TY - GEN
T1 - Employing Multi-Sensors to Implement Real-Time Neurofeedback System for Improving Performance of STEM Curriculum
AU - Chien, Yu Cheng
AU - Huang, Yueh Min
AU - Lai, Chia Hung
N1 - Funding Information:
ACKNOWLEDGMENT This research is partially supported by the Ministry of Science and Technology, Taiwan, R.O.C. under Grant no. MOST 106-2511-S-006 -006 -MY3, MOST 106-2511-S-006 - 001 -MY3, MOST 106-2511-S-006 -010 -MY3, MOST 103-2511-S-006 -002 -MY3, and MOST 103-2511-S-006 -007 - MY3.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/9/17
Y1 - 2018/9/17
N2 - This study aims based on brainwave and visual sensors to construct an attention recognition mechanism and apply it to develop a real-time neurofeedback system that can maintain an effective learning status. Through employing attention recognition mechanism, this system can activate a feedback to improve his/her attention in real-time when learners' reading attention was detected too low. In this investigate, a total of 30 students from one high school in South Taiwan were recruited to participate in this experiment. Science, technology, engineering and mathematics (STEM) education issue have received a lot of attention. Researchers, educators, practitioners, and business communities forwarded several high profile proposals to improve competitiveness in science and technology development (Kuenzi, 2008). On the other hand, learning is an active processes of cognition, especially (Freeman et al., 2014). Schneps, Thomson, Chen, Sonnert, and Pomplun (2013) noted that sustain learner's attention is a very important in learning activities. According to attention can increase memory, comprehension, and cognition, which further improving learning performance. Hence, we develop a real-time neurofeedback system to enhance learner's attention in reading e-book. In this study, participants had asked to wear NeuroSky to reading e-books during experimental progress. The brainwave functions automatically activated to detect learner's attention. The briefly data had collected and analysis. The results indicate the neurofeedback can provide a way of feedback to affect learner's brain state to maintain an effective learning status, and further improving their learning performance. In the future, we suggest that designing further experiments to verify or enhance the principles and cues adopted. Different backgrounds variable can use to divide into difference group for investigating the influence of learning.
AB - This study aims based on brainwave and visual sensors to construct an attention recognition mechanism and apply it to develop a real-time neurofeedback system that can maintain an effective learning status. Through employing attention recognition mechanism, this system can activate a feedback to improve his/her attention in real-time when learners' reading attention was detected too low. In this investigate, a total of 30 students from one high school in South Taiwan were recruited to participate in this experiment. Science, technology, engineering and mathematics (STEM) education issue have received a lot of attention. Researchers, educators, practitioners, and business communities forwarded several high profile proposals to improve competitiveness in science and technology development (Kuenzi, 2008). On the other hand, learning is an active processes of cognition, especially (Freeman et al., 2014). Schneps, Thomson, Chen, Sonnert, and Pomplun (2013) noted that sustain learner's attention is a very important in learning activities. According to attention can increase memory, comprehension, and cognition, which further improving learning performance. Hence, we develop a real-time neurofeedback system to enhance learner's attention in reading e-book. In this study, participants had asked to wear NeuroSky to reading e-books during experimental progress. The brainwave functions automatically activated to detect learner's attention. The briefly data had collected and analysis. The results indicate the neurofeedback can provide a way of feedback to affect learner's brain state to maintain an effective learning status, and further improving their learning performance. In the future, we suggest that designing further experiments to verify or enhance the principles and cues adopted. Different backgrounds variable can use to divide into difference group for investigating the influence of learning.
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U2 - 10.1109/WEEF.2017.8467061
DO - 10.1109/WEEF.2017.8467061
M3 - Conference contribution
AN - SCOPUS:85055429492
T3 - Proceedings - 2017 7th World Engineering Education Forum, WEEF 2017- In Conjunction with: 7th Regional Conference on Engineering Education and Research in Higher Education 2017, RCEE and RHEd 2017, 1st International STEAM Education Conference, STEAMEC 2017 and 4th Innovative Practices in Higher Education Expo 2017, I-PHEX 2017
SP - 94
EP - 96
BT - Proceedings - 2017 7th World Engineering Education Forum, WEEF 2017- In Conjunction with
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th World Engineering Education Forum, WEEF 2017
Y2 - 13 November 2017 through 16 November 2017
ER -