Supporting Seamless Learning with a Learning Analytics Approach

  • Noriko UosakiEmail author
  • Kousuke Mouri
  • Mahiro Kiyota
  • Hiroaki Ogata
Part of the Lecture Notes in Educational Technology book series (LNET)


This chapter explores a learning analytics approach for the implementation of a seamless learning environment. Our developed seamless learning system called VASCORLL (Visualization and Analysis System for COnnecting Relationships of Learning Logs) and AETEL (Actions and learning on E-TExtbook Logging) System will be described. AETEL, an eBook system, was implemented on top of SCROLL, another developed system of ours. VASCORLL was also implemented on SCROLL. The objectives of VASCORLL are for visualizing and analyzing the learning logs collected from SCROLL to provide learners with more learning opportunities as well as to link eBook learning and real-life learning. Two types of visualization structures, eBook learning structure and real-life learning structure, were adapted. Our research questions are (1) Is VASCORLL able to enhance learners’ learning opportunities? (2) Does it facilitate finding important words in the seamless learning environment? and (3) Which centrality is the most effective in supporting learning in the seamless learning environment? From an evaluation experiment conducted at a university in Japan, it was found that VASCORLL enhanced learning opportunities and that it was a useful tool to find central words bridging eBook learning and real-life learning when it was based on betweenness centrality. VASCORLL had a high usability, and it contributed to enhancing learners’ learning opportunities in a way that it helped users link their eBook learning with a real-life learning as well as link their learning with that of other users. The system is expected to play an important role as a tool that links both learning modes.


eBook Learning analytics Mobile-assisted language learning Network graph Seamless learning Social network analysis 



Part of this research work was supported by PRESTO from Japan Science and Technology Agency, and the grant-in-aid for Scientific Research No. 16H06304 and No. 17K12947 from the Ministry of Education, Science, Sports, and Culture in Japan.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Noriko Uosaki
    • 1
    Email author
  • Kousuke Mouri
    • 2
  • Mahiro Kiyota
    • 3
  • Hiroaki Ogata
    • 4
  1. 1.Center for International Education and ExchangeOsaka UniversitySuita, OsakaJapan
  2. 2.Department of Computer and Information SciencesTokyo University of Agriculture and TechnologyKoganei, TokyoJapan
  3. 3.NTT Data Kyushu CorporationKyushu UniversityFukuokaJapan
  4. 4.Academic Center for Computing and Media StudiesKyoto UniversityKyotoJapan

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