driven by the primacy of the words or the pragmatics of the question. In Study 2, we then independently manipulated which word appeared first and which word served as the grammatical subject, and found that participants were more likely to generate explanations related to the subject. These findings highlight how the phrasing of a question can shape explanation generation, demonstrating that pragmatic understanding influences how people explore a conceptual space.

CognitionVol. 278
Carnegie Mellon University (US)
National Science Foundation
Openalex Percentile: Top 8%
Explainable Artificial Intelligence (XAI)
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.