Cristina Conati

Artificial Intelligence · 2000–2022

A researcher in the Science corpus: 5 papers; trusts 15 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it; #5,463 of 35,345 by trust here, #11,327 by citations
• Computer Science Applications — 14 citations into it
• Developmental and Educational Psychology — 11 citations into it
• Experimental and Cognitive Psychology — 8 citations into it
• Social Psychology — 8 citations into it
• Cognitive Neuroscience — 7 citations into it

Whom Cristina Conati trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Peter Brusilovsky
2. Rosalind W. Picard
3. Jennifer A. Healey
4. Judea Pearl
5. David E. Heckerman
6. P. Lachenbruch
7. Patrick Gebhard
8. Ashish Kapoor
9. João Dias
10. Ingrid Zukerman

Who trusts Cristina Conati overall

1. S. D’Mello
2. Michel C. Desmarais
3. Konstantina Chrysafiadi
4. Michelene T. H. Chi
5. A. Graesser
6. Ryan Shaun Joazeiro de Baker
7. Liping Shen
8. Guosheng Yang
9. Richard E. Mayer
10. Kurt VanLehn

Papers from Cristina Conati's perspective

Ordered by how strongly the researchers Cristina Conati trusts endorse each paper. Same corpus, a different order for every researcher.

1. Toward Machine Emotional Intelligence: Analysis of Affective Physiological State (IEEE Transactions on Pattern Analysis and Machine Intelligence)
2. Probabilistic reasoning in intelligent systems: Networks of plausible inference
3. Probabilistic reasoning in intelligent systems - networks of plausible inference
4. Probabilistic assessment of user's emotions in educational games (Applied Artificial Intelligence)
5. Multimodal affect recognition in learning environments (ACM Multimedia)
6. SmartCar: detecting driver stress (Proceedings 15th International Conference on Pattern Recognition. ICPR-2000)
7. Affect and learning: An exploratory look into the role of affect in learning with AutoTutor
8. A domain-independent framework for modeling emotion (Cognitive Systems Research)
9. Knowledge tracing: Modeling the acquisition of procedural knowledge (User modeling and user-adapted interaction)
10. Design of Experiments

Their papers

• Explainable Artificial Intelligence in education (2022) — 639 citations
• Empirically building and evaluating a probabilistic model of user affect (2009) — 364 citations
• Probabilistic assessment of user's emotions in educational games (2002) — 575 citations
• Using Bayesian Networks to Manage Uncertainty in Student Modeling (2002) — 572 citations
• Toward Computer-Based Support of Meta-Cognitive Skills: a Computational Framework to Coach Self-Explanation (2000) — 310 citations