Multimodal feedback for finger-based interaction in mobile augmented reality

Hürst, Wolfgang; Vriens, Kevin

doi:10.1145/2993148.2993163

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…Many researchers proposed free-handed gesture input recognition systems, for example, ubiquitous computing [1], wearables [12,35], phones [18], head-mounted displays [32], cars [5] and on-body interaction [24]. To control these interfaces various gestural interaction techniques have been investigated (e.g.…”

Section: Input By Hand Gesturesmentioning

confidence: 99%

GestureDrawer

Babic

Reiterer

Haller

2017

Proceedings of the 5th Symposium on Spatial User Interaction

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Existing 1 empty-handed mid-air interaction techniques for system control are typically limited to a confined gesture set or point-and-select on graphical user interfaces. In this paper, we introduce GestureDrawer, a one-handed interaction with a 3D imaginary interface. Our approach allows users to self-define an imaginary interface, acquire visuospatial memory of the position of its controls in empty space and enables them to select or manipulate those controls by moving their hand in all three dimensions. We evaluate our approach with three user studies and demonstrate that users can indeed position imaginary controls in 3D empty space and select them with an accuracy of 93% without receiving any feedback and without fixed landmarks (e.g. second hand). Further, we show that imaginary interaction is generally faster than mid-air interaction with graphical user interfaces, and that users can retrieve the position of their imaginary controls even after a proprioception disturbance. We condense our findings into several design recommendations and present automotive applications. CCS CONCEPTS • Human-centered computing~Gestural input • Humancentered computing~User interface design • Human-centered computing~User centered design KEYWORDS

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Section: Input By Hand Gesturesmentioning

confidence: 99%

GestureDrawer

Babic

Reiterer

Haller

2017

Proceedings of the 5th Symposium on Spatial User Interaction

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“…(Chuang, 2007;Elola & Oskoz, 2016;Elshirbini & Elashri, 2013;Faroha et al, 2016;Hadzic, 2016;Ismail et al, 2008;Maolida, 2013;Pakbaz, 2014;Phillips et al, 2016;Samarindo et al, 2013;Zhang, 2018) In addition, previous researchers also researched to improve the quality of teacher candidates through multimodal feedback and not improve the quality of HOTS-based questions. (Panhoon & Wongwanixh, 2013;Yusuf et al, 2017) There are also previous research that focused on the use of multimodal feedback with technology to improve learner abilities in general (Campbell & Feldmann, 2017;Emery et al, 2003;Hurst & Vriens, 2016;Jacko et al, 2004;J.-H. Lee & Spence, 2008;J. Lee et al, 2009;Sun et al, 2010) Furthermore, previous studies only focused on the perception of multimodal feedback (Dyan, 2017).…”

Section: Introductionmentioning

confidence: 99%

Multimodal Feedback Workshop for English Teachers in Designing Questions Based on Higher Order Thinking Skill

Syafryadin

Wardhana

Astrid

2022

AIJP

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This study aimed to determine whether or not there is quality improvement of HOTS-based questions through multimodal feedback made by English teachers. Besides, this study intended to find out the forms of feedback given during the implementation of multimodal feedback and English teachers' perception of multimodal feedback in designing HOTS-based English questions workshops. This study used a mixed-method involving 30 English teachers willing to participate in the training. Furthermore, research data collection was done through the provision of tests, interviews, and observations. Several experts have validated the instruments used in this study. The data were analyzed quantitatively and qualitatively. Quantitative data were analyzed using SPSS, while qualitative data in interviews and observation sheets were analyzed using several stages, including data reduction, data display, and concluding. The results of this study indicated a quality improvement of HOTS-based English questions that have been made by English teachers, which was evidenced by an increase in the results from pretest to posttest. The next finding is that three types of feedback helped teachers make HOTS-based English questions through multimodal feedback: peer feedback, oral conference, and written feedback. Another finding was that English teachers gave a positive perception towards designing HOTS-based English questions through multimodal feedback because these activities provided positive input on their ability to make HOTS-based English questions. In conclusion, the findings of this study benefit English teachers in designing HOTS-based questions, so that teachers can implement the result of the workshop in the teaching and learning process.

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Exploring Bi-modal Feedback in Augmented Reality

Varghese

2020

IndiaHCI '20: Proceedings of the 11th Indian Conference on Human-Computer Interaction

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Multimodal feedback for finger-based interaction in mobile augmented reality

Cited by 4 publications

References 12 publications

GestureDrawer

GestureDrawer

Multimodal Feedback Workshop for English Teachers in Designing Questions Based on Higher Order Thinking Skill

Exploring Bi-modal Feedback in Augmented Reality

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