Eda Okur

520 citations
23 papers · 244 · h-index 10

Impact in

Papers in

Eda Okur

22 papers receiving 238 citations

Peers

Eda Okur
Comparison fields: 5 of 60
  • Computer Science Applications 104
  • Developmental and Educational Psychology 68
  • Human-Computer Interaction 22
  • Health Informatics 4
  • Artificial Intelligence 103
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Franz Wortha Germany
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Marayna Martinez United States
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Citations per year

Countries citing papers authored by Eda Okur

Since Specialization
Citations

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

Fields of papers citing papers by Eda Okur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Eda Okur, 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 Eda Okur Line = papers co-authored together Eda Okur links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201971
2
Human Expert Labeling Process (HELP): Towards a Reliable Higher-order User State Labeling Process and Tool to Assess Student Engagement
201720
3 201619
4 201718
5 201715
6
Towards an Emotional Engagement Model: Can Affective States of a Learner be Automatically Detected in a 1: 1 Learning Scenario?
201613
7 202212
8 202412
9 20239
10 20189
11 20237
12 20187
13 20166
14 20176
15 20225
16 20234
17 20233
18 20202
19 20182
20 20202

About Eda Okur

Eda Okur is a scholar working on Artificial Intelligence, Computer Science Applications, Education, Experimental and Cognitive Psychology and Developmental and Educational Psychology, having authored 23 papers that have together received 244 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (9 papers), Online Learning and Analytics (7 papers), Speech and dialogue systems (5 papers), Topic Modeling (4 papers), Emotion and Mood Recognition (4 papers), Child Development and Digital Technology (3 papers), Online and Blended Learning (2 papers) and Impact of Technology on Adolescents (2 papers). The work is most often cited by research in Computer Science Applications (104 citations), Developmental and Educational Psychology (68 citations), Human-Computer Interaction (22 citations), Health Informatics (4 citations) and Artificial Intelligence (103 citations). Eda Okur has collaborated with scholars based in United States, Türkiye and Taiwan. Frequent co-authors include Sinem Aslan, Neşe Alyüz, Cagri Tanriover, Sidney K. D’Mello, Lama Nachman, Bert Arnrich, Saurav Sahay, Arzucan Özgür, Hakan Demir and Celal Savur. Their work appears in journals such as Educational Technology Research and Development, Computer Speech & Language, Biological Trace Element Research, British Journal of Educational Technology and Computers and Education Artificial Intelligence.

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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