Yan Li

Yan Li


Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2021 in Complexity
Verified
Journal Article
Open access
PDF file
Xuesong ZhaiXuesong Zhai
Xuesong Zhai
XCXiaoyan Chu
Xiaoyan Chu
CCChing Sing Chai
Ching Sing Chai
Morris JONGMorris JONG
Morris JONG
Andreja Istenic StarcicAndreja Istenic Starcic
Andreja Istenic Starcic
YLYan Li
Yan Li
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.

22 February 2024 in International Journal of Educational Technology in Higher Education
Verified
Journal Article
Open access
PDF file
DSDan Sun
Dan Sun
ABAzzeddine Boudouaia
Azzeddine Boudouaia
CZChengcong Zhu
Chengcong Zhu
YLYan Li
Yan Li
ChatGPT, an AI-based chatbot with automatic code generation abilities, has shown its promise in improving the quality of programming education by providing learners with opportunities to better understand the principles of programming. However, limited empirical studies have explored the impact of ChatGPT on learners’ programming processes. This study employed a quasi-experimental design to explore the possible impact of ChatGPT-facilitated programming mode on college students’ programming behaviors, performances, and perceptions. 82 college students were randomly divided into two classes. One class employed ChatGPT-facilitated programming (CFP) practice and the other class utilized self-directed programming (SDP) mode. Mixed methods were utilized to collect multidimensional data. Data analysis uncovered some intriguing results. Firstly, students in the CFP mode had more frequent behaviors of debugging and receiving error messages, as well as pasting console messages on the website and reading feedback. At the same time, students in the CFP mode had more frequent behaviors of copying and pasting codes from ChatGPT and debugging, as well as pasting codes to ChatGPT and reading feedback from ChatGPT. Secondly, CFP practice would improve college students’ programming performance, while the results indicated that there was no statistically significant difference between the students in CFP mode and the SDP mode. Thirdly, student interviews revealed three highly concerned themes from students' user experience about ChatGPT: the services offered by ChatGPT, the stages of ChatGPT usage, and experience with ChatGPT. Finally, college students’ perceptions toward ChatGPT significantly changed after CFP practice, including its perceived usefulness, perceived ease of use, and intention to use. Based on these findings, the study proposes implications for future instructional design and the development of AI-powered tools like ChatGPT.

5 December 2023 in Thinking Skills and Creativity
Verified
Journal Article
Closed access
LWLi Wang
Li Wang
XCXinya Chen
Xinya Chen
CWChung Wang
Chung Wang
LXLingna Xu
Lingna Xu
Rustam ShadievRustam Shadiev
Rustam Shadiev
YLYan Li
Yan Li

UGUsman Ghani
Usman Ghani
TTTimothy Teo
Timothy Teo
YLYan Li
Yan Li
MUMuhammad Usman
Muhammad Usman
ZIZia Ul Islam
Zia Ul Islam
Xuesong ZhaiXuesong Zhai
Xuesong Zhai
The extant literature has focused on individuals’ knowledge-sharing behavior and its driving factors, which stimulate the knowledge transmission and exchange in organizations. However, little research has focused on factors that inhibit knowledge sharing and encourage individuals to hide their knowledge. Therefore, based on social exchange and displaced aggression theories, the study proposed and checked a model that examined the effect of abusive supervision on knowledge hiding (KH) via a psychological contract breach (PCB). The Psychological ownership was regarded as a boundary condition on abusive supervision and KH relationship. Using a time-lagged method, we recruited 344 full-time employees enrolled in an executive development program in a large university in China. The findings show that PCB mediates the association between abusive supervision and KH. Similarly, psychological ownership moderates the association between abusive supervision and KH. Employees with high psychological ownership minimized the effect of abusive supervision on KH. Based on study findings, contributions to theory and practice, limitations, and future directions are discussed.

23 September 2021 in International Journal of STEM Education
Verified
Journal Article
Open access
PDF file
DSDan Sun
Dan Sun
FOFan Ouyang
Fan Ouyang
YLYan Li
Yan Li
CZCaifeng Zhu
Caifeng Zhu
Background: Unplugged programming is proved to be an effective means to foster the learner-centered programming learning. In addition to the final tests, learners’ programming knowledge, skills, and capacities are primarily demonstrated throughout the programming process, particularly in the situation when they encounter challenges and problems. However, few studies examine how learners engage in the programming processes and to what extent unplugged programming fosters learning. This research used a quasi-experimental design to investigate two instructional modes in China’s secondary education, namely, the instructor-directed lecturing and the learner-centered unplugged programming. Based on an analytical framework, this research used mixed methods to compare learners’ knowledge, behaviors, and attitudes under these two instructional modes.Results: The research results revealed discrepancies between two instructional modes. First, learners in the unplugged programming class achieved significantly higher scores on the programming knowledge assessment, compared to learners in the traditional lecturing class. Second, compared to the traditional lecturing class, learners in the unplugged programming class had higher test scores of the computational thinking skills, particularly on the cooperativity dimension. Next, discrepancies of in-class behaviors showed that learners in the unplugged programming class had frequent behaviors of listening to the instructor’s instructions and discussing with peers, while learners in the instructor-directed class had frequent behaviors of listening to instructor, taking notes, and irrelevant activities. Learners’ self-reported attitudes in the unplugged programming indicated a higher level of confidence than learners in the traditional lecturing class. Overall, this research revealed that the learner-centered unplugged programming had potential to improve learners’ programming knowledge, behaviors, and attitudes compared to the traditional instructor-directed lecturing of programming.Conclusions: As a feasible and easy-to-use instructional activity in computer science education, unplugged programming is encouraged to be integrated in formal education to increase learners’ programming interests, motivations, and qualities. This quasi-experimental research compared learners’ programming knowledge, behaviors, and attitudes under two instructional modes. The results revealed critical discrepancies between two instructional modes on learners’ knowledge gains, in-class behaviors, and changes of attitudes towards programming. Pedagogical and analytical implications were provided for future instructional design and learning analytics of computer programming education.

15 August 2015 in Educational Technology Research and Development
Verified
Journal Article
Open access
PDF file
EHErmei Hu
Ermei Hu
YLYan Li
Yan Li
JLJessica Li
Jessica Li
WHWen-Hao Huang
Wen-Hao Huang
Open educational resources (OER) as an innovation to share educational resources has been influential in past decade and expected to bring changes to higher education worldwide. There is, however, very limited literature on OER usage, especially from the perspective of college students in developing countries, who are often projected as the recipients and beneficiaries of OER. This study was designed to examine Chinese college students’ OER usage and perceived barriers impacting the diffusion of OER. Data was collected during the 2012–2013 academic year at Zhejiang University. A two-part survey instrument was administered to a sample of students (n = 1239). The results show that a significant number of university students have experienced with OER, but there are challenges involved with student, content, interface, and environment related factors that impacted rapid diffusion of OER. Gender was not associated with students’ perceptions about barriers to OER usage, but year in study was. The study highlighted the role of university and faculty members in diffusing the concept and practice of OER and recommended OER-related initiatives for faculty members and college students to foster the adoption of OER.