The limits of expert performance using hierarchic marking menus

Kurtenbach, Gordon; Buxton, William

doi:10.1145/169059.169426

Cited by 243 publications

(236 citation statements)

References 9 publications

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“…A technique may be evaluated with a task too simple to reflect its use in situ. For example, marking menus [15] are radial pop-up menus where an item can be selected by a mark without displaying the menu. In a simple item selection task, they were up to 3.5 times faster than other menus.…”

Section: Dangers Of Controlled Experimentsmentioning

confidence: 99%

Context matters: Evaluating Interaction Techniques with the CIS Model

Appert

Beaudouin-Lafon

Mackay

People and Computers XVIII — Design for Life

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This article introduces the Complexity of Interaction Sequences model (CIS). CIS describes the structure of interaction techniques and predicts their performance in the context of an interaction sequence. The model defines the complexity of an interaction technique as a measure of its effectiveness within a given context. We tested CIS to compare three interaction techniques: fixed unimanual palettes, fixed bimanual palettes and toolglasses. The model predicts that the complexity of both palettes depends on interaction sequences, unlike toolglasses. CIS also predicts that fixed bimanual palettes outperform the other two techniques. Predictions were tested empirically with a controlled experiment and contrast with previous studies. We argue that, in order to be generalisable, experimental comparisons of interaction techniques should include the concept of context sensitivity. RÉSUMÉCet article introduit le modèle Complexity of Interaction Sequences CIS). CIS décrit la structure des techniques d'interaction et prédit leur performance dans le contexte d'une séquence d'interaction. Le modèle définit la complexité d'une technique d'interaction comme la mesure de son efficacité dans un contexte donné. Nous avons testé CIS pour comparer trois techniques d'interaction : les palettes fixes unimanuelles, les palettes fixes bimanuelles et les toolglasses. Le modèle prédit que, contrairement aux toolglasses, la complexité des deux types de palette dépend des séquences d'interaction. CIS prédit également que les palettes fixes bimanuelles sont toujours plus efficaces que les deux autres techniques. Les prédictions ont été vérifiées empiriquement par une expérimentation contrôlée et contrastent avec les résultats des précédentes études. Nous argumentons que, afin d'être généralisables, les comparaisons expérimentales entre techniques d'interaction doivent prendre en compte le concept de sensibilité au contexte.

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Section: Dangers Of Controlled Experimentsmentioning

confidence: 99%

Context matters: Evaluating Interaction Techniques with the CIS Model

Appert

Beaudouin-Lafon

Mackay

People and Computers XVIII — Design for Life

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“…Kurtenbach et al [16,17] proposed and evaluated Marking Menus as an improved version of radial menus. The main difference between Marking Menus and transitional radial menus is the absence of a completely bounded target area for each menu item in the former.…”

Section: Marking Menusmentioning

confidence: 99%

“…We propose to utilize Marking Menus [16], a radial menu structure, as a central element of a novel interaction method employing the multi-touch screen of mobile devices. The touch screen is used to show (hierarchical) radial menus as they pop up.…”

Section: Introductionmentioning

confidence: 99%

Marking Menus for Eyes-Free Interaction Using Smart Phones and Tablets

Bauer

Ebert

Kreylos

et al. 2013

Availability, Reliability, and Security in Information Systems and HCI

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Abstract. Large displays are helpful tools for knowledge discovery applications. The increased screen real estate allows for more data to be shown at once. In some cases using virtual reality visualizations helps in creating more useful visualizations. In such settings, traditional input devices are not well-suited. They also do not scale well to multiple users, effectively limiting collaborative knowledge discovery scenarios. Smart phones and tablet computers are becoming increasingly ubiquitous and powerful, even having multi-core CPUs and dedicated Graphic Processing Units (GPUs). Given their built-in sensors they can serve as replacements for currently-used input devices, and provide novel functionality not achieved with traditional devices. Furthermore, their ubiquity ensures that they scale well to multi-user environments, where users can use their own devices. We present an application-independent way to integrate smart phones and tablets into knowledge discovery applications as input devices with additional functionality. This approach is based on Marking Menus, but extends the basic idea by employing the special capabilities of current consumer-level smart phones and tablets.

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“…During this study, 1024 pressure values or 120 tilt values were uniformly divided into 4, 6, 8, 10 and 12 levels, much like the way Marking Menus retain a uniform size regardless of the number of menu items [7]. Keeping the pressure or tilt to spatial movement mapping constant will likely facilitate the user's ability to develop haptic or visual memory of various pressure or tilt levels [17].…”

Section: Pressure and Tilt Spacementioning

confidence: 99%

A Comparison of Pressure and Tilt Input Techniques for Cursor Control

Zhou

Ren

2009

IEICE Trans. Inf. & Syst.

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SUMMARYThree experiments were conducted in this study to investigate the human ability to control pen pressure and pen tilt input, by coupling this control with cursor position, angle and scale. Comparisons between pen pressure input and pen tilt input have been made in the three experiments. Experimental results show that decreasing pressure input resulted in very poor performance and was not a good input technique for any of the three experiments. In "Experiment 1-Coupling to Cursor Position", the tilt input technique performed relatively better than the increasing pressure input technique in terms of time, even though the tilt technique had a slightly higher error rate. In "Experiment 2-Coupling to Cursor Angle", the tilt input performed a little better than the increasing pressure input in terms of time, but the gap between them is not so apparent as Experiment 1. In "Experiment 3-Coupling to Cursor Scale", tilt input performed a little better than increasing pressure input in terms of adjustment time. Based on the results of our experiments, we have inferred several design implications and guidelines. key words: pressure input, tilt input, target selection tasks, pen-based interfaces

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The limits of expert performance using hierarchic marking menus

Cited by 243 publications

References 9 publications

Context matters: Evaluating Interaction Techniques with the CIS Model

Context matters: Evaluating Interaction Techniques with the CIS Model

Marking Menus for Eyes-Free Interaction Using Smart Phones and Tablets

A Comparison of Pressure and Tilt Input Techniques for Cursor Control

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