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Construction on Learning Analytics Object for Sharing and Interoperation of Educational Big Data

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Current Developments in Web Based Learning (ICWL 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9584))

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Abstract

Educational Big Data (EBD) come from various types of Educational Systems such as LMS, CMS, ITS, SLS, and MOOCs. How to share and interoperate Educational Big Data for Learning Analytics (LA) has garnered a lot of research attention. In the paper, we probe into the process of Learning Analytics, outline the dataflow of EBD, define the Learning Analytics Object, and propose a new data format model for the Learning Analytics object to actualize the sharing and interoperability of Learning Analytics.

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References

  1. Ferreira, J.: Big Data in Education: The 5 Types That Matter [Blog post] (2013). https://www.knewton.com/resources/blog/ceo-jose-ferreira/big-data-in-education/. Accessed 12 Sept 2015

  2. Siemens, G.: Knewton-the future of education?. http://www.learninganalytics.net. Accessed 28 Aug 2015

  3. Adam Cooper, A.: CETIS Analytics Series: A Framework of Characteristics for Analytics, vol. 1, no. 7 (2012). http://publications.cetis.org.uk/2012/524

  4. IEEE: 1484.11.1, IEEE Standard for Learning Technology - Data Model for Content Object Communication (2004). http://www.ieee.org/index.html. Accessed 10 Aug 2015

  5. IEEE: 1484.11.2, IEEE Standard for Learning Technology - ECMAScript Application Programming Interface for Content to Runtime Services Communication (2003). http://www.ieee.org/index.html. Accessed 10 Aug 2015

  6. Advanced Distributed Learning. Experience API Version 1.0.1. https://github.com/adlnet/xAPI-Spec/blob/master/xAPI.md. Accessed 10 Aug 2015

  7. Learning Measurement for Analytics Whitepaper, IMS Global Learning Consortium. http://www.imsglobal.org/IMSLearningAnalyticsWP.pdf. Accessed 10 Aug 2015

  8. Booch, G., Maksimchuk, R.A., Engle, M.W., Young, B.J., Conallen, J., Housyon, K.A.: Object-Oriented Analysis and Design with Applications, 3rd edn. Pearson Education India, Chennai (2006)

    Google Scholar 

  9. Polsani, P.R.: Use and abuse of reusable learning objects. J. Digit. Inf. 3(4) (2003). https://journals.tdl.org/jodi/index.php/jodi/article/view/89

  10. IEEE: IEEE Learning Technology Standards Committee (LTSC) IEEE P1484.12 Learning Object Metadata Working Group; WG12 Home page (2001). http://ltsc.ieee.org/wg12/s_p.html

  11. Wiley, D.A.: Connecting learning objects to instructional design theory: a definition, a metaphor, and a taxonomy (2002). http://www.reusability.org/read/chapters/wiley.doc. Accessed 10 Aug 2015

  12. Verbert, K., Manouselis, N., Drachsler, H., Duval, E.: Dataset-driven research to support learning and knowledge analytics. Educ. Technol. Soc. 15(3), 133–148 (2012)

    Google Scholar 

  13. TEL Europe: DataShop. https://pslcdatashop.web.cmu.edu/index.jsp?datasets=public. Accessed 10 Aug 2015

  14. Koedinger, K.R., Baker, R.S.J.d., Cunningham, K., Skogsholm, A., Leber, B., Stamper, J.: A data repository for the EDM community: the PSLC DataShop. In: Handbook of Educational Data Mining, vol. 2011, pp. 43–55. CRC Press (2010)

    Google Scholar 

  15. Siemens, G.: What Are Learning Analytics. http://www.elearnspace.org/blog/2010/08/25/what-are-learning-analytics/. Accessed 16 Jan 2011

  16. Elias, T.: Learning Analytics: Definitions, Processes and Potential. http://learninganalytics.net/LearningAnalyticsDefinitionsxProcessesPotential.pdf. Accessed 16 Jan 2011

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Acknowledgments

This work was supported by the 2014 Shanghai Pujiang Program (Grant 14PJC034) and the 2014 Shanghai “Technology Innovation Action Plan” Project (Grant 14511109300).

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Authors and Affiliations

  1. East China Normal University, 3663 Zhongshan Road (N.), Shanghai, China

    Yonghe Wu & Wei Zhong

  2. East China Normal University, 500 Dongchuan Road, Shanghai, China

    Chun Zhou & Xiaoling Ma

Authors
  1. Yonghe Wu
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  2. Wei Zhong
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  3. Chun Zhou
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  4. Xiaoling Ma
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Corresponding author

Correspondence to Yonghe Wu .

Editor information

Editors and Affiliations

  1. University of Macau, Macau, China

    Zhiguo Gong

  2. The University of Hong Kong, Hong Kong, China

    Dickson K. W. Chiu

  3. The Hong Kong Polytechnic University, Hong Kong, China

    Di Zou

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© 2016 Springer International Publishing Switzerland

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Wu, Y., Zhong, W., Zhou, C., Ma, X. (2016). Construction on Learning Analytics Object for Sharing and Interoperation of Educational Big Data. In: Gong, Z., Chiu, D., Zou, D. (eds) Current Developments in Web Based Learning. ICWL 2015. Lecture Notes in Computer Science(), vol 9584. Springer, Cham. https://doi.org/10.1007/978-3-319-32865-2_20

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  • DOI: https://doi.org/10.1007/978-3-319-32865-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32864-5

  • Online ISBN: 978-3-319-32865-2

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