Skip to main content

Learning Analytics Data Flow and Visualizing for Ubiquitous Learning Logs in LMS and Learning Analytics Dashboard

  • Conference paper
  • First Online:
Distributed, Ambient and Pervasive Interactions (HCII 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12203))

Included in the following conference series:

Abstract

In this paper, we describe about a kind of data flow design that between ubiquitous learning log system called SCROLL and learning analytics and visualizing system called Learning Analytics Dashboard (LAD). SCROLL is a ubiquitous learning system what is logging students’ learning behaviors data in database, and SCROLL can provide students suitable learning method and location to learn efficiently. Lots of paper show that it is appreciate to share the learning data in SCROLL to the other learning analytics system like LTI, Bookroll, Moodle and so on. Learning Analytics Dashboard (LAD) is also a learning data analytics and visualizing system. So share students’ learning data from SCROLL to LAD to show and help students to know their students’ learning situation is the proposal of this paper.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ogata, H., Matsuka, Y., El-Bishouty, M.M., Yano, Y.: LORAMS: linking physical objects and videos for capturing and sharing learning experiences towards ubiquitous learning. Int. J. Mob. Learn. Organ. 3(4), 337–350 (2009)

    Article  Google Scholar 

  2. Hwang, G.-J., Tsai, C.-C., Yang, S.J.H.: Criteria, strategies and research issues of context-aware ubiquitous learning. Educ. Technol. Soc. 11(2), 81–91 (2008)

    Google Scholar 

  3. Wong, L.-H., Looi, C.-K.: Vocabulary learning by mobile-assisted authentic content creation and social meaning making: Two case studies. J. Comput. Assist. Learn. 26(5), 421–433 (2010)

    Article  Google Scholar 

  4. Nicholas, H., Ng, W.: Mobile seamless learning and its pedagogy. In: Wong, L.-H., Milrad, M., Specht, M. (eds.) Seamless Learning in the Age of Mobile Connectivity, pp. 261–280. Springer, Singapore (2015). https://doi.org/10.1007/978-981-287-113-8_13

    Chapter  Google Scholar 

  5. Ogata, H., Yin, C., Okubo, F., Shimada, A., Kojima, K., Yamada, M.: E-book-based learning analytics in university education. In: International Conference on Computer in Education (ICCE 2015), pp. 401–406 (2015)

    Google Scholar 

  6. Kitto, K., Cross, S., Waters, Z., Lupton, M.: Learning analytics beyond the LMS: the connected learning analytics toolkit. In: Proceedings of the Fifth International Conference on Learning Analytics and Knowledge, pp. 11–15 (2015)

    Google Scholar 

  7. Durall, E., Gros, B.: Learning analytics as a metacognitive tool. In: Proceedings of the 6th International Conference on Computer Supported Education - Volume 1, Portugal, pp. 380–384 (2014)

    Google Scholar 

  8. Majumdar, R., Akçapınar, A., Akçapınar, G., Flanagan, B., Ogata, H.: LAViEW: learning analytics dashboard towards evidence-based education (LAK 2019) (2019)

    Google Scholar 

Download references

Acknowledgements

The part of this research work was supported by the Grant in-Aid for Scientific Research No. 17K12947 from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Songran Liu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, S., Mouri, K., Ogata, H. (2020). Learning Analytics Data Flow and Visualizing for Ubiquitous Learning Logs in LMS and Learning Analytics Dashboard. In: Streitz, N., Konomi, S. (eds) Distributed, Ambient and Pervasive Interactions. HCII 2020. Lecture Notes in Computer Science(), vol 12203. Springer, Cham. https://doi.org/10.1007/978-3-030-50344-4_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-50344-4_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50343-7

  • Online ISBN: 978-3-030-50344-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics