SlideShare a Scribd company logo
1 of 6
Download to read offline
Environmental Factors Affecting Student Retention and
Attitudes in a Freshman Engineering Program
(1670 words)
Abstract
In this paper we analyzed the cultural and environmental factors that affect student
retention in a freshman engineering program. A survey was completed by all
freshman students who left the engineering program between 2007 and 2014
(n=1152). Descriptive statistics were used to analyze the data as well as looking at
the frequency of selected reasons for leaving engineering to assess students’ beliefs
and perceptions. The results of this study indicate there is a high tendency to leave
the program due to different factors, especially those that relate to a lack of
identification with engineering. This study provided information that could help
improve engineering culture by identifying key environmental factors that cause
students to leave the program at an early stage.
Purpose
Engineering programs are often evaluated on retention rates by observing
institutional factors such as administrators, faculty, facilities, and support systems
(Lau, 2003). While these are crucial to improving engineering programs,
environmental factors should also be considered including the program’s culture
(National Science Board, 2007; Rodgers & Marra, 2012). In order to provide better
support systems to students in engineering, it is critical to examine the potential
cultural and environmental factors that influence students’ decision to leave after
their freshman year. Many first-time freshman students experience a number of
changes such as moving away from home, not living with their parents, and a
heavier work-load than high school (Budny & Paul, 2003), which may increase the
likelihood of students’ decision to leave the program if no strong support systems
are in place. Although previous studies have indicated that academic and
institutional factors affect the attrition rates of freshman engineering students
(Turner & Thompson, 2014; Veenstra, 2009), little research has been done regarding
the internal cultural factors that are detrimental for student retention. The purpose
of this study is to analyze the factors related to engineering cultures and
institutional engineering environment that affect student retention in a freshman
engineering program.
Theoretical Framework
Previous literature indicates that the notion of “culture” in engineering is a relatively
new concept, thus there is an extensive need of research on the impact of how
engineering cultures may create unwelcoming environments for students –
specifically freshman engineering students. Lattuca and Stark (2009) described how
influences external and internal to the institution are embedded within a
sociocultural context model. In this model, different variables such as student and
faculty characteristics, collective beliefs about the discipline and program, and the
culture of a university play an important role in defining students’ success in
engineering. Similarly, Godfrey and Parker (2010) investigated the collective beliefs,
behaviors, and practices of students and faculty regarding engineering programs
and how these could influence students’ decisions to stay or leave engineering
programs. They identified six cultural dimensions for engineering education that
affect student’s attitudes towards engineering and ability to adapt and integrate
into the culture (Godfrey, 2014). From a sociocultural perspective, understanding
how the beliefs, behaviors, and practices affect engineering education is an integral
part in deciding how to provide support systems for students that may feel
alienated and excluded from engineering (Foor, Walden, & Trytten, 2007; Godfrey,
2014).
It is important to recognize that these cultures of engineering, including the
recognized “engineering norms”, have an effect on student retention and attitudes
towards engineering (Godfrey & Parker, 2010). These “engineering norms” can
include distinctive ways of thinking and acting as well as identifying with perceived
qualities of an engineer (Godfrey & Parker, 2010). These norms can potentially
create an exclusive environment for those who do not “fit in” (Godfrey & Parker,
2010; Stevens, O’Connor, & Garrison, 2005). Thus, sociocultural factors must be
investigated in order to better understand students’ decision-making processes
related to persistence in engineering programs.
Methods
This study originated from a need to understand the cultural and environmental
factors that may affect freshman students to leave the engineering program during
the first year. A large proportion of the student body at this public institution come
from low socioeconomic backgrounds, are first-time generation college students,
and come from predominantly rural areas. These students are typically the most
affected by engineering cultures because the norms of engineering do not align with
their social and cultural contexts (Orr et al., 2011; O'Keefe, 2013). A survey was
administered and completed by all freshman students (n =1152) who left the
engineering program between 2007 and 2014. The survey included demographic
information, closed form questions, and open form questions. For the purpose of this
study, only the closed form questions were analyzed. These types of questions were
aligned with four of the cultural dimensions described by Godfrey (2014) to help
analyze the environmental factors driving students out of engineering.
Descriptive statistics were used to analyze the data as well as looking at the
frequency of selected reasons for leaving engineering (Creswell, 2014; Gall et al.,
2007). These reasons were correlated with one or more cultural dimensions to
assess the beliefs and perceptions of freshman engineering students. The
relationship between students’ GPA and motivation to leave the program was also
analyzed. In addition, sets of different dispositions selected by the students in the
survey were investigated collectively to determine what motivated the student to
leave engineering.
Data Sources
The survey was used to collect data from all exiting freshman in the engineering
program starting in 2007. Students completed the form and met with an academic
advisor to ensure completion of the form. All surveys undergo a final review from
the assistant dean and are entered into a spreadsheet which is stored in a secure
database. The data are used both as a student record and a tool for analysis of
future program improvement.
The survey included one major closed-response question asking students about
their decision to leave. The students were provided with eleven different options
linked to that specific question. Students had no guidelines for selecting a minimum
or maximum number of reasons. The multiple options included statements such as
“engineering majors offered do not match my interests” and “I had problems with
advising” in order to capture internal and external influences representative of
sociocultural factors.
Results
In order of frequency, the top five selected reasons for leaving the engineering
program were “engineering majors do not match my interest” (41%), “I am having
academic difficulty” (38%), “I do not think I can succeed in engineering” (32%), “too
much effort required when I am uncertain what I want to do” (28%), and “other”
(27%). The “other” category reasons included transferring due to finances, only
starting in engineering because of the money and job outlook, having parents or
close family members in engineering, being more interested in another major or
engineering technology, and repeating other reasoning options in their own words.
Nearly half the exiting students selected that engineering did not match their
interests. As indicated by Godfrey and Parker (2010), developing an engineering
identity is key for retention. These students were confident in their decision to
leave the field after less than eight months in the program. This indicates it is
pivotal to help students develop an identity and sense of belonging within
engineering in this short time frame. Students did not see how their interests were
related to engineering, thus never having that crucial sense of “belonging” (Rodgers
& Marra, 2012). Godfrey and Parker also analyzed the perception of an engineering
way of thinking and doing. Those students who did not believe they could succeed
in engineering were likely exposed to those concepts and felt alienated, resulting in
attrition from the program. Additionally, the logic that engineering was too difficult
when students were unsure of their future plans coincides with other assertions of
how engineering is perceived. It is assumed that engineering should be hard and
include a heavy workload (Stevens et al., 2007).
Thirty-eight (38) percent of exiting students indicated that they had academic
difficulty, yet 82% of the students left the program with a GPA of 2.0 or higher, half
of those with a 3.0 or higher. The institution’s rules state a student will be put on
academic probation only when her/his GPA falls below a 2.0. Even if the remaining
18% of students who would have been placed on probation selected this reason,
that still leaves a high number of students who left the program while in good
academic standing. Of the students who did not pass their recent math class (D, F,
or W), 13% did not believe they were having academic difficulty.
When analyzing sets of dispositions, the most frequently paired motives were “I do
not think I can succeed in engineering” and “I am having academic difficulty”. This
relationship highlights student’ perception that if they are struggling academically,
they will never make it in the engineering field. Additional common pairs includes
“fields don’t match my interests” with “I don’t think I can succeed”, “I do not think I
can succeed in engineering” with “too much effort and uncertain of what I want to
do”, and “fields don’t match my interests” with “too much effort and uncertain of
what I want to do”. This last pair may indicate the student was only exposed to
aspects of engineering they did not like, but did not get the change to explore fields
they would be interested in.
The results of this study indicate there is a high tendency to leave the engineering
program after the first year due to different factors, especially those that relate to a
lack of identification with engineering. Many students did not feel like they would
succeed in engineering nor that they had interests within the field. Even though
their academic performance was satisfactory, this suggests academic performance
is only a small factor in their decision. It was determined that the culture and
environment of both the freshman and engineering program contribute to student
retention.
Significance
This study gave the opportunity to analyze environmental and cultural factors
affecting retention of freshman engineering students. Analysis of retention rates
and the effect of cultural and environmental factors allowed us to learn more about
the institution’s program, advance our understanding of engineering culture, and
provide information necessary for the development of educational strategies that
could be used to improve the learning environment for students. Additionally, this
study will assist the freshman engineering program in identifying key areas for
improvement and culture change within the program. This study also provides
information necessary to improve the survey administered to students leaving the
program as well as the program’s collection and management of data. Future work
will include qualitative studies that help expand our understanding of additional
environmental factors affecting students’ attitudes towards engineering. This body
of work contributes to the engineering education literature by providing information
that could help improve engineering culture by identifying key environmental
factors that cause students to leave the program at an early stage.
References
Budny, D. D., & Paul, C. A. (2003). Working with Students and Parents to Improve
the Freshman Retention. Journal of STEM Education: Innovations & Research, 4(3/4),
1-9.
Bushong, S. (2009). Freshman Retention Drops, Except at 2-Year Colleges. Chronicle
of Higher Education, 55(21), A17.
Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed
Methods Approaches. Los Angeles, CA: SAGE Publications.
Gall. M. D., Gall, J. P., Borg, W. R. (2007). Educational Research: An Introduction (8th
ed.). Boston, MA: Allyn and Bacon.
Gee, J. P. (2008). Social linguistics and literacies: Ideology in discourses (3rd ed.)
London, England: Routledge.
Godfrey, E. (2014). Understanding Disciplinary Cultures: The first Step to Cultural
Change. In Cambridge Handbook of Engineering Education Research (pp.439-446).
New York, NY: Cambridge University Press.
Godfrey, E., & Parker, L. (2010) Mapping the cultural landscape in engineering
education. Journal of Engineering Education, 99(1), 5-22.
Hensel, R. A. M., Poland, M. (2015). Freshman Engineering Program ABET Report &
Documentation. Morgantown, WV: West Virginia University
Lau, L. K. (2003). Institutional Factors Affecting Student Retention. Education,
124(1), 126-136.
Lattuca, L. R., & Litzinger, T. A. (2014). Studying Teaching and Learning in
Undergraduate Engineering Programs: Conceptual Frameworks to Guide Research
on Practice. In Cambridge Handbook of Engineering Education Research (pp.487-
490). New York, NY: Cambridge University Press.
Lattuca, L. R., & Stark, J. S. (2009). Shaping the college curriculum: Academic plans
in context. San Francisco, CA: Jossey-Bass.
Mejia, Joel Alejandro, "A Sociocultural Analysis of Latino High School Students' Funds
of Knowledge and Implications for Culturally Responsive Engineering Education"
(2014). All Graduate Theses and Dissertations. Paper 3969.
http://digitalcommons.usu.edu/etd/3969
National Science Board. (2007). Moving Forward to Improve Engineering Education.
National Science Foundation. Retrieved from
http://www.nsf.gov/pubs/2007/nsb07122/nsb07122.pdf.
O'Keefe, P. (2013). A Sense of Belonging: Improving Student Retention. College
Student Journal, 47(4), 605-613.
Orr, M.K., Ramirez, N.M., & Ohland, M.W. (2011). Socioeconomic trends in
engineering: enrollment, persistence, and academic achievement. In Proceedings of
the American Society for Engineering Education Annual Conference and Exposition.
Vancouver, BC, Canada. Washington, DC: ASEE.
Rodgers, K. A., & Marra, R. M. (2012). Why They’re Leaving. ASEE Prism, 21(5), 43.
Stevens, R., Amos, D. L., Jocuns, A., Garrison, L. (2007). Engineering Lifestyle and a
meritocracy of difficulty: Two pervasive beliefs among engineering students and
their possible effects. In Proceedings of the Annual conference of Exposition
American Society for Engineering Education. Honolulu, HI.
Stevens, R. O’Connor, K., & Garrison, L. (2005). Engineering student identities in the
navigation of the undergraduate curriculum. In Proceedings of the 2005 American
Society for Engineering Education Annual Conference. Portland, OR: ASEE
Stevens, R., O'Connor, K., Garrison, L., Jocuns, A., & Amos, D. M. (2008). Becoming
an engineer: Toward a three dimensional view of engineering learning. Journal of
Engineering Education, 97(3), 355-368
Turner, P., & Thompson, E. (2014). College Retention Initiatives Meeting the Needs of
Millennial Freshman Students. College Student Journal, 48(1), 94-104.
Veenstra, C. P. (2009). A strategy for improving freshman college retention. The
Journal for Quality and Participation, 31(4), 19-23.

More Related Content

What's hot

Comparative and non-comparative evaluation in educational technology
Comparative and non-comparative evaluation in educational technologyComparative and non-comparative evaluation in educational technology
Comparative and non-comparative evaluation in educational technologysara Al-thihli
 
Nan L. Kalke MWERA presentation October 19, 2017
Nan L. Kalke MWERA presentation October 19, 2017Nan L. Kalke MWERA presentation October 19, 2017
Nan L. Kalke MWERA presentation October 19, 2017Nan Kalke
 
Aep wire-09-2010-sabol-nclb
Aep wire-09-2010-sabol-nclbAep wire-09-2010-sabol-nclb
Aep wire-09-2010-sabol-nclbAqib Iqbal
 
Statistical Scoring Algorithm for Learning and Study Skills
Statistical Scoring Algorithm for Learning and Study SkillsStatistical Scoring Algorithm for Learning and Study Skills
Statistical Scoring Algorithm for Learning and Study Skillsertekg
 
Postdocpaper Career Satisfaction of postdocs
Postdocpaper Career Satisfaction of postdocsPostdocpaper Career Satisfaction of postdocs
Postdocpaper Career Satisfaction of postdocsMoniek de Boer MSc
 
Massey University PhD Induction July 2018 NCTL Session
Massey University PhD Induction July 2018 NCTL SessionMassey University PhD Induction July 2018 NCTL Session
Massey University PhD Induction July 2018 NCTL SessionMartin McMorrow
 
Challenges to the Dissemination and Diffusion of Educational Innovations
Challenges to the Dissemination and Diffusion of Educational InnovationsChallenges to the Dissemination and Diffusion of Educational Innovations
Challenges to the Dissemination and Diffusion of Educational InnovationsBrandon Muramatsu
 
PhD research proposal presentation Sonia Saddiqui 28 Nov 2013
PhD research proposal presentation Sonia Saddiqui 28 Nov 2013PhD research proposal presentation Sonia Saddiqui 28 Nov 2013
PhD research proposal presentation Sonia Saddiqui 28 Nov 2013Sonia Saddiqui
 
The influence of postgraduate students’ personal characteristics on their res...
The influence of postgraduate students’ personal characteristics on their res...The influence of postgraduate students’ personal characteristics on their res...
The influence of postgraduate students’ personal characteristics on their res...Alexander Decker
 
Yan Zhu_Dissertation Abtract
Yan Zhu_Dissertation AbtractYan Zhu_Dissertation Abtract
Yan Zhu_Dissertation AbtractYan Zhu
 
An abstraction of research findings for policy formulation and decision makin...
An abstraction of research findings for policy formulation and decision makin...An abstraction of research findings for policy formulation and decision makin...
An abstraction of research findings for policy formulation and decision makin...Alexander Decker
 
Robin garzaresearch
Robin garzaresearchRobin garzaresearch
Robin garzaresearchRobin Garza
 
GRE, measure of graduate school success (fnl)
GRE, measure of graduate school success (fnl)GRE, measure of graduate school success (fnl)
GRE, measure of graduate school success (fnl)Phyllis Behrens
 

What's hot (15)

Comparative and non-comparative evaluation in educational technology
Comparative and non-comparative evaluation in educational technologyComparative and non-comparative evaluation in educational technology
Comparative and non-comparative evaluation in educational technology
 
Nan L. Kalke MWERA presentation October 19, 2017
Nan L. Kalke MWERA presentation October 19, 2017Nan L. Kalke MWERA presentation October 19, 2017
Nan L. Kalke MWERA presentation October 19, 2017
 
Aep wire-09-2010-sabol-nclb
Aep wire-09-2010-sabol-nclbAep wire-09-2010-sabol-nclb
Aep wire-09-2010-sabol-nclb
 
Retention at FUS
Retention at FUSRetention at FUS
Retention at FUS
 
Statistical Scoring Algorithm for Learning and Study Skills
Statistical Scoring Algorithm for Learning and Study SkillsStatistical Scoring Algorithm for Learning and Study Skills
Statistical Scoring Algorithm for Learning and Study Skills
 
Postdocpaper Career Satisfaction of postdocs
Postdocpaper Career Satisfaction of postdocsPostdocpaper Career Satisfaction of postdocs
Postdocpaper Career Satisfaction of postdocs
 
Massey University PhD Induction July 2018 NCTL Session
Massey University PhD Induction July 2018 NCTL SessionMassey University PhD Induction July 2018 NCTL Session
Massey University PhD Induction July 2018 NCTL Session
 
Challenges to the Dissemination and Diffusion of Educational Innovations
Challenges to the Dissemination and Diffusion of Educational InnovationsChallenges to the Dissemination and Diffusion of Educational Innovations
Challenges to the Dissemination and Diffusion of Educational Innovations
 
PhD research proposal presentation Sonia Saddiqui 28 Nov 2013
PhD research proposal presentation Sonia Saddiqui 28 Nov 2013PhD research proposal presentation Sonia Saddiqui 28 Nov 2013
PhD research proposal presentation Sonia Saddiqui 28 Nov 2013
 
amusan22274
amusan22274amusan22274
amusan22274
 
The influence of postgraduate students’ personal characteristics on their res...
The influence of postgraduate students’ personal characteristics on their res...The influence of postgraduate students’ personal characteristics on their res...
The influence of postgraduate students’ personal characteristics on their res...
 
Yan Zhu_Dissertation Abtract
Yan Zhu_Dissertation AbtractYan Zhu_Dissertation Abtract
Yan Zhu_Dissertation Abtract
 
An abstraction of research findings for policy formulation and decision makin...
An abstraction of research findings for policy formulation and decision makin...An abstraction of research findings for policy formulation and decision makin...
An abstraction of research findings for policy formulation and decision makin...
 
Robin garzaresearch
Robin garzaresearchRobin garzaresearch
Robin garzaresearch
 
GRE, measure of graduate school success (fnl)
GRE, measure of graduate school success (fnl)GRE, measure of graduate school success (fnl)
GRE, measure of graduate school success (fnl)
 

Viewers also liked

Auction Certificate Geng Jing
Auction Certificate Geng JingAuction Certificate Geng Jing
Auction Certificate Geng JingJing Geng
 
Franco Denari - Corso Mkt Lezione VI
Franco Denari - Corso Mkt Lezione VIFranco Denari - Corso Mkt Lezione VI
Franco Denari - Corso Mkt Lezione VIFranco Denari
 
N_Anderson Capstone Final Document_ word
N_Anderson Capstone Final Document_ wordN_Anderson Capstone Final Document_ word
N_Anderson Capstone Final Document_ wordNicole Anderson
 
DA7-project-Kowalski
DA7-project-KowalskiDA7-project-Kowalski
DA7-project-KowalskiAli Anderson
 
Whats app? Even private chatter now exploited by billionaires
Whats app? Even private chatter now exploited by billionairesWhats app? Even private chatter now exploited by billionaires
Whats app? Even private chatter now exploited by billionairesDavid Kreps
 
Presentacion de mi investigacion
Presentacion de mi investigacionPresentacion de mi investigacion
Presentacion de mi investigacionJaqueline_Giselle
 
9 interesting photography facts by nishan kohli
9 interesting photography facts by nishan kohli9 interesting photography facts by nishan kohli
9 interesting photography facts by nishan kohliNishan Kohli
 

Viewers also liked (10)

Auction Certificate Geng Jing
Auction Certificate Geng JingAuction Certificate Geng Jing
Auction Certificate Geng Jing
 
Franco Denari - Corso Mkt Lezione VI
Franco Denari - Corso Mkt Lezione VIFranco Denari - Corso Mkt Lezione VI
Franco Denari - Corso Mkt Lezione VI
 
N_Anderson Capstone Final Document_ word
N_Anderson Capstone Final Document_ wordN_Anderson Capstone Final Document_ word
N_Anderson Capstone Final Document_ word
 
DA7-project-Kowalski
DA7-project-KowalskiDA7-project-Kowalski
DA7-project-Kowalski
 
Whats app? Even private chatter now exploited by billionaires
Whats app? Even private chatter now exploited by billionairesWhats app? Even private chatter now exploited by billionaires
Whats app? Even private chatter now exploited by billionaires
 
Snort
SnortSnort
Snort
 
Presentacion de mi investigacion
Presentacion de mi investigacionPresentacion de mi investigacion
Presentacion de mi investigacion
 
PRESENTATION-SBM
PRESENTATION-SBMPRESENTATION-SBM
PRESENTATION-SBM
 
Informe Técnico
Informe TécnicoInforme Técnico
Informe Técnico
 
9 interesting photography facts by nishan kohli
9 interesting photography facts by nishan kohli9 interesting photography facts by nishan kohli
9 interesting photography facts by nishan kohli
 

Similar to AERA16 - Environmental Factors in a Freshman Engineering Program - Abstract

Assessment Of Interest As Subjective Personal Data Of Engineering Freshmen To...
Assessment Of Interest As Subjective Personal Data Of Engineering Freshmen To...Assessment Of Interest As Subjective Personal Data Of Engineering Freshmen To...
Assessment Of Interest As Subjective Personal Data Of Engineering Freshmen To...Tracy Hill
 
Statistical Scoring Algorithm for Learning and Study Skills
Statistical Scoring Algorithm for Learning and Study SkillsStatistical Scoring Algorithm for Learning and Study Skills
Statistical Scoring Algorithm for Learning and Study SkillsGurdal Ertek
 
Academic Self-Concept And Critical Thinking Dispositions Devising A Predicti...
Academic Self-Concept And Critical Thinking Dispositions  Devising A Predicti...Academic Self-Concept And Critical Thinking Dispositions  Devising A Predicti...
Academic Self-Concept And Critical Thinking Dispositions Devising A Predicti...Sabrina Green
 
The learning strategies of successful research graduates; a survey on the msi...
The learning strategies of successful research graduates; a survey on the msi...The learning strategies of successful research graduates; a survey on the msi...
The learning strategies of successful research graduates; a survey on the msi...mizzyatie14
 
Analysis of First-year Engineering Student Essays on Engineering Interests fo...
Analysis of First-year Engineering Student Essays on Engineering Interests fo...Analysis of First-year Engineering Student Essays on Engineering Interests fo...
Analysis of First-year Engineering Student Essays on Engineering Interests fo...Anna Landers
 
Attitudes And Perceptions Towards Mathematics By Greek Engineering Students A...
Attitudes And Perceptions Towards Mathematics By Greek Engineering Students A...Attitudes And Perceptions Towards Mathematics By Greek Engineering Students A...
Attitudes And Perceptions Towards Mathematics By Greek Engineering Students A...Christine Williams
 
Wilson jones, linda graduate females focus v6 n1 2011
Wilson jones, linda graduate females focus v6 n1 2011Wilson jones, linda graduate females focus v6 n1 2011
Wilson jones, linda graduate females focus v6 n1 2011William Kritsonis
 
A Survey of Mathematics Education Technology Dissertation Scope and Quality ...
A Survey of Mathematics Education Technology Dissertation Scope and Quality  ...A Survey of Mathematics Education Technology Dissertation Scope and Quality  ...
A Survey of Mathematics Education Technology Dissertation Scope and Quality ...Crystal Sanchez
 
Oumh1103 pdf factor influencing adult learners' decicion to drop out or per...
Oumh1103 pdf factor influencing adult learners'  decicion to drop  out or per...Oumh1103 pdf factor influencing adult learners'  decicion to drop  out or per...
Oumh1103 pdf factor influencing adult learners' decicion to drop out or per...Mohamad Kelana Mat
 
Demaris Final Presentation
Demaris  Final  PresentationDemaris  Final  Presentation
Demaris Final Presentationguestcc1ebaf
 
Demaris final presentation
Demaris final presentationDemaris final presentation
Demaris final presentationguest2b32b2e
 
Demaris final presentation
Demaris final presentationDemaris final presentation
Demaris final presentationguest2b32b2e
 
A Phenomenological Study Of Attrition From A Doctoral Cohort Program Changes...
A Phenomenological Study Of Attrition From A Doctoral Cohort Program  Changes...A Phenomenological Study Of Attrition From A Doctoral Cohort Program  Changes...
A Phenomenological Study Of Attrition From A Doctoral Cohort Program Changes...Lori Mitchell
 
A Scholarship Model For Student Recruitment And Retention In STEM Disciplines
A Scholarship Model For Student Recruitment And Retention In STEM DisciplinesA Scholarship Model For Student Recruitment And Retention In STEM Disciplines
A Scholarship Model For Student Recruitment And Retention In STEM DisciplinesRenee Lewis
 
Academic Achievement And Admission Policy As Correlate Of Student Retention I...
Academic Achievement And Admission Policy As Correlate Of Student Retention I...Academic Achievement And Admission Policy As Correlate Of Student Retention I...
Academic Achievement And Admission Policy As Correlate Of Student Retention I...Mary Calkins
 
Linda wilson jones (done) focus
Linda wilson jones (done) focusLinda wilson jones (done) focus
Linda wilson jones (done) focusWilliam Kritsonis
 
Students’ Perceptions of the Effectiveness of Technology Use by Professors
Students’ Perceptions of the Effectiveness of Technology Use by ProfessorsStudents’ Perceptions of the Effectiveness of Technology Use by Professors
Students’ Perceptions of the Effectiveness of Technology Use by ProfessorsCathy Yang
 
An Examination Of University Students Learning And Studying Approaches
An Examination Of University Students  Learning And Studying ApproachesAn Examination Of University Students  Learning And Studying Approaches
An Examination Of University Students Learning And Studying ApproachesAngie Miller
 

Similar to AERA16 - Environmental Factors in a Freshman Engineering Program - Abstract (20)

Assessment Of Interest As Subjective Personal Data Of Engineering Freshmen To...
Assessment Of Interest As Subjective Personal Data Of Engineering Freshmen To...Assessment Of Interest As Subjective Personal Data Of Engineering Freshmen To...
Assessment Of Interest As Subjective Personal Data Of Engineering Freshmen To...
 
Statistical Scoring Algorithm for Learning and Study Skills
Statistical Scoring Algorithm for Learning and Study SkillsStatistical Scoring Algorithm for Learning and Study Skills
Statistical Scoring Algorithm for Learning and Study Skills
 
41
4141
41
 
Academic Self-Concept And Critical Thinking Dispositions Devising A Predicti...
Academic Self-Concept And Critical Thinking Dispositions  Devising A Predicti...Academic Self-Concept And Critical Thinking Dispositions  Devising A Predicti...
Academic Self-Concept And Critical Thinking Dispositions Devising A Predicti...
 
The learning strategies of successful research graduates; a survey on the msi...
The learning strategies of successful research graduates; a survey on the msi...The learning strategies of successful research graduates; a survey on the msi...
The learning strategies of successful research graduates; a survey on the msi...
 
Analysis of First-year Engineering Student Essays on Engineering Interests fo...
Analysis of First-year Engineering Student Essays on Engineering Interests fo...Analysis of First-year Engineering Student Essays on Engineering Interests fo...
Analysis of First-year Engineering Student Essays on Engineering Interests fo...
 
Attitudes And Perceptions Towards Mathematics By Greek Engineering Students A...
Attitudes And Perceptions Towards Mathematics By Greek Engineering Students A...Attitudes And Perceptions Towards Mathematics By Greek Engineering Students A...
Attitudes And Perceptions Towards Mathematics By Greek Engineering Students A...
 
Wilson jones, linda graduate females focus v6 n1 2011
Wilson jones, linda graduate females focus v6 n1 2011Wilson jones, linda graduate females focus v6 n1 2011
Wilson jones, linda graduate females focus v6 n1 2011
 
A Survey of Mathematics Education Technology Dissertation Scope and Quality ...
A Survey of Mathematics Education Technology Dissertation Scope and Quality  ...A Survey of Mathematics Education Technology Dissertation Scope and Quality  ...
A Survey of Mathematics Education Technology Dissertation Scope and Quality ...
 
Oumh1103 pdf factor influencing adult learners' decicion to drop out or per...
Oumh1103 pdf factor influencing adult learners'  decicion to drop  out or per...Oumh1103 pdf factor influencing adult learners'  decicion to drop  out or per...
Oumh1103 pdf factor influencing adult learners' decicion to drop out or per...
 
Demaris Final Presentation
Demaris  Final  PresentationDemaris  Final  Presentation
Demaris Final Presentation
 
Finalpaper!
Finalpaper!Finalpaper!
Finalpaper!
 
Demaris final presentation
Demaris final presentationDemaris final presentation
Demaris final presentation
 
Demaris final presentation
Demaris final presentationDemaris final presentation
Demaris final presentation
 
A Phenomenological Study Of Attrition From A Doctoral Cohort Program Changes...
A Phenomenological Study Of Attrition From A Doctoral Cohort Program  Changes...A Phenomenological Study Of Attrition From A Doctoral Cohort Program  Changes...
A Phenomenological Study Of Attrition From A Doctoral Cohort Program Changes...
 
A Scholarship Model For Student Recruitment And Retention In STEM Disciplines
A Scholarship Model For Student Recruitment And Retention In STEM DisciplinesA Scholarship Model For Student Recruitment And Retention In STEM Disciplines
A Scholarship Model For Student Recruitment And Retention In STEM Disciplines
 
Academic Achievement And Admission Policy As Correlate Of Student Retention I...
Academic Achievement And Admission Policy As Correlate Of Student Retention I...Academic Achievement And Admission Policy As Correlate Of Student Retention I...
Academic Achievement And Admission Policy As Correlate Of Student Retention I...
 
Linda wilson jones (done) focus
Linda wilson jones (done) focusLinda wilson jones (done) focus
Linda wilson jones (done) focus
 
Students’ Perceptions of the Effectiveness of Technology Use by Professors
Students’ Perceptions of the Effectiveness of Technology Use by ProfessorsStudents’ Perceptions of the Effectiveness of Technology Use by Professors
Students’ Perceptions of the Effectiveness of Technology Use by Professors
 
An Examination Of University Students Learning And Studying Approaches
An Examination Of University Students  Learning And Studying ApproachesAn Examination Of University Students  Learning And Studying Approaches
An Examination Of University Students Learning And Studying Approaches
 

AERA16 - Environmental Factors in a Freshman Engineering Program - Abstract

  • 1. Environmental Factors Affecting Student Retention and Attitudes in a Freshman Engineering Program (1670 words) Abstract In this paper we analyzed the cultural and environmental factors that affect student retention in a freshman engineering program. A survey was completed by all freshman students who left the engineering program between 2007 and 2014 (n=1152). Descriptive statistics were used to analyze the data as well as looking at the frequency of selected reasons for leaving engineering to assess students’ beliefs and perceptions. The results of this study indicate there is a high tendency to leave the program due to different factors, especially those that relate to a lack of identification with engineering. This study provided information that could help improve engineering culture by identifying key environmental factors that cause students to leave the program at an early stage. Purpose Engineering programs are often evaluated on retention rates by observing institutional factors such as administrators, faculty, facilities, and support systems (Lau, 2003). While these are crucial to improving engineering programs, environmental factors should also be considered including the program’s culture (National Science Board, 2007; Rodgers & Marra, 2012). In order to provide better support systems to students in engineering, it is critical to examine the potential cultural and environmental factors that influence students’ decision to leave after their freshman year. Many first-time freshman students experience a number of changes such as moving away from home, not living with their parents, and a heavier work-load than high school (Budny & Paul, 2003), which may increase the likelihood of students’ decision to leave the program if no strong support systems are in place. Although previous studies have indicated that academic and institutional factors affect the attrition rates of freshman engineering students (Turner & Thompson, 2014; Veenstra, 2009), little research has been done regarding the internal cultural factors that are detrimental for student retention. The purpose of this study is to analyze the factors related to engineering cultures and institutional engineering environment that affect student retention in a freshman engineering program. Theoretical Framework Previous literature indicates that the notion of “culture” in engineering is a relatively new concept, thus there is an extensive need of research on the impact of how engineering cultures may create unwelcoming environments for students – specifically freshman engineering students. Lattuca and Stark (2009) described how influences external and internal to the institution are embedded within a
  • 2. sociocultural context model. In this model, different variables such as student and faculty characteristics, collective beliefs about the discipline and program, and the culture of a university play an important role in defining students’ success in engineering. Similarly, Godfrey and Parker (2010) investigated the collective beliefs, behaviors, and practices of students and faculty regarding engineering programs and how these could influence students’ decisions to stay or leave engineering programs. They identified six cultural dimensions for engineering education that affect student’s attitudes towards engineering and ability to adapt and integrate into the culture (Godfrey, 2014). From a sociocultural perspective, understanding how the beliefs, behaviors, and practices affect engineering education is an integral part in deciding how to provide support systems for students that may feel alienated and excluded from engineering (Foor, Walden, & Trytten, 2007; Godfrey, 2014). It is important to recognize that these cultures of engineering, including the recognized “engineering norms”, have an effect on student retention and attitudes towards engineering (Godfrey & Parker, 2010). These “engineering norms” can include distinctive ways of thinking and acting as well as identifying with perceived qualities of an engineer (Godfrey & Parker, 2010). These norms can potentially create an exclusive environment for those who do not “fit in” (Godfrey & Parker, 2010; Stevens, O’Connor, & Garrison, 2005). Thus, sociocultural factors must be investigated in order to better understand students’ decision-making processes related to persistence in engineering programs. Methods This study originated from a need to understand the cultural and environmental factors that may affect freshman students to leave the engineering program during the first year. A large proportion of the student body at this public institution come from low socioeconomic backgrounds, are first-time generation college students, and come from predominantly rural areas. These students are typically the most affected by engineering cultures because the norms of engineering do not align with their social and cultural contexts (Orr et al., 2011; O'Keefe, 2013). A survey was administered and completed by all freshman students (n =1152) who left the engineering program between 2007 and 2014. The survey included demographic information, closed form questions, and open form questions. For the purpose of this study, only the closed form questions were analyzed. These types of questions were aligned with four of the cultural dimensions described by Godfrey (2014) to help analyze the environmental factors driving students out of engineering. Descriptive statistics were used to analyze the data as well as looking at the frequency of selected reasons for leaving engineering (Creswell, 2014; Gall et al., 2007). These reasons were correlated with one or more cultural dimensions to assess the beliefs and perceptions of freshman engineering students. The relationship between students’ GPA and motivation to leave the program was also analyzed. In addition, sets of different dispositions selected by the students in the survey were investigated collectively to determine what motivated the student to leave engineering.
  • 3. Data Sources The survey was used to collect data from all exiting freshman in the engineering program starting in 2007. Students completed the form and met with an academic advisor to ensure completion of the form. All surveys undergo a final review from the assistant dean and are entered into a spreadsheet which is stored in a secure database. The data are used both as a student record and a tool for analysis of future program improvement. The survey included one major closed-response question asking students about their decision to leave. The students were provided with eleven different options linked to that specific question. Students had no guidelines for selecting a minimum or maximum number of reasons. The multiple options included statements such as “engineering majors offered do not match my interests” and “I had problems with advising” in order to capture internal and external influences representative of sociocultural factors. Results In order of frequency, the top five selected reasons for leaving the engineering program were “engineering majors do not match my interest” (41%), “I am having academic difficulty” (38%), “I do not think I can succeed in engineering” (32%), “too much effort required when I am uncertain what I want to do” (28%), and “other” (27%). The “other” category reasons included transferring due to finances, only starting in engineering because of the money and job outlook, having parents or close family members in engineering, being more interested in another major or engineering technology, and repeating other reasoning options in their own words. Nearly half the exiting students selected that engineering did not match their interests. As indicated by Godfrey and Parker (2010), developing an engineering identity is key for retention. These students were confident in their decision to leave the field after less than eight months in the program. This indicates it is pivotal to help students develop an identity and sense of belonging within engineering in this short time frame. Students did not see how their interests were related to engineering, thus never having that crucial sense of “belonging” (Rodgers & Marra, 2012). Godfrey and Parker also analyzed the perception of an engineering way of thinking and doing. Those students who did not believe they could succeed in engineering were likely exposed to those concepts and felt alienated, resulting in attrition from the program. Additionally, the logic that engineering was too difficult when students were unsure of their future plans coincides with other assertions of how engineering is perceived. It is assumed that engineering should be hard and include a heavy workload (Stevens et al., 2007). Thirty-eight (38) percent of exiting students indicated that they had academic difficulty, yet 82% of the students left the program with a GPA of 2.0 or higher, half of those with a 3.0 or higher. The institution’s rules state a student will be put on academic probation only when her/his GPA falls below a 2.0. Even if the remaining 18% of students who would have been placed on probation selected this reason, that still leaves a high number of students who left the program while in good
  • 4. academic standing. Of the students who did not pass their recent math class (D, F, or W), 13% did not believe they were having academic difficulty. When analyzing sets of dispositions, the most frequently paired motives were “I do not think I can succeed in engineering” and “I am having academic difficulty”. This relationship highlights student’ perception that if they are struggling academically, they will never make it in the engineering field. Additional common pairs includes “fields don’t match my interests” with “I don’t think I can succeed”, “I do not think I can succeed in engineering” with “too much effort and uncertain of what I want to do”, and “fields don’t match my interests” with “too much effort and uncertain of what I want to do”. This last pair may indicate the student was only exposed to aspects of engineering they did not like, but did not get the change to explore fields they would be interested in. The results of this study indicate there is a high tendency to leave the engineering program after the first year due to different factors, especially those that relate to a lack of identification with engineering. Many students did not feel like they would succeed in engineering nor that they had interests within the field. Even though their academic performance was satisfactory, this suggests academic performance is only a small factor in their decision. It was determined that the culture and environment of both the freshman and engineering program contribute to student retention. Significance This study gave the opportunity to analyze environmental and cultural factors affecting retention of freshman engineering students. Analysis of retention rates and the effect of cultural and environmental factors allowed us to learn more about the institution’s program, advance our understanding of engineering culture, and provide information necessary for the development of educational strategies that could be used to improve the learning environment for students. Additionally, this study will assist the freshman engineering program in identifying key areas for improvement and culture change within the program. This study also provides information necessary to improve the survey administered to students leaving the program as well as the program’s collection and management of data. Future work will include qualitative studies that help expand our understanding of additional environmental factors affecting students’ attitudes towards engineering. This body of work contributes to the engineering education literature by providing information that could help improve engineering culture by identifying key environmental factors that cause students to leave the program at an early stage.
  • 5. References Budny, D. D., & Paul, C. A. (2003). Working with Students and Parents to Improve the Freshman Retention. Journal of STEM Education: Innovations & Research, 4(3/4), 1-9. Bushong, S. (2009). Freshman Retention Drops, Except at 2-Year Colleges. Chronicle of Higher Education, 55(21), A17. Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Los Angeles, CA: SAGE Publications. Gall. M. D., Gall, J. P., Borg, W. R. (2007). Educational Research: An Introduction (8th ed.). Boston, MA: Allyn and Bacon. Gee, J. P. (2008). Social linguistics and literacies: Ideology in discourses (3rd ed.) London, England: Routledge. Godfrey, E. (2014). Understanding Disciplinary Cultures: The first Step to Cultural Change. In Cambridge Handbook of Engineering Education Research (pp.439-446). New York, NY: Cambridge University Press. Godfrey, E., & Parker, L. (2010) Mapping the cultural landscape in engineering education. Journal of Engineering Education, 99(1), 5-22. Hensel, R. A. M., Poland, M. (2015). Freshman Engineering Program ABET Report & Documentation. Morgantown, WV: West Virginia University Lau, L. K. (2003). Institutional Factors Affecting Student Retention. Education, 124(1), 126-136. Lattuca, L. R., & Litzinger, T. A. (2014). Studying Teaching and Learning in Undergraduate Engineering Programs: Conceptual Frameworks to Guide Research on Practice. In Cambridge Handbook of Engineering Education Research (pp.487- 490). New York, NY: Cambridge University Press. Lattuca, L. R., & Stark, J. S. (2009). Shaping the college curriculum: Academic plans in context. San Francisco, CA: Jossey-Bass. Mejia, Joel Alejandro, "A Sociocultural Analysis of Latino High School Students' Funds of Knowledge and Implications for Culturally Responsive Engineering Education" (2014). All Graduate Theses and Dissertations. Paper 3969. http://digitalcommons.usu.edu/etd/3969 National Science Board. (2007). Moving Forward to Improve Engineering Education. National Science Foundation. Retrieved from http://www.nsf.gov/pubs/2007/nsb07122/nsb07122.pdf.
  • 6. O'Keefe, P. (2013). A Sense of Belonging: Improving Student Retention. College Student Journal, 47(4), 605-613. Orr, M.K., Ramirez, N.M., & Ohland, M.W. (2011). Socioeconomic trends in engineering: enrollment, persistence, and academic achievement. In Proceedings of the American Society for Engineering Education Annual Conference and Exposition. Vancouver, BC, Canada. Washington, DC: ASEE. Rodgers, K. A., & Marra, R. M. (2012). Why They’re Leaving. ASEE Prism, 21(5), 43. Stevens, R., Amos, D. L., Jocuns, A., Garrison, L. (2007). Engineering Lifestyle and a meritocracy of difficulty: Two pervasive beliefs among engineering students and their possible effects. In Proceedings of the Annual conference of Exposition American Society for Engineering Education. Honolulu, HI. Stevens, R. O’Connor, K., & Garrison, L. (2005). Engineering student identities in the navigation of the undergraduate curriculum. In Proceedings of the 2005 American Society for Engineering Education Annual Conference. Portland, OR: ASEE Stevens, R., O'Connor, K., Garrison, L., Jocuns, A., & Amos, D. M. (2008). Becoming an engineer: Toward a three dimensional view of engineering learning. Journal of Engineering Education, 97(3), 355-368 Turner, P., & Thompson, E. (2014). College Retention Initiatives Meeting the Needs of Millennial Freshman Students. College Student Journal, 48(1), 94-104. Veenstra, C. P. (2009). A strategy for improving freshman college retention. The Journal for Quality and Participation, 31(4), 19-23.