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題名 A Smartphone Assisted Learning System with Wireless Sensors
作者 蔡子傑
Tsai,Tzu-Chieh;Peng,Chen-Tzu
貢獻者 資科系
關鍵詞 Wireless sensor;Smartphone;Learning;Education
日期 2011-08
上傳時間 2-九月-2014 17:19:31 (UTC+8)
摘要 We propose a portable and convenient learning assisted system by using Android Smartphone with wireless sensors. The system senses and collects the data of learning behaviors with the Smartphone as the processing unit. In order to optimize the inference, we used SVM (Support Vector Machine) technology to analyze the collected data. For the evaluation experiment, we invite college students to use it. The result shows that 78% of subject feels satisfied with the usage and interface of the system. In addition, the average accuracy of the prediction model using progress label is 83%. In conclusion, we confirmed the feasibility of improving study effect by using Smartphone with wireless sensors.
關聯 Advances in Computer Science, Environment, Ecoinformatics, and Education Communications in Computer and Information Science Volume 216, 2011, pp 557-561
資料類型 book/chapter
DOI http://dx.doi.org/10.1007/978-3-642-23345-6_100
dc.contributor 資科系en_US
dc.creator (作者) 蔡子傑zh_TW
dc.creator (作者) Tsai,Tzu-Chieh;Peng,Chen-Tzuen_US
dc.date (日期) 2011-08en_US
dc.date.accessioned 2-九月-2014 17:19:31 (UTC+8)-
dc.date.available 2-九月-2014 17:19:31 (UTC+8)-
dc.date.issued (上傳時間) 2-九月-2014 17:19:31 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/69582-
dc.description.abstract (摘要) We propose a portable and convenient learning assisted system by using Android Smartphone with wireless sensors. The system senses and collects the data of learning behaviors with the Smartphone as the processing unit. In order to optimize the inference, we used SVM (Support Vector Machine) technology to analyze the collected data. For the evaluation experiment, we invite college students to use it. The result shows that 78% of subject feels satisfied with the usage and interface of the system. In addition, the average accuracy of the prediction model using progress label is 83%. In conclusion, we confirmed the feasibility of improving study effect by using Smartphone with wireless sensors.en_US
dc.format.extent 170369 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Advances in Computer Science, Environment, Ecoinformatics, and Education Communications in Computer and Information Science Volume 216, 2011, pp 557-561en_US
dc.subject (關鍵詞) Wireless sensor;Smartphone;Learning;Educationen_US
dc.title (題名) A Smartphone Assisted Learning System with Wireless Sensorsen_US
dc.type (資料類型) book/chapteren
dc.identifier.doi (DOI) 10.1007/978-3-642-23345-6_100en_US
dc.doi.uri (DOI) http://dx.doi.org/10.1007/978-3-642-23345-6_100en_US