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Improving the Requirements Inspection Abilities of Computer Science Students through Analysis of their Reading and Learning Styles

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Conference

2017 ASEE Annual Conference & Exposition

Location

Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Software Engineering Concepts

Tagged Division

Computers in Education

Page Count

13

Permanent URL

https://peer.asee.org/28498

Download Count

54

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Paper Authors

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Anurag Goswami North Dakota State University

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Anurag Goswami is a Ph. D. Candidate in the department of Computer Science at North Dakota State University. His main research interests include empirical software engineering, human factors in software engineering, and software quality. He is a member of the IEEE Computer Society.

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Gursimran Singh Walia North Dakota State University

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Gursimran S. Walia is an associate professor of Computer Science at North Dakota State University. His main research interests include empirical software engineering, software engineering education, human factors in software engineering, and software quality. He is a member of the IEEE Computer Society. Contact him at gursimran.walia@ndsu.edu

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Ganesh Padmanabhan North Dakota State University

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I am a research-oriented applications developer with more than ten years of professional programming experience primarily in the area of cognitive and vision research. I have been working at the Center for Visual and Cognitive Neuroscience at North Dakota State University since 2005. I have expertise in mathematics, software development, and hardware and software, trouble-shooting. I have had experience with computer programming from the time when FORTRAN was popular as a language and personal computers were just being introduced. As an undergraduate, programming was a tool to augment my interests in biology and psychology. In graduate school, I had the opportunity to hone my skills, and formalize my computer science and neuroscience education. Since then, I have had experience implementing experiments involving virtual immersion, EEG recording, gaze tracking, image processing, statistical analyses, and various types of computer modelling.

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Mark E McCourt Department of Psychology, North Dakota State University

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DR. MARK E. McCOURT, JAMES A. MEIER and DALE HOGOBOOM DISTINGUISHED PROFESSOR, NORTH DAKOTA STATE UNIVERSITY DEPARTMENT OF PSYCHOLOGY, DIRECTOR, NDSU NIH IDeA PROGRAM CENTER FOR VISUAL AND COGNITIVE NEUROSCIENCE

Mark E. McCourt earned his Ph.D. in Psychology from the University of California, Santa Barbara in 1982. At NDSU he was awarded the James A. Meier and Dale Hogoboom Professorships in 2004 and 2009, respectively. In 2004 he was awarded an NIH/IDeA Centers of Biomedical Research Excellence (COBRE) grant which established the NDSU Center for Visual and Cognitive Neuroscience, which is funded through 2021 and which he currently directs. Dr. McCourt is internationally known for his scientific contributions in the area of human perception and cognition, particularly in the areas of brightness/lightness perception, spatial attention, and multisensory integration. He has published over 100 peer-reviewed papers and given numerous contributed and invited talks. He is a member of the Editorial Board for the international journals NeuroReport and Vision, and is an Associate Editor for the journal Frontiers in Human Neuroscience. Dr. McCourt is a regular reviewer for over 50 scientific journals, and has reviewed for major funding agencies such as NIH, NSF, AFOSR, the Netherlands Organization for Scientific Research, the US-Israel Bi-National Science Foundation, the Canada Research Chairs Program, the Canada National Sciences and Engineering Council, and the Wellcome Trust. Dr. McCourt has received over $31M in competitive grant funding over his career from NIH, NSF, AFOSR, and other sources.

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Abstract

Software Engineering (SE) students learn various concepts in academia that prepares them for working in software industry. To fulfil the demand of delivering quality software, industries focus on inspection technique, introduced by Fagan at IBM in 1976, for early detection and removal of faults that saves rework effort and cost. Due to the importance of inspections, academic institutions have begun training students on inspection technique. This helps them to understand the nature of faults made during development and help them avoid committing the same defects. Despite the importance of inspections as an effective verification technique, training students on becoming effective inspectors is especially hard because the background factors (education, experience, personalities) of inspectors do not impact their individual fault detection effectiveness. On that note, our prior results showed that students tend to perceive & process information presented in Natural Language (NL) requirements document in different ways and is known as Learning Styles (LS). To gain insights into the reading patterns of individual inspectors during the requirements inspection, this research utilizes the eye tracking concept along with the psychological research on LS to identify the reading pattern of students as they inspect NL requirements document. The paper reports results from an academic study where inspection data of thirty-nine students were used to understand how educator can improve their inspection training technique. First, LS of each student was collected and students were trained on fault-checklist based inspection technique with sample requirements to guide inspections. Next, each student inspected requirements document (with seeded faults) and reported faults. The results were handed back with seeded fault list to introspect which helps students to understand inspection technique. Next, each student performed inspection on a second document (with seeded faults) in an eye tracking laboratory settings. Each student read requirements document on a computer monitor and eye movements were recorded by an eye tracker sitting at the bottom of the monitor. The faults reported were checked for fault positives by one of the researchers to generate final fault list for each student. The eye movement data was utilized to visualize scanpaths (linear/random reading trend) of students with fixations (where eye movements are relatively stationary) on the document along with the fixations at fault region. The data was then analyzed to evaluate the reading patterns in general and with different LS preference. Results show that inspection performance is significantly affected by the fixations especially at the fault regions. Results also showed that students had higher degree of linear reading pattern than random jumps during inspection and LS preferences had varying eye movement factors that affected inspection performance. Results provided insights into the design and execution of inspection training program that could be utilized to train students to focus more at fault prone areas for improved inspection outcome. Results also provided insights into the specific sections of requirements document that demonstrated regressive fixations and how the improvement in the requirements organization can improve the readability of requirements which in turn would improve their inspection performance.

Goswami, A., & Walia, G. S., & Padmanabhan, G., & McCourt, M. E. (2017, June), Improving the Requirements Inspection Abilities of Computer Science Students through Analysis of their Reading and Learning Styles Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. https://peer.asee.org/28498

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