Chapter 7
Development of a cognitive model of web-navigation
Easiness of navigation within a website is an important factor for information seeking performance. Several cognitive models exist that simulate the web-navigation process and these models in turn can be useful in supporting information seeking behavior. In this chapter we first discuss previous work we did on further developing a cognitive model of web-navigation CoLiDeS (Comprehension-based Linked model of Deliberate Search) that takes information from pictures into consideration, next to information from hyperlinks. This model is called CoLiDeS + Pic. Just like its parent model CoLiDeS, it uses Latent Semantic Analysis to compute semantic similarity in order to measure the information scent of hyperlinks available on a page. Next, we propose a new model CoLiDeS ++ Pic that adds path adequacy (with information from both hyperlinks and pictures) and applies backtracking. We hypothesize that in this way the information seeking process can be better modeled when compared to the previous model CoLiDeS + Pic. This was verified by simulating the model on a mockup website and comparing the results with the previous CoLiDeS + Pic model. The results support our hypothesis. We also present briefly the results of an experiment with tool-support based on the new model CoLiDeS ++ Pic. The results prove that model-generated support is fostering information seeking performance and helps in search tasks. We further discuss the challenges and advantages of automating navigation support using the proposed model.
Article outline
- Introduction
- Comprehension-based linked model of deliberate search
- Related work: CoLiDeS + Pic
- The moment of processing pictures on a web page
-
Efficacy of the CoLiDeS + Pic model
- Validation of CoLiDeS + Pic model with behavioral data
- Usefulness of automatic model-generated support
-
New model: CoLiDeS ++ Pic
- Current implementation and running of CoLiDeS ++ Pic
- Efficacy of CoLiDeS ++ Pic model
- Experiment with model-generated support
- Conclusion
-
References
References
References
Bezdan, E.
(
2013)
Graphical Overviews in Hypertext Learning Environments: When one size does not fit all. Unpublished PhD dissertation Open University, The Netherlands, Heerlen.
Blackmon, M. H., Kitajima, M., & Polson, P. G.
(
2005)
Tool for accurately predicting website navigation problems, non-problems, problem severity, and effectiveness of repairs. In
Proc CHI2005, ACM Press, 31–40.
Blackmon, M. H., Kitajima, M., Mandalia, D. R., & Polson, P. G.
(
2007)
Cognitive walkthrough for the Web puts LSA to work on real-world HCI design problems. In
T. Landauer,
D. McNamara,
S. Dennis &
W. Kintsch (Eds.),
Handbook of Latent Semantic Analysis. Mahwah, NJ: L. Erlbaum Ass., 345–375.
Cockburn, A., & McKenzie, B.
(
2001)
What do web users do? An empirical analysis of web use.
International Journal of Human-Computer Studies 54(6), 903–922.
Hofman, R., & van Oostendorp, H.
(
1999)
Cognitive effects of a structural overview in a hypertext.
British Journal of Educational Technology 30, 129–140.
Jul, S., & Furnas, G. W.
(
1997)
Navigation in electronic worlds: a CHI 97 workshop.
SIGCHI bulletin 29, 44–49.
Juvina, I.
(
2006)
Development of a Cognitive Model for Navigating on the Web. Unpublished PhD dissertation Utrecht University, The Netherlands, Utrecht.
Juvina, I. & van Oostendorp, H.
Juvina, I., & van Oostendorp, H.
(
2008)
Modeling semantic and structural knowledge in Web navigation.
Discourse Processes 45(4–5), 346–364.
Karanam, S., van Oostendorp, H., & Fu, W. -T.
(
2016)
Performance of computational cognitive models of web-navigation on real websites.
Journal of Information Science 41 (1), 94–113.
Karanam, S., Van Oostendorp, H., & Indurkhya, B.
(
2012)
Evaluating CoLiDeS+ Pic: the role of relevance of pictures in user navigation behaviour.
Behaviour & Information Technology, 31(1), 31–40.
Karanam, S., Van Oostendorp, H., & Indurkhya, B.
(
2011)
Towards a Fully Computational Model of Web-Navigation. In
Modern Approaches in Applied Intelligence. Vol. 6703 LNCS, Springer, 327–337.
Karanam, S., van Oostendorp, H., & Indurkhya, B.
(
2010)
The role of content in addition to hyperlinks in user clicking behavior.
Proceedings European Conference on Cognitive Ergonomics (ECCE 2010). Technical University Delft, The Netherlands.
Kintsch, W.
(
1998)
Comprehension: A Paradigm for Cognition. Cambridge University Press.
Kerka, S
(
2000)
Incidental Learning: Trends and Issues. Alert no 18. Columbus, OH: Eric Clearinghouse on Adult Career and Vocational Education.
Kitajima, M., Blackmon, M. H., & Polson, P. G.
(
2000)
A comprehension-based model of Web navigation and its application to Web usability analysis.
People and computers XIV – Usability or else!, Springer, 357–373.
Kitajima, M., Polson, P. G., & Blackmon, M. H.
(
2007)
CoLiDeS and SNIF-ACT: Complementary models for searching and sense making on the Web. In
HCIC Winter Workshop.
Landauer, T. K., Foltz, P. W., & Laham, D.
(
1998)
An introduction to latent semantic analysis.
Discourse Processes 25(2–3), 259–284.
Landauer, T. K., McNamara, S., Dennis, S., & Kintsch, W.
(
2007)
Handbook of Latent Semantic Analysis. Mahwah, NJ: L. Erlbaum Ass.
Lazar, J.
(
2003)
The World Wide Web. In
J. Jacko &
A. Sears (Eds.),
The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications. Mahwah, NJ: L. Erlbaum Ass, 714–730.
Marsick, V. J., & Watkins, K. E.
(
1990)
Informal and Incidental Learning in the Workplace. N.Y.: Routledge.
Martin, D. I., & Berry, M. W.
(
2007)
Mathematical Foundation Behind Latent Semantic Analysis. In
T. Landauer,
D. McNamara,
S. Dennis &
W. Kintsch (Eds.),
Handbook of Latent Semantic Analysis, Mahwah, NJ: L. Erlbaum Ass., 35–55.
McDonald, S., & Stevenson, R. J.
(
1998)
Navigation in hyperspace: An evaluation of the effects of navigational tools and subject experience on browsing and information retrieval in hypertext.
Interacting with Computers 10, 129–142.
Nilsson, R. M., & Mayer, R. E.
(
2002)
The effects of graphic organizers giving cues to the structure of hypertext document on user’ navigation strategies and performance.
Human-Computer Studies 57, 1–26.
Olston, C., & Chi, E. H.
(
2003)
ScentTrails: Integrating browsing and searching on the Web.
TOCHI 10(3), ACM Press, 177–197.
Pirolli, P., & Card, S.
(
1999)
Information foraging.
Psychological Review 106(4), 643–675.
Smith, P. A
(
1996)
Towards a practical measure of hypertext usability.
Interacting with Computers 8(4), 365–381.
Van Oostendorp, H., Karanam, S., & Indurkhya, B.
(
2012)
CoLiDeS + Pic: a cognitive model of web-navigation based on semantic information from pictures.
Behaviour & Information Technology 31(1), 17–30.
Cited by
Cited by 1 other publications
Ferguson, Chris & Herre van Oostendorp
2020.
Lost in Learning: Hypertext Navigational Efficiency Measures Are Valid for Predicting Learning in Virtual Reality Educational Games.
Frontiers in Psychology 11
This list is based on CrossRef data as of 12 april 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers.
Any errors therein should be reported to them.