The Application of Multimedia and Deep Learning in the Integration of Professional and Innovative Education in Colleges

The Application of Multimedia and Deep Learning in the Integration of Professional and Innovative Education in Colleges

Shilin Xu
DOI: 10.4018/IJITSA.320489
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Abstract

In this paper, the authors study the assessment of professional practice courses in the integrated education of specialization and innovation, and use the multimedia and deep learning technology to complete the action recognition of students in practice courses. Firstly, the skeletal features are extracted from multimedia video data by Openpose algorithm, which is used for subsequent classification while ensuring privacy; then the LSTM method is used to recognize typical motions in student practice, and the average recognition result exceeds 89%; finally, practical application tests are conducted for laboratory and office scenes, and the results illustrate that the proposed framework performs well in the tests with recognition rate exceeding 80%. The algorithm framework provides a new idea for the curriculum setting and evaluation method of professional practice education, and gives data guarantee for their integration and innovation education.
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Introduction

The role of professional education is becoming increasingly prominent within our rapidly developing societies. Due to an increasing demand for innovative talent, there is a need to promote high-quality professional development and enhancements in higher education. In this context, the integration of professional education and innovative education has become a first choice for many schools (Jarvis & Wilson, 2004). Vocational curriculum should be closely connected to professional development. This education should be distinct and flexible according to industrial needs, occupational standards, and production processes (Orishev Burkhonov, 2021). It is also necessary to develop trends in science and technology to meet market demand. In doing so, we can better integrate and promote advanced innovative education and professional education (Morales & Suárez-Rocha, 2022). Figure 1 shows the main principles of the integration of professional and creative education (Ramírez-Montoya et al., 2021).

Figure 1.

Principle of the integration of professional and creative education

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According to Figure 1, the current integration of professional and creative education considers professional education as a research theme. It completes the integration of specialization and innovation in the new era by complementing it with innovation education, improving the quality of human resources (Wu, 2022). Therefore, a university’s teaching and curriculum should stress the value of professional education with a focus on practical values.

In the process of continuous iteration of science and technology, teaching methods have undergone great change. The application of streaming media technology continues its development. Today, its interactive, real-time network multimedia teaching system that has become a powerful channel for teaching. The network multimedia system adopts a variety of advanced information technologies. For example, video technology provides a two-way interactive network multimedia teaching platform. The advantages of multimedia lectures can be fully utilized in course development and combined with the latest artificial intelligence to improve efficient talent training (Lu & Wu, 2022).

Innovation education continues to take shape after years of development. Thus, the integration of professional education into innovation education through intelligent means is a priority. Professional education is focused on putting knowledge from textbooks into practice and connecting it with one’s life. The current educational process can be complicated by the type of practice, making it difficult to complete an assessment or its accurate integration with innovative education (Dovha et al., 2021). In today’s world of highly developed multimedia teaching and artificial intelligence (AI), it is possible to use online multimedia data to gain an intelligent assessment of students’ professional educational practices with the help of AI.

Deep learning techniques and powerful neural networks (NN) form a black box effect to complete the analysis of multimedia multimodal data. It can realize the task of identification, assessment, and analysis of students in such courses (Onan, 2021). The current multimedia-based education on innovative AI technologies within universities study how the use of wearable devices, video devices, and related assistive devices enhance professional education. In physical education, online course evaluation is based on AI multimedia technology and human motion capture technology. Psychological education efficiency is improved through the acquisition of multi-source physiological signals and the recognition of facial micro-expressions. In course evaluation, the intelligent analysis of final grades is realized through a high-precision NN approach that integrates usual performance and coursework (Wollowski et al., 2016).

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