The effect of time-based cost of error in target-directed pointing tasks

Banović, Nikola; Grossman, Tovi; Fitzmaurice, George

doi:10.1145/2470654.2466181

Cited by 28 publications

(7 citation statements)

References 37 publications

(77 reference statements)

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“…In contrast to scrolling, discrete swipe is often used in horizontal grids to flip through pages, which can be modeled by adding a single swipe constant between grid pages. Integration of performance components such as user error, e.g., when selecting a wrong item resulting in additional correction time [8], would further complete the model.…”

Section: Discussion and Limitationsmentioning

confidence: 99%

Analysis and Modeling of Grid Performance on Touchscreen Mobile Devices

Pfeuffer

2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

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Touchscreen mobile devices can afford rich interaction behaviors but they are complex to model. Scrollable twodimensional grids are a common user interface on mobile devices that allow users to access a large number of items on a small screen by direct touch. By analyzing touch input and eye gaze of users during grid interaction, we reveal how multiple performance components come into play in such a task, including navigation, visual search and pointing. These findings inspired us to design a novel predictive model that combines these components for modeling grid tasks. We realized these model components by employing both traditional analytical methods and data-driven machine learning approaches. In addition to showing high accuracy achieved by our model in predicting human performance on a test dataset, we demonstrate how such a model can lead to a significant reduction in interaction time when used in a predictive user interface.

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Section: Discussion and Limitationsmentioning

confidence: 99%

Analysis and Modeling of Grid Performance on Touchscreen Mobile Devices

Pfeuffer

2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

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“…visual search [14,35,62], multitasking [10,33,34], typing [32,56], pointing [7,11], decision making [42,53] and drawing [58].…”

Section: Modeling Interactive Behavior With Reinforcement Learningmentioning

confidence: 99%

Modeling Touch-based Menu Selection Performance of Blind Users via Reinforcement Learning

Putkonen

et al. 2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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Although menu selection has been extensively studied in HCI, most existing studies have focused on sighted users, leaving blind users' menu selection under-studied. In this paper, we propose a computational model that can simulate blind users' menu selection performance and strategies, including the way they use techniques like swiping, gliding, and direct touch. We assume that selection behavior emerges as an adaptation to the user's memory of item positions based on experience and feedback from the screen reader.A key aspect of our model is a model of long-term memory, predicting how a user recalls and forgets item position based on previous menu selections. We compare simulation results predicted by our model against data obtained in an empirical study with ten blind users. The model correctly simulated the efect of the menu length and menu arrangement on selection time, the action composition, and the menu selection strategy of the users. CCS CONCEPTS• Human-centered computing → Accessibility theory, concepts and paradigms; Empirical studies in accessibility; HCI theory, concepts and models; User models.

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“…We removed spatial outliers if the distance of the first click position was shorter than 𝐴/2 [4,30] to omit clear accidental operations such as double-clicking the previous target. Another criterion used in these laboratory-based studies was to remove trials in which the click position was more than 2𝑊 from the target center, but we did not use this criterion, as there are a variety of target-size definitions in our diagonal-movement task with rectangular targets [29].…”

Section: Outlier Data Screeningmentioning

confidence: 99%

Test-retest Reliability on Movement Times and Error Rates in Target Pointing

Yamanaka¹

2022

Designing Interactive Systems Conference

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Target-selection tasks have been frequently conducted to evaluate novel input devices and pointing-facilitation techniques. Recently, Sharif et al. showed that a unifed metric to evaluate the pointing performance, called throughput TP, was not stable across two sessions performed by the same participant group, which indicates poor test-retest reliability. Because there are cases in which using TP is inappropriate depending on the research topic, we extend their fnding to two other metrics: movement time MT and error rate ER. We demonstrated that, even for the participants who kept their TPs across two sessions stable, they would exhibit unstable MT s and ERs. Thus, if time allows, researchers should design their experiments to run multiple sessions for obtaining the central tendency of user performance, which increases the validity of their user studies. CCS CONCEPTS• Human-centered computing → HCI theory, concepts and models; Pointing.

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The effect of time-based cost of error in target-directed pointing tasks

Cited by 28 publications

References 37 publications

Analysis and Modeling of Grid Performance on Touchscreen Mobile Devices

Analysis and Modeling of Grid Performance on Touchscreen Mobile Devices

Modeling Touch-based Menu Selection Performance of Blind Users via Reinforcement Learning

Test-retest Reliability on Movement Times and Error Rates in Target Pointing

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