Aldo Ramírez-Arellano
- Education top 10%
- Statistical and Nonlinear Physics top 10%
- Developmental and Educational Psychology top 10%
- Computer Science Applications top 5%
- Information Systems
- Co-authors
- Juan Bory ReyesElizabeth Acosta GonzagaMayra Antonio-CruzJie ZhaoKang Hao CheongMarcell NagyJuan Irving Vasquez-GomezRoland Molontay
- Topics
- Complex Network Analysis Techniques (8 papers)Online Learning and Analytics (6 papers)Statistical Mechanics and Entropy (6 papers)
In The Last Decade
Aldo Ramírez-Arellano
31 papers receiving 278 citations
Peers
Comparison fields: 5 of 73
- Education 86
- Statistical and Nonlinear Physics 72
- Developmental and Educational Psychology 62
- Computer Science Applications 55
- Information Systems 40
Countries citing papers authored by Aldo Ramírez-Arellano
This map shows the geographic impact of Aldo Ramírez-Arellano'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 Aldo Ramírez-Arellano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aldo Ramírez-Arellano more than expected).
Fields of papers citing papers by Aldo Ramírez-Arellano
This network shows the impact of papers produced by Aldo Ramírez-Arellano. 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 Aldo Ramírez-Arellano. The network helps show where Aldo Ramírez-Arellano may publish in the future.
Co-authorship network of co-authors of Aldo Ramírez-Arellano
This figure shows the co-authorship network connecting the top 25 collaborators of Aldo Ramírez-Arellano. A scholar is included among the top collaborators of Aldo Ramírez-Arellano 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 Aldo Ramírez-Arellano. Aldo Ramírez-Arellano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 8 | |
| 10 | 6 | |
| 11 | Fractional Online Learning Rate: Influence of Psychological Factors on Learning Acquisition. | 3 |
| 12 | 1 | |
| 13 | 18 | |
| 14 | 7 | |
| 15 | 16 | |
| 16 | 9 | |
| 17 | 13 | |
| 18 | 19 | |
| 19 | 32 | |
| 20 | 3 |
About Aldo Ramírez-Arellano
Aldo Ramírez-Arellano is a scholar working on Computer Science Applications, Statistical and Nonlinear Physics and Developmental and Educational Psychology, having authored 32 papers that have together received 284 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (8 papers), Online Learning and Analytics (6 papers) and Statistical Mechanics and Entropy (6 papers). The work is most often cited by research in Computer Science Applications (55 citations), Statistical and Nonlinear Physics (72 citations) and Developmental and Educational Psychology (62 citations). Aldo Ramírez-Arellano has collaborated with scholars based in Mexico, China and Singapore. Frequent co-authors include Juan Bory Reyes, Elizabeth Acosta Gonzaga, Mayra Antonio-Cruz, Jie Zhao, Kang Hao Cheong, Marcell Nagy, Juan Irving Vasquez-Gomez and Roland Molontay. Their work appears in journals such as Computers & Education, Sustainability and Chaos Solitons & Fractals.
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.