A quasi-experimental study on the influence of different media scaffolds toward physics problem-solving processes

ABSTRACT

Physics is a subject requiring strong logical thinking, and writing a problem-solving path according to logical thinking can enhance students’ knowledge and problem-solving ability. The purpose of the study was to explore the effects of problem presentation of different scaffolds (MAPS or dynamic figures) on students’ physical problem solving. MAPS scaffold is a modeling applied to problem-solving pedagogy. The study adopts a quasi-experimental design, as participants were divided into four groups tested under different scaffolds. These groups are Traditional group (problems with static figures), MAPS group (MAPS combined with static figures), Dynamic Figure group (problems with dynamic figures), and MAPS + Dynamic Figure group (MAPS combined with dynamic figures). The results indicated that the students assisted by MAPS could more effectively describe and interpret key concepts and knowledge in questions, and they selected formulas appropriately according to the physics conditions. However, the findings did not reveal any significant difference between the dynamic figure. Thus, we will explore dynamic figures in different types of physics questions in future research, so that dynamic figures can be more effectively used by students for physics problem-solving.

KEYWORDS:

• Scaffold
• animation
• question representation
• MAPS
• physics problem-solving

Acknowledgement

I would like to express my sincere gratitude to Prof. David E. Pritchard for giving the valuable discussions and revised suggestions. Prof. Guangtian Zhu and Xiaoling Su contributed equally to this work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Guangtian Zhu

Guangtian Zhu is an associate professor in the Department of College of Teacher Education at East China Normal University, China. His research focuses on physics education research (RER), investigating students’ common difficulties in learning advanced physics courses. E-mail: [email protected].

Xiaoling Su

Xiaoling Su is a postgraduate in the Department of Educational Technology at Shanghai Normal University, China. Her research focused on information technology discipline innovation integration, mainly in the physical education. E-mail:[email protected]

Juan Du

Du Juan is a postgraduate in the Department of Educational Technology at Shanghai Normal University, China. Her research focused on STEM education, educational game development and application. E-mail:[email protected]

Qingwei Chen

Qingwei Chen is a graduate student in the Department of College of Teacher Education at East China Normal University, China. His research focuses on physics education research (RER). E-mail: [email protected].

Bolong Xiong

Bolong Xiong is from industrial and systems engineering department at Lehigh University, his research focuses on optimization, mathematical modeling and machine learning. E-mail:[email protected].

Feng-Kuang Chiang

Feng-Kuang Chiang is a distinguished professor and director in the Department of Educational Technology at Shanghai Normal University, China. His research focused on STEM education, learning space and integration of information technology and curriculum. E-mail:[email protected].