| Autor: |
P. Radhika, Varma, P. Suresh, M. Santosh, Rao, G. V., Kamakshaiah, K. |
| Předmět: |
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| Zdroj: |
International Journal of Advanced Research in Computer Science; Nov/Dec2017, Vol. 8 Issue 9, p240-244, 5p |
| Abstrakt: |
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. 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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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