Thread Structure Prediction for MOOC Discussion Forum

• 作者: Chengjie Sun Lei Lin Shang-wen Li
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: THREAD STRUCTURE PREDICTION Crowdsourcing Lightly supervised LEARNING MOOC
• 年，卷（期）: 2016,（2）
• 页码范围: 30-32
• 页数: 3页
• 分类号: C5

摘要

Discussion forums are an indispensable interactive component for Massive Open Online Courses(MOOC).However,the organization of current discussion forums is not well-designed.Trouble-shooting threads are valuable for both learners and instructors,but they are drowned out in the forums with huge amounts of threads.This work first built a labeled data set for trouble-shooting thread structure prediction by crowdsourcing and then proposed methods for trouble-shooting thread detection and thread structure prediction on the data set.The output of this work can be used to spot trouble-shooting threads and show them along with structure tags in MOOC discussion forums.