-ANALYSIS OF RELEVANCY USING RAPID MINER WITH AN EXPERIMENTAL STUDY ON POPULAR DISCUSSION FORUM

Radhika Patthi, Dr P.Suresh Varma, M. Santosh, Dr.G.V. Rao, K. Kamakshaiah

Abstract


Massive Open Online Courses (MOOCs) is a model for delivering course content online independent of attendance and place .Online Discussion not only brings opportunities for innovation in education but also shifts focus from traditional educations. MOOCs in Computer Programming can help in attracting students because it personalizing their learning experiences at lower cost. In addition to watching videos, students also engage in discussion forums to share their understanding. On the other hand, online discussion forums provide a platform to ingenious students to share their ideas in a holistic way which is not possible through regular websites, videos, online courses. Both novice and expert users search the web exhaustively for their coding practises to learn gradations behind libraries, programming languages and frameworks.[1,2] In community-based question-answering communities, where students ask questions there is no guarantee that students get their what they are searching for. This poses an unsatisfactory level in the student. In this paper, we present a machine learning model that predicts the relevancy of answers to the forum questions using historical forum data .The study attempted to identify the relevance criteria that people use when browsing a discussion forum

Keywords


MOOC’s, Engagement, Discussion forums, Prediction, Relevancy.

Full Text:

PDF

References


J. Brandt, P. J. Guo, J. Lewenstein, M. Dontcheva, and S. R. Klemmer, “Two studies of opportunistic programming: Interleaving web foraging, learning, and writing code,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ser. CHI ’09. New York, NY, USA: ACM, 2009, pp. 1589–1598.

J. Brandt, M. Dontcheva, M. Weskamp, and S. R. Klemmer, “Examplecentric programming: Integrating web search into the development environment,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ser. CHI ’10. New York, NY, USA: ACM, 2010, pp. 513–522.

Smith, M.K., Wood, W.B., Adams, W.K., Wieman, C., Knight, J.K., Guild, N., Su, T.T.: Why peer discussion improves student performance on in-class concept questions. Science 323, 122–124 (2009)

Stephens-Martinez, K., Hearst, M.A., Fox, A.: Monitoring moocs: which information sources do instructors value? In: Proceedings of the First ACM Conference on Learning@ Scale Conference, pp. 79–88. ACM (2014)

Andresen, M.A.: Asynchronous discussion forums: Success factors, outcomes, assessments, and limitations. Educational Technology & Society 12, 249–257 (2009)

Zhu, E.: Interaction and cognitive engagement: An analysis of four asynchronous online discussions. Instructional Science 34, 451–480 (2006)

Wen, M., Yang, D., Rosè, C.P.: Sentiment analysis in MOOC discussion forums: What does it tell us? In: Proceedings of Educational Data Mining (2014)

Huang, J., Dasgupta, A., Ghosh, A., Manning, J., Sanders, M.: Superposter behavior in mooc forums. In: Proceedings of the First ACM Conference on Learning@ Scale Conference, pp. 117–126. ACM (2014)

Anderson, D. Huttenlocher, J. Kleinberg, and J. Leskovec, “Discovering value from community activity on focused question answering sites: A case study of stack overflow,” in Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ser. KDD ’12. New York, NY, USA: ACM, 2012, pp. 850–858.

L. Mamykina, B. Manoim, M. Mittal, G. Hripcsak, and B. Hartmann, “Design lessons from the fastest q&a site in the west,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ser. CHI ’11. New York, NY, USA: ACM, 2011, pp. 2857–2866.

S. L. Emerson, “Usenet: A Bulletin Board for Unix Users,” Byte magazine, vol. 8, no. 10, pp. 219–236, October 1983.

H. Rheingold, The virtual community : homesteading on the electronic frontier. Reading, Massachusetts: Addison Wesley, 1993.

“edX course: Introduction to Computer Science and Programming Using Python,” https://www.edx.org/course/ introduction-computer-science-mitx-6-00-1x-0, accessed: March 2015.




DOI: https://doi.org/10.26483/ijarcs.v8i9.4899

Refbacks

  • There are currently no refbacks.




Copyright (c) 2017 International Journal of Advanced Research in Computer Science