Challenges for a Computational Cognitive Psychology for the New Digital Ecosystem

Abstract

Advances in computational cognitive psychology have played an important role in understanding and engineering human-information interaction systems. These computational models include several addressing the cognition involved in the human sensemaking process, user models that capture the knowledge that humans acquire from interaction, and how people judge the credibility of online Twitter users who influence decision-making. The models presented in this chapter build on earlier information foraging models in which it is important to model individual-level knowledge and experience because these clearly influence human-information interaction processes. This chapter concludes with a discussion of challenges to computational cognitive models as digital information interaction becomes increasingly pervasive and complex. 2.1 Introduction Human-information interaction is concerned with how people interact with and process outwardly accessible information (Pirolli 2007a). It is an application field in which new systems can benefit from cognitive engineering models that synthesize results from sound cognitive science and provide predictions about technology and information designs. In turn, interactive digital systems serve as testbeds for integrated psychological theories that provide the foundation for cognitive engineering. In this chapter, I provide a brief review of some of the advances that have been made in computational cognitive psychology that have been relevant to understanding and engineering human-information interaction systems. This chapter focuses on cognitive models of the human sensemaking process, user models that capture the knowledge that they acquire from interaction, and how people judge the credibility of online Twitter users who influence decision-making. These models address tasks