When adaptive learning is effective learning: comparison of an adaptive learning system to teacher-led instruction

ABSTRACT

Adaptive learning systems personalize instruction to students’ individual learning needs and abilities. Such systems have shown positive impacts on learning. Many schools in the United States have adopted adaptive learning systems, and the rate of adoption in China is accelerating, reaching almost 2 million unique users for one product alone in the past 3 years. Given such rapid adoption in China, it is useful to examine the efficacy of adaptive learning within that country’s educational system. This study aimed to compare the learning impacts of individualized adaptive learning courseware to two common instructional approaches in China: large-group and small-group classroom instruction. This paper describes the results of two efficacy studies of one of China’s first adaptive learning systems, Squirrel AI Learning. One study compares classroom-based individualized adaptive learning instruction to large-group instruction, and another to small-group instruction. Chinese eighth-grade students from two provinces randomly assigned to use Squirrel AI Learning showed greater gains on a mathematics test than those randomly assigned to whole-class or small-group instruction led by expert teachers. Findings provide a basis for further research into the selection, use, and impact of adaptive learning systems in Chinese education.

KEYWORDS:

• Artificial intelligence
• adaptive learning system
• efficacy study
• mathematics education

Disclosure statement

No potential conflict of interest was reported by the author(s). In addition, the authors have taken steps to protect research participants, ensuring that they were not disadvantaged, and that the data were anonymized prior to analysis.

Additional information

Funding

This work was supported by Squirrel AI Learning by Yixue Education Group.

Notes on contributors

Shuai Wang

Shuai Wang, Ph.D., an education researcher at SRI International (previously known as Stanford Research Institute), has extensive experience in developing and evaluating diverse digital STEM education approaches, and specializes in research planning and statistical modeling in evaluations of education interventions. Dr. Wang has served as Principal Investigator, Co-Principal Investigator, and senior personnel for a large number of research projects, including studies funded by U.S. National Science Foundation (NSF) and U.S. Department of Education. His STEM education work has led to many top-tier journal publications, book chapters, and conference presentations. These have resulted in global media coverage, including the U.S. National Science Foundation homepage.

Claire Christensen

Claire Christensen, Ph.D., is a senior education researcher at SRI International. She leads quantitative and mixed methods research on the use of media and technology to support children's learning.

Wei Cui

Wei Cui, Ph.D., is a co-founder and Chief Scientist of Squirrel AI Learning by Yixue Education Group, the leading AI and adaptive education innovator for K-12 students in China. He led the development of Squirrel AI’s intelligent adaptive learning system, and has published over 20 peer-reviewed academic papers and articles in AI, agent-based modeling, complex adaptive system, quantitative finance and AI education. He was awarded MIT Technology Review "35 Innovators Under 35 China” in 2018.

Richard Tong

Richard Tong, M.A., is the Chief Architect of Squirrel AI Learning by Yixue Education Group and the Chair of IEEE Learning Technology Standard Committee, 2020-2021. He is an experienced technologist, executive, entrepreneur and one of the leading evangelists for standardization effort for global education technology.

Louise Yarnall

Louise Yarnall, Ph.D., is a senior research social scientist in SRI Education with expertise in the evaluation and design of adaptive learning products. She uses learning science to improve instruction around college and career readiness and to support research and development of new forms of workforce learning technologies.

Linda Shear

Linda Shear, M.A., is the Director of Commercial and International Strategy in SRI Education. Shear’s research and consulting work focuses on systemic educational change and powerful uses of ICT (information and communications technology) to support deeper learning for all students.

Mingyu Feng

Mingyu Feng, Ph.D., is a Senior Research Associate with the Science, Technology, Engineering, & Mathematics (STEM) program at WestEd, and has strong expertise in the design, development and research of technology-supported learning systems, and rigorous evaluation of impact of educational technologies on learning. She is also an expert in educational data mining and learning analytics, with extensive experience in analyzing usage data from different kind of learning systems and leveraging analytics to monitor implementation fidelity.