Skip to main content
SpringerLink
Log in

Challenges for a Computational Cognitive Psychology for the New Digital Ecosystem

  • Chapter
  • First Online:
Book cover Understanding and Improving Information Search

Part of the book series: Human–Computer Interaction Series ((HCIS))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://twitter.com/wefollow?lang=en.

References

  • Anderson JR (2007) How can the human mind occur in the physical universe? Oxford University Press, Oxford, UK

    Google Scholar 

  • Baumeister RF, Vohs KD, Funder DC (2007) Psychology as the science of self-reports and finger movements: whatever happened to actual behavior? Perspect Psychol Sci 2(4):396–403. https://doi.org/10.1111/j.1745-6916.2007.00051.x

    Google Scholar 

  • Birnbaum MH (1979) Source credibility in social judgment: bias, expertise, and the judge’s point of view. J Pers Soc Psychol 37(1):48–74

    Google Scholar 

  • Blei DM, Ng AY, Jordan MI (2003) Latent Dirichlet allocation. J Mach Learn Res 3:993–1022

    MATH  Google Scholar 

  • Brusilovsky P, Somyurek S, Guerra J, Hosseini R, Zadorozhny V, Durlach PJ (2016) Open social student modeling for personalized learning. IEEE Trans Emerg Top Comput 4:450–461. https://doi.org/10.1109/TETC.2015.2501243

    Google Scholar 

  • Canini K, Suh B, Pirolli P (2011) Finding credible information sources in social networks based on content and social structure. Paper presented at the IEEE international conference on social computing, SocialCom 2011, Boston, MA

    Google Scholar 

  • Card SK, Moran TP, Newell A (1983) The psychology of human-computer interaction. Lawrence Erlbaum Associates, Hillsdale, NJ

    Google Scholar 

  • Collins LM, Murphy SA, Strecher V (2007) The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. Am J Prev Med 32(5 Suppl):S112–118. https://doi.org/10.1016/j.amepre.2007.01.022

    Google Scholar 

  • Diana F, Bahry S, Masrom M, Masrek MN (2016) Website credibility and user engagement: a theoretical integration. Paper presented at the 2016 4th international conference on user science and engineering (i-USEr), 23–25 August 2016

    Google Scholar 

  • Gardner H (1985) The mind’s new science. Basic Books, New York

    Google Scholar 

  • Gonzalez C, Lerch JF, Lebiere C (2003) Instance-based learning in dynamic decision making. Cogn Sci 27:591–635

    Google Scholar 

  • Gray WD (2008) Cognitive modeling for cognitive engineering. In: Sun R (ed) The Cambridge handbook of computational psychology. Cambridge University Press, Cambridge, pp 565–588

    Google Scholar 

  • Gray WD, John BE, Atwood ME (1993) Project Ernestine: A validation of GOMS for prediction and explanation of real-world task performance. Hum-Comput Interact 8:237–309

    Google Scholar 

  • Griffiths TL, Steyvers M, Tenenbaum JB (2007) Topics in semantic representation. Psychol Rev 114(2):211–244

    Google Scholar 

  • Hearst MA (2009) Search user interfaces. Cambridge University Press, New York

    Google Scholar 

  • Hovland CI, Janis IL, Kelley HH (1953) Communication and persuasion. Yale University Press, New Haven, CT

    Google Scholar 

  • Kammerer Y, Nairn R, Pirolli P, Chi EH (2009) Signpost from the masses: learning effects in an exploratory social tag search browser. Paper presented at the proceedings of the 27th international conference on human factors in computing systems, Boston, MA, USA

    Google Scholar 

  • Klasnja P, Hekler EB, Shiffman S, Boruvka A, Almirall D, Tewari A, Murphy SA (2015) Micro-randomized trials: an experimental design for developing just-in-time adaptive interventions. Health Psychol: Official J Div Health Psychol, Am Psychol Assoc 34:1220–1228. https://doi.org/10.1037/hea0000305

    Google Scholar 

  • Klein G, Moon B, Hoffman RR (2006a) Making sense of sensemaking 1: alternative perspectives. IEEE Intell Syst 21(4):70–73

    Google Scholar 

  • Klein G, Moon B, Hoffman RR (2006b) Making sense of sensemaking 2: a macrocognitive model. IEEE Intell Syst 21(5):88–92

    Google Scholar 

  • Kotseruba I, Tsotsos JK (2018) 40 years of cognitive architectures: core cognitive abilities and practical applications. Artif Intell Rev. https://doi.org/10.1007/s10462-018-9646-y

    Google Scholar 

  • Laird JE, Lebiere C, Rosenbloom PS (2017) A standard model of the mind: toward a common computational framework across artificial intelligence, cognitive science, neuroscience, and robotics. AI Mag 38:13–16. https://doi.org/10.1609/aimag.v38i4.2744

    Google Scholar 

  • Lebiere C, Pirolli P, Thomson R, Paik J, Rutledge-Taylor M, Staszewski J, Anderson JR (2013) A functional model of sensemaking in a neurocognitive architecture. Comput Intell Neurosci 2013:921695. https://doi.org/10.1155/2013/921695

    Google Scholar 

  • Liao QV, Pirolli P, Fu W (2012) An ACT-R model of credibility judgment of micro-blogging Web pages. Proceedings of the international conference on cognitive modeling (ICCM 2012). Universitätsverlag der TU Berlin, Berlin, pp 103–108

    Google Scholar 

  • Marchionini G (2006) Exploratory search: from finding to understanding. Commun ACM 49(4):41–46. http://doi.acm.org/10.1145/1121949.1121979

    Google Scholar 

  • Nelson L, Held C, Pirolli P, Hong L, Schiano D, Chi EH (2009) With a little help from my friends: examining the impact of social annotations in sensemaking tasks. Paper presented at the proceedings of the 27th international conference on human factors in computing systems, Boston, MA, USA

    Google Scholar 

  • Newell A (1990) Unified theories of cognition. Harvard University Press, Cambridge, MA

    Google Scholar 

  • Nickerson RS (1998) Confirmation bias: a ubiquitous phenomenon in many guises. Rev Gen Psychol 2(2):175–220. https://doi.org/10.1037/1089-2680.2.2.175

    Google Scholar 

  • Olston C, Chi EH (2003) ScentTrails: integrating browsing and searching on the Web. ACM Trans Comput-Hum Interact 10(3):177–197

    Google Scholar 

  • Orr MG, Lebiere C, Stocco A, Pirolli P, Pires B, Kennedy WG (2019) Multi-scale resolution of neural, cognitive and social systems. Comput Math Organ Theor 25(1):4–23. https://doi.org/10.1007/s10588-018-09291-0

    Google Scholar 

  • Pirolli P (1999) Cognitive engineering models and cognitive architectures in human-computer interaction. In: Durso FT, Nickerson RS, Schvaneveldt RW, Dumais ST, Lindsay DS, Chi MTH (eds) Handbook of applied cognition. Wiley, West Sussex, England, pp 441–477

    Google Scholar 

  • Pirolli P (2007a) Cognitive models of human-information interaction. In: Durso FT (ed) Handbook of applied cognition, 2nd edn. Wiley, West Sussex, England, pp 443–470

    Google Scholar 

  • Pirolli P (2007b) Information foraging theory: adaptive interaction with information. Oxford University Press, Oxford; New York

    Google Scholar 

  • Pirolli P (2007c) Information foraging: a theory of adaptive interaction with information. Oxford University Press, New York

    Google Scholar 

  • Pirolli P, Card SK (1999) Information foraging. Psychol Rev 106:643–675

    Google Scholar 

  • Pirolli P, Card SK (2005) The sensemaking process and leverage points for analyst technology. Paper presented at the 2005 international conference on intelligence analysis, McLean, VA

    Google Scholar 

  • Pirolli P, Kairam S (2013) A knowledge-tracing model of learning from a social tagging system. User Model User-Adap Inter 1–30. https://doi.org/10.1007/s11257-012-9132-1

    Google Scholar 

  • Pirolli P, Russell DM (2011) Introduction to this special issue on sensemaking. Hum-Comput Inter 26:1–8

    Google Scholar 

  • Pirolli P, Schank P, Hearst M, Diehl C (1996) Scatter/Gather browsing communicates the topic structure of a very large text collection. Proceedings of the conference on human factors in computing systems, CHI ’96. ACM Press, Vancouver, BC, pp 213–220

    Google Scholar 

  • Pirolli P, Youngblood GM, Du H, Konrad A, Nelson L, Springer A (2018) Scaffolding the mastery of healthy behaviors with fittle + systems: evidence-based interventions and theory. Hum–Comput Interact, 1–34. https://doi.org/10.1080/07370024.2018.1512414

  • Rasch G (1960) Probabilistic models for some intelligence and attainment tests. Danish Institute for Educational Research, Copenhagen

    Google Scholar 

  • Russell DM, Stefik MJ, Pirolli P, Card SK (1993) The cost structure of sensemaking. Paper presented at the INTERCHI ’93 conference on human factors in computing systems, Amsterdam

    Google Scholar 

  • Suh B, Woodruff A, Rosenholtz R, Glass A (2002) Popout prism: adding perceptual principles to overview + detail document interfaces. CHI 2002, ACM Conf Hum Fact Comput Syst, CHI Lett 4(1):251–258

    Google Scholar 

  • Tversky A, Kahneman D (1974) Judgment under uncertainty: heuristics and biases. Science 185:1124–1131

    Google Scholar 

  • Vydiswaran V, Zhai C, Roth D, Pirolli P (2012) Unibiased learning of controversial topics. In Proceedings of the annual meeting of the American Society for Information Science and Technology (ASIST), ASIST, Baltimore, MD.

    Google Scholar 

  • Vydiswaran VGV, Zhai C, Roth D, Pirolli P (2012) BiasTrust: teaching biased users about controversial topics. In CIKM 2012. ACM, Maui, Hawaii

    Google Scholar 

  • White RW, Kules B, Drucker SM, schraefel mc (2006) Supporting exploratory search: introduction. Commun ACM 49(4):36–39. http://doi.acm.org/10.1145/1121949.1121978

Download references

Author information

Authors and Affiliations

  1. Florida Institute for Human and Machine Cognition, Pensacola, FL, USA

    Peter Pirolli

Authors
  1. Peter Pirolli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter Pirolli .

Editor information

Editors and Affiliations

  1. Raytheon BBN Technologies, Cambridge, MA, USA

    Wai Tat Fu

  2. Utrecht University, Utrecht, The Netherlands

    Herre van Oostendorp

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Pirolli, P. (2020). Challenges for a Computational Cognitive Psychology for the New Digital Ecosystem. In: Fu, W., van Oostendorp, H. (eds) Understanding and Improving Information Search. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-030-38825-6_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-38825-6_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38824-9

  • Online ISBN: 978-3-030-38825-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation