1. Background of curriculum reform
With the advent of the information age, big data technology has become one of the hottest technologies in today's society, and it is also one of the core driving forces for industrial model transformation and economic development in the digital era. The growing demand for data across industries means that more professionals with big data technology are needed to address new challenges and opportunities.
The course aims to cultivate big data analysis specialists with intelligent decision-making thinking, data modeling technology and data operation skills for the big data analysis industry, and cultivate scarce technical skills for the digital transformation and upgrading of enterprises. However, as the "main battlefield" of talent training quality, the traditional classroom is facing many problems, which is an important part of the teaching reform of colleges and universities.
Based on the above background, the course team explored and practiced the "classroom revolution" around the course. According to the report of the 19th National Congress of the Communist Party of China, it is necessary to promote the deep integration of the Internet, big data, artificial intelligence and the real economy, support the optimization and upgrading of traditional industries, deeply integrate big data technology with different fields of China's smart people's livelihood, design business scenarios and introduce real data mining tasks, and reconstruct the teaching content based on the deep integration of "post course certificates".
With the help of abundant self-created teaching resources, the teaching team has formed a relatively mature teaching model of "three ladders, seven linkages, and three educations" with reference significance through exploration and practice, and combined with the big data technology in the course content, the self-developed student behavior evaluation and education system are used to achieve accurate teaching evaluation and education.
The teaching mode is shown in Figure 1.
2. Curriculum reform measures
(1) Design comprehensive learning tasks, and deeply integrate and reconstruct the teaching content of the "post course certificate".
The original teaching content of the course includes four projects, and the workflow is only completed once after all the courses are completed, so it is difficult to consolidate the complete job skills step by step.
Based on this, the teaching team combined with the national professional teaching standards, based on the comprehensive learning task-oriented quaternary (4C ID) teaching theory, based on the core vocational competencies of big data positions obtained from the survey of hundreds of enterprises, integrated the vocational skills competition and 1+X certificate evaluation standards, consulted the business ability growth stage of big data analysis specialists, introduced the real data tasks undertaken by data consulting enterprises, designed contextual teaching content, and reconstructed four step-by-step whole-process work modules.
Taking module 3 as an example, according to the workflow of program formulation, data processing, data modeling, and conclusion application in the operation of intelligent big data, focusing on important issues such as intelligent product recommendation, patient intelligent consultation, scientific epidemic assessment, and farmers' smart planting in the field of smart people's livelihood, 4 projects and 8 data tasks were carefully designed, and new technologies, new models and new norms in the digital era were reflected through the integration of posts, classes, competitions, and certificates.
(2) Based on the improvement of teaching effectiveness, enrich "digital and contextual" teaching resources
In order to improve the effectiveness of teaching, we will continue to enrich resources and digital means
1.Self-built micro-lessons, 2D situational animations, and 3D animations create immersive learning scenarios to help students understand the abstract data modeling process.
2.Self-built data algorithm exploration 3D game strengthens group independent exploration and interactive thinking, and fully stimulates students' interest.
3.Independently operate WeChat*** to expand knowledge related to big data applications and improve migration capabilities.
4.The industry's cutting-edge big data modeling system is introduced to help students complete the data mining and modeling process through visual graphical interface operations.
5.Self-built SPOC courses, integrating various resources, and effectively promoting blended teaching through the vocational education cloud platform.
Figure 3 Teaching resources for the course.
(3) In accordance with the data workflow, implement the classroom revolution of "three ladders and seven linkages".
1.According to the principle of scaffolding, three ladders of data tasks are built
Based on teaching experience, it is found that students have problems such as "not being able to learn and not being able to reach" for complex data modeling and other skills. Combined with the smart livelihood scenario, for different tasks, the scaffolding principle is used to design a three-order data task with increasing difficulty in each lesson to help students cross the "nearest development zone". Combined with different learning contents, we establish an upward "handrail" for the task ladder by completing data tasks and interacting with digital games, so as to help students improve their data skills.
2.Based on the 5e teaching model, the seven linkages of teaching links are designed
According to the analysis of the learning situation, it is found that students have problems such as "no interest and no desire to learn" for abstract data mining principles. Based on the 5e teaching model of "attraction-interpretation-transfer-evaluation", combined with the three-order data task, the teaching process is expanded and designed step by step through the teaching process, and the seven-link teaching linkage of "low-level practice, low-level test, intermediate first, thinking before learning, high-level training, perception improvement, and expansion and strengthening" is constructed, and an independent learning path of "first practice to find problems, then theoretical analysis of problems, and then practice to solve problems" is constructed.
3.Implement the classroom revolution of "three ladders and seven linkages".
Taking module 3 as an example, each task implements low-level exercises before class, and introduces the situation through the low-level inspection link in the class, the middle-level first-stage link cooperates with the middle-level data task to find problems, the thinking and then learning link breaks through the key points in the cooperative learning mode, and the high-level training link uses individual training and group actual combat to complete the high-level data task to resolve difficulties, and the perception improvement link is summarized and ideological and political sublimation. After-class enrichment sessions to reinforce the learning content. This is shown in Figure 4.
Fig.4 Module 3 "Three Ladders, Seven Linkages" Classroom Revolution.
(4) Combined with professional teaching content, the implementation of curriculum ideological and political "three education".
Focusing on the ideological and political main line of using data technology to build a smart life, the teaching is carried out.
Before class, students complete low-level data tasks to preview the smart livelihood micro-course;
In the class, students will extend their understanding of data technology and improve their character literacy. Summarize and reflect on the key task points of the data mining workflow, and strengthen the professionalism required by big data analysis specialists; Think about the cases of breaking the algorithm blockade and empowering the country with computing power derived from the third-order data task, and establish the feeling of serving the country with science and technology.
After class, students will complete the expansion tasks and learn self-built ideological and political resources to further strengthen their literacy and feelings.
Fig.5 Implementation of ideological and political education in the curriculum.
(5) Based on the data of learning behavior, the evaluation of "seven indicators and five models" is implemented
Based on the big data algorithm of the course's key learning, the teaching team independently developed the student behavior evaluation and evaluation system, and formulated 7 learning evaluation indicators in detail. In the teaching process, 7 online and offline learning evaluation indicators were recorded.
After class, the recorded data will be input into the student behavior evaluation and evaluation system, and the value-added evaluation and comprehensive evaluation will be realized through the evaluation model, and the future learning behavior mode and possible learning results will be controlled through four big data algorithm models, so as to adjust the teaching strategy in time and accurately feed back the teaching. This is shown in Figure 6.
Fig.6 The implementation process of the "Seven Indicators, Five Models" evaluation of the course.
(6) Examples of specific curriculum implementation
Taking the implementation of the decision tree and random forest in module 3 task 4 "Seeking Doctors and Asking Drugs - Patient Smart Consultation" as an example, relying on the third-order smart medical data task, the seven links of teaching covering before, during and after class are linked, and the ideological and political education is integrated at three levels, and interactive teaching is carried out through resources such as decision tree algorithm 3D game and random forest 3D animation, so that students can effectively master the principles of decision tree and random forest algorithm and consolidate their modeling skills.
The student behavior data is recorded throughout the teaching process and evaluated and evaluated by the system after class. This is shown in Figure 7.
Figure 7 Examples of specific curriculum implementation.
3. The effect of curriculum reform
(1) Raise interests, have ideals, and enhance professionalism and patriotism
The classroom revolution has sparked students' interest in big data operations and significantly improved classroom engagement. With the continuous advancement of teaching, the number of interactions on online learning platforms and the average time per capita have continued to rise.
Through the combined weighted analysis of learning evaluation indicators, it can be seen that students' labor consciousness, team awareness, innovation spirit, and craftsman spirit have been significantly improved, which has enhanced the professionalism of big data analysis specialists, and the patriotic feelings of serving the country with science and technology have been gradually enhanced.
(2) Understand algorithms, be able to apply, and achieve both knowledge goals and ability goals
Taking the second-year students majoring in business data analysis and application as an example, compared with the previous module, the scores of all 33 students in the class in module 3 have been steadily improved, which reflects that the students' knowledge level has been improved from multi-dimensional data analysis to intelligent algorithm analysis.
At the same time, in the big data job skills assessment jointly designed by schools and enterprises, the five core skills required by the position have been significantly improved, effectively achieving the knowledge ability goal.
(3) Pass the competition certificate, be able to conduct scientific research, and improve the thinking and comprehensive ability of entrepreneurship and entrepreneurship
Students extend their knowledge and skills to the after-class, and the growth rate of the number of winners of vocational skills competitions at all levels, the establishment of innovative practice projects and innovation and entrepreneurship competitions exceeds 50%, and the growth rate of the number of students who pass the 1+x certificate assessment is also more than 50%, which is a significant increase.
Teachers and students jointly form interest research groups, and students participate in data processing and modeling of provincial projects, national patents and high-level **. The participation in the competition and research was 100%, which comprehensively improved the thinking and comprehensive ability of entrepreneurship and innovation.
Fig. 8 Effect of curriculum reform.
Fourth, reform and innovation points
(1) Form a new paradigm of content reconstruction that is progressive, process-complete, and cutting-edge
Focusing on the core competencies of the post, benchmarking the work content of employees at different growth stages, the teaching content is innovatively reconstructed into a number of full-process work modules with progressive difficulty, so that the learning rules of students are unified with the development of employees' vocational abilities, and help students integrate scattered knowledge independently.
(2) Form a new idea of teaching design for task advancement, use of guidance, and integration of ideology and politics
Each class promotes the ability improvement through the three-level data tasks of low, medium and high levels, and constructs an independent learning path of "practice-thinking-re-practice" through the linkage of teaching links, so as to stimulate students' spirit of exploration with guidance. At the same time, in the implementation of the third-level tasks, the main line of ideology and politics in the same direction as the course is integrated to achieve the effect of moisturizing things silently.
(3) Form a new means of teaching diagnosis and reform that is guided by indicators, comprehensively evaluated, and accurate
Combined with the big data model of course learning, we have independently developed a student behavior evaluation and evaluation system, and innovatively constructed a standardized learning evaluation index system, which can achieve a comprehensive and objective evaluation of students' learning process and effect through the modeling of index data, and design accurate teaching strategies for future learning effects.
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