Assessment of Digital Graduation Competences for Programs Degrees in Computing and Information Technology Under the Society 5.0 Paradigm

Rodríguez, Francisco Javier Álvarez; Vera, Raúl A. Aguilar

doi:10.1109/rita.2022.3167006

Cited by 5 publications

(1 citation statement)

References 9 publications

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“…At present, the wave of informatization characterized by digitalization, networking and intelligence is prevailing the world, promoting mankind to officially enter the digital information society [1][2][3][4][5][6][7]. The rapid development of information technology has had a major impact on all industries in society, not only changing human production and lifestyle [8][9][10][11][12], but also bringing about major changes in thinking and learning methods, and the new era background and new social background put forward higher goals for the cultivation of innovative talents [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Higher Vocational Students’ Innovation and Entrepreneurship Ability Demand Prediction

Gong¹,

Miao²,

Zhao³

et al. 2023

Int. J. Emerg. Technol. Learn.

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The new era background and new social background put forward higher goals for the cultivation of innovative talents. The accurate prediction of the demand for innovation and entrepreneurship vocational ability of higher vocational students provides an important reference for higher vocational educators to formulate refined innovation and entrepreneurship education management strategies, more balanced allocation of limited innovation and entrepreneurship education resources, and make more scientific innovation and entrepreneurship education decisions. This paper studies the prediction of innovation and entrepreneurship vocational ability demand of higher vocational students under the background of digital informatization and theoretically discusses the demand for innovation and entrepreneurship vocational ability of higher vocational students and its connotation. It constructs the demand prediction framework of innovation and entrepreneurship vocational ability of higher vocational students for data identified on the Knowledge Retrieval Engine or High-quality Knowledge Q&A and Sharing Community, and develops the collection and use methods of students' innovation and entrepreneurship resource retrieval data. It makes the feature selection of the keyword sequence and the corresponding time lag sequence selected by the higher vocational students' innovation and entrepreneurship resource retrieval and builds the prediction model of the vocational ability demand for innovation and entrepreneurship of higher vocational students. Experimental results verify the effectiveness of the proposed model.

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