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Working Memory and Learning Underlying Website Structure
Steven Banas & Christopher A. Sanchez Cognitive Science & Engineering
Arizona State University
Information Gathering on the Web• The World-Wide-Web is complex and organized
in many different ways– Not all websites include navigational aids
• Without navigational aids users must rely on mental models created from information from various sources to guide their searching– i.e., Previous experience with domain or web
structure• Goal: match user’s mental model to actual
structure
Matching mental models
• During search, prior knowledge must be combined with incoming information to guide a users searching behavior– For example, previous experiences with Wikipedia
and similarities with the current page– Effortful and conscious process
• This process of combing incoming knowledge with previous knowledge has been shown to occur within the working memory system.
Working Memory
• Working memory capacity (WMC) has emerged in the past 30+ years as a powerful theory that predicts performance and behavior across a wide array of tasks.– Reading performance, g, science learning, anti-saccade, etc.
• Strongly tied to the notion of controlled attention– Ability to focus attention on relevant information and
either suppress or otherwise ignore task irrelevant information.
• More than just STM, as it includes aspects of both executive processing AND storage.
Working Memory and Web Learning
• Remember:– WMC predicts how well individuals connect discrete
concepts and make appropriate inferences – High WMC individuals have been shown to be better able
to retain information that is relevant and useful for integrating textual information, even in the face of related processing demands
• So…– Relative to the context of web search for understanding,
WMC should also predict learning from multiple web documents
– Integrating this information across discrete pages
Current study
• Participants (N=62) read a Wikipedia-like page on Plant Taxonomy
Website
• Hierarchical tree structure that contained 4 levels– 24 total pages– Each page ~ 500 words
• Navigated only using links– Links mirrored hierarchical structure of content
• Participants were not given a site map• Participants entered the website at the top
Screenshot of Website
Pre/Posttest Questions
• Participants rated their knowledge of plants and biology on a 1-5 scale
• Also completed– Hierarchical tree construction task.
• Place terms in correct location in hierarchy• More global measure of hierarchy
– Matching task• Choose item immediately connected in hierarchy• More local measure of hierarchy
• Completed tasks again after reading
Search Questions
• 18 short answer questions to be completed while searching the website
• Simple factual questions, drawn evenly from the entire website. – i.e. “What is the scientific name of clubmosses? “
WMC Measure
• Automated Operation Span task (AOSpan)
• Equation-letter strings were presented in sets of between 2 and 7 strings.
• Participants completed 3 trials of each set size, and the order of these sets was randomized.
IS 8/4 +1 =2? C
Hypotheses
• High WMC Individuals– Better able to construct a more accurate tree than lower
WMC individuals due to a better more robust mental model of the material and inferencing
– Better able to complete both the search questions and the tree construction due to the increased capability to handle both simultaneous tasks
• Low WMC Individuals– More taxed by the secondary search task, less likely
to develop an accurate mental model needed to complete the tree construction task
Results: Search Questions
• Overall, participants were able to adequately complete the search task (M=9.93, SD=3.73).
• Performance was not significantly correlated with – WMC (r(61)=.04, p>.05)– Knowledge of plants (r(61)=.07, p>.05)– Knowledge of biology (r(61)=.08, p>.05).
• Search Questions were more or less difficult regardless of WMC of prior knowledge
Results: Matching
• Significant improvement pre-post– F(1, 61)=34.99, ηp
2=.37, p<.01
Matching0
1
2
3
4
5
6
PrePost
Change in Matching Task• Hierarchical regression on improvement
– First block: WMC, knowledge of plants, and knowledge of biology
– Second block: interaction terms between WMC and both prior knowledge variables
• First block Results: – R2=.07, F(3, 61)=1.37, ns– No variables significant predictors
• Second block Results: – Interaction Terms did not significantly improve the fit of the
model• R2 change=.01, p>.05
Results: Tree Construction Task
• Participants did significantly improve pre to post – F(1, 61)=36.15, ηp
2=.37, p<.01).
Tree Construction0
1
2
3
4
5
6
PrePost
Change in Tree Construction Task• Hierarchical regression on
improvement– First block: WMC, knowledge of
plants, and knowledge of biology– Second block: interaction terms
between WMC and both prior knowledge variables
• First block Results: – R2=.12, F(3, 61)=3.71, p<.05– WMC only significant predictor of
learning gains gain (β=.35, p<.05)
• Second block Results: – Interaction Terms did not
significantly improve the fit of the model
Discussion
• Results show that WMC does influence how well individuals learn and remember the underlying, non-explicit, structure of complex material. – High WMC individuals improved their implicit understanding of
the material on the website, lower did not– Effect was not mediated by prior knowledge
• Results are important for online learning environment designers as it shows that individual differences do impact how learners grasp implicit information
• Also shows that user control over what navigational tools are available to them would benefit the user experience and learning
Future Work
• Extend to other domains• Other relevant individual differences• Test-bed for creation of better navigational
tools and learning aids