Yeongwook Yang

934 total citations
35 papers, 544 citations indexed

About

Yeongwook Yang is a scholar working on Computer Science Applications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Yeongwook Yang has authored 35 papers receiving a total of 544 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Science Applications, 14 papers in Artificial Intelligence and 11 papers in Information Systems. Recurrent topics in Yeongwook Yang's work include Online Learning and Analytics (14 papers), Educational Games and Gamification (7 papers) and Topic Modeling (6 papers). Yeongwook Yang is often cited by papers focused on Online Learning and Analytics (14 papers), Educational Games and Gamification (7 papers) and Topic Modeling (6 papers). Yeongwook Yang collaborates with scholars based in South Korea, Estonia and Taiwan. Yeongwook Yang's co-authors include Danial Hooshyar, Margus Pedaste, Heuiseok Lim, Minhong Wang, Liina Malva, Yueh‐Min Huang, Chanjun Park, Gwo‐Jen Hwang, Jaechoon Jo and Chanhee Lee and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and Expert Systems with Applications.

In The Last Decade

Yeongwook Yang

30 papers receiving 525 citations

Peers

Yeongwook Yang

CSA

DEP

EDUCA

Gökhan Akçapınar Türkiye

Felix Mödritscher Austria

María Puerto Paule Ruiz Spain

Stefano A. Cerri France

Diego Zapata‐Rivera United States

Fumiya Okubo Japan

Jordi Conesa Spain

Alexandros Paramythis Austria

Pilar Rodrı́guez Spain

Diana Pérez-Marín Spain

Gökhan Akçapınar Türkiye

Yeongwook Yang

354 ×1.3

CSA

134 ×0.7

109 ×0.6

DEP

109 ×0.9

166 ×2.8

EDUCA

Citations per year, relative to Yeongwook Yang Yeongwook Yang (= 1×) peers Gökhan Akçapınar

Countries citing papers authored by Yeongwook Yang

Since Specialization

Citations

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

Fields of papers citing papers by Yeongwook Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yeongwook Yang. 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 Yeongwook Yang. The network helps show where Yeongwook Yang may publish in the future.

Co-authorship network of co-authors of Yeongwook Yang

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

All Works

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20 of 20 papers shown

Hooshyar, Danial & Yeongwook Yang. (2025). Predicting Course Grades Through Comprehensive Modeling of Students’ Learning Behavioral Patterns. Complexity. 2025(1).

Hooshyar, Danial, Yeongwook Yang, Eve Kikas, et al.. (2025). Towards responsible AI for education: Hybrid human-AI to confront the elephant in the room. Computers and Education Artificial Intelligence. 9. 100524–100524.

Hooshyar, Danial, Roger Azevedo, & Yeongwook Yang. (2024). Augmenting Deep Neural Networks with Symbolic Educational Knowledge: Towards Trustworthy and Interpretable AI for Education. SHILAP Revista de lepidopterología. 6(1). 593–618. 14 indexed citations

Hooshyar, Danial & Yeongwook Yang. (2024). Problems With SHAP and LIME in Interpretable AI for Education: A Comparative Study of Post-Hoc Explanations and Neural-Symbolic Rule Extraction. IEEE Access. 12. 137472–137490. 11 indexed citations

Yang, Yeongwook, et al.. (2024). A Comparative Study of Computational Thinking Perception Between Freshmen and Senior of Computer Science. The Journal of Korean Association of Computer Education. 27(1). 63–69.

Hooshyar, Danial, et al.. (2023). Modeling Learners to Early Predict Their Performance in Educational Computer Games. IEEE Access. 11. 20399–20417. 5 indexed citations

Yang, Yeongwook, et al.. (2023). Machine Learning Based Representative Spatio-Temporal Event Documents Classification. Applied Sciences. 13(7). 4230–4230. 3 indexed citations

Hooshyar, Danial, Yueh‐Min Huang, & Yeongwook Yang. (2022). GameDKT: Deep knowledge tracing in educational games. Expert Systems with Applications. 196. 116670–116670. 23 indexed citations

Yang, Yeongwook, et al.. (2021). FP-Growth Algorithm for Discovering Region-Based Association Rule in the IoT Environment. Electronics. 10(24). 3091–3091. 7 indexed citations

10.

Yang, Yeongwook, et al.. (2020). A Hybrid Recommender System for Sequential Recommendation: Combining Similarity Models With Markov Chains. IEEE Access. 8. 190136–190146. 13 indexed citations

11.

Yang, Yeongwook, Danial Hooshyar, Margus Pedaste, et al.. (2020). Prediction of students’ procrastination behaviour through their submission behavioural pattern in online learning. Journal of Ambient Intelligence and Humanized Computing. 17 indexed citations

12.

Malva, Liina, Danial Hooshyar, Yeongwook Yang, & Margus Pedaste. (2020). Engaging Estonian primary school children in computational thinking through adaptive educational games: A qualitative study. 188–190. 10 indexed citations

13.

Hooshyar, Danial, et al.. (2020). Investigating the Learning Impact of Autothinking Educational Game on Adults: A Case Study of France. SPIRE - Sciences Po Institutional REpository. 188–196. 5 indexed citations

14.

Hooshyar, Danial, Margus Pedaste, Yeongwook Yang, et al.. (2020). From Gaming to Computational Thinking: An Adaptive Educational Computer Game-Based Learning Approach. Journal of Educational Computing Research. 59(3). 383–409. 85 indexed citations

15.

Hooshyar, Danial, Liina Malva, Yeongwook Yang, et al.. (2020). An adaptive educational computer game: Effects on students' knowledge and learning attitude in computational thinking. Computers in Human Behavior. 114. 106575–106575. 85 indexed citations

16.

Park, Chanjun, Yeongwook Yang, Kinam Park, & Heuiseok Lim. (2020). Decoding Strategies for Improving Low-Resource Machine Translation. Electronics. 9(10). 1562–1562. 18 indexed citations

17.

Yang, Yeongwook, Jaechoon Jo, & Heuiseok Lim. (2019). Unifying user preference and item knowledge-based similarity models for top-N recommendation. Personal and Ubiquitous Computing. 26(2). 407–416. 3 indexed citations

18.

Yang, Yeongwook, Danial Hooshyar, Jaechoon Jo, & Heuiseok Lim. (2018). A group preference-based item similarity model: comparison of clustering techniques in ambient and context-aware recommender systems. Journal of Ambient Intelligence and Humanized Computing. 11(4). 1441–1449. 12 indexed citations

19.

Yang, Yeongwook & Heuiseok Lim. (2011). The Development of Serious Game for the Cognitive Ability Training using Smart Device. Journal of Korea Game Society. 11(6). 23–31.

20.

Yang, Yeongwook, Jaechoon Jo, & Heuiseok Lim. (2010). The Smart Phone Application Implement for Cognitive Ability Training. 43–46. 1 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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