Jui-Long Hung

1.9k total citations
54 papers, 1.2k citations indexed

About

Jui-Long Hung is a scholar working on Computer Science Applications, Education and Developmental and Educational Psychology. According to data from OpenAlex, Jui-Long Hung has authored 54 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Science Applications, 18 papers in Education and 18 papers in Developmental and Educational Psychology. Recurrent topics in Jui-Long Hung's work include Online Learning and Analytics (27 papers), Innovative Teaching and Learning Methods (18 papers) and Online and Blended Learning (16 papers). Jui-Long Hung is often cited by papers focused on Online Learning and Analytics (27 papers), Innovative Teaching and Learning Methods (18 papers) and Online and Blended Learning (16 papers). Jui-Long Hung collaborates with scholars based in United States, China and Taiwan. Jui-Long Hung's co-authors include Xu Du, Ke Zhang, Brett E. Shelton, Juan Yang, Wu He, Yu‐Chang Hsu, Kerry Rice, Jiancheng Shen, Patrick R. Lowenthal and Yu‐Hui Ching and has published in prestigious journals such as IEEE Access, Industrial Marketing Management and British Journal of Educational Technology.

In The Last Decade

Jui-Long Hung

50 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jui-Long Hung United States 20 585 412 299 267 218 54 1.2k
Edmundo Tovar Spain 16 581 1.0× 247 0.6× 394 1.3× 221 0.8× 144 0.7× 160 1.2k
Jarkko Suhonen Finland 20 486 0.8× 350 0.8× 437 1.5× 150 0.6× 274 1.3× 87 1.4k
Ismaila Temitayo Sanusi Finland 20 854 1.5× 353 0.9× 393 1.3× 353 1.3× 290 1.3× 95 1.7k
Anuradha Mathrani New Zealand 17 358 0.6× 219 0.5× 201 0.7× 154 0.6× 97 0.4× 73 908
Dietrich Albert Austria 17 452 0.8× 261 0.6× 254 0.8× 443 1.7× 551 2.5× 174 1.4k
Zacharoula Papamitsiou Greece 15 639 1.1× 275 0.7× 199 0.7× 266 1.0× 202 0.9× 31 1.1k
Uwe Matzat Netherlands 21 326 0.6× 326 0.8× 232 0.8× 171 0.6× 112 0.5× 58 1.4k
Jan Μ. Pawlowski Germany 18 483 0.8× 306 0.7× 283 0.9× 123 0.5× 100 0.5× 106 1.3k
Anders I. Mørch Norway 18 319 0.5× 207 0.5× 305 1.0× 244 0.9× 195 0.9× 87 1.2k
Mohamed Amine Chatti Germany 18 1.2k 2.1× 593 1.4× 417 1.4× 273 1.0× 307 1.4× 45 1.8k

Countries citing papers authored by Jui-Long Hung

Since Specialization
Citations

This map shows the geographic impact of Jui-Long Hung'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 Jui-Long Hung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jui-Long Hung more than expected).

Fields of papers citing papers by Jui-Long Hung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jui-Long Hung. 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 Jui-Long Hung. The network helps show where Jui-Long Hung may publish in the future.

Co-authorship network of co-authors of Jui-Long Hung

This figure shows the co-authorship network connecting the top 25 collaborators of Jui-Long Hung. A scholar is included among the top collaborators of Jui-Long Hung 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 Jui-Long Hung. Jui-Long Hung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Hung, Jui-Long, et al.. (2025). Supporting social interactions analyses with multi-agent large language models (MALLM) – an exploratory study. Information Discovery and Delivery. 1–15.
3.
Tang, Hengtao, et al.. (2024). Understanding College Students’ Behavioral Patterns in a Blended Learning Class. TechTrends. 68(2). 317–324.
4.
Du, Xu, et al.. (2024). Exploring the effects of roles and group compositions on social and cognitive interaction structures in online collaborative problem-solving. Education and Information Technologies. 29(14). 18149–18180. 4 indexed citations
5.
Rice, Kerry, et al.. (2023). The influence of course community and personal community support on learner engagement in online courses. Educational Technology Research and Development. 71(4). 1397–1420. 5 indexed citations
6.
Tang, Hengtao, et al.. (2023). Understanding college students’ cognitive engagement in online collaborative problem-solving: A multimodal data analysis. Distance Education. 44(2). 306–323. 20 indexed citations
7.
Du, Xu, et al.. (2022). A multimodal analysis of college students’ collaborative problem solving in virtual experimentation activities: a perspective of cognitive load. Journal of Computing in Higher Education. 35(2). 272–295. 26 indexed citations
8.
Dai, Miao, Jui-Long Hung, Xu Du, Hengtao Tang, & Hao Li. (2021). Knowledge Tracing: A Review of Available Technologies. Aquila Digital Community (University of Southern Mississippi). 14(2). 1–20. 5 indexed citations
9.
Hung, Jui-Long, et al.. (2016). FinTech in Taiwan: a case study of a Bank’s strategic planning for an investment in a FinTech company. Financial Innovation. 2(1). 57 indexed citations
10.
Hung, Jui-Long, et al.. (2015). A case study on learning analytics using Experience API. Society for Information Technology & Teacher Education International Conference. 2015(1). 2273–2278. 3 indexed citations
11.
Rice, Kerry & Jui-Long Hung. (2015). Data mining in Online Professional Development Program Evaluation: An Exploratory Case Study. Scholar Works (Boise State University). 11(1). 1–20. 4 indexed citations
12.
Hung, Jui-Long, et al.. (2015). Identifying At-Risk Students for Early Interventions—A Time-Series Clustering Approach. IEEE Transactions on Emerging Topics in Computing. 5(1). 45–55. 77 indexed citations
13.
Hung, Jui-Long & Dazhi Yang. (2015). The Validation of an Instrument for Evaluating the Effectiveness of Professional Development Program on Teaching Online. Aquila Digital Community (University of Southern Mississippi). 8(1). 2 indexed citations
14.
Zheng, Haichao, Jui-Long Hung, & Zhangxi Lin. (2013). An Empirical Study of Guarantee in Service E-Commerce. Scholar Works (Boise State University). 148. 1 indexed citations
15.
Hung, Jui-Long, Yu‐Chang Hsu, & Kerry Rice. (2012). Integrating Data Mining in Program Evaluation of K-12 Online Education. Educational Technology & Society. 15(3). 27–41. 46 indexed citations
16.
Zhang, Ke & Jui-Long Hung. (2011). Global Themes and Future Trends of Mobile Learning: Data Mining of Publications in AACE EDITLib Digital Library Database. EdMedia: World Conference on Educational Media and Technology. 2011(1). 3880–3886. 1 indexed citations
17.
Zhang, Ke & Jui-Long Hung. (2009). E-Learning in Supplemental Educational Systems in Taiwan: Present Status and Future Challenges. International journal on e-learning. 8(4). 479–494. 4 indexed citations
18.
Zhang, Ke, et al.. (2009). Online collaborative learning in a project‐based learning environment in Taiwan: a case study on undergraduate students’ perspectives. Educational Media International. 46(2). 123–135. 41 indexed citations
19.
Hung, Jui-Long, et al.. (2008). Computer-Based Instruction and Cognitive Load. Scholar Works (Boise State University). 12(4). 207. 3 indexed citations
20.
Hung, Jui-Long & Ke Zhang. (2006). Data Mining Applications to Online Learning. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2006(1). 2014–2021. 3 indexed citations

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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