Less Is More: Information Needs, Information Wants, and What Makes Causal Models Useful

Autor/inn/en	Kleinberg, Samantha; Marsh, Jessecae K.
Titel	Less Is More: Information Needs, Information Wants, and What Makes Causal Models Useful
Quelle	In: Cognitive Research: Principles and Implications, 8 (2023), Artikel 57 (23 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Kleinberg, Samantha)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
DOI	10.1186/s41235-023-00509-7
Schlagwörter	Information Needs; Causal Models; Decision Making; Difficulty Level; Information Seeking + Suchen Sie Ihr Suchwort? Information need; Informationsbedürfnis; Kausalanalyse; Decision-making; Entscheidungsfindung; Schwierigkeitsgrad; Informationserschließung
Abstract	Each day people make decisions about complex topics such as health and personal finances. Causal models of these domains have been created to aid decisions, but the resulting models are often complex and it is not known whether people can use them successfully. We investigate the trade-off between simplicity and complexity in decision making, testing diagrams tailored to target choices (Experiments 1 and 2), and with relevant causal paths highlighted (Experiment 3), finding that simplicity or directing attention to simple causal paths leads to better decisions. We test the boundaries of this effect (Experiment 4), finding that including a small amount of information beyond that related to the target answer has a detrimental effect. Finally, we examine whether people know what information they need (Experiment 5). We find that simple, targeted, information still leads to the best decisions, while participants who believe they do not need information or seek out the most complex information performed worse. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01