Sarah E. Schwarm
Impact in
- Artificial Intelligence top 5%
- Text Readability and Simplification
- Natural Language Processing Techniques
- Speech Recognition and Synthesis
- Topic Modeling
- Text and Document Classification Technologies
- Intelligent Tutoring Systems and Adaptive Learning
Papers in
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- Teaching and Learning Programming 2
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- Speech Recognition and Synthesis 2
- Text Readability and Simplification 1
- Co-authors
- Mari Ostendorf (3 shared papers)Tammy VanDeGrift (3 shared papers)Ivan Bulyko (1 shared paper)
- Journals
- IEEE Transactions on Speech and Audio Processing (1 paper)Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE) (1 paper)IEEE International Conference on Acoustics Speech and Signal Processing (1 paper)Annual Meeting of the Association for Computational Linguistics (ACL) (1 paper)ACM SIGCSE Bulletin (1 paper)
- Partner nations
- United States
In The Last Decade
Sarah E. Schwarm
6 papers receiving 247 citations
Peers
Comparison fields: 5 of 27
- Artificial Intelligence 232
- Computer Science Applications 8
- Developmental and Educational Psychology 20
- General Social Sciences 5
- Language and Linguistics 17
Countries citing papers authored by Sarah E. Schwarm
This map shows the geographic impact of Sarah E. Schwarm'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 Sarah E. Schwarm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sarah E. Schwarm more than expected).
Fields of papers citing papers by Sarah E. Schwarm
This network shows the impact of papers produced by Sarah E. Schwarm. 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 Sarah E. Schwarm. The network helps show where Sarah E. Schwarm may publish in the future.
Co-authors
The 3 scholars most cited alongside Sarah E. Schwarm, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 242 | |
| 2 | 2004 | 13 | |
| 3 | 2002 | 11 | |
| 4 | Using Classroom Assessment to Detect Students' Misunderstanding and Promote Metacognitive Thinking | 2002 | 5 |
| 5 | 2003 | 3 | |
| 6 | 2003 | 2 |
About Sarah E. Schwarm
Sarah E. Schwarm is a scholar working on Computer Science Applications, Artificial Intelligence, Education, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 6 papers that have together received 276 indexed citations. Recurring topics across this work include Student Assessment and Feedback (3 papers), Speech Recognition and Synthesis (2 papers), Teaching and Learning Programming (2 papers) and Text Readability and Simplification (1 paper). The work is most often cited by research in Artificial Intelligence (232 citations), Computer Science Applications (8 citations), Developmental and Educational Psychology (20 citations), General Social Sciences (5 citations) and Language and Linguistics (17 citations). Sarah E. Schwarm has collaborated with scholars based in United States. Frequent co-authors include Mari Ostendorf, Tammy VanDeGrift and Ivan Bulyko. Their work appears in journals such as IEEE Transactions on Speech and Audio Processing, Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE), IEEE International Conference on Acoustics Speech and Signal Processing, Annual Meeting of the Association for Computational Linguistics (ACL) and ACM SIGCSE Bulletin.
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.