Lijun Ni

947 citations
34 papers · 595 indexed · h-index 14
Topics
Teaching and Learning Programming (24 papers)Gender and Technology in Education (13 papers)Child Development and Digital Technology (12 papers)
Partner nations
United StatesCanada

In The Last Decade

Lijun Ni

30 papers receiving 579 citations

Peers

Lijun Ni
Comparison fields: 5 of 56
  • Computer Science Applications 426
  • Education 205
  • Developmental and Educational Psychology 205
  • Gender Studies 152
  • Information Systems 111
Replace Ninger Zhou with:
Ninger Zhou United States
Monica M. McGill United States
Rebecca Vivian Australia
Briana B. Morrison United States
Adrienne Decker United States
Jane Waite United Kingdom
Simon Humphreys United Kingdom
Quinn Burke United States
Brian Dorn United States
Andrew Csizmadia United Kingdom
Lijun Ni relative to Ninger Zhou United States Ninger Zhou's profile →
Citations per field
00.5×1.5×2.3×
Ninger Zhou · 1×
Citations per year

Countries citing papers authored by Lijun Ni

Since Specialization
Citations

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

Fields of papers citing papers by Lijun Ni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lijun Ni

This figure shows the co-authorship network connecting the top 25 collaborators of Lijun Ni. A scholar is included among the top collaborators of Lijun Ni 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 Lijun Ni. Lijun Ni 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
#WorkIndexed citations
1 0
2 0
3 1
4 2
5 1
6 2
7 9
8 1
9 94
10
Creating Socially Relevant Mobile Apps: Infusing Computing into Middle School Curricula in Two School Districts.
2
11
Empowering middle school students to create data-enabled social apps
1
12 6
13 46
14 23
15 13
16 24
17 14
18 64
19 60
20
What Makes Teachers Change? Factors that Influence Post-secondary Teachers’ Adoption of New Computing Curricula
2

About Lijun Ni

Lijun Ni is a scholar working on Computer Science Applications, Gender Studies and Human Factors and Ergonomics, having authored 34 papers that have together received 595 indexed citations. Recurring topics across this work include Teaching and Learning Programming (24 papers), Gender and Technology in Education (13 papers) and Child Development and Digital Technology (12 papers). The work is most often cited by research in Computer Science Applications (426 citations), Developmental and Educational Psychology (205 citations) and Gender Studies (152 citations). Lijun Ni has collaborated with scholars based in United States and Canada. Frequent co-authors include Mark Guzdial, Tom McKlin, Alandeom W. Oliveira, Guo Li, Reza Feyzi-Behnagh, Briana B. Morrison, Douglas Blank, Tucker Balch, Keith J. O’Hara and Deepak Kumar. Their work appears in journals such as Journal of Research on Technology in Education, ACM Transactions on Computing Education and Computer Science Education.

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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