Qiao Lin

772 citations
9 papers · 558 indexed · 1 hit paper · h-index 5
Topics
Teaching and Learning Programming (5 papers)Online Learning and Analytics (3 papers)Intelligent Tutoring Systems and Adaptive Learning (2 papers)
Partner nations
United StatesChina

In The Last Decade

Qiao Lin

8 papers receiving 545 citations

Hit Papers

Assessing computational thinking: A systematic review of ...20202026202220242020100200300400

Peers

Qiao Lin
Comparison fields: 5 of 50
  • Computer Science Applications 483
  • Developmental and Educational Psychology 253
  • Molecular Biology 79
  • Information Systems 75
  • Education 72
Replace Roxana Hadad with:
Roxana Hadad United States
Kathryn M. Rich United States
Yizhou Qian China
Veronica Cateté United States
Benjamin Xie United States
Yihuan Dong United States
Kyu Han Koh United States
Lechen Zhang Sweden
Ashok Basawapatna United States
Jane Waite United Kingdom
Qiao Lin relative to Roxana Hadad United States Roxana Hadad's profile →
Citations per field
00.5×1.5×
Roxana Hadad · 1×
Citations per year

Countries citing papers authored by Qiao Lin

Since Specialization
Citations

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

Fields of papers citing papers by Qiao Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiao Lin

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

All Works

9 of 9 papers shown
#WorkIndexed citations
1 0
2 1
3 7
4 59
5
Assessing computational thinking: A systematic review of empirical studiesbreakdown →
418
6 4
7 64
8
Making Computational Thinking Evident: A Validation Study of a Computational Thinking Test.
3
9 2

About Qiao Lin

Qiao Lin is a scholar working on Computer Science Applications, Software and Management Science and Operations Research, having authored 9 papers that have together received 558 indexed citations. Recurring topics across this work include Teaching and Learning Programming (5 papers), Online Learning and Analytics (3 papers) and Intelligent Tutoring Systems and Adaptive Learning (2 papers). The work is most often cited by research in Computer Science Applications (483 citations), Developmental and Educational Psychology (253 citations) and Software (41 citations). Qiao Lin has collaborated with scholars based in United States and China. Frequent co-authors include Xiaodan Tang, Roxana Hadad, Yue Yin, Xiaoming Zhaı, Yoon Soo Park, Ning Ye, Yerim Kim and James A. Swartz. Their work appears in journals such as PLoS ONE, Computers & Education and Frontiers in Psychology.

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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