Françeska Xhakaj
- Computer Science Applications top 5%
- Developmental and Educational Psychology top 10%
- Education top 10%
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Co-authors
- Vincent AlevenYuvraj AgarwalAmy OganKaran AhujaIoana JivetChris HarrisonJudy KayKatrien Verbert
- Topics
- Intelligent Tutoring Systems and Adaptive Learning (4 papers)Online Learning and Analytics (2 papers)Innovative Teaching and Learning Methods (1 paper)
- Cited by
- Computer Science ApplicationsDevelopmental and Educational PsychologyHuman-Computer Interaction
- Journals
- Software Practice and ExperienceProceedings of the ACM on Interactive Mobile Wearable and Ubiquitous TechnologiesLirias (KU Leuven)
- Partner nations
- United StatesSwitzerlandAustralia
In The Last Decade
Françeska Xhakaj
7 papers receiving 230 citations
Peers
Comparison fields: 5 of 53
- Computer Science Applications 106
- Developmental and Educational Psychology 73
- Education 71
- Artificial Intelligence 61
- Computer Vision and Pattern Recognition 38
Countries citing papers authored by Françeska Xhakaj
This map shows the geographic impact of Françeska Xhakaj'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 Françeska Xhakaj with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Françeska Xhakaj more than expected).
Fields of papers citing papers by Françeska Xhakaj
This network shows the impact of papers produced by Françeska Xhakaj. 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 Françeska Xhakaj. The network helps show where Françeska Xhakaj may publish in the future.
Co-authorship network of co-authors of Françeska Xhakaj
This figure shows the co-authorship network connecting the top 25 collaborators of Françeska Xhakaj. A scholar is included among the top collaborators of Françeska Xhakaj 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 Françeska Xhakaj. Françeska Xhakaj is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 28 | |
| 2 | 90 | |
| 3 | 94 | |
| 4 | Luna: A Dashboard for Teachers Using Intelligent Tutoring Systems. | 1 |
| 5 | Developing a Teacher Dashboard For Use with Intelligent Tutoring Systems. | 10 |
| 6 | 2 | |
| 7 | 9 |
About Françeska Xhakaj
Françeska Xhakaj is a scholar working on Computer Science Applications, Human-Computer Interaction and Artificial Intelligence, having authored 7 papers that have together received 234 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (4 papers), Online Learning and Analytics (2 papers) and Innovative Teaching and Learning Methods (1 paper). The work is most often cited by research in Computer Science Applications (106 citations), Developmental and Educational Psychology (73 citations) and Human-Computer Interaction (27 citations). Françeska Xhakaj has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include Vincent Aleven, Yuvraj Agarwal, Amy Ogan, Karan Ahuja, Ioana Jivet, Chris Harrison, Judy Kay, Katrien Verbert, Dan Davis and Robert Bodily. Their work appears in journals such as Software Practice and Experience, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies and Lirias (KU Leuven).
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.