Abstracts

Using CiteSpace to analyze Chinese journal publications： an optimized research paradigm

Weichen Jia， Wenguang Li and Mingmei Yu

As a tool for knowledge mapping， CiteSpace is often used for the purpose of bibliometrics. Nevertheless， research shows that CiteSpace is only capable of handling several basic types of clusters and data analysis when used to process Chinese journal data. Hence， CiteSpace-based research paradigm needs to be further optimized in order to enable in-depth interpretation of this kind of data. This study first identified a standard CiteSpace-based research paradigm as well as the corresponding research paradigm adopted by publications from Chinese academic journals included in the Chinese Social Sciences Citation Index （CSSCI）. A comparision of the two research paradigms reveals areas for improvement in the Chinese journal publication approach. In light of findings from the comparison， a more advanced method for Chinese literature retrieval strategy and document data processing was then developed by using a typical topic mining model， the Latent Dirichlet Allocation （LDA） model to process the abstract. The optimized research paradigm aims to enable an in-depth analysis of Chinese literature data by improving Chinese literature retrieval strategies and data processing technologies. Finally， it is used to analyze Chinese journal publications on the topic of AI in education and proves to perform better than the traditional research paradigm in data collection， data analysis， and data interpretation.

Keywords： journal publication knowledge mapping; bibliometrics; LDA model; CiteSpace; research paradigm; AI in education; Chinese Social Sciences Citation Index

The development of intelligent education equipment in China： status quo and directions for future R&D

Yafeng Zheng， Chunxiao Wang Yang， Xiaomei Yan， Zhizhen Zhang and Yonghe Zheng

Intelligent education equipment is essential to teaching and learning in the smart age， playing a direct role in the education process. It can facilitate curricular reforms， improve the quality of education， as well as cultivate students core qualities and their practical and innovative skills. It is argued that education equipment in China cannot cater for the digitalization trend. This article defines the concept of intelligent education equipment. It also makes a case for developing intelligent education equipment and proposes new approaches for this purpose. To put it more specifically， the article focuses on the construction of intelligent education equipment， key research directions and suggestions on future development with the aim of updating education equipment to meet emerging needs in China.

Keywords： intelligent education equipment; AI education; standard formulation; intelligent education environment; effect evaluation; human-machine cooperation; discipline-specific equipment; smart classroom

Worldwide wisdom of the crowd in education and development

Sanjaya Mishra

The paper outlines the global challenges faced and particularly highlights the challenges in education， which has the potential to impact the achievement of all the 17 Sustainable Development Goals （SDGs）， if planned and designed well. Using the framework of the wisdom of crowds and crowdsourcing， the paper presents two educational innovations that have the potential to change the educational landscape. Open Educational Resources （OERs） and Massive Open Online Courses （MOOCs） use the power of the Web to provide access to quality education and lower the cost， making education affordable to all. It makes a case for rethinking education and development through the prism of harnessing the power of the masses to offer 21st Century learning beyond the four walls of educational institutions.

Keywords： Open Educational Resources （OERs）; Massive Open Online Courses （MOOCs）; wisdom of crowds; crowdsourcing; education and development

A study of the relationship between university students ‘early-rising and ‘book-borrowing bahaviours and their learning performance

Shuang Du， Yunqian Fei， Mu He and Hang Hu

Advancements in big data analytics enable education researchers to identify learning behaviours and patterns hidden in the educational data. In contrast， there is a dearth of research using behavior log data to examine the relationship between learning behavior and learning performance. This study collected the log data of library book borrowing and smart card consumption of 833 university students and constructed characteristics index systems for learning performance， book-borrowing behavior， and early-rising behavior. Clustering and correlational analysis were administered to investigate the impact of book-borrowing and early-rising on learning performance as well as their relationship. Together with findings from the metacognition questionnaire survey， the correlation between collective learning behavior and overall learning performance and metacognition was established. Findings from the study show that book-borrowing and early-rising are correlated with learning performance， through the mediation of metacognition. Moreover， early-rising reflects their metacognitive experience and planning competence; early-rising is more correlated with learning performance in terms of rising time than rising pattern. As for book-borrowing， it reveals disparities in their metacognitive thinking monitoring and reflection; reading speed is found to have the greatest impact on learning performance， and large amount of reading and in-depth reading are conducive to knowledge and skill acquisition. Suggestions on creating deep learning environments， optimizing knowledge dissemination and repositioning the roles of library are also discussed.

Keywords： university students; early-rising behavior; book-borrowing behavior; learning performance; cluster analysis; correlational analysis; metacognition

The impact of virtual reality technology on learning performance： a meta-analysis of 59 experiments and quasi-experiments

Yuting Cui and Zhiqun Zhao

Virtual reality technology is an umbrella term for virtual reality， augmented reality and mixed reality. Findings from experimental and quasi-experimental studies in this field vary significantly in terms of its impacts on learning performance. The current study sets out to make a meta-analysis of 59 studies published in international English-medium journals which involved a total sample of 4，991 participants. In-depth analysis is made of moderator variables such as level of education， subject， length of （quasi-）experiment， technology used and learning environment. Results from the analysis show that virtual reality technology can improve learning performance to a considerable extent. Its effect on teaching is affected by the above-mentioned variables. Mixed reality is most effective but with a small sample， followed by augmented reality and virtual reality. Implications from the study are also discussed.

Keywords： virtual reality; augmented reality; mixed reality; learning performance; meta-analysis

（英文目次、摘要譯者：肖俊洪）