The Art and Science of Persuasion: Not All Crowdfunding Campaign Videos Are The Same, Sanorita Dey, Brittany Duff, Karrie Karahalios, Wai-Tat Fu, CSCW 2017.
Adult age differences in information foraging in an interactive reading environment. Liu, Xiaomei; Chin, Jessie; Payne, Brennan R.; Fu, Wai-Tat; Morrow, Daniel G.; Stine-Morrow, Elizabeth A. L. Psychology and Aging, Vol 31(3), May 2016, 211-223.
From distributed cognition to collective intelligence: Supporting cognitive search to facilitate massive collaboration (2016). Mass Collaboration and Education, Springer.
Chinthammit, W., Yoo, S., Parker, C., Turland, S., Pederson, S., Fu, W.-T. (2016). MolyPoly: An Immersive Gesture Controlled Approach to Visuo-Spatial Learning of Organic Chemistry. The Cognitive Effects of Spatial Interaction, Learning, and Ability. Springer-Verlag.
Rao, H., Huang, S.-W., Fu, W.-T. (2016). Towards a crowd-powered object locations schematization system. ACM Transactions on Intelligent Systems and Technology (TIST), 7 (4), no. 54
Karanam, S., van Oostendorp, H., Fu, W.-T. (2016). Performance of computational cognitive models of web-navigation on real websites. Journal of Information Science, 42 (1), 94-113
Fu, W.-T. (2016). The Central Role of Heuristic Search in Cognitive Computation Systems. Mind and Machines, 26 (1), 103-123.
Yi-Chieh Lee, Chi-Hsien Yen and Wai-Tat Fu. An Effective Donation Distribution System for Crowdfunding Websites. International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction (SBP). Washington, DC.
Liao, Q. V., Strohmaier, M., Fu, W.-T. (2016). #Snowden: Understanding Behavioral Differences of Majority and Minority Opinion Groups on Social Media. In Proceedings of the ACM CHI conference on Human Factors in Computing Systems.
Kim, J. G., Kong, H. K., Karahalios, K., Fu, W.-T., Hong, H. (2016). The Power of Collective Endorsements: Credibility Factors in Medical Crowdfunding Campaigns. In Proceedings of the ACM CHI conference on Human Factors in Computing Systems.
Chinthammit, W., Yoo, S., Parker, C., Turland, S., Pedersen, S., and Fu, W.-T. (2015). MolyPoly: A 3D Immersive Gesture Controlled Approach to Visuo-Spatial Learning of Organic Chemistry. In Computer-Human Interaction. Cognitive Effects of Spatial Interaction, Learning, and Ability, LNCS, pp 153-170. [
PDF] [ Abstract ]
Currently, first-year chemistry students learn about three-dimensional molecular structures using a combination of lectures, tutorials, and practical hands-on experience with molecular chemistry kits. We have developed a basic 3D molecule construction simulation, called MolyPoly. The system was designed to augment the teaching of organic chemistry by helping students grasp the concepts of chemistry through visualisation in an immersive environment, 3D natural interaction, and audio lesson feedback. This paper presents the results of a pilot study conducted with a first-year chemistry class at the University of Tasmania. Participating students were split into two groups: MolyPoly group (no lecturer in the sessions) and traditional classroom group during the four in-semester classroom sessions over a period of two weeks. We present our comparative analyses over the knowledge-based pretest and posttest of the two groups, by discussing the overall improvement as well as investigating the improvement over the test questions with different knowledge difficulty levels and different required spatial knowledge.
Liao, Q. V., Fu, W.-T., Mamidi, S. (2015). It Is All About Perspective: An Exploration of Mitigating Selective Exposure with Aspect Indicators. In Proceedings of the ACM CHI conference on Human Factors in Computing Systems.
Chin, J., Payne, B., Fu, W-T., Morrow, D. G., Stine-Morrow, E.A. L. (In Press). Information foraging across the life span: Search and switch in unknown patches. Topics in Cognitive Science.
Chin, J., Chevalier, A., He., J. & Fu, W-T. (2014). Linking knowledge in the head to knowledge in the world: Age differences in web exploration with the search engine. Poster of the Cognitive Aging Conference 2014, Atlanta, GA.
Chin, J., Payne, B.R., Fu, W-T., Morrow, D., Stine-Morrow, E.A.L. (2014). Information foraging across the life span: Search and switch in unknown patches. Poster of the Cognitive Aging Conference 2014, Atlanta, GA.
Liao, Q. V. & Fu, W.-T. (2014). Expert Voices in Echo Chambers: Effects of Source Expertise Indicators on Exposure to Diverse Opinions. In Proceedings of the ACM CHI conference on Human Factors in Computing Systems. [PDF] [Nominated for Best Paper, top 5 %]
Xu, A., Yang, X., Rao, H., Fu, W.-T., Huang, S.-W., Bailey, B. P. (2014). Show me the Money! An Analysis of Project Updates during Crowdfunding Campaigns. In Proceedings of the ACM CHI conference on Human Factors in Computing Systems. [PDF] [Abstract]
Rao, H., Xu, A., Yang, X., Fu, W.-T. (2014) Emerging Dynamics in Crowdfunding Campaigns. In International Social Computing, Behavioral-Cultural Modeling and Prediction Conference. [PDF] [Abstract]
Liao, Q. V.& Fu, W. (2014) Can You Hear Me Now? Mitigating the Echo Chamber Effect by Source Position Indicators. 17th ACM conference on Computer Supported Cooperative Work and Social Computing. [PDF] [Abstract]
Cervantes, C. and Fu, W.-T. (2013). Narrative Fragment Creation: An Approach for Learning Narrative Knowledge. In Proceedings of the Second Annual Conference on Advances in Cognitive Systems (ACS), pp 237-254. [PDF] [ Abstract ]
Storytelling is an integral part of the human experience, and understanding how stories - or narratives - are generated can offer insight into their importance. Current research focuses on the introduction of narrative knowledge into the generation process in order to facilitate the creation of qualitatively good narratives. Narrative generation and narrative knowledge, however, are two sides of the same coin; as knowledge about narrative events is necessary for generation, so is the ability to generate narratives indispensable to understanding the events therein. We propose the narrative fragment - a construct intended to capture narrative knowledge - and a method for automatically creating these fragments with narrative generation through partial order planning and analysis through n-gram modeling. The generated plans establish causal and temporal relationships, and by modeling those relationships and creating fragments, our system learns narrative knowledge.
Liao, Q. V.& Fu, W. (to appear) Age Differences in Credibility Judgment of Online Health Information. ACM Transactions on Computer-Human Interaction (TOCHI). [PDF] [Abstract]
Rao, H., Huang, S.-W., Fu, W.-T. (2013).What Will Others Choose? How a Majority Vote Reward Scheme Can Improve Human Computation in a Spatial Location Identification Task. First AAAI Conference on Human Computation and Crowdsourcing, Palm Springs, California, USA. [PDF] [ Abstract ]
We created a spatial location identification task (SpLIT) in which workers recruited from Amazon Mechanical Turk were presented with a camera view of a location, and were asked to identify the location on a two-dimensional map. In cases where these cues were ambiguous or did not provide enough information to pinpoint the exact location, workers had to make a best guess. We tested the effects of two reward schemes. In the "ground truth" scheme, workers were re- warded if their answers were close enough to the correct lo- cations. In the "majority vote" scheme, workers were told that they would be rewarded if their answers were similar to the majority of other workers. Results showed that the major- ity vote reward scheme led to consistently more accurate an- swers. Cluster analysis further showed that the majority vote reward scheme led to answers with higher reliability (a higher percentage of answers in the correct clusters) and precision (a smaller average distance to the cluster centers). Possible rea- sons for why the majority voting reward scheme was better were discussed.
Rao, H., Huang, Fu, W.-T. (2013). Combining Schematic and Augmented Reality Representations in a Remote Spatial Assistance System. IEEE ISMAR 2013 Workshop on Collaboration in Merging Realities, Adelaide, SA, Australia. [PDF] [ Abstract ]
Remote collaborative systems allow people at remote locations to accomplish a task as a team. One unique and critical challenge for these systems is to support communication of spatial information, as people at remote locations cannot anchor their conversation by directly referencing objects in the same spatial environment. We focus on the task of indoor navigation assistance to highlight this challenge, and propose a general framework that allows two or more persons at remote locations to better communicate and make spatial inferences. We show how schematic representations and augmented reality tools can be combined to help them establish anchors that allow them to both see and refer to the same locations, such that the users can develop a richer representation of the spatial environment. The tools can also provide guidance on actions and facilitate spatial inferences. We demonstrate this idea using a version of remote spatial assistance to a local user who navigates in an unfamiliar indoor environment. The system aims at efficiently connecting the local user and the remote expert to collaboratively infer and develop a spatial plan, locate and correct the position of the local user without the use of a GPS system, and provide spatial guidance using landmarks developed by the pair of users. The system demonstrates the combination of an autonomous system and human computation system. Implication to future development of such systems for remote spatial assistance is discussed.
Fu, W.-T., D'Andrea, L., & Bertel, S. (2013). Effects of collaborative technologies on communication and performance in a remote spatial orientation task. Spatial Cognition and Computation. [PDF] [Abstract]
An experiment was conducted to examine the impact of communication
methods (text-only, audio-only, and audio-plus-video) on communication patterns and
effectiveness in a 2-person remote spatial orientation task. The task required a pair of
participants to figure out the cardinal direction of a target object by communicating
spatial information and perspectives. Results showed that overall effectiveness in the
audio-only condition was better than the text-only and audio-plus-video conditions,
and communication patterns were more predictive of errors than individual differences
in spatial abilities. Discourse analysis showed that participants in the audio-plusvideo
condition performed less mental transformation of spatial information when
communicating, which led to more interpretation errors by the listener. Participants
in the text-only conditions performed less confirmation and made more errors by
misreading their own display. Results suggested that speakers in the audio-plusvideo
condition minimized effort by communicating spatial information based on their
own perspective but speakers in the audio-only and text-only conditions would more
likely communicate transformed spatial information. Analysis of gestures in the audioplus-
video condition confirmed that iconic gestures tended to co-occur with spatial
transformation. Iconic gesture rates were negatively correlated with transformation
errors, indicating that iconic gestures more likely co-occurred with successful communication
of spatial transformation. Results show that when visual interactive feedback
is available, speakers tend to adopt egocentric spatial perspectives to minimize effort
in mental transformation and rely on the feedback to ensure that the hearer correctly
interprets the information. When visual interactive feedback is not available, speakers
will put more effort in transforming spatial information to help the hearer to understand
the information. The current result demonstrated that allowing two persons to see and communicate with each other during a remote spatial reasoning task can lead to more
errors because of the use of a suboptimal communication strategy.
Fu, W.-T., Lee, H., Boot, W., & Kramer, A. (2013). Bridging across cognitive training and brain plasticity: a neurally inspired computational model of interactive skill learning. WIREs Cognitive Science, 4, 225-236. [PDF] [Abstract]
This article reviews recent empirical and brain imaging data on effects of cognitive
training methods on complex interactive skill learning, and presents a neurally
inspired computational model that characterizes the effects of these training
methods. In particular, the article focuses on research that shows that variable
priority training (VPT), which requires learners to shift their priorities to different
task components during training, often leads to better acquisition and retention of
skills than fixed priority training (FPT). However, there is only weak evidence that
shows that VPT can enhance transfer of complex interactive skills to untrained
situations. Brain imaging studies show that VPT leads to significantly lower
activations and a higher reduction of activities in attentional control areas after
training than FPT. Research also shows that the volume of the striatum predicts
the learning effects, but only in VPT. The computational model, developed based
on learning mechanisms at the neural level, bridges across the empirical and the
braining imaging results by explaining the effects of VPT and FPT at both the
behavioral and neural levels. The results were discussed in the context of previous
findings on cognitive training
Fu, W.-T. & Pirolli, P. (2013). Establishing the micro-to-macro link: Multilevel models of human-information interaction. The Oxford Handbook of Cognitive Engineering. [PDF] [Abstract]
We argue that the time is ripe to develop multilevel models that provide explanations at both the
individual and social levels to extend research in human-computer interaction to the emerging area
called socio-computer interaction. We provide three examples of such multilevel models. We first
describe the SNIF-ACT model, which was developed to explain individuals’ information foraging
behavior as they navigate through web pages to find target information, and to explain the general
tendency for people to stay on any particular website. We then describe the social information
Foraging theory, which characterizes how search efficiencies may be improved by utilizing social
signals generated by other information foragers. Finally, we describe the semantic imitation model,
which characterizes how individual users may generate social tags to index their own documents and
could lead to aggregate indices that act as semantic structures that help other users to find relevant
information. The models demonstrate the significance in capturing the social dynamics involved in
systems that afford socio-computer interaction.
Liao, Q., & Fu. W.-T. (2013). Beyond the filter bubble: Interactive effects of perceived threat and topic involvement on selective exposure to information. In Proceedings of the ACM SIGCHI conference on Human Factors in Computing Systems (CHI), Paris, France. [PDF] [Abstract]
We investigated participants’ preferential selection of
information and their attitude moderation in an online
environment. Results showed that even when opposing
views were presented side-to-side, people would still
preferentially select information that reinforced their
existing attitudes. Preferential selection of information was,
however, influenced by both situational (e.g., perceived
threat) and personal (e.g., topic involvement) factors.
Specifically, perceived threat induced selective exposure to
attitude consistent information for topics that participants
had low involvement. Participants had a higher tendency to
select peer user opinions in topics that they had low than
high involvement, but only when there was no perception of
threat. Overall, participants’ attitudes were moderated after
being exposed to diverse views, although high topic
involvement led to higher resistance to such moderation.
Perceived threat also weakened attitude moderation,
especially for low involvement topics. Results have
important implication to the potential effects of
"information bubble" – selective exposure can be induced
by situational and personal factors even when competing
views are presented side-by-side.
Huang, S. W., & Fu, W.-T. (2013). Don't hide in the crowd! Increasing social transparency between peer workers improves crowdsourcing outcomes. In Proceedings of the ACM SIGCHI conference on Human Factors in Computing Systems (CHI), Paris, France. [PDF] [Abstract]
This paper studied how social transparency and different
peer-dependent reward schemes (i.e., individual, teamwork,
and competition) affect the outcomes of crowdsourcing. The
results showed that when social transparency was increased
by asking otherwise anonymous workers to share their demographic
information (e.g., name, nationality) to the paired
worker, they performed significantly better. A more detailed
analysis showed that in a teamwork reward scheme, in which
the reward of the paired workers depended only on the collective
outcomes, increasing social transparency could offset
effects of social loafing by making them more accountable
to their teammates. In a competition reward scheme, in
which workers competed against each other and the reward
depended on how much they outperformed their opponent,
increasing social transparency could augment effects of social
facilitation by providing more incentives for them to outperform
their opponent. The results suggested that a careful
combination of methods that increase social transparency and
different reward schemes can significantly improve crowdsourcing
Rao, H., & Fu, W.-T. (2013). A General Framework for a Collaborative Mobile Indoor Navigation Assistance System. In Proceedings of the ACM International Conference on Intelligent User Interfaces (IUI), Santa Monica, CA.
Huang, S. W., Pei-Fen Tu, & Fu, W.-T. (2013). Leveraging the crowd to improve feature-sentiment analysis of user review. In Proceedings of the International Conference on Intelligent User Interfaces (IUI), Santa Monica, CA. [PDF] [Abstract]
Crowdsourcing and machine learning are both useful techniques
for solving difficult problems (e.g., computer vision
and natural language processing). In this paper, we propose
a novel method that harnesses and combines the strength of
these two techniques to better analyze the features and the
sentiments toward them in user reviews. To strike a good
balance between reducing information overload and providing
the original context expressed by review writers, the proposed
system (1) allows users to interactively rank the entities
based on feature-rating, (2) automatically highlights sentences
that are related to relevant features, and (3) utilizes implicit
crowdsourcing by encouraging users to provide correct
labels of their own reviews to improve the feature-sentiment
classifier. The proposed system not only helps users to save
time and effort to digest the often massive amount of user reviews,
but also provides real-time suggestions on relevant features
and ratings as users generate their own reviews. Results
from a simulation experiment show that leveraging on the
crowd can significantly improve the feature-sentiment analysis
of user reviews. Furthermore, results from a user study
show that the proposed interface was preferred by more participants
than interfaces that use traditional noun-adjective
pairs summarization, as the current interface allows users to
view feature-related information in the original context.
Huang, S.W., & Fu, W.-T. (2013). Enhancing reliability using peer consistency evaluation in human computation. In Proceedings of the 16th ACM conference on Computer Supported Cooperative Work (CSCW), San Antonio, TX. [PDF] [Abstract]
Peer consistency evaluation is often used in games with a
purpose (GWAP) to evaluate workers using outputs of other
workers without using gold standard answers. Despite its
popularity, the reliability of peer consistency evaluation has
never been systematically tested to show how it can be used
as a general evaluation method in human computation systems.
We present experimental results that show that human
computation systems using peer consistency evaluation can
lead to outcomes that are even better than those that evaluate
workers using gold standard answers. We also show that
even without evaluation, simply telling the workers that their
answers will be used as future evaluation standards can significantly
enhance the workers’ performance. Results have
important implication for methods that improve the reliability
of human computation systems.
Huang, S.W., & Fu, W.-T. (2013). Motivating crowds using social facilitation and social transparency. In Proceedings of the 16th ACM conference on Computer Supported Cooperative Work (CSCW), San Antonio, TX.
Chin, J., Payne, B., Fu, W-T., Morrow, D., Stine-Morrow, E.A. L. (2012). Information foraging in the unknown patches across the life span. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 1404-1409). Austin, TX: Cognitive Science Society.
Fu, W.-T. & Dong, W. (2012). From Collaborative Indexing to Knowledge Exploration: A Social Learning Model. IEEE Intelligent Systems. [PDF] [Abstract]
The World Wide Web has evolved from a read-only information resource
to a participatory environment that lets people share, explore, and learn
through multiple forms of user-generated content (such as blogs and photos).
A social information system, for example, is a form of social learning in which multiple users engage in knowledge exploration.
Learning in such situations involves
finding and evaluating relevant documents
related to the topic, comprehending and extracting
information from the documents,
and integrating the information with existing
knowledge. This form of knowledge exploration
becomes social when users share
found documents through systems such as
Delicious (formerly del.icio.us), a site that
lets users collaboratively index documents
with short "tags" and share them with other
users. Such collaborative indexing using social
tags can not only provide structures to
information on the Web but can also act as
navigational cues for other users to find relevant
We focus on these kinds of collaborative
or social tagging systems. Researchers
have argued that social tagging systems can
effectively improve knowledge exploration
and sense-making activities,1,2 and studies
have analyzed the knowledge structures in
these systems, making them an ideal testbed
for social learning. We describe a social learning model that characterizes the iterative
process of knowledge exploration and
learning activities. We also present results
from an empirical study that directly tested
the social learning model.
Fu, W.-T. (2012). From Plato to the WWW: Exploratory Information Foraging. In P. M. Todd & T. Robbins (Eds.), Cognitive Search. MIT Press. [PDF] [Abstract]
Generally speaking, two conditions make cognitive search possible: (a) symbolic structures
must be present in the environment and (b) these structures must be detectable by
a searcher, whose behavior changes based on the structures detected. In this chapter,
information search on the Internet is used to illustrate how a theoretical framework
of these two conditions can assist our understanding of cognitive search. Discussion
begins with information foraging theory (IFT), which predicts how general symbolic
structures may exist in an information environment and how the searcher may use these
structures to search for information. A computational model called SNIF-ACT (developed
based on IFT) is then presented and provides a good match to online information
search for specifi c target information. Because a further component important to
cognitive search is the ability to detect and learn useful structures in the environment,
discussion follows on how IFT can be extended to explain search behavior that involves
incremental learning of the search environment. Illustration is provided on how different
forms of semantic structures may exist in the World Wide Web, and how human
searchers can learn from these structures to improve their search. Finally, the SNIFACT
model is extended to characterize directed and exploratory information foraging
behavior in information environments.
Huang, S.W., Tu, P.-F., Amanzadeh, M., & Fu W.-T. (2012). Review Explorer: An Innovative Interface for Displaying and Collecting Categorized Review Information. Poster Presentation at the 25th ACM Symposium on User Interface Software and Technology (UIST), Cambridge, MA.
Huang, S.-W. & Fu, W.-T. (2012). Systematic Analysis of Output Agreement Games: Effects of Gaming Environment, Social Interaction, and Feedback. In Proceedings of the 4th Human Computation Workshop (HCOMP 2012), Toronto, ON. [PDF] [Abstract]
We report results from a human computation study that
tests the extent to which output agreement games are
better than traditional methods in terms of increasing
quality of labels and motivation of voluntary workers on
a task with a gold standard. We built an output agreement
game that let workers recruited from Amazon’s
Mechanical Turks label the semantic textual similarity
of 20 sentence pairs. To compare and test the effects
of the major components of the game, we created interfaces
that had different combinations of a gaming
environment (G), social interaction (S), and feedback
(F). Our results show that the main reason that an output
agreement game can collect more high-quality labels
is the gaming environment (scoring system, leaderboard,
etc). On the other hand, a worker is much more
motivated to voluntarily do the task if he or she can
do it with another worker (i.e., with social interaction).
Our analysis provides human computation researchers
important insight on understanding how and why the
method of Game with a Purpose (GWAP) can generate
high-quality outcomes and motivate more voluntary
Fu, W.-T., & Liao, Q. V. (2012). Information and Attitude Diffusion in Networks. In Proceedings of the International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP), College Park, MD.
Dong, W., & Fu, W. T. (2012). One Piece at a Time: Why Video-Based Communication is Better for Negotiation and Conflict Resolution. In Proceedings of the 2012 ACM Conference on Computer Supported Cooperative Work (CSCW), Seattle, WA. [Nominated for Best Paper, top 5 %] [PDF] [Abstract]
We compared the effects of three computer mediated
communication (CMC) channels (text, audio, and video) on
how people performed an appointment-scheduling task. The
task involved a grounding and a conflict resolution
component. The results showed that video conferencing
supported participant dyads in reaching a consensus that
had better balanced performance between the dyads only
when task difficulty was high and when there were more
inherent conflicts in the task. Participants across the three
CMC conditions also demonstrated different patterns of
conversation dynamics during information exchange and
negotiation. Mediation analysis showed that in video-based
communication, strategies of exchanging less information
at a time predicted higher levels of negotiation, which in
turn predicted smaller performance differences in high
conflict conditions. The results suggested that the design
and use of communication technologies for remote conflict
resolution should promote the strategy of exchanging
information in small pieces, which could better support
subsequent negotiation and foster a sense of fairness.
Liao, V. Q., & Fu, W.-T. (2012). Age Differences in Credibility Judgment of Online Health Information. In Proceedings of the 2nd International conference on Health Informatics (IHI), Miami, FL. [PDF] [Abstract]
To better support older adults’ consumption of high quality health information on the Internet, it is important to understand how older adults make credibility judgments with online health information. For this purpose, we conducted two laboratory studies to explore how the credibility cues in message contents, website features, and user reviews could differentially impact younger and older adults’ credibility judgments. Results from the first experiment showed that older adults, compared to younger ones, were less sensitive to the credibility cues in message contents, as well as those in the website features. Results from the second experiment showed that user reviews that were consistent with the credibility cues in message contents could reinforce older adults’ credibility judgments. Older adults, compared to younger adults, seemed to be less swayed by user reviews that were inconsistent with the message contents. These results provided implications for designing health information websites that better support older adults’ credibility judgments.
Chin, J., & Fu, W.-T. (2012). Age Differences in Exploratory Learning from a Health Information Website. In Proceedings of the 30th international conference on Human factors in computing systems (CHI), Austin, TX. [PDF] [Abstract]
An empirical study was conducted to investigate how older
and younger users learned by performing exploratory
search of health information using an interface that
recommended relevant links based on browsing histories.
While older and younger users gained both factual and
structural knowledge about the health topics, significant age
differences were observed. Our results showed that
processing of recommended and regular Web links imposed
distinct demands on cognitive abilities, which at least
partially explained the observed age differences in the
search process. The use of recommended links was
positively associated with general knowledge, while the use
of regular Web links was positively associated with
processing capacity. Results also showed that the
recommended links benefited both younger and older adults
by broadening the exploration of information, which led to
better learning. Implications on designs of health
information interfaces that facilitate exploratory search and
learning for different age groups were discussed.
Liao, Q. V., Wagner, C. Pirolli, P., & Fu, W.-T. (2012). Understanding Experts' and Novices' Expertise Judgment of Twitter Users. In Proceedings of the 30th international conference on Human factors in computing systems (CHI), Austin, TX. [PDF] [Abstract]
Judging topical expertise of micro-blogger is one of the key challenges for information seekers when deciding which information sources to follow. However, it is unclear how useful different types of information are for people to make expertise judgments and to what extent their background knowledge influences their judgments. This study explored differences between experts and novices in inferring expertise of Twitter users. In three conditions, participants rated the level of expertise of users after seeing (1) only the tweets, (2) only the contextual information including short biographical and user list information, and (3) both tweets and contextual information. Results indicated that, in general, contextual information provides more useful information for making expertise judgment of Twitter users than tweets. While the addition of tweets seems to make little difference, or even add nuances to novices’ expertise judgment, experts’ judgments were improved when both content and contextual information were presented.
Moghaddam, R. Z., Bailey, B., & Fu, W.-T. (2012). Consensus Building in Open Source User Interface Design Discussions. In Proceedings of the 30th international conference on Human factors in computing systems (CHI), Austin, TX. [PDF] [Abstract]
We report results of a study which examines consensus
building in user interface design discussions in open source
software communities. Our methodology consisted of
conducting interviews with designers and developers from
the Drupal and Ubuntu communities (N=17) and analyzing
a large corpus of interaction data collected from Drupal.
The interviews captured user perspectives on the challenges
of reaching consensus, techniques employed for building
consensus, and the consequences of not reaching consensus.
We analyzed the interaction data to determine how different
elements of the content, process, and user relationships in
the design discussions affect consensus. The main result
from this analysis shows that design discussions having
participants with more experience and prior interaction are
more likely to reach consensus. Based on all of our results,
we formulated design implications for promoting consensus
in distributed discussions of user interface design issues.
Kannampallil, T. G., Waicekauskas, K., Morrow, D. G., Kopren, K. M., & Fu, W.-T. (2011). External Tools for Collaborative Medication Scheduling. Cognition, Technology, & Work.
Fu, W.-T. (2011). A Dynamic Context Model of Interactive Behavior. Cognitive Science. [PDF] [Abstract]
A dynamic context model of interactive behavior was developed to explain results from two experiments
that tested the effects of interaction costs on encoding strategies, cognitive representations,
and response selection processes in a decision-making and a judgment task. The model assumes that
the dynamic context defined by the mixes of internal and external representations and processes are
sensitive to the interaction cost imposed by the task environment. The model predicts that changes in
the dynamic context may lead to systematic biases in cognitive representations and processes that
eventually influence decision-making and judgment outcomes. Consistent with the predictions by the
model, results from the experiments showed that as interaction costs increased, encoding strategies
and cognitive representations shifted from perception-based to memory-based. Memory-based comparisons
of the stimuli enhanced the similarity and dominance effects, and led to stronger systematic
biases in response outcomes in a choice task. However, in a judgment task, memory-based representations
enhanced only the dominance effects. Results suggested that systematic response biases in the
dominance context were caused by biases in the cognitive representations of the stimuli, but response
biases in the similarity context were caused by biases in the comparison process induced by the
choice task. Results suggest that changes in interaction costs not only change whether information
was assessed from the external world or from memory but also introduce systematic biases in the cognitive
representation of the information, which act as biased inputs to the subsequent decision-making
and judgment processes. Results are consistent with the idea of interactive cognition, which proposes
that representations and processes are contingent on the dynamic context defined by the information
flow between the external task environment and internal cognition.
Fu, W.-T., Chin, J., Dong, W., & liao, Q. V. (2011). Interactive Skills. In N. M. Seel (Ed.), Encyclopedia of the Sciences of Learning, Springer-Verlag. [PDF]
Fu, W.T., Rong, P., Lee, H.K., Kramer, A., & Graybiel, A. (2011). A Computational Model of Complex Skill Learning in Varied-Priority Training. In Proceedings of the 33rd Annual conference of the Cognitive Science Society. [PDF] [Abstract]
We reported a computational model of complex skill learning
that captures the differential effects of Fixed Priority (FP) and
Varied Priority (VP) training on complex skill learning. The
model is developed based on learning mechanisms associated
with the modular circuits linking Basal Ganglia, the prefrontal
association cortex, and the pre-motor cortex during skill
learning. Two forms of learning occur simultaneously. In
discrimination learning, goal-directed actions are selected
through recognition of external stimuli through the
connections between the frontal cortex and the striatum, and
is mediated by dopaminergic signals through a reinforcement
learning mechanism. With practice, skill learning shifts from
discrimination learning to Hebbian learning, which directly
associates stimuli to responses by strengthening the
connection between the prefrontal and pre-motor cortex. The
model shows that FP training, in which all task components
are equally weighted during training, leads to less flexible
discrimination learning than VP training. The model explains
why VP training benefits lower performance participants
more, and why learning was more strongly correlated with the
size of the striatum in VP than FP training.
Liao, V. Q. & Fu, W.-T. (2011). Effects of Aging and Individual Differences on Credibility Judgment of Online Health Information. In Proceedings of the 33rd Annual conference of the Cognitive Science Society.
Liao, V.Q. & Fu, W.-T. (2011). The Impact of User Reviews on Older and Younger Adults' Attitude towards Online Medication Information. In Proceedings of the 33rd Annual conference of the Cognitive Science Society. [PDF] [Abstract]
A laboratory study was conducted to study whether the presence of online user reviews, specifically its interaction with the credibility of information on the Website, has differential impact on younger and older adults' attitude towards medication information on the Internet. Results showed that while there was age difference in how message contents and website features influenced credibility judgments, the presence of user reviews moderated the age difference. Specifically we found: 1) when credibility cues in user reviews were consistent with the credibility cues in Web page contents, older adults’ attitude towards the medication was reinforced more than younger adults, and 2) when the credibility cues in user reviews were inconsistent with the credibility cues in Web page contents, older adults were less sensitive to the influence of user reviews. Especially when highly positive user reviews were given to a seemingly non-credible medication, older adults were less likely to be swayed by user reviews. Possible causes of this age difference in the effects of user reviews were discussed. Results have important implications for the dual-process model of information processing and age differences in attitude change in the context of Internet.
Dong, W., & Fu, W.-T. (2011). Conflict Resolution in Remote Collaborative Work: A Comparison of Different Computer Mediated Communication Methods. In Proceedings of the 33rd Annual conference of the Cognitive Science Society. [PDF] [Abstract]
We compared the effects of text-, audio- and video-based
communication methods on how people performed an
appointment-scheduling task that involved both a cooperative
and a conflict resolution component. The results showed that
video-based communication method was more supportive of
cooperative tasks when the task difficulty was high, and when
there were more inherent conflicts in the task, in which more
negotiation was required to resolve the conflicts. As a result,
performance difference of the dyad was smaller in video
communication. Different patterns of conversation dynamics
and problem space visitations further supported the effect of
communication methods. Results of this study have important
implications in understanding the process of collaborative
problem solving and conflict resolution when different
communication channels were used for remote collaborators.
Bertal, S., Lee, H. K., & Fu, W.-T. (2011). Sequential Integration of Object Locations in a Spatial Updating and Reasoning Task. In Proceedings of the 33rd Annual conference of the Cognitive Science Society. [PDF] [Abstract]
We present results from an experiment studying how people
mentally integrated partial configurations of objects shown
across a sequence of displays with varying matches between
frames of reference. Consistent with previous research on
spatial updating, performance was better when the frame of
reference in the final display aligned with the main display
axes (up/down, left/right) than when it aligned with the
diagonal axes. However, we also found that spatial updating
was more efficient when the sequence of presentation of
objects was consistent with the final frame of reference from
which objects were integrated. Results suggested that spatial
updating depended on the sequence of spatial operations
required to integrate new spatial information into existing
ones. Implications to theories of spatial updating in reasoning
tasks are discussed.
Chin, J., & Fu, W.-T. (2011). To go or to stay? Age differences in Cognitive Foraging. In Proceedings of the 33rd Annual conference of the Cognitive Science Society. [PDF] [Abstract]
The study used the word search puzzle paradigm to
investigate the cognitive foraging behavior among younger
and older adults. Older adults had equivalent search
performance with younger adults regardless of their decline in
processing speed. Older adults tended to switch fewer times
and persist longer in the patch than younger adults. Results
further showed that switch behavior was based on the
individual reflection of information uptake, which long
exploitation in the patch of older adults could not be
explained solely by general slowing but their higher tolerance
of the decreasing marginal rate of gain. Overall, older adults
expected to reach higher gains than younger adults before
leaving the current patch. The age-dependent adaptive
foraging behavior was also discussed.
Fu, W.-T., & liao, Q. V. (2011). Quality Control of Online Information: A Quality-based Cascade Model. Paper presented at the International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction. [PDF] [Abstract]
We extend previous cascade models of social influence to investigate
how the exchange of quality information among users may moderate cascade
behavior, and the extent to which it may influence the effectiveness of collective
user recommendations on quality control of information. We found that
while cascades do sometimes occur, their effects depend critically on the accuracies
of individual quality assessments of information contents. Contrary to
predictions of cascade models of information flow, quality-based cascades tend
to reinforce the propagation of individual quality assessments rather than being
the primary sources that drive the assessments. We found even small increase in
individual accuracies will significantly improve the overall effectiveness of
crowdsourcing quality control. Implication to domains such as online health
information Web sites or product reviews are discussed.
Liao, Q. V., & Fu, W.-T. (2011). How User Reviews Influence Older and Younger Adults' Credibility Judgments of Online Health Information In Proceedings of the 29th international conference on Human factors in computing systems (CHI), Vancouver, BC. [Third Prize in Research Competition]
Dong, W., & Fu, W.-T. (2011). Cultural Difference in Image Searching. Paper presented at the 29th international conference on Human factors in computing systems (CHI), Vancouver, BC. [Second Prize in Research Competition]
Fu, W.-T. (2011). An Agent-based Model of Information Cascades. Paper presented at the Human Social Cultural Modeling, Chantilly, VA.
Zhang, Y., & Fu, W.-T. (2011). Designing consumer health information retrieval systems: What user-generated questions tell us? . Paper presented at the International Conference of Human-Computer Interaction (HCII), Orlando, FL.
Javadi, E., & Fu, W.-T. (2011). Idea Visibility, Information Diversity, and Idea Integration in Electronic Brainstorming. Paper presented at the International Conference on Human-Computer Interaction, Orlando, FL.
Petry, J., L. Thomas, L., Park, H., & Fu, W.-T. (2011). The Role of Expertise in VFR Flight Decisions with Inconsistent Weather Information. In Proceedings of the 16th International Symposium on Aviation Psychology, Dayton, OH.
Fu, W.-T., & Dong, W. (in press). From Collaborative Indexing to Knowledge Exploration: A Social Learning Model. IEEE Intelligent Systems.
Fu, W.-T., Kannampalli, T. G., Kang, R., & He, J. (2010). Semantic imitation in social tagging. ACM Transactions on Computer-Human Interaction. [PDF] [Abstract]
We present a semantic imitation model of social tagging and exploratory search based on theories of cognitive sciences. The model assumes that social tags evoke a spontaneous tag-based topic inference process that primes the semantic interpretation of resource contents during exploratory search, and the semantic priming of existing tags in turn influences future tag choices. The model predicts that (1) users who can see tags created by others tend to create tags that are semantically similar to these existing tags, demonstrating the social influence of tag choices; and (2) users who have similar information goals tend to create tags that are semantically similar, but this effect is mediated by the semantic representation and interpretation of social tags. Results from the experiment comparing tagging behavior between a social group (where participants can see tags created by others) and a nominal group (where participants cannot see tags created by others) confirmed these predictions. The current results highlight the critical role of human semantic representations and interpretation processes in the analysis of large-scale social information systems. The model implies that analysis at both the individual and social levels are important for understanding the active, dynamic processes between human knowledge structures and external folksonomies. Implications on how social tagging systems can facilitate exploratory search, interactive information retrievals, knowledge exchange, and other higher-level cognitive and learning activities are discussed.
Fu, W.-T., & Dong, W. (2010). Facilitating knowledge exploration in folksonomies: Expertise ranking by link and semantic structures. In Proceedings of the 2010 International Conference on Computational Science and Engineering, Minneapolis, MN. [PDF] [Abstract]
We developed user models of knowledge exploration in a social tagging system to test the expertise rankings generated by a link-structure method and a semantic-structure method. The link-structure method assumed a referential definition of expertise, in which experts were users who tagged resources that were frequently tagged by other experts; the semantic-structure method assumed a representational definition of expertise, in which experts were users who had better knowledge of a particular domain and were better at assigning distinctive tags associated with certain domain-specific resources. Simulations results showed that the two methods of expert identification, although based on different assumptions, were in general consistent but did show significant differences. As expected, the link-structure method was better at facilitating exploration of popular "hot" topics than the semantic-structure method. However, the semantic-structure method was better at guiding users to find less popular “cold” topics than the link-structure method. Resources tagged by domain experts could contain cold topics that were associated with high quality tags, but these resources were less likely highlighted by the link-structure method. We argue that to facilitate knowledge exploration in social tagging systems, it is important to keep a good balance between helping user to follow hot topics and to discover cold topics by including expertise rankings generated by both link and semantic structures.
Fu, W.-T., Kannampallil, T., & Kang, R. (2010). Facilitating Exploratory Search by Model-Based Navigational Cues. In Proceedings of the International Conference on Intelligent User Interfaces, Hong Kong, China. [PDF] [Abstract]
We present an extension of a computational cognitive model of social tagging and exploratory search called the semantic imitation model. The model assumes a probabilistic representation of semantics for both internal and external knowledge, and utilizes social tags as navigational cues during exploratory search. We used the model to generate a measure of information scent that controls exploratory search behavior, and simulated the effects of multiple presentations of navigational cues on both simple information retrieval and exploratory search performance based on a previous model called SNIF-ACT. We found that search performance can be significantly improved by these model-based presentations of navigational cues for both experts and novices. The result suggested that exploratory search performance depends critically on the match between internal knowledge (domain expertise) and external knowledge structures (folksonomies). Results have significant implications on how social information systems should be designed to facilitate knowledge exchange among users with different background knowledge.
Kang, R., & Fu, W.-T. (2010). Exploratory Information Search by Domain Experts and Novices. In Proceedings of the International Conference on Intelligent User Interfaces, Hong Kong, China.
Dong, W., & Fu, W.-T. (2010). Toward a cultural-sensitive image tagging tools. In Proceedings of the International Conference on Intelligent User Interfaces, Hong Kong, China.
Chin, J. & Fu, W.-T. (2010). Interactive Effects of Age and Interface Differences on Search Strategies and Performance. In Proceedings of the ACM Conference on Computer-Human Interaction, Atlanta, GA. [PDF] [Abstract]
We present results from an experiment that studied the information search behavior of younger and older adults in a medical decision-making task. To study how different combination of tasks and interfaces influenced search strategies and decision-making outcomes, we varied information structures of two interfaces and presented different task descriptions to participants. We found that younger adults tended to use different search strategies in different combination of tasks and interfaces, and older adults tended to use the same top-down strategies across conditions. We concluded that older adults were able to perform mental transformation of medical terms more effectively than younger adults. Thus older adults did not require changing strategies to maintain the same level of performance.
Kang, R., Fu, W.-T., & Kannampallil, T. (2010). Exploiting Knowledge-in-the-head and Knowledge-in-the-social-web: Effects of Domain Expertise on Exploratory Search in Individual and Social Search Environments. In Proceedings of the ACM Conference on Computer-Human Interaction, Atlanta, GA. [PDF] [Abstract]
Our study examined how experts and novices performed exploratory search using a traditional search engine and a social tagging system. As expected, results showed that social tagging systems could facilitate exploratory search for both experts and novices. We, however, also found that experts were better at interpreting the social tags and generating search keywords, which made them better at finding information when they were using the two interfaces. Specifically, experts found more general information than novices by better interpretation of social tags; and experts found more domain-specific information than novices by generating better keywords when using the search engine. We found a dynamic interaction between knowledge-in-the-head and knowledge-in-the-social-web, and demonstrated that although information seekers are becoming more and more reliant on information from the social Web, domain expertise is still important in guiding them to find information and evaluate the relevance of information. Implications on the design of social search systems that facilitate exploratory search are discussed.
Dong, W. & Fu, W.-T. (2010). Cultural Difference in Image Tagging. In Proceedings of the ACM Conference on Computer-Human Interaction, Atlanta, GA. [PDF] [Abstract]
Do people from different cultures tag digital images differently? The current study compared the content of tags for digital images created by two cultural groups: European Americans and Chinese. In line with previous findings on cultural differences in attentional patterns, we found similar cultural differences in the order of the image parts (e.g., foreground or background objects) that people tag. We found that for European Americans, the first tag was more likely assigned to the main objects than that by Chinese; but for Chinese, the first tag was more likely assigned to the overall description or relations between objects in the images. The findings had significant implications for designing cultural-sensitive tools to facilitate the tagging and search process of digital media, as well as for developing data-mining tools that identify user profiles based on their tagging patterns and cultural origins.
Wang, Y., Dong, W., & Fu, W.-T. (2010). To Customize or Not to Customize? The Use of a Customization Tool to Augment Information Indexing in a Computer Desktop Environment. In Proceedings of the 54th conference of the Human Factors and Ergonomics Society. [PDF] [Abstract]
We studied when and how people will use a customization tool that helps users offload information indexing to the external environment to augment finding and re-finding of information in a computer desktop environment. An experiment was conducted to study how the cost and benefit of customization may influence when and how participants customize, and how the customization may help them find and re-find information. Results showed that participants were sensitive to the cost and benefit of customization. In general, participants performed more customization when the cost was low and when the benefit was high. Customization was also found to influence their information indexing strategy. Implications to design of customization tools for information indexing were discussed.
Waicekauskas, K., Kannampallil, T. G., Kopren, K., Tan, P.-H., Fu, W.-T., & Morrow, D. (2010). Collaborative Tools in a Simulated Patient-Provider Medication Scheduling Task. Paper presented at the 54th conference of the Human Factors and Ergonomics Society, San Francisco, CA. [PDF] [Abstract]
Medication adherence is an essential activity for successful self-care, particularly for older adults who take multiple medications. Adherence depends on understanding how to take medication, which in turn depends on effective communication with providers. Unfortunately, physician and patient communication is often substandard and ineffective. Furthermore, successful adherence is often tied to supporting the patient's prospective memory by integrating medication taking with a daily routine. We have developed a paper-based tool (MedTable) for supporting provider-patient collaborative planning about taking medication, which has improved performance in a simulated medication scheduling task. The tool is used as an external workspace that reduces cognitive demands while also facilitating collaboration in a planning task. In the current study, the MedTable was redesigned and an electronic version was also developed. Both tools were compared to a less structured paper tool similar to medication reconciliation cards used in many health care settings (Medcard). 144 community dwelling older adults (aged 60 and over) participated in pairs in a simulated patient-provider medication scheduling task. Each pair solved four medication scheduling problems (2 simple and 2 complex) using one of the three tools (MedTable, e-MedTable, Medcard). Although all three tools supported highly accurate solutions, the MedTable produced significantly more accurate schedules than the Medcard (there were no tool differences in solution time). Moreover, participants rated workload associated with problem solving as lower for the two structured tools compared to the Medcard. The MedTable was also rated more usable than the non-structured aid. Finally, there was no evidence that older adults had difficulty using the computer-based tool, which suggests that a computer-based tool could be an effective intervention for improving provider-patient collaboration.
Wang, Yi, Moon, M., Fu, W.-T., Boot, W., Erickson, K., & Kramer, A. (2010). Effects of Varied Priority Training on Complex Perceptual-Motor Learning. In Proceedings of the 32nd Annual Conference of the Cognitive Science Society.
D'Andrea, L. & Fu, W.-T. (2010). The Effects of Communication Medium Upon Collaborative Orientation Task Performance. In Proceedings of the 32nd Annual Conference of the Cognitive Science Society.
Moon, M. & Fu, W.-T. (2010). Adaptive Information Indexing in Re-finding Information. In Proceedings of the 32nd Annual Conference of the Cognitive Science Society.
D'Andrea, L., Bertel, S., & Fu, W.-T. (2010). Collaborative Orientation Task Performance: Effects of Communication Medium and Relative Spatial Abilities. Paper presented at the Spatial Cognition conference.
Fu, W.-T. & Kannampallil, T. (2009). Harnessing Web 2.0 for context-aware learning: The impact of social tagging system on knowledge adaption. In N. Lambropoulos and R. Margarida (Eds.), Educational Social Software for Context-Aware Learning: Collaborative Methods and Human Interaction. IGI Global.
Fu, W.-T., Kannampallil, T. G., Kang, Ruogu (2009), A Semantic Imitation Model of Social Tag Choices. In Proceedings of the 2009 International Conference on Social Computing, pp. 66-72, Vancouver, BC. [PDF] [Abstract]
We describe a semantic imitation model of social tagging that integrates formal representations of semantics and a stochastic tag choice process to explain and predict emergent behavioral patterns. The model adopts a probabilistic topic model to separately represent external word-topic and internal word-concept relations. These representations are coupled with a tag-based topic inference process that predicts how existing tags may influence the semantic interpretation of a document. The inferred topics influence the choice of tags assigned to a document through a random utility model of tag choices. We show that the model is successful in explaining the stability in tag proportions across time and power-law frequency-rank distributions of tag co-occurrences for semantically general and narrow tags. The model also generates novel predictions on how emergent behavioral patterns may change when users with different domain expertise interact with a social tagging system. The model demonstrates the weaknesses of single-level analyses and highlights the importance of adopting a multi-level modeling approach to explain online social behavior.
Chin, J., Fu, W.-T., & Kannampallil, T. (2009). Adaptive Information Search: Age-Dependent Interactions between Cognitive Profiles and Strategies. In Proceedings of the 27th annual conference of ACM Computer-Human Interaction (CHI) conference, Boston, MA, US. [PDF] [Abstract]
Previous research has shown that older adults performed worse in web search tasks, and attributed poorer performance to a decline in their cognitive abilities. We conducted a study involving younger and older adults to compare their web search behavior and performance in illdefined and well-defined information tasks using a health information website. In ill-defined tasks, only a general description about information needs was given, while in well-defined tasks, information needs as well as the specific target information were given. We found that older adults performed worse than younger adults in well-defined tasks, but the reverse was true in ill-defined tasks. Older adults compensated for their lower cognitive abilities by adopting a top-down knowledge-driven strategy to achieve the same level of performance in the ill-defined tasks. Indeed, path analysis showed that cognitive abilities, health literacy, and knowledge influenced search strategies adopted by older and younger adults. Design implications are also discussed.
Fu, W.-T. & Kannampallil, T. (2009). Harnessing Web 2.0 for context-aware learning: The impact of social tagging system on knowledge adaption. In N. Lambropoulos and R. Margarida (Eds.), Educational Social Software for Context-Aware Learning: Collaborative Methods and Human Interaction. IGI Global.
Moon, J. M., & Fu, W.-T. (2009). Effects of spatial locations and luminance on finding and re-finding information in a desktop environment. In Proceedings of the 27th annual conference of ACM Computer-Human Interaction (CHI) conference, Boston, MA, US.
Kang, R., Kannampallil, T., He, J ,& Fu, W.-T. (2009). Conformity out of Diversity: Dynamics of Information Needs and Social Influence of Tags in Exploratory Information Search. In Proceedings of the International conference of Human-Computer Interaction, CA: San Diego, US. [PDF] [Abstract]
We studied the dynamic effects of information needs and social influence of tags in an exploratory search task. Although initially differences in information needs led to diversity in tag choices, this diversity disappeared as participants collaboratively tagged the same set of resources. Our findings are in general consistent with the notion that people conform to the collective interpretation of contents in an information system. In addition, our results showed that conformity does not only arise out of imitation of behavior, but also from the same underlying semantic interpretation or knowledge structures of users as they engage in informal collaboration through the social tagging system. Implications for design of social information system are discussed.
Kannampallil, T., & Fu, W.-T. (2009). Trail Patterns in Social Tagging Systems: Role of Tags as Digital Pheromones. In Proceedings of the International conference of Human-Computer Interaction, CA: San Diego, US.
Fu, W.-T., & Park, H. (2009). The role of information seeking in risk assessment. In Proceedings of the Annual Conference of the Society of Judgment and Decision Making, Boston, MA.
Chin, J. & Fu, W.-T. (2009). Age-Dependent Interactions Between Cognitive Profiles and Information Search Strategies. In Proceedings of the Annual Meeting of the Psychonomics Society, Boston, MA.
Fu, W.-T., Anderson, J. (2008). Dual Learning Processes in Interactive Skill Acquisition. Journal of Experimental Psychology, Applied, 14 (2), 179-191.[PDF] [Abstract]
Acquisition of interactive skills involves the use of internal and external cues. Experiment 1 showed that when actions were interdependent, learning was effective with and without external cues in the single-task condition but was effective only with the presence of external cues in the dual-task condition. In the dual-task condition, actions closer to the feedback were learned faster than actions farther away but this difference was reversed in the single-task condition. Experiment 2 tested how knowledge acquired in single and dual-task conditions would transfer to a new reward structure. Results confirmed the two forms of learning mediated by the secondary task: A declarative memory encoding process that simultaneously assigned credits to actions and a reinforcement-learning process that slowly propagated credits backward from the feedback. The results showed that both forms of learning were engaged during training, but only at the response selection stage, one form of knowledge may dominate over the other depending on the availability of attentional resources.
Fu, W.-T., Anderson, J. (2008), Solving the Credit Assignment Problem: Explicit and Implicit Learning of Action Sequences with Probabilistic Outcomes. Psychological Research, 72 (3), 321-330. [PDF] [Abstract]
In most problem-solving activities, feedback is received at the end of an action sequence. This creates a credit-assignment problem where the learner must associate the feedback with earlier actions, and the interdependencies of actions require the learner to remember past choices of actions. In two studies, we investigated the nature of explicit and implicit learning processes in the credit-assignment problem using a probabilistic sequential choice task with and without a secondary memory task. We found that when explicit learning was dominant, learning was faster to select the better option in their Wrst choices than in the last choices. When implicit reinforcement learning was dominant, learning was faster to select the better option in their last choices than in their Wrst choices. Consistent with the probability learning and sequence-learning literature, the results show that credit assignment involves two processes: an explicit memory encoding process that requires memory rehearsals and an implicit reinforcement-learning process that propagates credits backwards to previous choices.
Fu, W.-T. (2008). Is a single-bladed knife enough to dissect cognition? Cognitive Science, 32 (1), 155-161. [PDF] [Abstract]
Griffiths, Christian, and Kalish (this issue) present an iterative-learning paradigm applying aBayesian model to understand inductive biases in categorization. The authors argue that the paradigm is useful as an exploratory tool to understand inductive biases in situations where little is known about the task. It is argued that a theory developed only at the computational level is much like a single-bladed knife that is only useful in highly idealized situations. To be useful as a general tool that cuts through the complex fabric of cognition, we need at least two-bladed scissors that combine both computational and psychological constraints to characterize human behavior. To temper its sometimes expansive claims, it is time to show what a Bayesian model cannot explain. Insight as to how human reality may differ from the Bayesian predictions may shed more light on human cognition than the simpler focus on what the Bayesian approach can explain. There remains much to be done in terms of integrating Bayesian approaches and other approaches in modeling human cognition.
Fu, W.-T. (2008). The microstructures of social tagging: A rational model. In Proceedings of the ACM 2008 conference on Computer Supported Cooperative Work (CSCW), pp 229-238. San Diego, CA, US. [PDF] [Abstract]
This article presents a rational model developed under the distributed cognition framework that explains how social tags influence knowledge acquisition and adaptation in exploratory ill-defined information tasks. The model provides integrated predictions on the interactions among link selections, use and creation of tags, and the formation of mental categories. The model shows that the quality of tags not only influences search efficiency, but also the quality of mental categories formed during exploratory search. In addition, the model shows that aggregate regularities can be explained by microstructures of behavior that emerged from the adaptive assimilation of concepts and categories of multiple users through the social tagging system. The model has important implications on how collaborative systems could influence higher-level cognitive activities.
Fu, W.-T. (2008). How adaptive is consumer sequential decision making? In Proceedings of the Annual Conference of the Society of Judgment and Decision Making, Chicago, IL, US.
Fu, W.-T. (2008). SNIF-DM: A Cognitive Model of Information Seeking and Decision Making on the World Wide Web. In Proceedings of the 2nd International Conference on Applied Human Factors, Las Vegas, NV, US.
Moon, M., & Fu, W.-T. (2008). A situated cognitive model of the routine evolution of skills. In Proceedings of the 52nd Conference of the Human Factors and Ergonomics Society, New York, NY.
Fu, W.-T., Pirolli, P. (2007), SNIF-ACT: A Model of Information-Seeking Behavior in the World Wide Web. Human-Computer Interaction, 22, 355-412. [PDF] [Abstract]
How do humans or animals adapt to a new environment? After years of research, it is embarrassing how little we understand the underlying processes of adaptation: just look at how difficult it is to build a robot that learns to navigate in a new environment or to teach someone to master a second language. It is amazing how seagulls and vultures have learned to be landfill scavengers in the last century and be able to sort through human garbage to dig out edible morsels. At the time this chapter is written, an alligator is found in the city park of Los Angeles, outwitting licensed hunters who tried to trap the alligator for over 2 months. The ability to adapt to new environments goes beyond hardwired processes and relies on the ability to acquire new knowledge of the environment. An important step in the adaptation process is to sample the effects of possible actions and world states so that the right set of actions can be chosen to attain important goals in the new environment.
Fu, W.-T. (2007), Adaptive Tradeoffs Between Exploration and Exploitation: A Rational-Ecological Approach. In W. D. Gray (Ed.), Integrated Models of Cognitive Systems. Oxford: Oxford University Press. [PDF] [Abstract]
We describe the development of a computational cognitive model that explains navigation behavior on the World Wide Web. The model, called SNIF-ACT (Scent-basedNavigation and Information Foraging in the ACT cognitive architecture), is motivated by Information Foraging Theory (IFT), which quantifies the perceived relevance of aWeb link to a user’s goal by a spreading activation mechanism. The model assumes that users evaluate links on a Web page sequentially and decide to click on a link or to go back to the previous page by a Bayesian satisficing model (BSM) that adaptively evaluates and selects actions based on a combination of previous and current assessments of the relevance of link texts to information goals. SNIF-ACT 1.0 utilizes the measure of utility, called informationscent, derived from IFT to predict rankings of links on different Web pages. The model was tested against a detailed set of protocol data collected from 8 participants as they engaged in two information-seeking tasks using the World Wide Web. The model provided a good match to participants’ link selections. In SNIF-ACT 2.0, we included the adaptive link selection mechanism from the BSM that sequentially evaluates links on a Web page. The mechanism allowed the model to dynamically build up the aspiration levels of actions in a satisficing process (e.g., to follow a link or leave aWeb site) as it sequential assessed link texts on aWeb page. The dynamic mechanism provides an integrated account of how and when users decide to click on a link or leave a page based on the sequential, ongoing experiences with the link context on current and previous Web pages. SNIF-ACT 2.0 was validated on a data set obtained from 74 subjects. Monte Carlo simulations of the model showed that SNIF-ACT 2.0 provided better fits to human data than SNIF-ACT 1.0 and a Position model that used position of links on aWeb page to decide which link to select.We conclude that the combination of the IFT and the BSMprovides a good description of user–Web interaction. Practical implications of the model are discussed.
Miller, S. & Fu, W.-T. (2007). The role of temporal sequence learning in guiding visual attention allocation. In Proceedings of the 51st Conference of the Human Factors and Ergonomics Society, Baltimore, MD, US. [PDF] [Abstract]
Models of visual attention allocation suggest that monitoring is driven primarily by proximal cues like bandwidth and value. However, these cues might not always be predictive of the meaningful events an operator is asked to monitor. The aim of the current study is to extend visual sampling models by studying whether sampling can be influenced by more distal cues, like detecting patterns in the monitored signal, when proximal cues, like bandwidth, are not predictive of the meaningful events the operator is asked to monitor. Ten participants completed a task based on Senders’ (1964) experiment where operators were asked to monitor a series of four gauges to detect when the gauges traveled into the alarm region. The performance results suggest that participants could successfully adapt to the temporal sequence. However, participants did not show explicit awareness of the sequence, indicating that this type of learning could, in some cases, be implicit. Implications for display design and training are discussed.
Fu, W.-T., Gray, W. D. (2006), Suboptimal tradeoffs in information-seeking. Cognitive Psychology, 52, 195-242. [PDF] [Abstract]
Explicit information-seeking actions are needed to evaluate alternative actions in problem-solving tasks. Information-seeking costs are often traded off against the utility of information. We present three experiments that show how subjects adapt to the cost and information structures of environments in a map-navigation task. We found that subjects often stabilize at suboptimal levels of performance. A Bayesian satisficing model (BSM) is proposed and implemented in the ACT-R architecture to predict information-seeking behavior. The BSM uses a local decision rule and a global Bayesian learning mechanism to decide when to stop seeking information. The model matched the human data well, suggesting that adaptation to cost and information structures can be achieved by a simple local decision rule. The local decision rule, however, often limits exploration of the environment and leads to suboptimal performance. We propose that suboptimal performance is an emergent property of the dynamic interactions between cognition and the environment.
Fu, W.-T., Anderson, J. R. (2006), From recurrent choice to skilled learning: A reinforcement learning model. Journal of Experimental Psychology: General, 135(2), 184-206. [PDF] [Abstract]
The authors propose a reinforcement-learning mechanism as a model for recurrent choice and extend it to account for skill learning. The model was inspired by recent research in neurophysiological studies of the basal ganglia and provides an integrated explanation of recurrent choice behavior and skill learning. The behavior includes effects of differential probabilities, magnitudes, variabilities, and delay of reinforcement. The model can also produce the violation of independence, preference reversals, and the goal gradient of reinforcement in maze learning. An experiment was conducted to study learning of action sequences in a multistep task. The fit of the model to the data demonstrated its ability to account for complex skill learning. The advantages of incorporating the mechanism into a larger cognitive architecture are discussed.
Fu, W.-T., Bothell, D., Douglass, S., Haimson, C., Sohn, M.-H., Anderson, J. A. (2006), Toward a real-time model-based training system. Interacting with Computers, 18(6), 1216-1230. [PDF] [Abstract]
This article describes the development of a real-time model-based training system that provides adaptive ''over-the-shoulder'' (OTS) instructions to trainees as they learn to perform an Anti-Air Warfare Coordinator (AAWC) task. The long-term goal is to develop a system that will provide real-time instructional materials based on learners’ actions, so that eventually the initial set of instructions on a task can be strengthened, complemented, or overridden at different stages of training. The training system is based on the ACT-R architecture, which serves as the theoretical background for the cognitive model that monitors the learning process of the trainee. An experiment was designed to study the impact of OTS instructions on learning. Results showed that while OTS instructions facilitated short-term learning, (a) they took time away from the processing of current information, (b) their effects tended to decay rapidly in initial stages of training, and (c) their effects on training diminished when the OTS instructions were proceduralized in later stages of training. A cognitive model that learned from both theupfront and OTS instructions was created and provided good fits to the learning and performance data collected from human participants. Our results suggest that to fully capture the symbiotic performance between humans and intelligent training systems, it is important to closely monitor the learning process of the trainee so that instructional interventions can be delivered effectively at different stages of training. We proposed that such a flexible system can be developed based on an adaptive cognitive model that provides real-time predictions on learning and performance.
Gray, W. D., Sims, C. R., Fu, W.-T., Schoelles, M. J. (2006), The soft constraints hypothesis: A rational analysis approach to resource allocation for interactive behavior. Psychological Review, 113(3), 461-482. [PDF] [Abstract]
Soft constraints hypothesis (SCH) is a rational analysis approach that holds that the mixture of perceptual-motor and cognitive resources allocated for interactive behavior is adjusted based on temporal cost-benefit tradeoffs. Alternative approaches maintain that cognitive resources are in some sense protected or conserved in that greater amounts of perceptual-motor effort will be expended to conserve lesser amounts of cognitive effort. One alternative, the minimum memory hypothesis (MMH), holds that people favor strategies that minimize the use of memory. SCH is compared with MMH across 3 experiments and with predictions of an Ideal Performer Model that uses ACT-R's memory system in a reinforcement learning approach that maximizes expected utility by minimizing time. Model and data support the SCH view of resource allocation; at the under 1000-ms level of analysis, mixtures of cognitive and perceptual-motor resources are adjusted based on their cost-benefit tradeoffs for interactive behavior.
Fu, W.-T., Anderson, J. R. (2006), Solving the credit assignment problem: Explicit and implicit learning with internal and external state information. Proceedings of the 28th Annual Conference of the Cognitive Science Society. Hillsdale, NJ: LEA.
Fu, W.-T., Gonzalez, C. (2006), Learning to control dynamic systems: Information utilization and future planning. Proceedings of the 28th Annual Conference of the Cognitive Science Society. Hillsdale, NJ: LEA.
Fu, W.-T., Gonzalez, C, Healy, A., Kole, J., Bourne, L. (2006), Building predictive human performance models of skill acquisition in a data entry task. Proceedings of the 50th Annual Meeting of the Human Factors and Ergonomics Society (pp. 1122-1126). Santa Monica, CA: Human Factors and Ergonomics Society. [PDF] [Abstract]
This paper presents a predictive model of a simple, but important, data entry task. The task requires participants to perceive and encode information on the screen, locate the corresponding keys for the information on different layouts of the keyboard, and enter the information. Since data entry is a central component in most human-machine interaction, a predictive model of performance will provide useful information that informs interface design and effectiveness of training. We created a cognitive model of the data entry task based on the ACT-R 5.0 architecture. The same model provided good fits to three existing data sets, which demonstrated the effects of fatigue with prolonged work, repetition priming, depth of processing, and the suppression of subvocal rehearsal. The model also makes predictions on how performance deteriorates with different delays after training, how different amounts of rehearsal during training affect retention, and how re-training helps retention of skills.using either the keypad on the right-hand side of the computer keyboard or the number row on the top of the keyboard. In some cases, they respond instead by typing the initial letters of each word (e.g., f e t s). Typically, no feedback concerning the accuracy of the responses is provided to the subjects, and they do not see their typed responses. There are three major component-processing stages in the data-entry task: encoding, response preparation, and response execution. Encoding involves perceptual processes, response preparation involves the mental construction of a motor program for entering the sequence, and response execution involves the actual motoric button presses.
Fu, W.-T. (2006), Adaptive acquisition of enactive knowledge. Proceedings of the Third International Conference on Enactive Interfaces, Montpellier, France.
Fu, W.-T., Gray, W. D. (2004), Resolving the paradox of the active user: Stable suboptimal performance in interactive tasks. Cognitive Science, 28(6), 901-935. [PDF] [Abstract]
This paper brings the intellectual tools of cognitive science to bear on resolving the "paradox of the active user" [Interfacing Thought: Cognitive Aspects of Human–Computer Interaction, Cambridge, MIT Press, MA, USA]—the persistent use of inefficient procedures in interactive tasks by experienced or even expert users when demonstrably more efficient procedures exist. The goal of this paper is to understand the roots of this paradox by finding regularities in these inefficient procedures. We examine three very different data sets. For each data set, we first satisfy ourselves that the preferred procedures used by some subjects are indeed less efficient than the recommended procedures. We then amass evidence, for each set, and conclude that when a preferred procedure is used instead of a more efficient, recommended procedure, the preferred procedure tends to have two major characteristics: (1) the preferred procedure is a well-practiced, generic procedure that is applicable either within the same task environment in different contexts or across different task environments, and (2) the preferred procedure is composed of interactive components that bring fast, incremental feedback on the external problem states. The support amassed for these characteristics leads to a new understanding of the paradox. In interactive tasks, people are biased towards the use of general procedures that start with interactive actions. These actions require much less cognitive effort as each action results in an immediate change to the external display that, in turn, cues the next action. Unfortunately for the users, the bias to use interactive unit tasks leads to a path that requires more effort in the long run. Our data suggest that interactive behavior is composed of a series of distributed choices; that is, people seldom make a once-and-for-all decision on procedures. This series of biased selection of interactive unit tasks often leads to a stable suboptimal level of performance.
Gray, W. D., Fu, W.-T. (2004), Soft constraints in interactive behavior: The case of ignoring perfect knowledge in-the-world for imperfect knowledge in-the-head. Cognitive Science, 28(3), 359-382. [PDF] [Abstract]
Constraints and dependencies among the elements of embodied cognition form patterns or microstrategies of interactive behavior. Hard constraints determine which microstrategies are possible. Soft constraints determine which of the possible microstrategies are most likely to be selected. When selection is non-deliberate or automatic the least effort microstrategy is chosen. In calculating the effort required to execute a microstrategy each of the three types of operations, memory retrieval, perception, and action, are given equal weight; that is, perceptual-motor activity does not have a privileged status with respect to memory. Soft constraints can work contrary to the designer's intentions by making the access of perfect knowledge in-the-world more effortful than the access of imperfect knowledge in-the-head. These implications of soft constraints are tested in two experiments. In experiment 1 we varied the perceptual-motor effort of accessing knowledge in-the-world as well as the effort of retrieving items from memory. In experiment 2 we replicated one of the experiment 1 conditions to collect eye movement data. The results suggest that milliseconds matter. Soft constraints lead to a reliance on knowledge in-the-head even when the absolute difference in perceptual-motor versus memory retrieval effort is small, and even when relying on memory leads to a higher error rate and lower performance. We discuss the implications of soft constraints for routine interactive behavior, accounts of embodied cognition, and tool and interface design.
Fu, W.-T., Anderson, J. R. (2004), Extending the computational abilities of the procedural learning mechanism in ACT-R. Proceedings of the 26th Annual Conference of the Cognitive Science Society. Hillsdale, NJ: LEA.
Fu, W.-T., Bothell, D., Douglass, S., Haimson, C., Sohn, M.-H, Anderson, J. A. (2004), Learning from real-time over-the-shoulder instructions in a dynamic task. Proceedings of the Sixth International Conference on Cognitive Modeling. Pittsburgh, PA.
Gray, W. D., Veksler, D., Fu, W.-T. (2004), Probing the paradox of the active user: Asymmetrical transfer may produce stable, suboptimal performance. Proceedings of the 26th Annual Conference of the Cognitive Science Society. Hillsdale, NJ: LEA.
Fu, W.-T. (2003), A Bayesian satisficing model of human adaptive planning. Proceedings of the 25th Annual Conference of the Cognitive Science Society (pp. 420-425). Hillsdale, NJ: LEA.
Fu, W.-T. (2003), An ACT-R adaptive planner in a simple map- navigation task. In F. Detje, D. Doerner, & H. Schaub (Eds.), Proceedings of the Fifth International Conference on Cognitive Modeling (pp. 99-104). Bamberg, Germany: Universitats-Verlag Bamberg.
Pirolli, P., Fu, W.-T. (2003), SNIF-ACT: A model of information foraging on the world wide web. Proceedings of the Ninth International Conference on User Modeling. New York: Springer-Verlag. (Winner of Best Theoretical Paper Award).
Pirolli, P., Fu, W.-T., Reeder, R., Card, S. K. (2002), A user-tracing architecture for modeling interaction with world wide web. Proceedings of the Sixth International Conference on Advanced Visual Interfaces. New York: ACM Press.
Fu, W.-T. (2001), ACT-PRO action protocol analyzer: A tool for analyzing discrete action protocols. Behavior Research Methods, Instruments, & Computers, 33 (2), 149-158. [PDF] [Abstract]
This article presents a top-down approach for analyzing sequential events in behavioral data. Analysis of behavioral sequential data often entails identifying patterns specified by the researchers. Algorithms were developed and applied to analyze a kind of behavioral data, called discrete action protocol data. Discrete action protocols consist of discrete user actions, such as mouse clicks and keypresses. Unfortunately, the process of analyzing the huge volume of actions (typically, >105) is very labor intensive. To facilitate this process, we developed an action protocol analyzer (ACT-PRO) that provides two levels of pattern matching. Level one uses formal grammars to identify sequential patterns. Level two matches these patterns to a hierarchical structure. ACT-PRO can be used to determine how well data fit the patterns specified by an experimenter. Complementarily, it can be used to focus an experimenter's attention on data that do not fit the prespecified patterns.
Fu, W.-T., Gray, W. D. (2001), Modeling cognitive versus perceptual-motor tradeoffs using ACT-R/PM. Proceedings of the Fourth International Conference on Cognitive Modeling (pp. 247-248). Mahwah, NJ: Lawrence Erlbaum Associates.
Gray, W. D., Fu, W.-T. (2001), Ignoring perfect knowledge in-the- world for imperfect knowledge in-the-head: Implications of rational analysis for interface design. Proceedings of the ACM CHI'01 Conference on Human Factors in Computing Systems. Also in CHI Letters, 3(1).
Fu, W.-T., Gray, W. D. (2000), Memory versus perceptual-motor tradeoffs in a blocks world task. Proceedings of the 22nd Annual Conference of the Cognitive Science Society, Mahwah, NJ: Erlbaum.
Gray, W. D., Fu, W.-T. (2000), The influence of source and cost of information access on correct and errorful interactive behavior. Proceedings of the 22nd Annual Conference of the Cognitive Science Society, Mahwah, NJ: Erlbaum.
Gray, W. D., Schoelles, J. J., Fu, W.-T. (2000), Modeling a continuous dynamic task. Proceedings of the Third International Conference on Cognitive Modeling (pp. 158-168). Groningen, NL: Universal Press.
Trickett, S. B., Fu, W.-T., Schunn, D. D., Trafton, J. G. (2000), From dipsy-doodles to streaming motions: Changes in representation in the analysis of visual scientific data. Proceedings of the 22nd Annual Conference of the Cognitive Science Society, Mahwah, NJ: Erlbaum.
Fu, W.-T., Gray, W. D. (1999), Redirecting direct-manipulation, or, what happens when the goal is in front of you but the interface says to turn left. Proceedings of ACM CHI'99 Conference on Human Factors in Computing Systems (pp. 226-227). New York: ACM Press.