{"title":"Ill-Defined Problems in Wicked Learning Environments","authors":"Linus Tan , Anita Kocsis","doi":"10.1016/j.sheji.2024.11.004","DOIUrl":null,"url":null,"abstract":"<div><div>Many of today’s global problems are complex and difficult to solve—some may even be impossible. They are characterized by interconnectedness, non-linear causality, and a lack of clear solutions or definitive answers. Designing for such complex problems is unavoidable, but doing so without understanding biases and the repercussions of one’s design experience and actions compounds its complexity. This article explores what informs designers’ decisions (design cognition) and drives their activities (design behavior) when addressing complex problems and their implications. First, it examines problems through two intersecting theoretical lenses: cognitive psychology and learning. Then, it contextualizes its findings using the co-evolution of design to articulate how designing for complex problems is prone to biases and inaccurate feedback.</div></div>","PeriodicalId":37146,"journal":{"name":"She Ji-The Journal of Design Economics and Innovation","volume":"10 4","pages":"Pages 456-473"},"PeriodicalIF":1.8000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"She Ji-The Journal of Design Economics and Innovation","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405872624000984","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"HUMANITIES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Many of today’s global problems are complex and difficult to solve—some may even be impossible. They are characterized by interconnectedness, non-linear causality, and a lack of clear solutions or definitive answers. Designing for such complex problems is unavoidable, but doing so without understanding biases and the repercussions of one’s design experience and actions compounds its complexity. This article explores what informs designers’ decisions (design cognition) and drives their activities (design behavior) when addressing complex problems and their implications. First, it examines problems through two intersecting theoretical lenses: cognitive psychology and learning. Then, it contextualizes its findings using the co-evolution of design to articulate how designing for complex problems is prone to biases and inaccurate feedback.