Jaye Nias

406 citations
20 papers · 309 · h-index 7

Impact in

Papers in

Jaye Nias

18 papers receiving 293 citations

Peers

Jaye Nias
Comparison fields: 5 of 47
  • Human-Computer Interaction 159
  • Computer Science Applications 59
  • Developmental and Educational Psychology 74
  • Cognitive Neuroscience 80
  • Education 108
Replace Cristina Sylla with:
Cristina Sylla Portugal
Emanuela Mazzone United Kingdom
Vicente Nacher Spain
Alessandra Melonio Italy
Kaiju Kangas Finland
Marc-Antoine Nüssli Switzerland
Brendan Cassidy United Kingdom
Nima Motamedi Canada
Indy Y.T. Hsiao Taiwan
Nesra Yannier United States
Jaye Nias relative to Cristina Sylla Portugal Cristina Sylla's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jaye Nias

Since Specialization
Citations

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

Fields of papers citing papers by Jaye Nias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2012102
2 201379
3 201350
4 201329
5 201511
6 202110
7 20206
8 20204
9 20214
10 20153
11 20172
12
Challenges of Replicating Empirical Studies with Children in HCI.
20132
13 20152
14 20231
15 20251
16 20221
17 20221
18 20191
19 20250
20 20250

About Jaye Nias

Jaye Nias is a scholar working on Human-Computer Interaction, Computer Science Applications, Sociology and Political Science, Cognitive Neuroscience and Education, having authored 20 papers that have together received 309 indexed citations. Recurring topics across this work include Teaching and Learning Programming (7 papers), Interactive and Immersive Displays (5 papers), Usability and User Interface Design (5 papers), Tactile and Sensory Interactions (4 papers), Innovative Human-Technology Interaction (4 papers), Educational Games and Gamification (2 papers), AI in Service Interactions (2 papers) and Child Development and Digital Technology (2 papers). The work is most often cited by research in Human-Computer Interaction (159 citations), Computer Science Applications (59 citations), Developmental and Educational Psychology (74 citations), Cognitive Neuroscience (80 citations) and Education (108 citations). Jaye Nias has collaborated with scholars based in United States and India. Frequent co-authors include Lisa Anthony, Quincy Brown, Robin Brewer, Bryan Dosono, Daniel K. Gardner, Jakita O. Thomas, Audrey Bennett, Yolanda A. Rankin, Ian Arawjo and Ihudiya Finda Ogbonnaya-Ogburu. Their work appears in journals such as International Journal of Child-Computer Interaction, interactions and Personal and Ubiquitous Computing.

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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