Abstract
Discussion forum boards play a crucial role in the interactions among learners and supervisors on e-learning. SWAYAM (Study webs of Active Learning for Young Aspiring Minds) is the first Indian MOOC (Massive open online course) adopted in all higher education institutes, high schools, and vocational schools as a database of their learning materials and discussions. However, being in its initial stage, SWAYAM lacks a well-designed structure in its discussion forums which is necessary for encouraging student engagement in learning.
In this study, we aim to redesign the discussion forum systematically by classifying queries to enhance the learner-supervisor interactions in SWAYAM. In a previous study, FENG [1] developed a model with a convolutional neural network on Rossi’s data set to classify posts in the discussion forum of Coursera which helped to improve the course quality in MOOCs and students’ learning effect. Our study initially adopted a manual classification while in the future we will implement a hybrid approach of machine learning along with the Rule-Based expert system to predict a type of query in the discussion forum of SWAYAM. This proposed system will segregate the comments of the discussion forum using specified indicators and identify repetitive comments. The learners can acquire knowledge frequently from the discussions instead of navigating all the comments separately or retrieving the visual learning materials. On the other hand, subject matter experts (SME) can answer the relevant queries at once after indicator-based segregation of queries and need not to reply to every query distinctly.
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Neha, Kim, E. (2020). Designing Discussion Forum in SWAYAM for Effective Interactions Among Learners and Supervisors. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2020 – Late Breaking Posters. HCII 2020. Communications in Computer and Information Science, vol 1294. Springer, Cham. https://doi.org/10.1007/978-3-030-60703-6_38
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DOI: https://doi.org/10.1007/978-3-030-60703-6_38
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