This study provided a content analysis of studies aiming to disclose how artificial intelligence (AI) has been applied to the education sector and explore the potential research trends and challenges of AI in education. A total of 100 papers including 63 empirical papers (74 studies) and 37 analytic papers were selected from the education and educational research category of Social Sciences Citation Index database from 2010 to 2020. The content analysis showed that the research questions could be classified into development layer (classification, matching, recommendation, and deep learning), application layer (feedback, reasoning, and adaptive learning), and integration layer (affection computing, role-playing, immersive learning, and gamification). Moreover, four research trends, including Internet of Things, swarm intelligence, deep learning, and neuroscience, as well as an assessment of AI in education, were suggested for further investigation. However, we also proposed the challenges in education may be caused by AI with regard to inappropriate use of AI techniques, changing roles of teachers and students, as well as social and ethical issues. The results provide insights into an overview of the AI used for education domain, which helps to strengthen the theoretical foundation of AI in education and provides a promising channel for educators and AI engineers to carry out further collaborative research.

Good balance between product and service is the key in the innovative design of product service systems (PSS). In this study, the evolution route of the PSS based on Teoriya Resheniya Izobretatelskikh Zadatch ideal final result was provided. The function model of the PSS was constructed according to the service blueprint and function system diagrams. On this basis, an innovation design method of the PSS based on function incentive was established. The function incentive strategies included function synergy, function supplement, and function substitution. Finally, the PSS design process of agricultural machinery based on computer-aided innovation platform was analyzed to verify this method.

Constructing an all-directional, multilevel, and composite interconnection network, accelerating the free flow of producer services elements across regions, and further improving the efficiency of resource integration demand to conduct a comprehensive and systematic analysis of producer services trade. Thus, using bilateral trade data, this paper builds producer services trade network composed of 61 major countries and innovatively combines the methods of social network and economic geography to explore its spatiotemporal evolution and system properties. The results show that, firstly, the producer services trade network has spatial heterogeneity, which is characterized by high-value agglomerations in Western Europe and East Asia, and low-value agglomerations in Southern Europe and Southeast Asia. Secondly, most countries tend to choose trading partners with close geographical locations or common cultures to establish a cohesive subgroup. Thirdly, the producer services trade network has a significant core-periphery structure, the “spaghetti bowl” effect, which leads to a downward trend in the number of core and semi-peripheral countries. Finally, the trade agreement relations, language relations, and differences in economy, geography, institution, and technology all have a significant impact on the evolution of producer services trade network, but this change has little relationship with the population size divergences of different countries.