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A Study On Social Networking Among Engineering Freshmen

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Conference

2007 Annual Conference & Exposition

Location

Honolulu, Hawaii

Publication Date

June 24, 2007

Start Date

June 24, 2007

End Date

June 27, 2007

ISSN

2153-5965

Conference Session

Emerging Trends in Engineering Education Poster Session

Page Count

16

Page Numbers

12.129.1 - 12.129.16

Permanent URL

https://peer.asee.org/2864

Download Count

49

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Paper Authors

biography

Denise Jackson University of Tennessee-Knoxville

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Denise Jackson is an Associate Professor in the Department of Industrial and Information Engineering at the University of Tennessee, Knoxville.

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biography

Sara Abdulla University of Tennessee, Knoxville

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Sara Abdulla received her Bachelor of Science Degree with a major in Biomedical Engineering from the University of Tennessee, Knoxville in 2002. She completed her Masters of Science degree in Industrial and Information Engineering with a concentration in Human Factors at the University of Tennessee, Knoxville in 2006.

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

Analysis of Information Networks of Freshman Engineering Students

Abstract

The effect of social interactions on individual and collective performance is receiving increased attention. The general assumption is that an individual’s success is, to a large extent, dependent on social ties and attainment of social capital. This paper presents the results of a study performed to determine if social interaction within freshman classes in the College of Engineering (COE) at The University of Tennessee, Knoxville (UTK) correlates with academic performance. Also of interest was whether the interactions between genders had a significant affect on academic performance. Better academic performance is cited in the literature as improving retention and graduation rates; therefore, if factors that affect academic performance can be understood measures can be taken to help students perform better.

Five UTK freshman classes taught by the Engineering Fundamentals (EF) Division were surveyed to determine their interaction with the rest of the members in their class. Academic performance of the class as a whole and of each gender was retrieved from the class’s instructor at the end of the semester. This data was analyzed in terms of demographics and sharing of information. Social network analysis of the interactions within the class was used to identify density and structure of networks. A description of the analysis, results, conclusions, and recommendations are provided as a basis for recognizing the potential impact of social networking in forming teams and in conducting classroom discussions. These results could also be used to determine better ways to present materials and provide information to improve academic performance. Investigation of factors that influence academic performance is important in order to know what may improve the success rate of engineering students. By improving the success rate of students, more students will remain and graduate in engineering.

Introduction

Amongst graduating high school students, the number of students interested in engineering is declining; and, of the students who enter engineering, only fifty percent graduate in engineering.8 The Science, Math, and Engineering (SME) majors have “the highest defection rates among undergraduates [and] the lowest recruitment rates.”14 The number of students leaving the engineering curriculum would not affect the numbers so “severely if there were compensating inflows [of students] along the way; however, the dominant flow is outward.”14 In education columnist Jay Matthew’s16 article, “Five Weird Ways To Graduate College,” number five on the list was “don’t major in engineering.” Unfortunately, it seems that engineering students feel this way as well and are choosing to switch majors or drop out of college entirely.

Important factors that lead to the successful retention of college students have been studied for decades. Several factors that researchers agree contribute to a student’s academic success are “high standards for academic learning and conduct, meaningful and engaging pedagogy and curriculum, professional learning communities among staff, and personalized learning environments.”13 One of the single major predictors of persistence within engineering is

Jackson, D., & Abdulla, S. (2007, June), A Study On Social Networking Among Engineering Freshmen Paper presented at 2007 Annual Conference & Exposition, Honolulu, Hawaii. https://peer.asee.org/2864

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