The development of artificial intelligence (AI) technology and the demand for general-subject teaching give birth to general-subject AI teacher-led courses. In this study, 79 fourth-grade pupils from two classes in a primary school in Guangzhou City are selected as the samples. The research methods of interview, classroom observation, and questionnaire survey are used to explore the effects of the AI general- subject teacher on pupils’ learning effectiveness based on the framework of anthropomorphic learning process theory. The results show that the AI general-subject teacher can significantly enhance pupils’ learning motivation (including intrinsic motivation and extrinsic motivation), increase pupils’ learning engagement (including behavioral engagement, cognitive engagement, and emotional engagement), and improve pupils’ learning outcomes (including knowledge and skills, process and method, emotional attitude and values). The findings confirm the important role of the AI general-subject teacher as the main instructor to promote pupils’ efficient learning and provide a significant reference for solving the shortage problem of excellent teachers and reducing the burden on teachers.
In recent years, China has been issuing artificial intelligence (AI) education policies to promote the deep integration between AI and education. Setting AI courses at the basic education phase can cultivate students’ AI literacy and enhance the country’s science and technology competitiveness in the future. However, due to shortages of AI teachers and inadequate conditions for practice, the current AI courses in primary and secondary schools are not enough in effectiveness. In light of current problems, this study, based on the foundation of university-enterprise cooperation, integrates the “competition and education” mechanism into informal AI course design and practice. Using a design-based research paradigm, the study proposes the design framework from four dimensions: goals, themes and content, methods and steps, and evaluation, and then further refines the framework through two rounds of iterations, to provide a reference for the development and practice of AI courses.
Under the background of “emerging engineering education,” the engineering education with national defense characteristics, has put forward higher requirements for the engineering practice training of college students. Based on this, focusing on three characteristics of virtual reality (VR) technology, this paper puts forward the construction ideas of VR technology applied in engineering practice training courses. Then, by taking Northwestern Polytechnical University’s “VR Assembly Composite Practice Training Course” for example, this paper designs the teaching process of the practice training course and analyzes the teaching effect through questionnaires. It finds that VR technology can avoid teaching risks, improve teaching quality, and have a high promotion value in the existing engineering practice training courses. Finally, three suggestions on the VR technology applied in engineering practice teaching are put forward.
Assignments are an important tool to evaluate learners’ learning effectiveness in online courses. Clarifying assignment design strategies is of great significance for promoting the quality construction of online education courses. This paper uses Bloom’s taxonomy framework revised by Anderson and Krathwohl (2001) as a reference to label the knowledge types and cognitive dimensions in the assignment context of eight courses. Combined with a literature review, a discipline–objective–schedule (DOS) threedimensional analysis framework based on the achievement of curriculum objectives, the design of chapter schedule, and the heterogeneity of disciplines is constructed to conduct an in-depth analysis of online course assignment design strategies. The research findings show that the online course assignment design strategy has an obvious curriculum objective orientation, follows the gradual learning rule, and presents typical disciplinary differences. The study finds that the current assignment design of online courses has three issues: first, a mismatch between assignment design and curriculum objectives; second, a lack of diversity in assignment formats; and third, insufficient comprehensiveness of some subject assignments. Based on the above discussions, corresponding suggestions are provided.
With the application of the internet, big data, and artificial intelligence (AI) in education, a new form of textbook construction has been developed, promoting digital textbook development. However, problems during digital textbook construction still exist. This study analyzes the necessity of intelligent textbook development and explains the educational characteristics of intelligent textbooks, such as intelligent adaptation learning, intelligent guidance, accompanying evaluation, and in-depth learning interaction from the perspective of instruction theory. Moreover, combining the technical advantages of AI, including knowledge mapping, learning analysis, online tracking, learner digital profiles, and in-depth interaction, and taking existing achievements for reference, it describes the methods and strategies of intelligent textbooks to achieve corresponding educational functions and also makes interpretation with specific cases. Given the educational and engineering characteristics of intelligent textbooks, this study analyzes the strategies for promoting the construction of intelligent textbooks from adhering to the instruction theory, paying attention to the iteration of practice, and adopting technical methods to supervise and regulate.