Michael Pin-Chuan Lin
- Computer Science Applications top 2%
- Artificial Intelligence top 10%
- Developmental and Educational Psychology top 10%
- Education top 10%
- Information Systems top 10%
- Co-authors
- Daniel ChangShiva HajianYu-Feng LanPhilip H. WinneMladen RakovićMaiga ChangEric PoitrasJohn C. Nesbit
- Topics
- Online Learning and Analytics (5 papers)Innovative Teaching and Learning Methods (4 papers)AI in Service Interactions (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaSustainabilityEducational Technology Research and Development
In The Last Decade
Michael Pin-Chuan Lin
9 papers receiving 288 citations
Peers
Comparison fields: 5 of 56
- Computer Science Applications 151
- Artificial Intelligence 137
- Developmental and Educational Psychology 96
- Education 67
- Information Systems 50
Countries citing papers authored by Michael Pin-Chuan Lin
This map shows the geographic impact of Michael Pin-Chuan Lin'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 Michael Pin-Chuan Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Pin-Chuan Lin more than expected).
Fields of papers citing papers by Michael Pin-Chuan Lin
This network shows the impact of papers produced by Michael Pin-Chuan Lin. 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 Michael Pin-Chuan Lin. The network helps show where Michael Pin-Chuan Lin may publish in the future.
Co-authorship network of co-authors of Michael Pin-Chuan Lin
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Pin-Chuan Lin. A scholar is included among the top collaborators of Michael Pin-Chuan Lin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Pin-Chuan Lin. Michael Pin-Chuan Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 14 | |
| 4 | 8 | |
| 5 | 28 | |
| 6 | 143 | |
| 7 | Enhancing Post-secondary Writers’ Writing Skills with a Chatbot: A Mixed-Method Classroom Study | 44 |
| 8 | 26 | |
| 9 | 2 | |
| 10 | 11 | |
| 11 | 27 |
About Michael Pin-Chuan Lin
Michael Pin-Chuan Lin is a scholar working on Health Informatics, Computer Science Applications and Developmental and Educational Psychology, having authored 11 papers that have together received 303 indexed citations. Recurring topics across this work include Online Learning and Analytics (5 papers), Innovative Teaching and Learning Methods (4 papers) and AI in Service Interactions (4 papers). The work is most often cited by research in Health Informatics (46 citations), Computer Science Applications (151 citations) and Developmental and Educational Psychology (96 citations). Michael Pin-Chuan Lin has collaborated with scholars based in Canada, Taiwan and Argentina. Frequent co-authors include Daniel Chang, Shiva Hajian, Yu-Feng Lan, Philip H. Winne, Mladen Raković, Maiga Chang, Eric Poitras, John C. Nesbit, Jovita Vytasek and Chih‐Lin Hu. Their work appears in journals such as SHILAP Revista de lepidopterología, Sustainability and Educational Technology Research and Development.
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.