Rwitajit Majumdar
- Computer Science Applications top 0.5%
- Education top 2%
- Developmental and Educational Psychology top 5%
- Information Systems top 5%
- Artificial Intelligence top 10%
- Co-authors
- Hiroaki OgataBrendan FlanaganMei‐Rong Alice ChenGökhan AkçapınarSridhar IyerSamar HelouSahana MurthyGwo‐Jen Hwang
- Topics
- Online Learning and Analytics (55 papers)Innovative Teaching and Learning Methods (23 papers)Online and Blended Learning (20 papers)
- Journals
- SHILAP Revista de lepidopterologíaCommunications of the ACMIEEE Access
In The Last Decade
Rwitajit Majumdar
78 papers receiving 748 citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Computer Science Applications 394
- Education 356
- Developmental and Educational Psychology 214
- Information Systems 153
- Artificial Intelligence 125
Countries citing papers authored by Rwitajit Majumdar
This map shows the geographic impact of Rwitajit Majumdar'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 Rwitajit Majumdar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rwitajit Majumdar more than expected).
Fields of papers citing papers by Rwitajit Majumdar
This network shows the impact of papers produced by Rwitajit Majumdar. 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 Rwitajit Majumdar. The network helps show where Rwitajit Majumdar may publish in the future.
Co-authorship network of co-authors of Rwitajit Majumdar
This figure shows the co-authorship network connecting the top 25 collaborators of Rwitajit Majumdar. A scholar is included among the top collaborators of Rwitajit Majumdar 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 Rwitajit Majumdar. Rwitajit Majumdar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 49 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 11 | |
| 8 | 18 | |
| 9 | 4 | |
| 10 | 15 | |
| 11 | 12 | |
| 12 | 10 | |
| 13 | 37 | |
| 14 | Fostering Evidence-Based Education with Learning Analytics: Capturing Teaching-Learning Cases from Log Data | 5 |
| 15 | LAView: Learning Analytics Dashboard Towards Evidence-based Education | 16 |
| 16 | Using Learning Analytics to Detect Off-Task Reading Behaviors in Class | 4 |
| 17 | 1 | |
| 18 | Learning Analytics Dashboard Widgets to Author Teaching-Learning Cases for Evidence-based Education | 7 |
| 19 | 1 | |
| 20 | 1 |
About Rwitajit Majumdar
Rwitajit Majumdar is a scholar working on Computer Science Applications, Developmental and Educational Psychology and Education, having authored 85 papers that have together received 793 indexed citations. Recurring topics across this work include Online Learning and Analytics (55 papers), Innovative Teaching and Learning Methods (23 papers) and Online and Blended Learning (20 papers). The work is most often cited by research in Computer Science Applications (394 citations), Developmental and Educational Psychology (214 citations) and Health Informatics (20 citations). Rwitajit Majumdar has collaborated with scholars based in Japan, India and Taiwan. Frequent co-authors include Hiroaki Ogata, Brendan Flanagan, Mei‐Rong Alice Chen, Gökhan Akçapınar, Sridhar Iyer, Samar Helou, Sahana Murthy, Gwo‐Jen Hwang, Juliana Elisa Raffaghelli and Dirk Ifenthaler. Their work appears in journals such as SHILAP Revista de lepidopterología, Communications of the ACM and IEEE Access.
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.