Vanessa Echeverría
- Computer Science Applications top 0.5%
- Developmental and Educational Psychology top 5%
- Artificial Intelligence top 10%
- Education top 5%
- Information Systems top 5%
- Co-authors
- Roberto Martínez‐MaldonadoSimon Buckingham ShumDragan GaševićGloria Milena Fernandez-NietoKatherine ChiluizaLixiang YanYueqiao JinZachari Swiecki
- Topics
- Online Learning and Analytics (34 papers)Innovative Teaching and Learning Methods (23 papers)Online and Blended Learning (16 papers)
- Journals
- Computers & EducationBritish Journal of Educational TechnologyJournal of Computer Assisted Learning
- Partner nations
- AustraliaEcuadorUnited States
In The Last Decade
Vanessa Echeverría
55 papers receiving 754 citations
Peers
Comparison fields: 5 of 70
- Computer Science Applications 394
- Developmental and Educational Psychology 237
- Artificial Intelligence 186
- Education 169
- Information Systems 119
Countries citing papers authored by Vanessa Echeverría
This map shows the geographic impact of Vanessa Echeverría'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 Vanessa Echeverría with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vanessa Echeverría more than expected).
Fields of papers citing papers by Vanessa Echeverría
This network shows the impact of papers produced by Vanessa Echeverría. 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 Vanessa Echeverría. The network helps show where Vanessa Echeverría may publish in the future.
Co-authorship network of co-authors of Vanessa Echeverría
This figure shows the co-authorship network connecting the top 25 collaborators of Vanessa Echeverría. A scholar is included among the top collaborators of Vanessa Echeverría 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 Vanessa Echeverría. Vanessa Echeverría is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 0 | |
| 4 | 8 | |
| 5 | 1 | |
| 6 | 28 | |
| 7 | 6 | |
| 8 | 3 | |
| 9 | 10 | |
| 10 | 7 | |
| 11 | 25 | |
| 12 | 13 | |
| 13 | 19 | |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 11 | |
| 18 | 18 | |
| 19 | 3 | |
| 20 | Cognitive and Meta-Cognitive Skills Measurement: What about the Task in Web 2.0 Environments? | 1 |
About Vanessa Echeverría
Vanessa Echeverría is a scholar working on Computer Science Applications, Health Informatics and Developmental and Educational Psychology, having authored 60 papers that have together received 791 indexed citations. Recurring topics across this work include Online Learning and Analytics (34 papers), Innovative Teaching and Learning Methods (23 papers) and Online and Blended Learning (16 papers). The work is most often cited by research in Computer Science Applications (394 citations), Health Informatics (56 citations) and Developmental and Educational Psychology (237 citations). Vanessa Echeverría has collaborated with scholars based in Australia, Ecuador and United States. Frequent co-authors include Roberto Martínez‐Maldonado, Simon Buckingham Shum, Dragan Gašević, Gloria Milena Fernandez-Nieto, Katherine Chiluiza, Lixiang Yan, Yueqiao Jin, Zachari Swiecki, Riordan Alfredo and Cristina Conati. Their work appears in journals such as Computers & Education, British Journal of Educational Technology and Journal of Computer Assisted Learning.
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.