%Original file available from http://www.cs.odu.edu/~jbollen/bibliographies/bibtex/HCI_gen.bib %Last update: Thursday 10 March 2005 %Current number of entries: 32 @article{implic:kelly2003, author = {Diane Kelly and Jaime Teevan}, title = {Implicit feedback for inferring user preference: a bibliography}, journal = {SIGIR Forum}, volume = {37}, number = {2}, year = {2003}, issn = {0163-5840}, pages = {18--28}, doi = {http://doi.acm.org.proxy.lib.odu.edu/10.1145/959258.959260}, publisher = {ACM Press}, } @inproceedings{social:riedl2003, author = {Mark O. Riedl and Robert {St. Amant}}, title = {Social navigation: modeling, simulation, and experimentation}, booktitle = {Proceedings of the second international joint conference on Autonomous agents and multiagent systems}, year = {2003}, isbn = {1-58113-683-8}, pages = {361--368}, location = {Melbourne, Australia}, doi = {http://netserv.lib.odu.edu:2378/10.1145/860575.860634}, publisher = {ACM Press}, } @inproceedings{implic:claypool2001, author = {Mark Claypool and Phong Le and Makoto Wased and David Brown}, title = {Implicit interest indicators}, booktitle = {Proceedings of the 6th international conference on Intelligent user interfaces}, year = {2001}, isbn = {1-58113-325-1}, pages = {33--40}, location = {Santa Fe, New Mexico, United States}, doi = {http://netserv.lib.odu.edu:2378/10.1145/359784.359836}, publisher = {ACM Press}, } @INPROCEEDINGS{turnin:franzke1995, title = {Turning research into practice: characteristics of display-based interaction}, author = {Marita Franzke}, year = 1995, booktitle = {Conference proceedings on {H}uman {F}actors in {C}omputing {S}ystems}, publisher = {{ACM}}, month = {May}, address = {Denver, {CO}}, pages = {421 -- 428}, abstract = {This research investigates how several characteristics of display-based systems support or hinder the exploration and retention of the functions needed to perform tasks in a new application. In particular it is shown how the combination of the type of interface action, the number of interaction objects presented on the screen, and the quality of the label associated with these objects interact in supporting discovery and retention of the functionality embedded in those systems. An experiment is reported which provides empirical evidence for Polson & Lewis's CE+ theory of exploratory learning of computer systems [11]. It also extends this theory and therefore leads to a refinement of the cognitive walkthrough procedure that was derived from it. The study uses an experimental method that combines observations from realistically complex task scenarios with a detailed analysis of the observed performance.}, } @ARTICLE{compre:kitajima1997, author = {Muneo Kitajima and P. Polson}, title = {A comprehension-based model of exploration}, year = 1997, volume = 12, number = 4, pages = {345--389}, } @InProceedings{comput:kitajima1992, author = {Muneo Kitajima and Peter G. Polson}, title = {A computational model of skilled use of a graphical user interface}, booktitle = {Conference Proceedings on Human Factors in Computing Systems}, pages = {241 -- 249}, year = {1992}, address = {Monterey, {CA}}, month = {May}, abstract = {This paper describes a computational model of skilled use of a graphical user interface based on Kintsch's construction-integration theory [4, 8]. The model uses knowledge of a detailed representation of information on the display, a user's goals and expectations, knowledge about the interface, and knowledge about the application domain to compute actions necessary to accomplish the user's current goal. The model provides a well-motivated account of one kind of errors, action slips [14], made by skilled users. We show how information about the intermediate state of a task on the display plays a critical role in skilled performance, i.e., display-based problem solving.}, } @INPROCEEDINGS{modelo:rehder1995, author = {Bob Rehder and Clayton Lewis and Bob Terwilliger and Peter Polson and John Rieman}, title = {A model of optimal exploration and decision making in novel interfaces}, year = 1995, booktitle = {Proceedings of the Conference on Human Factors and Computing Systems.}, month = {May}, address = {Denver, CO}, publisher = {ACM}, pages = {230--231}, abstract = {Describes model of manu selections based on label-following. Assumptions are 1) traversal of menu structure 2) user encode an estimate of the relevance of a command given its label 3)user comes with prior experiences concerning the usefulness of a command. Model is based on signal detection theory: signal = command is relevant to task, noise=selected command is not relevant. Models uses cost function to explain certain phenomena in user behavior in novel interfaces.} } @INPROCEEDINGS{taskel:terwilliger1996, title = { Task elaboration or label following: an empirical study of representation in human-computer interaction}, author = {Robert B. Terwilliger and Peter G. Polson}, year = 1996, month = {April}, address = {Vancouver, Canada}, booktitle = {Proceedings of the {CHI} 1996 conference companion on Human factors in computing systems: common ground}, pages = {201 -- 202}, publisher = {{ACM}}, } @INPROCEEDINGS{wayfin:darken1996, author = {Rudolph P. Darken and John L. Sibert}, title = {Wayfinding strategies and behaviors in large virtual worlds}, year = 1996, booktitle = {Conference proceedings on {H}uman {F}actors in {C}omputing {S}ystems}, pages = {142--149}, month = {April 13-18}, publisher = {ACM}, address = {Vancouver Canada}, abstract = {People have severe problems wayfinding in large virtual worlds. However, current implementations of virtual worlds provide little support for effective wayfinding. We assert that knowledge about human wayfinding in the physical world can be applied to construct aids for wayfinding in virtual worlds. An experiment was conducted to determine whether people use physical world wayfinding strategies in large virtual worlds. The study measures subject performance on a complex searching task in a number of virtual worlds with differing environmental cues. The results show that subjects in the treatment without any additional cues were often disoriented and had extreme difficulty completing the task. In general, subjects' wayfinding strategies and behaviors were strongly influenced by the environmental cues in ways suggested by the underlying design principles. }, } @ARTICLE {modell:burnett1998, author = {Kathleen Burnett and E. Graham {McKinley}}, title = {Modelling Information Seeking}, journal = {Interacting with Computers}, volume = {10}, pages = {285--302}, year = 1998, } @ARTICLE {cogniti:sutcliffe1998, author = {Alistair Sutcliffe and Mark Ennis}, title = {Towards a cognitive theory of information retrieval}, journal = {Interacting with Computers}, volume = {10}, pages = {321-351}, year = 1998, } @BOOK{psycho:norman1991, author = {Kent L. Norman}, title = {The Psychology of Menu Selections}, year = {1991}, publisher = {Ablex Publishing}, address = {Norwoord, NJ}, } @INCOLLECTION{knowled:mark1986, author = {William Mark}, editor = {Donald A. Norman and Stephen W. Draper}, year = 1986, title = {Knowledge-Based Interface Design}, booktitle ={User Centered System Design}, publisher = {Lawrence Erlbaum Associates}, address = {Hillsdale, NJ}, } @BOOK{userce:norman1986, author = {Donald A. Norman and Stephen W. Draper}, title = {User Centered System Design}, year = 1986, publisher = {Lawrence Erlbaum Associates}, address = {Hillsdale, NJ}, } @BOOK{psycho:card1983, author = {Stuart K. Card and Thomas P. Moran and Allen Newel}, title = {The Psychology of Human-Computer Interaction}, year = 1983, publisher = {Lawrence Erlbaum Associates}, address = {Hillsdale, NJ}, } @ARTICLE{readin:muter1991, title = {Reading and skimming from computer screens and book: The paperless office revisited}, author = {Paul Mutter and Paula Maurutto}, year = 1991, journal = {Behaviour and Information Technology}, volume = 10, pages = {257 -- 266}, } @ARTICLE{develo:norman1983, title = {Development of Direct-Search Strategies in Hill-Climbing Problems}, author = {Kent L. Norman}, year = {1983}, journal = {Bulletin of the Psychonomic Society}, volume = 21, number = 4, pages = {469--471}, } @INPROCEEDINGS{compar:somberg1987, title = {A comparison of rule-based and positionally constant arrangements of computer menu items}, author = {Benjamin L. Somberg}, year = 1987, booktitle = {{CHI}/{GI} 1987 {C}onference {P}roceedings on {H}uman {F}actors in {C}omputing {S}ystems and {G}raphics {I}nterfaces}, month = {April}, address = {Toronto, Canada}, pages = {255--260}, abstract = {An experiment was conducted to evaluate user performance under four different menu item arrangements: alphabetic, probability of selection (most popular choices are positioned near the beginning of the list), random, and positionally constant (consistent assignment of individual items to screen positions). During the initial stages of practice, the rule-based approaches produced faster mean search times, but after moderate amounts of practice, the positionally constant arrangement appeared to be most efficient. People seem to remember quite easily the location of items on a display, indicating that positional constancy can be an important factor in increasing the efficiency of the search of computer menus and other displays.}, } @INCOLLECTION{humane:prabhu1997, author = {P. V. Prabhu and G. V. Prabhu}, editor = {M. Helander and T.K. landauer and P.V. Prabhu}, year = 1997, title = {Human Error and User-Interface Design}, booktitle ={HandBook of Human-Computer Interaction}, publisher = {Elsevier}, address ={Amsterdam}, } @INPROCEEDINGS{cognit:hornof1997, author = {Anthony J. Hornof and David E. Kieras}, month = {March}, year = 1997, title = {Cognitive Modeling Reveals Menu Search is Both Random and Systematic}, booktitle = {Proceedings of CHI97}, publisher = {ACM}, address = {Atlanta, USA}, pages = {399--406}, abstract = {To understand how people search for a known target item in an unordered pull-down menu, this research presents cognitive models that vary serial versus parallel processing of menu items, random versus systematic search, and different numbers of menu items fitting into fovea simultaneously. Varying these conditions, models constructed and run using the EPIC cognitive architecture. The selection times predicted by the models are compared with selection times of human subjects performing the same menu task. Comparing the predicted and observed times, the models reveal that 1) people process more than one menu item at a time, and 2) people search menus using both random and systematic search strategies.} } @ARTICLE{effec:sears1994, author = {A. Sears and B. Schneiderman}, title = {Split Menus: Effectively Using Selection Frequency to Organize Menus}, year = {1998}, journal = {ACM Transactions on Computer-Human Interaction}, volume = 1, number = 1, pages = {27--51}, } @ARTICLE{effec:snowberry, author = {K. Snowberry and S. Parkinson and N. Sisson}, title = {Effects of Help Fields on Navigating through Hierarchical Menu Structures}, year = {1985}, journal = {International Journal of Man-Machine Studies}, volume = 22, pages = {479--491}, } @InCollection{mental:allen1997, author = {R. B. Allen}, title = {Mental Models and User Models}, booktitle = {Handbook of {H}uman-{C}omputer {I}nteraction}, publisher = {Elsevier}, year = {1997}, editor = {M. Helander and T.K. Landauer and P. Prabhu}, address = {Amsterdam}, } @ARTICLE{mental:wilson1991, title = {Mental models-panacea or sidetrack?}, author = {J. R. Wilson and A. Rutherford}, journal = {{IEE} Colloquium - {HCI}: Issues for the Factory}, year = 1991, pages = {1 -- 3}, publisher = {{IEEE}}, address = {London, {UK}}, } @INPROCEEDINGS{operat:jonassen1995, author = {D. H. Jonassen}, title = {Operationalizing Mental Models}, year = 1995, booktitle = {Proceedings of the Computer Supported Collaborative Learning Conference}, address = {Bloomington, {IN}}, month = {October}, editor = {John L. Schnase and Edward L. Cunnius}, }, @INPROCEEDINGS{mental:lee1989, title = {Making mental models manifest}, author = {J. A. Lee and N. Moray}, year = 1989, booktitle = {{IEEE} {I}nternational {C}onference on {S}ystems, {M}an, and {C}ybernetics}, month = {November}, pages = {56 -- 60}, address = {Cambridge, MA}, abstract = {A study was conducted to determine what factors affect how humans detect correlation when forming mental models of complex systems. Using a paradigm that elicits the subject's mental model of a system by the subject's reconfiguration of the display, the authors conducted four experiments that illustrate humans' ability and factors affecting their ability to detect correlation in a dynamic display. It is shown that subjects can detect correlation in a dynamic system and that lowering the correlation makes detecting the correlation progressively more difficult. The data, combined with the subjects' comments, shows that the strategies adopted by the subjects govern their ability to detect correlation. The strategies adopted depend on the degree of correlation and the type of movement. Correlation predisposed subjects to discover grouping by either pairwise comparison (in the case of low correlation) or global search (in the case of high correlation). The type of movement, on the other hand, predisposed subjects to group bars by height (in the case of random walk movement) or correlation (in the case of Gaussian mean zero movement). Generally, this study forms the beginning of a research program investigating the factors that guide operators in generating mental models of complex systems.}, } @InCollection{someob:norman1983, author = {Donald A. Norman}, title = {Some observations on Mental Models}, booktitle = {Mental Models}, publisher = {Lawrence Erlbaum Associates}, year = {1983}, editor = {Genter and Stevens}, address = {Hillsdale, NJ}, pages = {7--14}, abstract = {Definition of Mental Model, explain difference between mental model and our conceptualization of mental model. Important ref for introduction to hc_model chapter of diss because it addresses the difficulties some readers had to understand the difference between what a mental model IS and how I operationalize it as a weighted graph for hypertext systems} } @INPROCEEDINGS{suffic:bhavnani1997, author = {Suresh K. Bhavnani and Bonnie E. John}, month = {March}, year = 1997, title = {From sufficient to Efficient Usage: an Analysis of Strategic Knowledge}, booktitle = {Proceedings of CHI97}, publisher = {ACM}, address = {Atlanta, USA}, pages = {91--98}, abstract = {Can good design guarantee the efficient use of computer tools? Can experience guarantee it? We raise these questions to explore why empirical studies of real-world usage show even experienced users under-utilizing the capabilities of computer applications. By analyzing the use of everyday devices and computer applications, as well as reviewing empirical studies, we conclude that neither good design nor experinece may be able to guarantee efficienct usage. Efficient use requires task decomposition strategies that exploit capabilities offered by computer applications such as the ability to aggregate objects, and to manipulate the aggregates with powerful operators. To understand the effects that strategies can have on performance, we present results from a GOMS analysis of a CAD task. Furthermore, we identify some key aggregation strategies that appear to generalize accross applications. Such strategies may provide a framework to enable users to move from a sufficient to a more efficient use of computer tools}, } @INPROCEEDINGS{studya:takahashi1996, title = {A study on automated shifting and shift timing using a driver's mental model}, author = {H. Takahashi and K. Kuroda}, year = 1996, booktitle = {Proceedings of the Intelligent Vehicles Symposium}, volume = 1996, number = 1909, pages = {300 -- 305}, month = {September}, address = {Tokyo, Japan}, abstract = {This paper presents a new control method designed to improve vehicle drivability on downhill grades. Vehicles normally gain speed when travelling downhill even if the driver desires not to accelerate. Under such situation drivers often shift into a lower gear in order to reduce the vehicle speed. With the control method described here, the gear shifting operation is executed automatically by using a driver's mental model to infer the intention to decelerate. The driver's mental model is identified by applying the Interactive Dichotomizer 3 to obtain the inductive relationship between the vehicle operating data and the driver's intention. A study was made of the timing difference between the automated gear shifting and the manual gear shifting by the driver. The results of this study verify the effectiveness of the inference mechanism on the driver's intentions to control the power-train of the vehicle.}, } @ARTICLE{identi:moray1998, title = {Identifying mental models of complex human-machine systems}, author = {Neville Moray}, year = 1998, journal = {International Journal of Industrial Ergonomics}, volume = 22, number = {4-5}, pages = {293 -- 297}, month = {November}, abstract = { The notion of a `mental model' is widespread but ill defined. Its meaning can be clarified by noting both the cognitive processes of the worker and the context of the task. A mental model is a mapping of the properties of the task to its representation in the mind of the worker. Traditionally, such models have been identified by the use of protocol analysis, but a method has been developed which finds the mapping through its effects on the coupling between human and machine. This method uses Conant's theory of system decomposition based on high-order Shannon information theory. An example of its use is given. Relevance to industry Operators make use of mental models of complex systems in process control and manufacturing. A method to identify such models is relevant to productivity, and to fault detection and management, since it gives insight into the way in which operators become coupled, by training and habit, to the dynamics of the processes they control.}, } @ARTICLE{mental:staggers1993, author = {Nancy Staggers and A. F. Norcio}, title = {Mental models: concepts for human-computer interaction research}, journal = {International Journal of Man-Machine Studies}, year = 1993, volume = 38, number = 4, month = {April}, pages = {587--605}, abstract = {In interacting with the world, people form internal representations or mental models of themselves and the objects with which they interact (Norman, 1983a). According to Norman, mental models provide predictive and explanatory powers for understanding the interaction. More abstractly, Gentner and Stevens (1983) propose that mental models focus on the way people understand a specific knowledge domain. More concretely, Carroll (1984) views mental models as information that is input into cognitive structures and processes. What are mental models? Are they always formed? When formed, what are their characteristics? What are the functional consequences of having no model (if that is possible), an immature model, or a mature model? This paper intends to explore these questions}, URL = {http://www.idealibrary.com/links/artid/imms.1993.1028/production/pdf}, } @ARTICLE{constr:hegarty1993, author = {M. Hegarty and M.A. Just}, title = {Constructing Mental Models of Machines from Text and Diagrams}, journal = {Journal of Memory and Language}, year = 1993, volume = 32, number = 6, month = {December}, pages = {717-742}, abstract = {Readers' comprehension and eye-fixations are monitored as they read descriptions of simple machines, pulley systems. The comprehension data indicate that readers' comprehension depends on both the medium of instruction and the ability of the reader. The conjunction of text and diagrams particularly facilitated the understanding of how the pulley system moved, whereas either medium alone was sufficient for conveying the system configuration. The eye-fixation data indicate that subjects integrate the information in the text and diagram at the level of individual pulley-system components or groups of connected components. They read the text in increments, often rereading the information about a component or group of components before constructing a spatial mental model of these components with the aid of the diagram. Subjects' diagram inspections vary from local inspections concerned with encoding the relations between two or three components to global inspections concerned with integrating the relations between many components.}, URL = {http://www.idealibrary.com/links/artid/jmla.1993.1036/production/pdf}, } @ARTICLE{probab:slegers2000, author = {David W. Slegers and Gregory L. Brake and Michael E. Doherty}, title = {Probabilistic Mental Models with Continuous Predictor}, journal = {Organizational Behavior and Human Decision Processes}, volume = 81, number = 1, month = {January}, year = 2000, pages = {98--114}, abstract = {Gigerenzer and his colleagues have sought to develop psychologically plausible models of human judgment. Their models are classified as ones of bounded rationality based on a principle of one-reason decision making. The models associated with the theory of Probabilistic Mental Models (PMM) have been developed for tasks in which all predictors are binary. This article extends PMM to the case of continuous predictors. The current model employs the limitation on the number of categories people use in making absolute judgments along a single perceptual dimension (7 1 2; Miller, 1956). The algorithm transforms each continuous predictor to be consistent with this limitation, then implements a step-down one-reason decision procedure similar to previous PMM models. Like previous PMM models, the 7 1 2 model predicts binary judgments as well as a multiple-regression model. However, the model does not successfully predict the probability judgments of individual participants, which is also true of all other models in the literature.}, URL = {http://www.idealibrary.com/links/artid/obhd.1999.2869/production/pdf}, }