A parallel neural network structure for sentiment classification of MOOCs discussion forums

Gao, Yi; Sun, Xia; Wang, Xin; Guo, Shou Xi; Feng, Jun

doi:10.3233/jifs-191572

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…The most significant feature of MOOCs is the two-way flow of information as compared to the traditional teaching methods available in literature. It is due to the fact that in the MOOC teaching method, students can discuss the difficulties they have encountered in their own learning or the areas of the teaching that they do not understand [ 9 , 10 ]. The problems or issues are conveyed to the teacher in the form of a message, and the teacher can understand the students' learning situation.…”

Section: Introductionmentioning

confidence: 99%

English Education Tutoring Teaching System Based on MOOC

Mi¹

2022

Computational Intelligence and Neuroscience

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In the process of continuous reform and development of education and teaching, some traditional teaching modes are gradually eliminated, whereas new teaching modes are gradually recognized by teachers and students. These modes are widely used in education and teaching due to their overwhelming characteristics. Among these emerging teaching modes, massive open online course (MOOC) is a relatively advanced teaching mode with a better application effect. Quickly and accurately detecting the cheating behavior of MOOC learners is of great significance for maintaining the development of the MOOC platform and English education counseling. This paper studies a deep-learning-based hybrid model for MOOC cheating detection. The model greatly improves the detection performance of a single model by integrating CNN, a bidirectional gated recurrent unit, and an attention mechanism. The proposed model selects the English learning behavior data of a MOOC platform to verify the performance of the algorithm. Simulation results show that the proposed scheme can greatly help MOOC-based English education tutoring.

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Section: Introductionmentioning

confidence: 99%

English Education Tutoring Teaching System Based on MOOC

Mi¹

2022

Computational Intelligence and Neuroscience

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“…Huang et al [ 27 ] used a layer of CNN and a double-layer LSTM to jointly capture text features for sentiment classification. Recently, some researchers have proposed a parallel combination of CNN + LSTM network structure and self-attention mechanism for the MOOC course review sentiment classification task, so as to better retain the features extracted from the network [ 28 ].…”

Section: Related Workmentioning

confidence: 99%

Modeling and Analysis of Learners’ Emotions and Behaviors Based on Online Forum Texts

Zhao

et al. 2022

Computational Intelligence and Neuroscience

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Under the continuous impact of the epidemic, online learning methods represented by MOOC have developed rapidly. The course forum area has produced a large amount of text-based unstructured data, which can reflect the potential characteristics of learners’ emotional states and behavioral interactions, and has an important impact on students’ learning outcomes. To this end, this paper constructs an emotional and behavioral analysis model based on online forum texts, obtains forum data from the “Python Language Programming” course on the Chinese University MOOC platform, uses domain dictionary emotion classification method to analyze learning emotions, and based on the method of cognitive behavior coding table and knowledge construction behavior coding table analyzes learners’ cognitive behavior and knowledge construction behavior. It can dynamically analyze learners’ emotions, behavior changes, and evolutionary trends. This research provides opinions and suggestions on the improvement of platform interactive functions for teachers’ online teaching, students’ online learning, and platform management, which can effectively improve the efficiency and effectiveness of online learning.

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Unter dem Zeichen Künstlicher Intelligenz. Berufe, Kompetenzen und Kompetenzvermittlung der Zukunft

Vladova,

Bertheau

2023

Künstliche Intelligenz in Der Bildung

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A parallel neural network structure for sentiment classification of MOOCs discussion forums

Cited by 5 publications

References 11 publications

English Education Tutoring Teaching System Based on MOOC

English Education Tutoring Teaching System Based on MOOC

Modeling and Analysis of Learners’ Emotions and Behaviors Based on Online Forum Texts

Unter dem Zeichen Künstlicher Intelligenz. Berufe, Kompetenzen und Kompetenzvermittlung der Zukunft

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