Under the background of double reduction, the digital transformation of the future higher vocational education is thinking one, the way of digital transformation 1, and the intelligent online learning platform as the starting point

For details, please click on the link: Reflections on the Digital Transformation of Future Higher Occupations I. Path of Digital Transformation II. Implementation Step III. Future Prospects

Editor's Note:

After the double subtraction "diversion", it caused many parents to be anxious, worried that their children's poor grades, went to vocational high technical schools, and the child's future was gone. This anxiety has brought new pressure on how to improve the quality of vocational education, how to transform and upgrade, the author combined with the digital transformation, the essence of vocational education to think, if the higher vocational through the path envisaged in this article transformation, your children to such a higher vocational study are you willing? Still anxious?

Higher vocational education to cultivate the industry urgently needed, applicable, easy to use, reliable, development potential, high comprehensive quality of the talent as the goal, but the current academic situation changes greatly, social development is rapid, how to improve the quality of talent training, enhance the competitiveness of running the school, has become a problem in front of the current higher vocational colleges.

In the future, or even in the near decade, it is necessary for vocational colleges and universities to be run with connotation attributes such as "the support point of career development, the power source of industry development, the aggregation of capital and manpower, and the important fulcrum of vocational culture inheritance", in order to better meet the needs of social development and develop and grow themselves.

For the sake of long-term development needs, the state has released two clear signals through the "Education Informatization 2.0 Plan": first, to meet the needs of learners for personalized learning, so as to strive to help learners achieve personalized and comprehensive development; second, to make good use of artificial intelligence technology, not only to improve the quality of running schools, the level of school running, but also to provide more powerful talents for future national development and international competition.

To achieve this series of goals, we must face the pain points and difficulties of the current development of higher vocational education and return to the essence of education. The author believes that with digital transformation as the starting point, the key means should be identified as the starting point, the problem of insufficient learning motivation should be solved, the quality service guarantee should be provided, a good practical environment should be created, and the talent should be further led to continuously improve the quality. With these elements, the development of higher vocational education will be better and faster into an efficient and high-quality development track, stimulate greater vitality of running schools, and obtain greater efficiency in running schools.

<h1 class="pgc-h-arrow-right" data-track="7" > the path of digital transformation</h1>

At present, the enthusiasm of higher vocational students to learn is not high, which has become a problem that currently plagues many front-line higher vocational teachers, how to crack it, where the reasons are, and there are different opinions. The author has been teaching for many years, and has been concerned about this issue for a long time, and has improved the teaching method, developed learning resources, done ideological counseling in his own teaching process, and has also had continuous and in-depth exchanges with students, and has exchanged and discussed with fellow faculty members. Taken together, there are two main key problems: first, the goal is not clear, the continuous motivation is insufficient; the second is that the learning foundation, learning progress, and learning problems vary widely. And the reasons behind the two are diverse and intertwined, like a mess, constantly cutting, rationalizing and messing. If this problem is not solved well, other school-running innovations are difficult to touch the core of the educated, resulting in various efforts and changes being greatly reduced, or even fruitless. The author believes that the digital transformation of higher vocational education in the future can start from the following five ways:

<h1 class="pgc-h-arrow-right" data-track="9" >1, with the intelligent online learning platform as the starting point</h1>

How do vocational colleges and universities solve the problems of different learning foundations, learning progress, and learning problems? As an inclusive education, higher vocational education does not aim to cultivate a small number of "elites", and how to solve this problem with lower cost and higher return has become the challenge and need of running a school in reality.

To solve this problem with the current practical conditions, it is necessary to carry out the necessary changes and adjustments to the school-running mode, teaching means and methods, so as to meet the needs of learners' learning foundation, learning progress, learning time, learning habits, etc. at a lower cost, and to achieve the learning goals. From the analysis of higher vocational learning conditions, higher vocational students are generally more repulsive to theoretical learning, and it is more difficult to learn, while the theoretical learning foundation is not solid, which indirectly affects the effect of professional ability training and career development space. Therefore, solving the problem of theoretical learning is the key to the key.

At present, the artificial intelligence technology with big data analysis as the core tends to be mature, and after the reform and optimization of teaching mode, teaching resources, teaching process organization and management, it can take into account the solution of this problem of lower cost, high efficiency and stable income, and is consistent with the direction of the reform of the complete credit system. If combined with the refined management of resources such as teaching venues, teachers, and practical training conditions, it can establish a more open, flexible, and autonomous learning environment for learners, and provide good basic conditions for assisting their personalized growth, thus providing realistic support for cultivating learners' enthusiasm for independent learning.

The specific realization idea is to build a learning map through the professional ability training goal as the core, from the perspective of the learner, including the professional ability growth level, and then decompose the professional skill training path accordingly, and then continue to derive the knowledge learning path, so as to build a complete learning map. The whole learning map is similar to a network of learning resources, the map is scattered with a large number of learning nodes, each node (knowledge points, skill points or professional ability points and other different learning resources) according to the teaching team according to each other's internal logic is associated, learners in the graph according to their own evaluation data through each node to dynamically determine the next learning node, and finally through the gradual improvement of professional ability to reach the end of map learning.

All kinds of necessary learning resources will be added to the map, and each resource should design an assessment plan to formulate evaluation indicators for learning status and learning outcomes. In addition, it also includes data collection and analysis of other aspects of learners, through the establishment of effective data analysis models, to integrate and analyze with the data in the platform, to provide learners with learning path selection, learning method suggestions, learning partner recommendations, suitable for teachers to provide reference basis.

Each major corresponds to a learning map, and the teaching team specifies an initial entrance, the learner starts the learning journey through the initial entrance, and each learning node will be given a specific evaluation data collection, and then combined with the data analysis model in the background, jump to the next learning node.

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