Natalie B. Steinhauser

14 papers receiving 174 citations

Peers

Natalie B. Steinhauser
Comparison fields: 5 of 48
  • Artificial Intelligence 138
  • Developmental and Educational Psychology 46
  • Computer Science Applications 45
  • Information Systems 23
  • Social Psychology 20
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Countries citing papers authored by Natalie B. Steinhauser

Since Specialization
Citations

This map shows the geographic impact of Natalie B. Steinhauser'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 Natalie B. Steinhauser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalie B. Steinhauser more than expected).

Fields of papers citing papers by Natalie B. Steinhauser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Natalie B. Steinhauser. 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 Natalie B. Steinhauser. The network helps show where Natalie B. Steinhauser may publish in the future.

Co-authorship network of co-authors of Natalie B. Steinhauser

This figure shows the co-authorship network connecting the top 25 collaborators of Natalie B. Steinhauser. A scholar is included among the top collaborators of Natalie B. Steinhauser 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 Natalie B. Steinhauser. Natalie B. Steinhauser is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
1 5
2 73
3 2
4 6
5 20
6
Beetle II: an adaptable tutorial dialogue system
7
7
Exploring User Satisfaction in a Tutorial Dialogue System
11
8
Beetle II: A System for Tutoring and Computational Linguistics Experimentation
30
9
SUSTAINING TEL: FROM INNOVATION TO LEARNING AND PRACTICE
1
10
The Impact of Interpretation Problems on Tutorial Dialogue
4
11
Metacognitive Awareness versus Linguistic Politeness: Expressions of Confusion in Tutorial Dialogues
2
12 10
13 12
14
Diagnosing natural language answers to support adaptive tutoring
10

About Natalie B. Steinhauser

Natalie B. Steinhauser is a scholar working on Developmental and Educational Psychology, Computer Science Applications and Artificial Intelligence, having authored 14 papers that have together received 193 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (9 papers), Innovative Teaching and Learning Methods (5 papers) and Speech and dialogue systems (4 papers). The work is most often cited by research in Computer Science Applications (45 citations), Artificial Intelligence (138 citations) and Developmental and Educational Psychology (46 citations). Natalie B. Steinhauser has collaborated with scholars based in United States, United Kingdom and Israel. Frequent co-authors include Gwendolyn E. Campbell, Johanna D. Moore, Myroslava O. Dzikovska, Elaine Farrow, Charles Callaway, Peter A. Hancock, Davin Pavlas, Peter Bell, Matthew Lineberry and Colin Matheson. Their work appears in journals such as International Journal of Artificial Intelligence in Education, Military Psychology and Ergonomics in Design The Quarterly of Human Factors Applications.

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.

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