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Applying Deliberate Practice to Facilitate Schema Acquisition in Learning Introductory Mechanics

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2021 ASEE Virtual Annual Conference Content Access


Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

NSF Grantees Poster Session

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NSF Grantees Poster Session

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Paper Authors


Yan Tang Embry-Riddle Aeronautical University - Daytona Beach Orcid 16x16

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Dr. Yan Tang is an associate professor of mechanical engineering at Embry-Riddle Aeronautical University in Daytona Beach, Fla. Her current research in engineering education focuses on cognitive load theory, deliberate practice, and effective pedagogical practices. Her background is in dynamics and controls.

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Haiyan Bai University of Central Florida

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Haiyan Bai, PhD., is Professor of Quantitative Research Methodology in the College of Community Innovation and Education at the University of Central Florida. Her interests include resampling method, propensity score analysis, research design, measurement and evaluation, and the applications of statistical methods in educational research and behavioral sciences. She is actively involved educational and social science research projects. Dr. Bai has published books and many professional articles in refereed national and international journals. She has won several competitive awards at the University of Central Florida for her excellent teaching and research. Dr. Bai also served on several professional journal editorial boards, such as Journal of Experimental Education, Frontiers in Quantitative Psychology and Measurement, and Journal of Data Analysis and Information Processing. She is also the Fellow of the Academy for Teaching, Learning, and Leadership and the Faculty Fellow at the University of Central Florida.

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Richard Catrambone Georgia Institute of Technology Orcid 16x16

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Richard Catrambone is a Professor in the School of Psychology at the Georgia Institute of Technology. He received his B.A. from Grinnell College and his Ph.D. in Experimental Psychology from the University of Michigan.

The question Catrambone likes to ask--and the thread that runs through the projects he does alone and in collaboration with others--is: What does someone need to know in order to solve novel problems or carry out tasks within a particular domain?

Catrambone’s research interests include problem solving, educational technology, and human-computer interaction. He is particularly interested in how people learn from examples in order to solve problems in domains such as algebra, probability, and physics. He explores how to create instructional materials that help learners understand how to approach problems in a meaningful way rather than simply memorizing a set of steps that cannot easily be transferred to novel problems. He researches the design of teaching and training materials--including software and multimedia environments--based on cognitive principles that help students learn basic tasks quickly and promote transfer to novel problems. He uses task analysis to identify what someone needs to know in order to solve problems or carry out tasks in a domain and then to use the results of the task analysis to guide the construction of teaching and training materials/environments.

Catrambone has served on the Cognitive Science Society governing board from 2011-2016 and was chair of the Society in 2015. He was co-chair of the Cognitive Science Conference in 2010. He has served as a consulting editor for the Journal of Educational Psychology (1/2008 - 12/2011), the Journal of Experimental Psychology: Learning, Memory, and Cognition (6/2000 - 12/2001 and 1/2009 - 12/2009), the Journal of Experimental Psychology: Applied (1/2001 - 12/2007), and the Journal of Experimental Psychology: General (6/2000 - 12/2001). He has published his research in journals such as the Journal of Experimental Psychology: General; Journal of Experimental Psychology: Learning, Memory, and Cognition; Journal of Experimental Psychology: Applied; Memory & Cognition; Journal of Educational Psychology; Human-Computer Interaction; Human Factors; and other basic and applied journals. He has also served on grant review panels for a variety of funding agencies including the National Science Foundation and the Institute of Education Sciences (U.S. Department of Education).

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Learning is usually conceptualized as a process during which new information is processed in working memory to form knowledge structures called schemas, which are stored in long-term memory. Practice plays a critical role in developing schemas through learning-by-doing. Contemporary expertise development theories have highlighted the influence of deliberate practice (DP) on achieving exceptional performance in sports, music, and different professional fields. Concurrently, there is an emerging method for improving learning efficiency by combining deliberate practice with cognitive load theory (CLT), a cognition-architecture-based theory for instructional design.

Mechanics is a foundation for most branches of engineering. It serves to develop problem-solving skills and consolidate understanding of other subjects, such as applied mathematics and physics. Mechanics has been a challenging subject. Students need to understand governing principles to gain conceptual knowledge and acquire procedural knowledge to apply these principles to solve problems. Due to the difficulty in developing conceptual and procedural knowledge, mechanics courses are among those which receive high DFW rates (percentage of students receiving a grade of D or F or Withdrawing from a course) and students are more likely to leave engineering after taking mechanics courses. Since deliberate practice can help novices develop good representations of the knowledge needed to produce superior problem solving performance, this study is to evaluate how deliberate practice helps students learn mechanics during the process of schema acquisition and consolidation. Considering cognitive capacity limitations, we will apply cognitive load theory to develop deliberate practice to help students build declarative and procedural knowledge without exceeding their working memory limitations.

We will evaluate the effects of three practice strategies based on CLT on the schema acquisition and consolidation in two mechanics courses (i.e., Statics and Dynamics). Examples and assessment results will be provided to evaluate the effectiveness of the practice strategies as well as the challenges.

Tang, Y., & Bai, H., & Catrambone, R. (2021, July), Applying Deliberate Practice to Facilitate Schema Acquisition in Learning Introductory Mechanics Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36691

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