2014
DOI: 10.1016/j.compedu.2014.06.008
|View full text |Cite
|
Sign up to set email alerts
|

Taking a signal: A review of gesture-based computing research in education

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
36
0
4

Year Published

2015
2015
2022
2022

Publication Types

Select...
5
3
1

Relationship

2
7

Authors

Journals

citations
Cited by 51 publications
(40 citation statements)
references
References 50 publications
0
36
0
4
Order By: Relevance
“…Hung et al (2014) devised learning strategies for learners to engage arm movements as learning stimuli to deal with abstract concepts of fundamental optics and improve their comprehension of the learning content. Many other researchers have also designed learning strategies based on embodied cognition to improve learners' learning performance and decrease cognitive load in terms of learning English, Chinese, mathematics, and functional fitness (Alibali and Nathan 2011;Chen and Fang 2014;Fang et al 2015;Hao et al 2010;Kuo et al 2014;Macedonia et al 2011;McNeill 1992;Sheu and Chen 2014;Sheu et al 2015). These previous studies have suggested that appropriate learning approaches supported by technologies for natural user interaction can help learners in obtaining better learning outcomes.…”
Section: Introductionmentioning
confidence: 96%
“…Hung et al (2014) devised learning strategies for learners to engage arm movements as learning stimuli to deal with abstract concepts of fundamental optics and improve their comprehension of the learning content. Many other researchers have also designed learning strategies based on embodied cognition to improve learners' learning performance and decrease cognitive load in terms of learning English, Chinese, mathematics, and functional fitness (Alibali and Nathan 2011;Chen and Fang 2014;Fang et al 2015;Hao et al 2010;Kuo et al 2014;Macedonia et al 2011;McNeill 1992;Sheu and Chen 2014;Sheu et al 2015). These previous studies have suggested that appropriate learning approaches supported by technologies for natural user interaction can help learners in obtaining better learning outcomes.…”
Section: Introductionmentioning
confidence: 96%
“…These technologies enable the user to interact with a computer device in ways that mimic natural communication forms such as speaking, using body movements, and hand gestures (Sheu and Chen 2014) and as such are also referred to as Bintuitive technology^ (Johnson et al 2014). Some examples of use in the classroom are ICTs based on gestural recognition, such as Microsoft Kinect, and input, such as tablets, e.g., the iPad (for a review of gesture-based computing research in education, see Sheu and Chen 2014). While ICTs based on gestural recognition interfaces are likely to remain niche products in classrooms, the prevalence of tablet use for learning in both schools and workplaces is increasing as part of a growing trend toward a Bbring your own device^model (Docebo 2014).…”
Section: Introductionmentioning
confidence: 99%
“…Many innovative applications for somatosensory technologies have been proposed in recent years, such as language learning, assisted living for the differently abled, medical rehabilitation, and posture adjustment in sports physiology (Hwang, Wu, & Kuo, 2013;Sheu & Chen, 2014;Zaharias, Michael, & Chrysanthou, 2013). In terms of language learning, somatosensory technologies have been used to propose game-based learning approaches to enable more immersive experience for the learners in simulation environments.…”
Section: Literature Reviewmentioning
confidence: 99%