EXTERNALIZING MENTAL MODELS TO AUGMENT DISTRIBUTED SENSEMAKING

Abstract

People spend an enormous amount of time making sense of the world online, whether programmers picking a software library, patients t,rying to determine the causes of their conditions, or citizens trying to understand the effects of a proposed health care bill. Esti,mates of the amount of time spent on such complex sensemaking tasks put it at around 70 billion hours a year in the U.S. alone; to p,ut this in perspective, it is about the time required to create Wikipedia ? twice ? spent every day. However, the tools people use f,or externalizing their evolving mental models ? such as tabs, documents, spreadsheets, or note-taking apps ? poorly support the cons,tantly shifting collecting, extracting, organizing and reorganizing needed to do so. The gap between the quickly evolving mental mod,els in peoples heads and the lagging external representations of those models in their browsers means that people often abandon the,ir efforts to externalize or avoid doing so in the first. Furthermore, evenif people do put in the work to organize and share an ext,ernal representation of their decision (such as creating a comparison table of libraries or a list of medical causes), it can be dif,ficult for others to evaluate whether they can or should reuse that work.We propose to perform empirical studies to develop deeper p,rocess-level models of sensemaking across various types of online decision making-related activities, and to use these as the scient,ific basis for tools that reduce the cost and/or increase the benefit to users in capturing, organizing, evaluating and adapting inf,ormation. A key insight we explore is that facilitating the externalization of user intent and context could not only make the user?,s computational tools more effective, but also help subsequent users decide whether and how to reuse the initial user?s work. We div,ide our efforts into four stages: helping the initial user (1) forage for and (2) structure information and helping subsequent users, (3) evaluate and (4) adapt the initial users? sensemaking and structures. At each stage our contributions include new theories, mod,els, systems and tools that connect and synergize the entire sensemaking process for initial and subsequent users

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 08, 2022
Source ID
N000142212650

Entities

People

  • Aniket Kittur

Organizations

  • Carnegie Mellon University
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Database Systems and Applications
  • Economics
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.