NDLI: Spatial computing goes to education and beyond: can semantic trajectory characterize students?

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Spatial computing goes to education and beyond: can semantic trajectory characterize students?

Content Provider	ACM Digital Library
Author	Ju, Sungha Oh, Won Seob Yun, Sung Bum Yoon, Sanghyun Ma, Jong Won Heo, Joon
Abstract	Spatial big data (SBD) has been utilized in many fields and we propose SBD analytics to apply to education with semantic trajectory data of undergraduate students in Songdo International Campus at Yonsei University. Higher education is under a pressure of disruptive innovation, so that colleges and universities strive to provide not only better education but also customized service to every single student, for a matter of survival in upcoming drastic wave. The entire research plan is to present a smart campus with SBD analytics for education, safety, health, and campus management, and this research is composed of four specific items: (1) to produce 3D mapping for project site; (2) to build semantic trajectory based on class attendance records, dorm gate entry records, etc.; (3) to collect pedagogical and other parameters of students; (4) to find relationship among trajectory patterns and pedagogical characteristics. Successful completion of the research would set a milestone to use semantic trajectory to predict student performance and characteristics, even further to go to proactive student care system and student activity guiding system. It can eventually present better customized education services to participating students.
Starting Page	14
Ending Page	17
Page Count	4
File Format	PDF
ISBN	9781450345811
DOI	10.1145/3006386.3006389
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-31
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Spatial big data (sbd) Education Student characterization Semantic trajectory
Content Type	Text
Resource Type	Article

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