Skip to main content

Classsourcing: Crowd-Based Validation of Question-Answer Learning Objects

  • Conference paper
Computational Collective Intelligence. Technologies and Applications (ICCCI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8083))

Included in the following conference series:

Abstract

The Web 2.0 principles reflect into learning domain and provide means for interactivity and collaboration. Student activities during learning in this environment can be utilized to gather data usable for learning corpora enrichment. It is now a research issue to examine, to what extent the student crowd is reliable in delivering useful artifacts and to bring in suitable tools to enable this. In this paper we present a method for crowd-based validation of question-answer learning objects involving interactive exercise for learners. The method utilizes students’ correctness estimations of answers provided by other students during learning. We show that aggregate student crowd estimations are to big extent comparable to teacher’s evaluations of provided answers.

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adamic, L.A., Zhang, J., Bakshy, E., Ackerman, M.S.: Knowledge sharing and yahoo answers: everyone knows something. In: Proc. of the 17th Int. Conf. on World Wide Web (WWW 2008), pp. 665–674. ACM, New York (2008)

    Chapter  Google Scholar 

  2. Agichtein, E., Castillo, C., Donato, D., Gionis, A., Mishne, G.: Finding high-quality content in social media. In: Proc. of the Int. Conf. on Web Search and Web Data Mining, WSDM 2008, pp. 183–194. ACM, New York (2008)

    Chapter  Google Scholar 

  3. Chen, B.C., Dasgupta, A., Wang, X., Yang, J.: Vote calibration in community question-answering systems. In: Proc. of the 35th Int. ACM SIGIR Conf. on Research and Development in Information Retrieval (SIGIR 2012), pp. 781–790. ACM, New York (2012)

    Chapter  Google Scholar 

  4. Downes, S.: E-learning 2.0. eLearn magazine 2005, vol. 10 (1). ACM, New York (2005)

    Google Scholar 

  5. IEEE LTS: Draft Standard for Learning Object Metadata. IEEE Standard 1484.12.1. IEEE (2002) (retrieved March 2013)

    Google Scholar 

  6. Ghauth, K.I., Abdullah, N.A.: The Effect of Incorporating Good Learners’ Ratings in e-Learning Content-based Recommender System. Educational Technology & Society 14(2), 248–257 (2011)

    Google Scholar 

  7. Golovchinsky, G., Qvarfordt, P., Pickens, J.: Collaborative information seeking. Information Seeking Support Systems (2008)

    Google Scholar 

  8. Kidd, J., O’Shea, P., Baker, P., Kaufman, J., Allen, D.: Student-authored Wikibooks: Textbooks of the Future? In: McFerrin, K., et al. (eds.) Proc. of Society for Information Technology & Teacher Education Int. Conf. 2008, pp. 2644–2647. AACE, Chesapeake (2008)

    Google Scholar 

  9. Lawson, M.: Berners-Lee on the read/write web. BBC, Technology (2005), http://news.bbc.co.uk/1/hi/technology/4132752.stm (accessed March 31, 2013)

  10. Quinn, A.J., Bederson, B.B.: Human computation: a survey and taxonomy of a growing field. In: Proc. of the 2011 Annual Conf. on Human Factors in Computing Systems (CHI 2011), pp. 1403–1412. ACM, New York (2011)

    Chapter  Google Scholar 

  11. Stahl, G., Koschmann, T., Suthers, D.: Computer-supported collaborative learning: An historical perspective. In: Sawyer, R.K. (ed.) Cambridge Handbook of the Learning Sciences, pp. 409–426. Cambridge University Press, Cambridge (2006)

    Google Scholar 

  12. Šimko, M., Barla, M., Bieliková, M.: ALEF: A Framework for Adaptive Web-based Learning 2.0. In: Reynolds, N., Turcsányi-Szabó, M. (eds.) KCKS 2010. IFIP AICT, vol. 324, pp. 367–378. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  13. Šimko, M., Barla, M., Mihál, V., Unčík, M., Bieliková, M.: Supporting Collaborative Web-Based Education via Annotations. In: Proc. of W. Conf. on Educational Multimedia, Hypermedia & Telecommunications, ED-MEDIA 2011, pp. 2576–2585. AACE (2011)

    Google Scholar 

  14. Wheeler, S., Yeomans, P., Wheeler, D.: The good, the bad and the wiki: Evaluating student-generated content for collaborative learning. British Journal of Educational Technology 39(6), 987–995 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Šimko, J., Šimko, M., Bieliková, M., Ševcech, J., Burger, R. (2013). Classsourcing: Crowd-Based Validation of Question-Answer Learning Objects. In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2013. Lecture Notes in Computer Science(), vol 8083. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40495-5_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40495-5_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40494-8

  • Online ISBN: 978-3-642-40495-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics