Abstract
“MOOC” (Massive Open Online Course) is a large-scale open online learning platform. MOOC forum is the learner to learn the mutual place, through the course of the forum interactive text data as the data base, the combination of word2vec and machine learning algorithm to build emotional, and then combined with the learning emotion of this emotion classifier on learners’ emotional tendency judgment, thus obtains the MOOC learning environment learning and emotional changes the exchange of learning, which can make up for the learning between the loss of emotion and increase the learning and improve the learning efficiency and learning quality of learners.
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References
Christensen, G., Steinmetz, A., Alcorn, B., et al.: The MOOC phenomenon: who takes massive open online courses and why? Social Science Electronic Publishing (2016)
游晓明, 方志军, 姚兴华. MOOC + 翻转课堂混合教学模式下应用型高校教学改革与实践. 软件导刊·教育技术 16(1), 7–9 (2017)
Rieber, L.P.: Participation patterns in a massive open online course (MOOC) about statistics. Br. J. Educ. Technol. 48(6), 1295–1304 (2017)
张慧毅, 徐荣贞, 孙杰,等. 基于MOOC教学平台的教学模式建构研究. 中国教育信息化 2, 32–34 (2017)
Sunar, A., Su, W., Abdullah, N., et al.: How learners’ interactions sustain engagement: a MOOC case study. IEEE Trans. Learn. Technol. PP(99), 475–487 (2017)
Brouns, F., Teixeira, A., Morgado, L., et al.: Designing massive open online learning processes: the sMOOC pedagogical framework. In: Open Education: from OERs to MOOCs. Springer, Heidelberg (2017). https://doi.org/10.1007/978-3-662-52925-6_16
Liu, Z., Zhang, W., Sun, J., et al.: Emotion and associated topic detection for course comments in a MOOC platform. In: International Conference on Educational Innovation Through Technology. IEEE (2017)
秦瑾若, 傅钢善. MOOC课程讨论区中的社会性交互研究——以中国大学MOOC平台《现代教育技术》课程为例. 中国教育信息化 5, 20–24 (2017)
Bergner, Y., Kerr, D., Pritchard, D.E.: Methodological challenges in the analysis of MOOC data for exploring the relationship between discussion forum views and learning outcomes. In: International Conference on Field Programmable Logic and Applications. IEEE, pp. 1–4 (2015)
Wong, J.S., Pursel, B., Divinsky, A., et al.: Analyzing MOOC discussion forum messages to identify cognitive learning information exchanges. In: Asis&t Meeting: Information Science with Impact: Research in and for the Community. American Society for Information Science, p. 23 (2015)
Dillon, J., Bosch, N., Chetlur, M., et al.: Student emotion, co-occurrence, and dropout in a MOOC context. In: EDM, pp. 353–357 (2016)
Tao, H.: The ethical risks and controlling of the participation of university library in MOOC construction. Library Work & Study (2017)
马相春, 钟绍春, 徐妲. 大数据视角下个性化自适应学习系统支撑模型及实现机制研究. 中国电化教育 4, 97–102 (2017)
Wise, A.F., Cui, Y., Vytasek, J.: Bringing order to chaos in MOOC discussion forums with content-related thread identification. In: International Conference on Learning Analytics & Knowledge, pp. 188–197. ACM (2016)
Dupré, D., Mckeown, G.: Dynamic analysis of automatic emotion recognition using generalized additive mixed models. In: Aisb Convention (2017)
李晓磊. 面向评论的文本倾向性分析中关键问题的研究. 北京化工大学 (2016)
张向阳, 那日萨. 基于复杂网络的情感分类特征选择. 计算机应用研究 4, 1000–1003 (2017)
曹杰, 冯雨晖, 宿晓坤,等. 基于深度学习模型Word2Vec的短文本语义相似性判别方法和系统, CN 106844346 A[P] (2017)
隋浩. 基于Word2Vec的微博情感新词识别与倾向判断研究. 广西大学 (2016)
陆峰. 基于word2vec扩充情感词典的商品评论倾向分析. 电脑知识与技术 13(5), 143–145 (2017)
付丽娜, 肖和, 姬东鸿. 基于OC-SVM的新情感词识别. 计算机应用研究 7, 1946–1948 (2015)
O’Connor, B., Balasubramanyan, R., Routledge, B.R., Smith, N.A.: From tweets to polls: Linking text sentiment to public opinion time series. ICWSM 11, 122–129 (2010)
Bollen, J., Mao, H., Zeng, X.: Twitter mood predicts the stock market. J. Comput. Sci. 2(1), 1–8 (2011)
Abeywardena, I.S.: Public opinion on OER and MOOC: a sentiment analysis of twitter data. In: International Conference on Open and Flexible Education (2014)
Costello, E., Nair, B., Brown, M., et al.: Social media #MOOC mentions: lessons for MOOC research from analysis of twitter data. In: Show Me the Learning Proceedings Ascilite (2016)
Wen, M., Yang, D., Rosé, C.P.: Sentiment analysis in MOOC discussion forums: what does it tell us? In: Educational Data Mining (2014)
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Fei, H., Li, H. (2018). The Study of Learners’ Emotional Analysis Based on MOOC. In: Xiao, J., Mao, ZH., Suzumura, T., Zhang, LJ. (eds) Cognitive Computing – ICCC 2018. ICCC 2018. Lecture Notes in Computer Science(), vol 10971. Springer, Cham. https://doi.org/10.1007/978-3-319-94307-7_14
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