Metacognitive Calibration and Student Performance in Adaptive Learning


Prior research suggests that average students performed significantly better in one-on-one learning situation than in a conventional classroom, because the instructor can personalize the course to fit student needs based on their strengths and weakness. To achieve similar outcomes, we have adopted an adaptive learning system which adjusts the course contents and testing questions based on student performance and engagement level. As the literature has found that metacognitive calibration can predict actual learning performance accurately, we collected metacognition and performance data from over 600 college students in the introductory information systems courses. The preliminary findings show that students who receive passing vs. non-passing grades are affected differently by metacognitive calibration in adaptive learning assignments. The results imply that the instructors should shift their focus on “what are students learning” to “how are they learning,” especially for underprepared students. Other than teaching the course contents, the instructors should explicitly teach students how to become more metacognitive even though adaptive learning is adopted.


Adaptive Learning, Metacognitive Calibration, Learning Outcomes


Technologies in Learning


Poster/Exhibit Session


  • Lin Zhao Zhao
    • Associate Professor, College of Business, Purdue University
    • Dr. Lin Zhao is an Associate Professor of Management Information Systems in the College of Business at Purdue University Northwest. Her present research focuses on IT-enabled organizational change, Human-Computer Interaction (HCI), and e-Learning. She is also interested in the application of Neural Networks and expert systems to time-series forecasting and data mining. She has published her research in Academy of Information and Management Sciences Journal, Review of Business Information Systems, Journal of Technology Research, and the Journal of American Business Review, International Journal of Education Research, and Academy of Educational Leadership Journal. She serves as an editorial review board member of Academy of Information and Management Sciences Journal, Journal of Organizational Culture, Communications and Conflict, and International Journal of e-Education, e-Business, e-Management and e-Learning. Dr. Zhao received her Ph.D. in Management with specialization in Information Systems from Case Western Reserve University in 2008. She also holds a B.E. in Systems Engineering and a M.Ec. in Quantitative Economics and Management from Tianjin University, China.