Lisa M. Rossi
- Artificial Intelligence top 10%
- Computer Science Applications top 2%
- Developmental and Educational Psychology top 10%
- Education
- Experimental and Cognitive Psychology
- Co-authors
- Ryan S. BakerSujith M. GowdaMichael WixonVincent AlevenJaclyn OcumpaughAngela Z. WagnerMa. Mercedes T. RodrigoArnon Hershkovitz
- Topics
- Intelligent Tutoring Systems and Adaptive Learning (6 papers)Online Learning and Analytics (4 papers)Innovative Teaching and Learning Methods (3 papers)
- Cited by
- Computer Science ApplicationsDevelopmental and Educational PsychologyArtificial Intelligence
- Journals
- Teachers College Record The Voice of Scholarship in EducationJournal of the Learning SciencesInternational Journal of Artificial Intelligence in Education
- Partner nations
- United StatesJapan
In The Last Decade
Lisa M. Rossi
6 papers receiving 175 citations
Peers
Comparison fields: 5 of 34
- Artificial Intelligence 129
- Computer Science Applications 126
- Developmental and Educational Psychology 89
- Education 36
- Experimental and Cognitive Psychology 26
Countries citing papers authored by Lisa M. Rossi
This map shows the geographic impact of Lisa M. Rossi'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 Lisa M. Rossi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lisa M. Rossi more than expected).
Fields of papers citing papers by Lisa M. Rossi
This network shows the impact of papers produced by Lisa M. Rossi. 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 Lisa M. Rossi. The network helps show where Lisa M. Rossi may publish in the future.
Co-authorship network of co-authors of Lisa M. Rossi
This figure shows the co-authorship network connecting the top 25 collaborators of Lisa M. Rossi. A scholar is included among the top collaborators of Lisa M. Rossi 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 Lisa M. Rossi. Lisa M. Rossi 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 | 11 | |
| 3 | 28 | |
| 4 | 32 | |
| 5 | Towards Sensor-Free Affect Detection in Cognitive Tutor Algebra. | 101 |
| 6 | Sensor-free automated detection of affect in a Cognitive Tutor for Algebra. | 23 |
About Lisa M. Rossi
Lisa M. Rossi is a scholar working on Computer Science Applications, Developmental and Educational Psychology and Artificial Intelligence, having authored 6 papers that have together received 197 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (6 papers), Online Learning and Analytics (4 papers) and Innovative Teaching and Learning Methods (3 papers). The work is most often cited by research in Computer Science Applications (126 citations), Developmental and Educational Psychology (89 citations) and Artificial Intelligence (129 citations). Lisa M. Rossi has collaborated with scholars based in United States and Japan. Frequent co-authors include Ryan S. Baker, Sujith M. Gowda, Michael Wixon, Vincent Aleven, Jaclyn Ocumpaugh, Angela Z. Wagner, Ma. Mercedes T. Rodrigo, Arnon Hershkovitz, Albert T. Corbett and William L. Miller. Their work appears in journals such as Teachers College Record The Voice of Scholarship in Education, Journal of the Learning Sciences and International Journal of Artificial Intelligence in Education.
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.