Malinka Ivanova

561 citations
66 papers · 275 · h-index 8

Impact in

Papers in

Malinka Ivanova

56 papers receiving 247 citations

Peers

Malinka Ivanova
Comparison fields: 5 of 86
  • Computer Science Applications 62
  • Human-Computer Interaction 28
  • Health Informatics 6
  • Information Systems 86
  • Education 69
Replace Carlo De Medio with:
Carlo De Medio Italy
Kostas Vassilakis Greece
Laura Farinetti Italy
Zoltán Szűts Hungary
Mariano Rico Spain
Mohammed Basheri Saudi Arabia
Marc Jansen Germany
Vetria Byrd United States
Mikel Larrañaga Spain
Filippos Giannakas Greece
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Citations per field
00.5×1.5×2.4×
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Citations per year

Countries citing papers authored by Malinka Ivanova

Since Specialization
Citations

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

Fields of papers citing papers by Malinka Ivanova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1
ENHANCEMENT OF LEARNING AND TEACHING IN COMPUTER GRAPHICSTHROUGH MARKER AUGMENTED REALITY TECHNOLOGY
201154
2 202419
3 201116
4 201913
5 202011
6 201210
7 202010
8 20228
9
FROM PERSONAL LEARNING ENVIRONMENT BUILDING TO PROFESSIONAL LEARNING NETWORK FORMING
20097
10 20157
11 20217
12 20097
13 20117
14 20106
15
Analysis of Personal Learning Networks in Support of Teachers Presence Optimization
20125
16 20135
17 20205
18 20095
19 20215
20 20095

About Malinka Ivanova

Malinka Ivanova is a scholar working on Computer Science Applications, Artificial Intelligence, Information Systems, Education and Electrical and Electronic Engineering, having authored 66 papers that have together received 275 indexed citations. Recurring topics across this work include Online Learning and Analytics (12 papers), Innovative Teaching and Learning Methods (9 papers), Industrial Vision Systems and Defect Detection (7 papers), Online and Blended Learning (7 papers), E-Learning and Knowledge Management (7 papers), Intelligent Tutoring Systems and Adaptive Learning (5 papers), Open Education and E-Learning (5 papers) and VLSI and Analog Circuit Testing (4 papers). The work is most often cited by research in Computer Science Applications (62 citations), Human-Computer Interaction (28 citations), Health Informatics (6 citations), Information Systems (86 citations) and Education (69 citations). Malinka Ivanova has collaborated with scholars based in Bulgaria, Romania and Spain. Frequent co-authors include Carmen Holotescu, Gabriela Grosseck, Mohamed Amine Chatti, Nikolay Petkov, Mikhail Ya. Melnikov, G. M. Zhidomirov, Mohamed Amine Chatti, David Bañeres, T. Lalinský and Roumiana Ilieva. Their work appears in journals such as Electronics, Informatics, Interactive Technology and Smart Education, Informatics in Education and Radiation Protection Dosimetry.

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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