How Yuzhong brought teacher research and training onto one platform

Digital transformation of teacher research and professional development in Chongqing’s Yuzhong District  

Gong Fangde, Yao Yutao, Li Li, Wu Qian, Chen Qilan  

Chongqing Yuzhong District Education Committee, Chongqing Yuzhong District Teachers’ Training Institute  

Abstract:Yuzhong District in Chongqing City takes the construction of a “smart education” platform based on the “1+N+X” ecosystem of Yuzhong’s smart education system, as well as regional educational big data, as a key approach. It carries out digital process reengineering for all aspects, scenarios, and elements of research and training activities, including teaching and research, scientific research, training, supervision, lesson observation and evaluation, and research and monitoring. The digital transformation of regional research and training is promoted systematically in various aspects such as platform development, system establishment, competency improvement, research projects, case demonstrations, and supervision and evaluation.    

Keywords:Intelligent research and training; digital transformation; systematic construction    

In order to implement the national strategy for digital education development, carry out the urban and district-level plans for digital education construction, and promote high-quality development in regional education, Yuzhong District in Chongqing has developed a smart education ecosystem based on the “1+N+X” framework – namely, one data platform, N basic applications, and X extended applications. On this basis, regional research and training activities have utilized the smart education ecosystem and regional education big data to explore ways of transformation from mixed research and training, digital research and training to smart research and training. By summarizing and learning from past experiences such as focusing solely on platform construction without addressing management systems, emphasizing functional applications rather than actual needs, it has become clear that the digital transformation of research and training involves not only the establishment of digital platforms, but also a reconfiguration of research and training methods, organization, management, and resources. To further promote the development of “smart research and training,” various initiatives have been carried out, including the formation of specialized teams, planning of programs, research on needs, development of platforms, establishment of mechanisms, evaluation and feedback, operation and management, data security and application standards, as well as research on topics and cases. This has led to the creation of a closed ecosystem that supports “smart research and training,” including a smart environment, smart competencies, smart integration, and smart talent, thereby enabling the digital transformation and reconfiguration of research and training.  

1. Top-level planning and system establishment  

(1) Top-level design and the formation of specialized teams  

The construction of the “Smart Research and Training” project is organized by the Education Commission of Yuzhong District, and implemented by the Yuzhong District Teachers’ Training Institute. After multiple investigations and evaluations, and in light of relevant policies, systems, and concepts, it was decided to achieve breakthroughs in multiple dimensions such as digital environments, digital literacy, digital integration, and digital governance. A systematic approach was adopted, involving various aspects such as platform development, institutional establishment, improvement of skills, research on topics, demonstration through cases, and supervision and evaluation. The “Implementation Plan for the Construction of the ‘Smart Research and Training’ Project” and the “Plan for Establishing Working Groups for the Construction of the ‘Smart Research and Training’ Project” were formulated. The responsibilities of the working groups involved in the implementation of the project, including the leading group and expert group for the “Smart Research and Training” project, the overall design and planning for project construction, the research and design development of the “Smart Research and Training” platform, the management system for digital research and training activities, training programs to improve digital research and training capabilities, research and management of topics related to digital research and training, data security maintenance and emergency management for the “Smart Research and Training” platform, and supervision and evaluation of project construction, were also defined.  

(II) Reengineering of the research and training process and restructuring of systems  

The digital transformation of education involves changes at three levels: technology, operations, and human aspects. The digital transformation at the operational level involves the upgrading, restructuring, and intelligent coordination of business processes. In order to adapt to the digitalization of research and training activities, a “Digital Management System for Research and Training Work” has been established. This system enables the digital reengineering of all aspects of research and training activities, including teaching and research activities, educational research, training practices, visits to schools, lesson evaluations, and research monitoring (as shown in Figure 1). It also redefines and standardizes the content of various activities, as well as the criteria for evaluation.  

II. Digital Platforms and Environment Construction  

(1) Design and development of digital platforms, as well as their functions  

1. Concepts and objectives for the design and development of a smart research and training platform

Smart research and training is a digital platform that supports the transformation of research and training in the region. It is based on the “1+N+X” smart education ecosystem in Yuzhong District, Chongqing, as well as regional education big data. By reengineering the entire process, scenarios, and elements of research and training activities, this platform enables precise and efficient hybrid research and training methods using regional education big data. This leads to the digitalization of research and training. The resources and data accumulated through long-term digital research and training provide a basis for improving the management of research and training activities. Through big data analysis models, an intelligent system is created to enhance the quality of research and training. Ultimately, this results in smart research and training.  

2. System architecture and main functions

The facility-level platform of the intelligent research and training platform deploys regional cloud servers. The support-level provides services and data interfaces for implementing a unified regional authentication system and for connecting with the regional big data platform. The data-level is a data pool for the platform’s applications. The application-level includes various applications for hybrid research and training, as well as digital research and training, which support the main business functions. The user-level includes all user entities involved in the platform (as shown in Figure 2).  

3. Main functions and tools

The functions of the intelligent research and training platform mainly include research and teaching activities, scientific research, training, supervision, and other related activities. It also provides information and data analysis to support these various activities (as shown in Figure 3). The research and training workshops are the most basic organizational structures for carrying out such activities. Users with appropriate permissions can request to establish workshops as needed, such as workshops for subject-related research and teaching, training workshops, and scientific research workshops. Workshops can form user teams, issue announcements and bulletins, gather resources, and collect data related to the workshops (as shown in Figure 4). The implementation of digital research and training activities involves designing activity processes, carrying out activities, and conducting assessments within the workshops. The design of activities can be done using various tools such as group chats, resource spaces, questionnaires, evaluations, video conferences, video documents, live broadcasts, offline meetings, course materials, assignments, collaborative documents, and online classrooms, depending on the needs (as shown in Figure 5). Through the design and implementation of digital workshops, a digital twin space for research and training activities can be created, enabling the ability to track, analyze, and diagnose research and training activities, thereby improving the management capabilities of these activities.  

4. Application cases

Research and training activities: Application for activities (including information such as timing, location, participants, equipment used, and activity plans); Activity design (designing the activity process using tools from subject-based workshop activities, including application of research and training activities before, during, and after the activity – such as attendance checks, questionnaires, interactive discussions during the activity, topic discussions, and assignments and evaluations after the activity). The activities are carried out as scheduled after being approved. Teachers participating in the activities complete attendance checks, fill out questionnaires, engage in both online and offline interactions, and finally submit evaluations and assignments. After the entire activity is completed, a report will be generated, including digital reports on timing, location, number of participants, and interaction levels, as well as information resources related to the activity process.  

Teaching inspections: Traditional teaching inspections are carried out mainly in-person. There are several problems associated with these inspections, such as insufficient information about the schools being inspected, difficulty in recording inspection-related data, difficulty in sharing inspection results, and challenges in managing all aspects of the inspection process. After digital transformation of teaching inspections through the intelligent research and training platform, these traditional problems have been effectively resolved. The research and training institutions issue “one theme per school” inspection plans for each semester; schools in the region report the issues that need to be addressed during the inspections (as shown in Figure 8). Through the school dashboard provided by the regional education big data platform, the research and training institutions can promptly obtain up-to-date information about the schools being inspected, thereby improving the relevance and accuracy of the inspections (as shown in Figure 9). During the inspections, inspection tools such as those used for listening to and evaluating classes are used to record information related to the inspections. Based on the feedback from these interactions, inspection issues are identified. Various disciplines submit structured inspection reports through the platform, which are then automatically compiled into diagnostic reports for the schools being inspected. These reports are then shared with all schools in the region through the platform, allowing them to identify common problems.  

After the digital transformation of teaching inspections, not only are the shortcomings of traditional inspections addressed, but the governance level of teaching inspection work is also improved. The recorded inspection processes and reports provide a basis for tracking the effectiveness of subsequent inspections. At the same time, this solution addresses the difficulty of having some trainers unable to participate in all teaching inspections uniformly (as shown in Figure 11).  

In addition, training related to research and training, as well as scientific research activities, are integrated through the intelligent research and training platform. Problems are identified during the teaching and research process; these problems then lead to the development of research projects. The research results are then transformed into training content. The data and resources that are generated during the application process are analyzed using data modeling techniques. These resources are utilized both within and outside the application processes, thereby ensuring the accurate implementation of research and training activities. This helps to create a regional intelligent research and training ecosystem.  

(2) Construction of digital environments  

To better realize the concepts and functions of the intelligent research and training platform, it is necessary to create a digital environment that matches its requirements. As part of the systematic implementation of intelligent research and training, the region has provided research and training institutions with digital devices for exploring digital research and training models. These devices enable the implementation of intelligent evaluation and feedback systems in digital classrooms and AI-based classrooms, and they are integrated deeply with the intelligent research and training platform (as shown in Figure 12).  

(3) Improvement of digital literacy  

Digital research and training is not simply a matter of transferring traditional research and training methods to the online environment. It represents a comprehensive transformation that involves concepts, models, tools, methods, and evaluation systems. Researchers and trainers play a crucial role as designers, leaders, supporters, and enablers of this transformation. Especially in light of the current impact of AI technology on traditional education, researchers and trainers should take a higher-level perspective to understand and embrace current educational changes, and actively enhance their ability to cope with the changes in the digital age.  

As a part of the digital talent training process in the implementation of the regional intelligent education system, in accordance with the requirements of relevant documents, “Goals for Improving the Competence of Teaching and Research Staff in the Digital Intelligence Era” have been established. These goals outline five main areas for improvement: enhancing the understanding of educational reforms in the digital intelligence era; improving the basic skills of teaching and research staff in data management; enhancing the ability to diagnose and evaluate digital intelligence-based teaching methods; improving the ability to integrate data platforms and intelligent tools; and enhancing the ability to conduct research and teaching activities based on digital intelligence. Through regional innovative projects in intelligent education, training, and study opportunities have been provided in advanced areas of educational digitization in Beijing, Shanghai, and Jiangsu. Many well-known experts from East China Normal University and South China Normal University have been invited to give lectures and provide training for teaching and research staff, resulting in significant achievements.  

III. Promote the integrated application and research of digital research and training  

Rogers pointed out that when groups or organizations serve as entities that receive innovation, their cumulative diffusion curve typically follows a “S” shape. Innovators and early adopters promote the spread of innovative ideas within the organization through interpersonal networks. The integration of digital training and research is an innovative approach; it inevitably challenges the comfort zones of those involved. To effectively promote the integration of digital training and research in the region, we rely on the influence and leadership of renowned educators in the region. Through workshops led by these experts, we facilitate the integration of blended training and research. We also organize online events for evidence-based evaluation of digital-driven classroom teaching. We collect examples of successful designs and integrations of digital training and research. The regional education research planning office provides special funding for such projects, and we encourage applications for projects at both municipal and national levels, thereby promoting the exploration and implementation of the integration of digital training and research.  

IV. Achievements and Issues  

Through the systematic implementation in recent years, regional intelligent research and training have achieved some initial results at a general level. More achievements will become apparent as these initiatives are further developed. However, in the process of digital transformation of regional research and training, there are several challenges: the lack of sufficient educational big data for supporting intelligent research and training; high costs associated with the development and maintenance of digital platforms and environments; insufficient digital literacy among some researchers and teachers; and a lack of high-quality integrated applications and research results. In the subsequent development of the digital transformation of regional research and training, it is necessary to better understand and grasp the strategic goals of educational digitalization, adopt a systematic approach, optimize and improve the overall planning based on practical experience, focus on key aspects, overcome development obstacles, and continue to promote the digital transformation of regional research and training.