Stephen E. Fancsali
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Stephen E. Fancsali has a total of 70 co-authors. Here are the top co-authors by number of shared publications:
- Steve Ritter
Carnegie Learning, Pittsburgh, USA
16 shared publications - April Murphy
Carnegie Learning, Pittsburgh, USA
7 shared publications - Husni Almoubayyed
Carnegie Learning
5 shared publications - Abisha Thapa Magar
University of Memphis
4 shared publications - Deepak Venugopal
University of Memphis
4 shared publications - Emma Brunskill
Computer Science, Stanford University, Stanford, California, USA
4 shared publications
Latest Publications
- 7 October 2026
- Published by Springer Nature
- p. 209-223
Dosage and Dialogue: Understanding Human Support in Hybrid Human-AI Math Tutoring
- 7 October 2026
- Published by Springer Nature
- p. 209-223
Dosage and Dialogue: Understanding Human Support in Hybrid Human-AI Math Tutoring
- 27 June 2026
- Published by Springer Nature
- p. 327-336
Using an MR-Based Teacher Orchestration Tool in AI-Supported K-12 Classrooms
- 27 June 2026
- Published by Springer Nature
- p. 327-336
Using an MR-Based Teacher Orchestration Tool in AI-Supported K-12 Classrooms
- Open Access
- 26 April 2026
- Published by Association for Computing Machinery (ACM)
- p. 457-468
Understanding and Modeling Math Strategy Use in Intelligent Tutoring Systems
- 26 April 2026
- Published by Association for Computing Machinery (ACM)
- p. 457-468
Open AccessUnderstanding and Modeling Math Strategy Use in Intelligent Tutoring Systems
- 5 November 2025
- Published by Taylor & Francis
- p. 245-258
Personalized Learning in Mathematics
Personalized learning presents both opportunities and challenges in the domain of mathematics. In this chapter, we consider approaches to personalization, distinguishing between personalization focused on learning and motivation goals. We present a framework for thinking about the impact of personalization and provide some practical guidance for developing personalized learning in the domain of mathematics. Our framework considers personalization based on prior and developing knowledge to select tasks or problems in adaptive mathematics software as well as personalization to promote students’ interest, autonomy, and choice as they work with content in such software. Examples are drawn from Carnegie Learning's MATHia, an intelligent tutoring system that is used by hundreds of thousands of learners across the United States every year as a part of their middle school and high school mathematics instruction.
- 5 November 2025
- Published by Taylor & Francis
- p. 245-258
Personalized Learning in Mathematics
Personalized learning presents both opportunities and challenges in the domain of mathematics. In this chapter, we consider approaches to personalization, distinguishing between personalization focused on learning and motivation goals. We present a framework for thinking about the impact of personalization and provide some practical guidance for developing personalized learning in the domain of mathematics. Our framework considers personalization based on prior and developing knowledge to select tasks or problems in adaptive mathematics software as well as personalization to promote students’ interest, autonomy, and choice as they work with content in such software. Examples are drawn from Carnegie Learning's MATHia, an intelligent tutoring system that is used by hundreds of thousands of learners across the United States every year as a part of their middle school and high school mathematics instruction.
- 21 July 2025
- Published by Springer Nature
- p. 356-363
Exploring Student Identity in Adaptive Learning Systems Through Qualitative Data
- 21 July 2025
- Published by Springer Nature
- p. 356-363
Exploring Student Identity in Adaptive Learning Systems Through Qualitative Data
- Open Access
- 17 July 2025
- Published by Association for Computing Machinery (ACM)
- p. 407-409
Sixth Annual Workshop on A/B Testing and Platform-Enabled Learning Engineering (PELE)
- 17 July 2025
- Published by Association for Computing Machinery (ACM)
- p. 407-409
Open AccessSixth Annual Workshop on A/B Testing and Platform-Enabled Learning Engineering (PELE)
- Open Access
- 3 March 2025
- Published by Association for Computing Machinery (ACM)
- p. 631-641
Predicting Long-Term Student Outcomes from Short-Term EdTech Log Data
- 3 March 2025
- Published by Association for Computing Machinery (ACM)
- p. 631-641
Open AccessPredicting Long-Term Student Outcomes from Short-Term EdTech Log Data