Jun‐Ming Su

632 citations
49 papers · 397 · h-index 11

Impact in

    • Online Learning and Analytics
    • Open Education and E-Learning
    • Teaching and Learning Programming
    • Educational Technology and Assessment
    • Data Mining Algorithms and Applications
    • Mobile Learning in Education

Papers in

Jun‐Ming Su

41 papers receiving 363 citations

Peers

Jun‐Ming Su
Comparison fields: 5 of 69
  • Computer Science Applications 169
  • Information Systems 197
  • Developmental and Educational Psychology 74
  • Software 20
  • Artificial Intelligence 110
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Thomas Way United States
Abdul Wahid India
Luisa M. Regueras Spain
Edward R. Sykes Canada
Juan Pablo de Castro Fernández Spain
Timo Hynninen Finland
Jui-Feng Weng Taiwan
Marco Temperini Italy
Susan Mengel United States
Igor Čavrak Croatia
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Citations per field
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Citations per year

Countries citing papers authored by Jun‐Ming Su

Since Specialization
Citations

This map shows the geographic impact of Jun‐Ming Su'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 Jun‐Ming Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun‐Ming Su more than expected).

Fields of papers citing papers by Jun‐Ming Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun‐Ming Su. 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 Jun‐Ming Su. The network helps show where Jun‐Ming Su may publish in the future.

Co-authors

The 25 scholars most cited alongside Jun‐Ming Su, 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 Jun‐Ming Su Line = papers co-authored together Jun‐Ming Su links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200571
2 200539
3
Learning Portfolio Analysis and Mining for SCORM Compliant Environment.
200634
4 201133
5 200423
6 201421
7 202019
8 199116
9 202315
10 201215
11
A content management scheme in a SCORM compliant learning object repository
200510
12 200510
13
Design and Implementation of an Object Oriented Learning Activity System
20068
14
OPASS: An Online Portfolio Assessment and Diagnosis Scheme to Support Web-Based Scientific Inquiry Experiments.
20117
15 20187
16 20177
17 20215
18 20075
19 20244
20 20174

About Jun‐Ming Su

Jun‐Ming Su is a scholar working on Computer Science Applications, Information Systems, Developmental and Educational Psychology, Computer Networks and Communications and Artificial Intelligence, having authored 49 papers that have together received 397 indexed citations. Recurring topics across this work include Online Learning and Analytics (12 papers), Educational Technology and Assessment (7 papers), Innovative Teaching and Learning Methods (7 papers), Teaching and Learning Programming (6 papers), Intelligent Tutoring Systems and Adaptive Learning (5 papers), Recommender Systems and Techniques (5 papers), Open Education and E-Learning (5 papers) and Radio Frequency Integrated Circuit Design (4 papers). The work is most often cited by research in Computer Science Applications (169 citations), Information Systems (197 citations), Developmental and Educational Psychology (74 citations), Software (20 citations) and Artificial Intelligence (110 citations). Jun‐Ming Su has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Shian‐Shyong Tseng, Jui-Feng Weng, Chun‐Han Chen, Wei Wang, Liuming Yan, Chi‐Jane Wang, Chao Sun, Baohua Yue, Jer‐Hao Chang and Yilin Liu. Their work appears in journals such as Educational Technology & Society, Digital Health, Computer Standards & Interfaces, Microwave and Optical Technology Letters and Japanese Journal of Applied Physics.

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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