Luzhen Tang

472 citations
4 papers · 187 · 1 hit paper · h-index 4

Impact in

Papers in

Luzhen Tang

4 papers receiving 183 citations

Luzhen Tang's Hit Papers

Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance 2024 · 162 citations
1620+1Years since publication50100150

Peers

Luzhen Tang
Comparison fields: 5 of 31
  • Health Informatics 25
  • Computer Science Applications 52
  • Developmental and Educational Psychology 33
  • Artificial Intelligence 50
  • Safety Research 9
Replace Matthew Nyaaba with:
Matthew Nyaaba United States
Ling Wei China
Ana Fuentes Martínez Sweden
Ulrika Gustafsson Sweden
Bronwen Patricia Dyson Australia
Jialu Zhao United States
Jianmin Dai United States
Kordula De Kuthy Germany
Ahmad Al Yakin Indonesia
Jennifer L. Weston United States
Luzhen Tang relative to Matthew Nyaaba United States Matthew Nyaaba's profile →
Citations per field
00.5×1.6×
Matthew Nyaaba · 1×
Citations per year

Countries citing papers authored by Luzhen Tang

Since Specialization
Citations

This map shows the geographic impact of Luzhen Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Luzhen Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luzhen Tang more than expected).

Fields of papers citing papers by Luzhen Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luzhen Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Luzhen Tang. The network helps show where Luzhen Tang may publish in the future.

Co-authors

The 8 scholars most cited alongside Luzhen Tang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Luzhen Tang Line = papers co-authored together Luzhen Tang links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown
#Work
1
Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance
Hit paper breakdown →
2024162
2 202412
3 20258
4 20255

About Luzhen Tang

Luzhen Tang is a scholar working on Artificial Intelligence, Computer Science Applications, Health Informatics, Education and Infectious Diseases, having authored 4 papers that have together received 187 indexed citations. Recurring topics across this work include Online Learning and Analytics (3 papers), Artificial Intelligence in Healthcare and Education (2 papers), Intelligent Tutoring Systems and Adaptive Learning (2 papers), AI in Service Interactions (1 paper), Higher Education Learning Practices (1 paper), Reflective Practices in Education (1 paper), Student Assessment and Feedback (1 paper) and Explainable Artificial Intelligence (XAI) (1 paper). The work is most often cited by research in Health Informatics (25 citations), Computer Science Applications (52 citations), Developmental and Educational Psychology (33 citations), Artificial Intelligence (50 citations) and Safety Research (9 citations). Luzhen Tang has collaborated with scholars based in China and Australia. Frequent co-authors include Yüan Shen, Huixiao Le, Dragan Gašević, Shufang Tan, Xinyu Li, Yizhou Fan, Qiong Wang and Jiyou Jia. Their work appears in journals such as British Journal of Educational Technology and Journal of Computer Assisted Learning.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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