Kate Forbes-Riley

1.4k citations
24 papers · 676 indexed · h-index 14
Topics
Intelligent Tutoring Systems and Adaptive Learning (22 papers)Speech and dialogue systems (19 papers)Topic Modeling (14 papers)
Partner nations
United States

In The Last Decade

Kate Forbes-Riley

24 papers receiving 603 citations

Peers

Kate Forbes-Riley
Comparison fields: 5 of 52
  • Artificial Intelligence 556
  • Experimental and Cognitive Psychology 202
  • Developmental and Educational Psychology 150
  • Computer Science Applications 101
  • Social Psychology 88
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Countries citing papers authored by Kate Forbes-Riley

Since Specialization
Citations

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

Fields of papers citing papers by Kate Forbes-Riley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kate Forbes-Riley. 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 Kate Forbes-Riley. The network helps show where Kate Forbes-Riley may publish in the future.

Co-authorship network of co-authors of Kate Forbes-Riley

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2
Adapting to Multiple Affective States in Spoken Dialogue
21
3 4
4
Using Performance Trajectories to Analyze the Immediate Impact of User State Misclassification in an Adaptive Spoken Dialogue System
1
5
Improving (Meta)Cognitive Tutoring by Detecting and Responding to Uncertainty.
3
6 7
7 7
8 49
9
Comparing Linguistic Features for Modeling Learning in Computer Tutoring
9
10 45
11 9
12 34
13 52
14 1
15 17
16
Dialogue-Learning Correlations in Spoken Dialogue Tutoring
22
17 26
18 27
19 80
20
Annotating Student Emotional States in Spoken Tutoring Dialogues
24

About Kate Forbes-Riley

Kate Forbes-Riley is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology and Developmental and Educational Psychology, having authored 24 papers that have together received 676 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (22 papers), Speech and dialogue systems (19 papers) and Topic Modeling (14 papers). The work is most often cited by research in Computer Science Applications (101 citations), Artificial Intelligence (556 citations) and Experimental and Cognitive Psychology (202 citations). Kate Forbes-Riley has collaborated with scholars based in United States. Frequent co-authors include Diane Litman, Mihai Rotaru, Joel Tetreault, Amruta Purandare, Hua Ai, Alison K. Huettner, Kurt VanLehn, Scott Silliman, Carolyn Penstein Rosé and Dumisizwe Bhembe. Their work appears in journals such as Speech Communication, Computer Speech & Language and User Modeling and User-Adapted Interaction.

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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