Pamela Jordan

2.7k total citations
67 papers, 1.3k citations indexed

About

Pamela Jordan is a scholar working on Artificial Intelligence, Developmental and Educational Psychology and Computer Science Applications. According to data from OpenAlex, Pamela Jordan has authored 67 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Artificial Intelligence, 15 papers in Developmental and Educational Psychology and 8 papers in Computer Science Applications. Recurrent topics in Pamela Jordan's work include Intelligent Tutoring Systems and Adaptive Learning (37 papers), Speech and dialogue systems (24 papers) and Topic Modeling (22 papers). Pamela Jordan is often cited by papers focused on Intelligent Tutoring Systems and Adaptive Learning (37 papers), Speech and dialogue systems (24 papers) and Topic Modeling (22 papers). Pamela Jordan collaborates with scholars based in United States, United Kingdom and Switzerland. Pamela Jordan's co-authors include Kurt VanLehn, Carolyn Penstein Rosé, Arthur C. Graesser, Barbara Di Eugenio, Derek Harter, Andrew M. Olney, G. Tanner Jackson, Marilyn Walker, Diane Litman and Min Chi and has published in prestigious journals such as Physics Today, Computer and Cognitive Science.

In The Last Decade

Pamela Jordan

65 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Pamela Jordan United States 18 1.1k 418 282 123 96 67 1.3k
Erin Shaw United States 13 451 0.4× 231 0.6× 120 0.4× 114 0.9× 116 1.2× 35 779
Philip I. Pavlik United States 13 698 0.6× 366 0.9× 462 1.6× 96 0.8× 92 1.0× 48 998
Anna N. Rafferty United States 14 457 0.4× 222 0.5× 211 0.7× 64 0.5× 200 2.1× 49 924
Richard R. Burton United States 12 831 0.8× 442 1.1× 217 0.8× 112 0.9× 332 3.5× 21 1.4k
Erin Walker United States 17 324 0.3× 352 0.8× 227 0.8× 69 0.6× 157 1.6× 70 822
Ivon Arroyo United States 16 623 0.6× 515 1.2× 549 1.9× 148 1.2× 194 2.0× 53 1.1k
Joseph E. Beck United States 18 769 0.7× 322 0.8× 583 2.1× 53 0.4× 120 1.3× 57 1.1k
John Stamper United States 16 665 0.6× 431 1.0× 778 2.8× 66 0.5× 188 2.0× 66 1.2k
Paul Brna United Kingdom 17 249 0.2× 337 0.8× 151 0.5× 107 0.9× 277 2.9× 69 845
Malcolm Bauer United States 11 288 0.3× 184 0.4× 86 0.3× 89 0.7× 118 1.2× 30 643

Countries citing papers authored by Pamela Jordan

Since Specialization
Citations

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

Fields of papers citing papers by Pamela Jordan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pamela Jordan. 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 Pamela Jordan. The network helps show where Pamela Jordan may publish in the future.

Co-authorship network of co-authors of Pamela Jordan

This figure shows the co-authorship network connecting the top 25 collaborators of Pamela Jordan. A scholar is included among the top collaborators of Pamela Jordan 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 Pamela Jordan. Pamela Jordan 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
1.
Katz, Sandra, et al.. (2021). Linking Dialogue with Student Modelling to Create an Adaptive Tutoring System for Conceptual Physics. International Journal of Artificial Intelligence in Education. 31(3). 397–445. 20 indexed citations
2.
Chounta, Irene‐Angelica, et al.. (2017). Modeling the Zone of Proximal Development with a Computational Approach.. Educational Data Mining. 4 indexed citations
3.
Jordan, Pamela, et al.. (2015). Shifting the Load: a Peer Dialogue Agent that Encourages its Human Collaborator to Contribute More to Problem Solving. International Journal of Artificial Intelligence in Education. 27(1). 101–129. 32 indexed citations
4.
Jordan, Pamela, et al.. (2013). Eliciting student explanations during tutorial dialogue for the purpose of providing formative feedback.. 3 indexed citations
5.
Litman, Diane, et al.. (2011). Predicting Changes in Level of Abstraction in Tutor Responses to Students. D-Scholarship@Pitt (University of Pittsburgh). 3 indexed citations
6.
Katz, Sandra, Pamela Jordan, & Diane Litman. (2011). Rimac: A Natural-Language Dialogue System that Engages Students in Deep Reasoning Dialogues about Physics.. Society for Research on Educational Effectiveness. 1 indexed citations
7.
Eugenio, Barbara Di, et al.. (2010). KSC-PaL: A Peer Learning Agent that Encourages Students to take the Initiative. North American Chapter of the Association for Computational Linguistics. 17–20. 4 indexed citations
8.
Chi, Min, et al.. (2008). Reinforcement Learning-based Feature Seleciton For Developing Pedagogically Effective Tutorial Dialogue Tactics.. Educational Data Mining. 258–265. 17 indexed citations
9.
VanLehn, Kurt, et al.. (2007). Natural Language Tutoring: A comparison of human tutors, computer tutors, and text. Cognitive Science. 31(1). 10 indexed citations
10.
Jordan, Pamela, et al.. (2006). A natural language tutorial dialogue system for physics. The Florida AI Research Society. 521–526. 34 indexed citations
11.
Makatchev, Maxim, et al.. (2006). Representation and Reasoning for Deeper Natural Language Understanding in a Physics Tutoring System. North-Eastern Hill University Library (North Eastern Hill University). 682–687. 1 indexed citations
12.
Bhembe, Dumisizwe, et al.. (2005). A Multi-Tier NL-Knowledge Clustering for Classifying Students' Essays. North-Eastern Hill University Library (North Eastern Hill University). 566–571. 5 indexed citations
13.
Graesser, Art, G. Tanner Jackson, Pamela Jordan, et al.. (2005). When is Reading Just as Effective as One-on-One Interactive Human Tutoring?. eScholarship (California Digital Library). 27(27). 13 indexed citations
14.
Makatchev, Maxim, et al.. (2004). Abductive Proofs as Models of Students' Reasoning about Qualitative Physics.. 166–171. 1 indexed citations
15.
Jordan, Pamela. (2004). Using Student Explanations as Models for Adapting Tutorial Dialogue.. The Florida AI Research Society. 905–910. 6 indexed citations
16.
Graesser, Arthur C., Kurt VanLehn, Carolyn Penstein Rosé, Pamela Jordan, & Derek Harter. (2001). Intelligent tutoring systems with conversational dialogue. AI Magazine. 22(4). 39–51. 232 indexed citations
17.
Jordan, Pamela. (2000). Influences on Attribute Selection in Redescriptions: A Corpus Study. eScholarship (California Digital Library). 22(22). 7 indexed citations
18.
Jordan, Pamela. (1999). An Empirical Study of the Communicative Goals Impacting Nominal Expressions. 4 indexed citations
19.
Jordan, Pamela, et al.. (1996). Deciding to remind during collaborative problem solving: empirical evidence for agent strategies. National Conference on Artificial Intelligence. 16–23. 6 indexed citations
20.
Jordan, Pamela, et al.. (1990). Yellow bar markings: their design and effect on driver behaviour. 15(7). 3 indexed citations

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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