Improving Teaching at Scale: Can AI Be Incorporated Into Professional Development to Create Interactive, Personalized Learning for Teachers?

Oct 15, 2026

Scalable and accessible professional development is critical for reducing the opportunity gap teachers face, yet many asynchronous online programs provide insufficient interaction and delayed or limited feedback. The study developed a virtual interactive program using intelligent tutoring systems to deliver just-in-time support to teachers. A randomized controlled trial assigned U.S. teachers to either the AI-based program or no additional training. Teachers who completed the program produced more mathematically rich tasks and generated more coherent, connected learning environments.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages36

Reading Time1 h 31 min

AccessFree to download

Introduction

Interactive, Personalized Learning for Teachers

American Educational Research Journal August 2024, Vol. 61, No. 4, pp. 767–802 DOI: 10.3102/00028312241248514 Article reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions) 􀀂 2024 AERA. [https://journals.sagepub.com/home/aer](https://journals.sagepub.com/home/aer) Improving Teaching at Scale: Can AI Be Incorporated Into Professional Development to Create Interactive, Personalized Learning for Teachers? Yasemin Copur-Gencturk Jingxian Li University of Southern California Sebnem Atabas University of Saint Joseph Scalable and accessible professional development programs have the potential to address the opportunity gap many teachers experience. Yet many asynchronous online programs lack interaction with and timelyfeedback to teachers. We addressed this problem by developing a virtual, interactive program that uses intelligent tutoring systems to provide just-in-time feedback to teachers. We conducted a randomized controlled trial with teachers across the United States in which teachers were assigned to either this program or no additional training. We found that teachers who completed our program (N = 29) used mathematically richer tasks and created a more coherent, connected learning YASEMIN COPUR-GENCTURK is an associate professor in the Rossier School of Education atthe University of Southern California, 904G Waite Phillips Hall 3470 Trousdale Parkway, Los Angeles, CA 90089; e-mail: [copurgen@usc.edu](copurgen@usc.edu. Her)[. Her](copurgen@usc.edu. Her) research aims to identify ways to improve mathematics teaching and learning. Her work focuses on teachers’ mathematical expertise and its development as well as the ways in which implicit bias occurs in mathematics classrooms. JINGXIAN LI is a PhD candidate in the Rossier School of Education at the University of Southern California; e-mail: [lijingxi@usc.edu](lijingxi@usc.edu. Her)[. Her](lijingxi@usc.edu. Her) research seeks to expand students’access to high-quality mathematics learning opportunities through improving the quality of current teacher workforce. Her work focuses on identifying and measuring teaching expertise needed for high-quality instruction, as well as understanding how teachers develop teaching expertise through their own teaching practice and in technology-enhanced learning environments. SEBNEM ATABAS is an assistant professor of mathematics education at the University of Saint Joseph; e-mail: [satabas@usj.edu](satabas@usj.edu. Her)[. Her](satabas@usj.edu. Her) research focuses on conceptualization of what a rich learning environment requires teachers to accomplish in mathematics classrooms, how to challenge already established instructional practices aligned with a traditional approach, and mechanisms of teacher learning and teacher change to position students to engage in mathematical thinking in meaningful ways. Copur-Gencturk et al. environmentfor students to build conceptual understandings than did teachers who were in the business-as-usual condition (N = 23) . KEYWORDS: mathematics education, teacher learning, instruction, randomized controlled trial, ratios and proportional relationships, teacher knowledge, teacher content knowledge, teacher pedagogical content knowledge, teacher professional development Introduction Professional development (PD) programs have been considered a key strategy for equipping teachers with the knowledge and skills to improve their students’ learning experiences (Ball & Cohen, 1999; Cohen & Hill, 2000; Copur-Gencturk, Plowman, & Bai, 2019) . Although there is evidence that some PD programs are effective in improving teachers’ knowledge (e.g. , Copur-Gencturk, Plowman, & Bai, 2019; Garet et al.,2016; Jacobs et al. , 2007), instructional practices (e.g., Boston & Smith, 2011; Garet et al., 2016; Jacobs et al., 2007; Kraft & Blazar, 2017), and student learning outcomes (e.g., Campbell & Malkus, 2011; Lewis & Perry, 2017; McMeeking et al. , 2012; Roschelle et al.,

FAQs

What problem does the study address in teacher professional development?

It targets the lack of interaction and timely feedback in many asynchronous online PD programs.

How was the proposed solution implemented?

The program used intelligent tutoring systems to provide just-in-time feedback in a virtual, interactive format.

How were teachers assigned in the randomized controlled trial?

Teachers were assigned to either complete the AI-based interactive program or receive no additional training.

Oct 15, 2026

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