Asee peer logo

Evaluating the Effects of Highlighting Text Animations on the Attention Distribution of Students with Math Learning Difficulties

Download Paper |


2018 ASEE Annual Conference & Exposition


Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

COED: Online and Blended Learning Part 2

Tagged Division

Computers in Education

Tagged Topic


Page Count




Permanent URL

Download Count


Request a correction

Paper Authors


Shuang Wei Purdue University, West Lafayette

visit author page

Shuang Wei is a Ph.D. student in the department of Computer Graphics Technology, Purdue University. She received her Master of Science degree from the same major and a Bachelor degree in digital media from Harbin Institute of Technology (China). Her research focuses on information visualization, human-computer interaction, and multimedia education.

visit author page

author page

Qingli Lei Purdue University, West Lafayette


Yingjie Chen Purdue University, West Lafayette

visit author page

Dr. Yingjie Chen is an assistant professor in the Department of Computer Graphics Technology of Purdue University. He received his Ph.D. degree in the areas of human-computer interaction, information visualization, and visual analytics from the School of Interaction Arts and Technology at Simon Fraser University (SFU) in Canada. He earned the Bachelor degree of Engineering from the Tsinghua University in China, and a Master of Science degree in Information Technology from SFU. His research covers interdisciplinary domains of information visualization, visual analytics, digital media, and human computer interaction. He seeks to design, model, and construct new forms of interaction in visualization and system design, by which the system can minimize its influence on design and analysis, and become a true free extension of human’s brain and hand.

visit author page


Yan Ping Xin Purdue University, West Lafayette

visit author page

Dr. Yan Ping Xin is a Professor in the Department of Educational Studies at Purdue University. Her research interests include effective instructional strategies in mathematics problem solving, algebra readiness, and computer-assisted mathematics intervention programs for students with learning difficulties. Her recent research agenda focuses on developing Conceptual Model-based / Mathematics Intelligent Tutors and promoting the use of this evidenced–based intervention program by elementary school teachers/practitioners who work with at-risk students. Dr. Xin’s work has been referenced in sources such as the National Mathematics Panel Final Report, the What Works Clearinghouse, and the Institute of Education Sciences Practitioner’s Guide. Her Conceptual Model-based Problem-Solving approach is included in National Council of Teachers of Mathematics authorized book “Useful and Useable Research Related to Core Mathematical Practices” (Silver & Kenney, 2015, 235-246) to inform teaching practices in K-12 mathematics classrooms. Recently, she guest edited the Cross-disciplinary Thematic Special Series: Special Education and Mathematics Education in the journal Learning Disability Quarterly.

visit author page

author page

Signe Kastberg Purdue University, West Lafayette

author page

Soojung Kim Purdue University, West Lafayette

Download Paper |


Computer-assisted learning benefits students by providing a great number of multimedia resources for improving response strength, streamlining information acquisition, and promoting knowledge construction [1]. Highlighting techniques have been widely used and, within the framework of cognitive load theory, are recognized as effective methods guiding students’ attention and reducing extraneous cognitive processes. This research study was designed to examine the effects of highlighting text animations (including blinking animation, popping out animation, and intense animation) on the attention distribution of students with math learning difficulties (MLD). As predicted, the results suggest that highlighting text animations are able to guide the attention allocation of students with MLD. In particular, intense animation significantly improved students’ fixation duration ratios on the key information areas in comparison to situations without highlighting text animation.

Wei, S., & Lei, Q., & Chen, Y., & Xin, Y. P., & Kastberg, S., & Kim, S. (2018, June), Evaluating the Effects of Highlighting Text Animations on the Attention Distribution of Students with Math Learning Difficulties Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30446

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2018 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015