Teachers'Data Intelligence Competence for Human-Machine Collaboration:Assessment Framework,Current Situation and Optimization Paths
Whether artificial intelligence can play a transformative role in the field of education depends on whether effective collaboration between artificial intelligence and educators and learners can be achieved.For teachers,effective human-machine collaboration not only requires them to possess intelligence competence and data competence,but also requires them to organically integrate the two to form"data intelligence competence".Teachers'data intelligence competence for human-machine collaboration consists of three dimensions:basic data intelligence knowledge and skills,high-order data intelligence thinking skills,data intelligence beliefs and ethics.A survey of 1017 primary and secondary school teachers in Shanghai found that teachers'current data intelligence competence for human-machine collaboration has not reached a relatively ideal level.The levels of teachers'data intelligence competence for human-machine collaboration are significantly affected by the types of schools,and some of its dimensions are significantly affected by teaching ages,professional titles and teaching subjects.Based on this,this study puts forward the following optimization paths:focusing on consolidating the knowledge base and attaching importance to thinking cultivation to promoting the sustainable development of teachers'data intelligence competence;focusing on improving the data intelligence competence of teachers with senior professional titles and liberal arts teachers to achieve the overall development of teachers'data intelligence competence;focusing on integrating the contents of data intelligence competence into teacher education curriculum to promote the integrated development of pre-service and in-service teacher education in the era of human-machine collaboration.
NETL
NSTL
万方数据
