A Framework of an Intelligent Education System for Higher Education Based on Deep Learning

Abstract

Intelligent learning platforms and education information application platforms are gaining ground, owing to the wide application of modern technologies such as the Internet of Things, big data analysis, artificial intelligence, and cloud computing. However, the current platforms cannot solve specific teaching problems, and the relevant research mostly focuses on primary and secondary education. Therefore, this paper constructs and analyzes a framework of intelligent education system for higher education based on the deep learning. Firstly, the functional block diagram of the system was built up. Next, a face detection algorithm was proposed based on the multi-task convolutional neural network, a face recognition algorithm was developed based on the improved deep convolutional neural network, and the knowledge learning status of students was tracked based on the memory augmented neural network. Finally, the proposed framework was proved effective and swift through experiments. The research results expand the application scope of the deep learning in education.

Analysis of Professional Psychological Adaptability of Students Majoring in Hotel Management and Digital Operation for Higher Vocational Education under Deep Learning

“…The use of this technique in ecological evaluation based smart education level analysis and image detection is discussed. The study in [11] focused on development and analysis of a framework of intelligent education system for higher education using deep learning. The study used a face detection algorithm based on multitask convolutional neural network to track the knowledge learning status of the students on the basis of memory augmented neural network.…”

Contemporary Value Assessment of Marxist Ideology under the Context of Deep Learning

“…The media industry, communication ecology, and public opinion environment are changing as a result of the iterative development of visual media and the rapid emergence of visual communication, and Internet users' “visual survival” is quietly affecting their cognitive habits and cognitive choices and, even to a degree, their intrinsic value judgment of information [ 8 – 10 ]. The Marxist materialistic dialectic emphasizes that things always have two sides, and it is necessary to grasp them comprehensively from both positive and negative aspects.…”

“…The explosion and fission of this kind of information are destined to produce ideological erosion among netizens, resulting in a steady reduction in the value of most netizens and even a misguided ideological shift. In such circumstances, Internet ideology, as a conceptual superstructure built on an economic foundation, is today facing the hazards of metaphorization [ 10 ], fragmentation, and panentertainment, all of which are affecting and contesting mainstream ideology's dominance. Figure 1 shows the meaning of Marxist philosophy.…”

[Retracted] Impact Assessment of Big Data on Higher Education Management Based on Time‐Varying Clustering Sampling Algorithm

“…Higher education, as an important part of the education industry, is increasingly affected by information technology [ 10 , 11 ]. How to use big data technology and methods to manage and innovate higher education, change the traditional educational disadvantages, and guide the quality and level of education to further improve is studied in [ 12 , 13 ].…”