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Evaluating Academic Procrastination In A Personalized System Of Instruction Based Curriculum

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Conference

2009 Annual Conference & Exposition

Location

Austin, Texas

Publication Date

June 14, 2009

Start Date

June 14, 2009

End Date

June 17, 2009

ISSN

2153-5965

Conference Session

Tricks of the Trade II

Tagged Division

New Engineering Educators

Page Count

15

Page Numbers

14.589.1 - 14.589.15

Permanent URL

https://peer.asee.org/5672

Download Count

91

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Paper Authors

biography

Srikanth Tadepalli University of Texas, Austin

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Srikanth Tadepalli is a PhD candidate in Mechanical Engineering at The University of Texas. After recieving his BS in Mechanical Engineering from India, he moved to UT where obtained his MSE in Manufacturing Systems Engineering specializing in Design for Manufacturing. He has worked as a Teaching Assistant and as an Assistant Instructor for the Computers and Programming course over a period of 3 years at The University of Texas at Austin and was awarded "The H. Grady Rylander Longhorn Mechanical Engineering Club Excellence in Teaching" Fellowship award for the years 2003-2004 and 2007-2008. He has also been cited in multiple publications of the "Who's Who" series. His research interests include Similitude and Scaling Theory, System Dynamics, Non-Linear Dimensional Analysis and Rapid Prototyping with specific emphasis in Selective Laser Sintering and applications in Product Design.

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biography

Cameron Booth University of Texas, Austin

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Cameron is a PhD student in the Mechanical Engineering department specializing in Dynamic Systems and Controls, and a recepient of the Thrust Fellowship. Cameron received his undergraduate education from Georgetown University and has worked for about 2 years as a Teaching Assistant for the Computers and Programming course taught at The University of Texas at Austin.

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Mitchell Pryor

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Evaluating Academic Procrastination in a Personalized System of Instruction based Curriculum Abstract

The impact of procrastination on student learning is a common researched topic and correlated with a lack of external/self-regulation, motivation and performance anxiety. Lecture-centric courses provide limited data to measure student procrastination. Projects, homework and midterm deadlines are binary indicators of a tendency to procrastinate. Other evidence is often subjective or anecdotal. In self-paced Personalized System of Instruction (PSI) courses, even these metrics do not exist since students learn material and take tests at their convenience. Yet PSI is an effective teaching strategy in courses such as an introductory programming where students have diverse backgrounds and varied computer literacy. PSI allows individuals to invest the appropriate time without overwhelming new programmers or underwhelming the experienced. Most importantly, a well-designed PSI course can instill time management skills to counter procrastination. Yet, PSI course designs must be evaluated and compared to quantify success. Using a web-based PSI approach, data can be collected and used to quantify procrastination. We present candidate procrastination metrics for comparing student populations, the merits of various teaching strategies, and the impact of course features. Additionally, correlations with traditional metrics (i.e. Grade Point Average (GPA), Scholastic Aptitude Test (SAT), hours completed, etc.) are examined to determine what external factors – if any – impact procrastination and require normalization for comparative evaluation of course designs.

Introduction

Procrastination symbolizes deliberate or intentional deferment of a scheduled task, possibly due to limited time before a deadline. The Webster's dictionary defines procrastination as “to put off intentionally and habitually.” Unnecessary and often avoidable anxiety and apprehension are induced when multiple tasks are due. Procrastination amplifies this physical strain if there is fear of failure. While procrastination itself is detrimental in almost all walks of life, it has a more profound impact in academia when students are expected to complete course requirements in a defined amount of time. Potential negative consequences of procrastination are reduced scholastic performance, increased pressure to cheat, mental and physical stress.

Most conventional courses have some indications of procrastination where the concerned instructor relies on test/project/homework performance, attendance, group activity, and personal interactions to gauge an individual's progress on assigned tasks. Based on such indicators and feedback, he/she can take corrective measures deemed necessary to minimize procrastination such as direct communication. However, for a PSI web-based course, the instructor lacks traditional physical presence. Thus, identifying and addressing procrastination is a challenge. In this regard, it is imperative to characterize procrastination using metrics that allow an “online” instructor to evaluate procrastination levels. This paper defines and uses these metrics to evaluate the (hopefully) beneficial impact of various course implementations strategies and features to combat procrastination.

Tadepalli, S., & Booth, C., & Pryor, M. (2009, June), Evaluating Academic Procrastination In A Personalized System Of Instruction Based Curriculum Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. https://peer.asee.org/5672

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: © 2009 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