Ju-Ling Shih

994 citations
49 papers · 733 · h-index 12

Impact in

Papers in

Ju-Ling Shih

41 papers receiving 685 citations

Peers

Ju-Ling Shih
Comparison fields: 5 of 71
  • Developmental and Educational Psychology 255
  • Information Systems 245
  • Human-Computer Interaction 48
  • Computer Science Applications 26
  • Speech and Hearing 20
Replace Clark N. Quinn with:
Clark N. Quinn Australia
Hsiu‐Ling Chen Taiwan
Emmanuel Fokides Greece
Ming‐Puu Chen Taiwan
Johanna Pöysä‐Tarhonen Finland
Marcela Borge United States
Lu‐Ho Hsia Taiwan
José Bidarra Portugal
J.C. Huizenga Netherlands
Victor Law United States
Ju-Ling Shih relative to Clark N. Quinn Australia Clark N. Quinn's profile →
Citations per field
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Clark N. Quinn · 1×
Citations per year

Countries citing papers authored by Ju-Ling Shih

Since Specialization
Citations

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

Fields of papers citing papers by Ju-Ling Shih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ju-Ling Shih. 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 Ju-Ling Shih. The network helps show where Ju-Ling Shih may publish in the future.

Co-authors

The 25 scholars most cited alongside Ju-Ling Shih, 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 Ju-Ling Shih Line = papers co-authored together Ju-Ling Shih 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 2015130
2 2010120
3 201664
4 201856
5 201054
6 201049
7 202044
8 201135
9 201727
10 201623
11 201919
12 202212
13 20109
14 20249
15 20127
16 20126
17
Proceedings of International Conference on Computational Thinking Education 2017
20176
18 20135
19 20145
20 20155

About Ju-Ling Shih

Ju-Ling Shih is a scholar working on Developmental and Educational Psychology, Information Systems, Computer Science Applications, General Social Sciences and Experimental and Cognitive Psychology, having authored 49 papers that have together received 733 indexed citations. Recurring topics across this work include Educational Games and Gamification (22 papers), Mobile Learning in Education (9 papers), Innovative Teaching and Learning Methods (3 papers), Problem and Project Based Learning (3 papers), Teaching and Learning Programming (3 papers), Educational Technology and Assessment (2 papers), Augmented Reality Applications (2 papers) and Creativity in Education and Neuroscience (2 papers). The work is most often cited by research in Developmental and Educational Psychology (255 citations), Information Systems (245 citations), Human-Computer Interaction (48 citations), Computer Science Applications (26 citations) and Speech and Hearing (20 citations). Ju-Ling Shih has collaborated with scholars based in Taiwan, Hong Kong and United Kingdom. Frequent co-authors include Gwo‐Jen Hwang, Hui‐Chun Chu, Kinshuk Kinshuk, Chih‐Kai Chang, Ching‐Yi Chang, Gheorghiță Ghinea, Shu-Hsien Huang, Alexandra Covaci, Chen‐Chung Liu and Baw‐Jhiune Liu. Their work appears in journals such as Research and Practice in Technology Enhanced Learning, Computers & Education, The Electronic Library, Journal of Educational Computing Research and System.

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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