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Individualized Learning through Computer Based Tutors

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Conference

2017 ASEE Mid Atlantic Section Spring Conference

Location

Morgan State University, Baltimore, Maryland

Publication Date

April 7, 2017

Start Date

April 7, 2017

End Date

April 8, 2017

Tagged Topic

Diversity

Page Count

6

Permanent URL

https://peer.asee.org/29261

Download Count

29

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Paper Authors

biography

Vasudeva Rao Aravind Clarion University

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Dr. Vasudeva Rao Aravind is an associate professor of physics at Clarion University. Dr. Aravind has a Ph.D from The Pennsylvania State University in Materials Science and Engineering and Master’s and Bachelor’s degrees in Physics from Sri Sathya Sai Institute of Higher Learning, India. Dr. Aravind is a highly accomplished scholar and researcher in the fields of materials science, condensed matter physics, materials for energy applications, and educational technology. He has published his work in more than 15 prestigious journal articles and presented numerous invited talks and conference presentations throughout the world. His current research involves nanoscale structure property exploration through microscopy, and effective use of educational technology in the undergraduate physics classroom.

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Kevin D Croyle Clarion University Of Pennsylvania

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Abstract

Improving student education in science, technology, engineering, and mathematics (STEM) is critical to the progress and success of an economy. Although it is well established that STEM related degree holders are likely to be more successful and earn a higher income that non-STEM degree holders, the number of students opting to study STEM courses do not show a significant growth. There are several reasons for this. One of the main reason is the rate of attrition in basic and required STEM classes such as physics and calculus. In this article, we describe our attempt at improving physics learning using a responsive computer based tutor. This automated tutor presents problems to students, takes their input, and provides immediate feedback and/or hints to the student based on their input. While it is interacting with the students, the computer collects anonymous student data at a very fine grained level, recording every mouse click, student response, and waiting times. Studying about 2000 such student interactions, we present the lessons learned, patterns of student behavior recognized, and suggestions for future deployment.

Aravind, V. R., & Croyle, K. D. (2017, April), Individualized Learning through Computer Based Tutors Paper presented at 2017 ASEE Mid Atlantic Section Spring Conference, Morgan State University, Baltimore, Maryland. https://peer.asee.org/29261

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