A marking menu is designed to allow a user to perform a menu selection by either popping-up a radial (or pie) menu, or by making a straight mark in the direction of the desired menu item without popping-up the menu. Previous evaluations in laboratory settings have shown the potential of marking menus. This paper reports on a case study of user behavior with marking menus in a real work situation. The study demonstrates the following: First, marking menus are used as designed. When users become expert with the menus, marks are used extensively. However, the transition to using marks is not one way. Expert users still switch back to menus to refresh their memory of menu layout. Second, marking is an extremely efficient interaction technique. Using a mark on average was 3.5 times faster than selection using the menu. Finally, design principles can be followed that make menu item/mark associations easier to learn, and interaction efficient.

This research focuses on the use of hand drawn marks as a human-computer input technique. Drawing a mark is an efficient command input technique in many situations. However, marks are not intrinsically self-explanatory as are other interactive techniques such as buttons and menus. This research develops and evaluates an interaction technique called marking menus which integrates menus and marks such that both self-explanation and efficient interaction can be provided. A marking menu allows a user to perform a menu selection by either popping up a radial menu and then selecting an item, or by drawing a straight mark in the direction of the desired menu item. Drawing a mark avoids popping up the menu. Marking menus can also be hierarchic. In this case, hierarchic radial menus and “zig-zag ” marks are used. Marking menus are based on three design principles: self-revelation, guidance and rehearsal. Self-revelation means a marking menu reveals to a user what functions or items are available. Guidance means a marking menu guides a user in selecting an item. Rehearsal means that the guidance

The paper argues that new approaches for delivering HCI knowledge from theory to designers will be necessary in the new millennium. First the progress made developing cognitive theories of interaction and their impact on the design process is reviewed. Direct application of current cognitive theories to design has been limited by scalability problems. This has led to bridging models that attempt to deliver insights from theory to design models in a more tractable manner. However, these too have met with limited success. An alternative is to represent HCI knowledge as claims and adopt the task-artefact approach to design in which theories are embedded in well-designed artefacts and explained to designers as psychologically motivated design rationale. Claims are proposed as a possible bridging representation that may enable theories to frame appropriate recommendations for designers and, vice versa, enable designers to ask appropriate questions for theoretical research. However, claims provide design advice grounded in specific scenarios and examples, which 1 limits their generality. Hence claims are their associated artefacts needs to be generalised so

This article investigates how and why people remember the existence of hidden information. To obtain data on this kind of memory phenomenon, we observed an experienced programmer doing her own work at her own computer. The programmer's interaction with the computer generates much more information than fits on the screen at once. Most of this information is hidden, scrolled out of the way by the programming environment to make Direct all correspondence to: Erik M. Altmann, George Mason University, Human Factors & Applied Cognition, Mailstop 2E5, Fairfax, VA 22030 USA; E-Mail: altmann@gmu.edu

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interaction, artificial intelligence. People make use of hidden external information, first recalling that it exists and then finding it. This dissertation investigates the memory phenomena involved in recalling that external information exists. We present data in which a programmer navigates to hidden features in a real-world task environment. We then present a model that accounts for this navigation by encoding and using simple episodic memories for having seen a feature. The model inherits constraints from its underlying cognitive architecture, which specify that learning is passive and pervasive, and that it creates simple memories that depend on the feature itself being present as a cue. The nature of these memories requires the model to recall features to its mind’s eye as cues in order to retrieve them. This retrieval process requires domain knowledge: familiarity with features in order to imagine them, and an idea of when it would be useful to recall having seen them. Recalling that a hidden feature exists prompts the model to scroll to that feature. Thus the model’s access to external information is a function of passively-encoded episodic memories, and retrieval of these memories using knowledge. As a claim applied to people, this appears to overlap with a recently-

‘Footprints’ are marks or features of a design that alert the analyst to the possible existence of usability difficulties caused by violations of design principles. PUMA Footprints make an explicit link between the theory underlying a Programmable User Model and the design principles that can be derived from that theory. While principles are widely presented as being intuitively obvious, it is desirable that they should have a theoretical basis. However, working directly with theory tends to be time-consuming, and demands a high level of skill. PUMA footprints offer a theory-based justification for various usability principles, with guidelines on detecting violations of those principles.

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