Dovan Rai

446 citations
17 papers · 347 · h-index 8

Impact in

Papers in

Dovan Rai

16 papers receiving 314 citations

Peers

Dovan Rai
Comparison fields: 5 of 47
  • Computer Science Applications 212
  • Developmental and Educational Psychology 158
  • Artificial Intelligence 203
  • Experimental and Cognitive Psychology 38
  • Education 61
Replace Lisa M. Rossi with:
Lisa M. Rossi United States
Deirdre Kerr United States
Leena Razzaq United States
Minghui Tai United States
Michael Wixon United States
Hogyeong Jeong United States
Moffat Mathews New Zealand
Stephen E. Fancsali United States
Yanjin Long United States
Shiva Hajian Canada
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Citations per field
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Citations per year

Countries citing papers authored by Dovan Rai

Since Specialization
Citations

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

Fields of papers citing papers by Dovan Rai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Dovan Rai, 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 Dovan Rai Line = papers co-authored together Dovan Rai links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2014196
2 201534
3
Does Self-Discipline impact students' knowledge and learning?
200923
4
Using Dirichlet Priors to Improve Model Parameter Plausibility.
200920
5
The Opportunities and Limitations of Scaling Up Sensor-Free Affect Detection
201419
6 201217
7
Exploring User Data From a Game-like Math Tutor: A Case Study in Causal Modeling.
201110
8 20128
9 20135
10 20184
11
Analysis of a causal modeling approach: a case study with an educational intervention.
20103
12 20102
13 20112
14 20102
15 20101
16 20131
17 20110

About Dovan Rai

Dovan Rai is a scholar working on Artificial Intelligence, Developmental and Educational Psychology, Computer Science Applications, Experimental and Cognitive Psychology and Automotive Engineering, having authored 17 papers that have together received 347 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (14 papers), Educational Games and Gamification (8 papers), Innovative Teaching and Learning Methods (7 papers), Online Learning and Analytics (5 papers), Teaching and Learning Programming (3 papers), Machine Learning and Algorithms (1 paper), Video Analysis and Summarization (1 paper) and Spatial Cognition and Navigation (1 paper). The work is most often cited by research in Computer Science Applications (212 citations), Developmental and Educational Psychology (158 citations), Artificial Intelligence (203 citations), Experimental and Cognitive Psychology (38 citations) and Education (61 citations). Dovan Rai has collaborated with scholars based in United States and Canada. Frequent co-authors include Ivon Arroyo, Beverly Park Woolf, Kasia Müldner, Joseph E. Beck, Minghui Tai, Yue Gong, Winslow Burleson, Michael Wixon and Neil T. Heffernan. Their work appears in journals such as International Journal of Artificial Intelligence in Education, Lecture notes in computer science, International Journal of Game-Based Learning and Educational Data Mining.

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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