2012, Johnson

BackgroundThe role of higher education, and specifically for community colleges as an educational pathway for the students to STEM (Science, Technology, Engineering and Math) degrees, continues to dominate local, state, and national agendas. This is due to the strategic and economic importance of STEM education at local, state, and national levels. Deemed a crisis, demand for STEM graduate is well documented, as exampled per the National Academy of Sciences 2007 report, Rising Above the Gathering Storm. This report highlighted the emergent crisis within the United States in regards to the failure of K-12 in student preparation; and Higher Education systems to graduate appropriate numbers of students in STEM fields. As cited in this 2007 report, “in South Korea, 38% of all undergraduates receive their degrees in natural science or engineering. In France, the figure is 47%, in China, 50%, and in Singapore, 67%. In the United States, the corresponding figure is 15%” (p. 16). To further illustrate the disparity between the U.S. and other countries, it was additionally cited that, “one estimate in 2004, China graduated about 350,000 engineers, computer scientists, and information technologists with 4-year degrees, while the United States graduated 140,000. China also graduated about 290,000 with 3-year degrees in these same fields, while the U.S. graduated about 85,000 with 2-or 3-year degrees” (p.16). In addition, the Department of Labor in a 2007 memo entitled, the STEM Workforce Challenge, provided several distinct points of discussion speaking to the importance of STEM education. Stating STEM fields have become increasingly central to U.S. economic growth, the Department of Labor elaborated, “trends in K-12 and higher education science and math preparation coupled with demographic and labor supply trends, point to a serious challenge our nations need to increase the supply and quality of workers whose specialized skills enable them to work productively in STEM fields” (p. 1).

The status of Iowa community colleges in meeting this demand has received significant attention this past year. With the Iowa Governors recently created STEM advisory council, and subsequent STEM recommendations published and STEM education expertise hubs created across the State, renewed scrutiny and expected forthcoming metrics for K-12, community colleges and Universities to more effectively develop and implement STEM student educational pathways are expected (STEM Advisory Council, 2011).

Self-Efficacy as Key Theoretical ConstructAccording to Bandura, (1977) self-efficacy is defined as: “A conviction that one can successfully execute the behavior required to produce outcome “(pg. 193). Impact of self-efficacy to student development is highlighted; “perceived self-efficacy influences choice of behavior. People fear and tend to avoid threatening situations believed to exceed personal ability, and instead choose to involve themselves in activities that are less intimidating,” (pg. 194). This definition illustrates the significance of self-efficacy to student decision making, particularly when accounting for what can be difficult subject matters within STEM classes; and possible student avoidance of such courses as a result of self-efficacy related concerns/challenges.

To the matter of impact of student self-efficacy to student academic achievement, Bandura (1993) stated, “student belief (self-efficacy) to regulate their own learning and to master their academic activities can determine a student’s aspirations, level of motivation, and academic achievement.” (p.117). The work of D.H. Schunk provides additional evidence. Schunk provides significant review of literature on this topic over several years of study, and his individual research on the impact of self-efficacy to student educational outcomes is noted. Schunk (2003)

The Influence of Self-Efficacy on Student Academic Success, Student Degree Aspirations, and Transfer PlanningJoel D. Johnson, Soko S. Starobin, Frankie Santos Laanan, and Daniel RussellIowa State University

School of Education October 2012

C O L L EG E O F H U M A N S C I E N C E S

ISSN 1939-361X (Print) and ISSN 1939-3628 (Online)

OCCRP RESEARCH BRIEF NO. 7Series on STEM Student Success Literacy Project

About SSSL-STEM Student Success Literacy SurveyThis is part of a five series policy brief based on the STEM Student Success Literacy project directed by Dr. Soko Starobin, Assistant Professor, School of Education and Director of Office of Community College Research and Policy at Iowa State University (ISU). This project is the first phase of a multi-year research study entitled, Measuring Constructs of STEM Student Success Literacy: Community College Students’ Self-Efficacy, Social Capital, and Transfer Knowledge, funded through the College of Human Sciences at ISU with Dr. Starobin serving as Principal Investigator (PI) and Dr. Frankie Santos Laanan and Dr. Daniel Russell as co-PI’s. The goal of this study is to ascertain the level of literacy of community college students regarding their transfer readiness for obtaining a baccalaureate degree in STEM fields. A team of researchers developed a survey instrument, STEM Student Success Literacy survey or (SSSL), which includes 63 items and measures self-efficacy, social capital, financial literacy, and general student demographics. In spring 2012, the research team conducted a pilot study with five community colleges in Iowa. An open section was provided for the pilot participating colleges to customize the instrument. This brief presents selected results and policy issues pertaining to the role of community colleges in STEM education in the State of Iowa.

2 School of Education Iowa State University

Stem Student Success Literacy Project OCCRP Research Brief No. 7

stated that, “a student’s self-efficacy beliefs influence such achievements behaviors as choice of tasks, effort, persistence, and achievement.” (pg. 160). This research provides a theoretical foundation for student academic support programming. Examples include such activities as learning communities, student academic support centers, advising/mentoring programs, and summer bridge programs such as HHMI. These programs are particularly important, providing opportunities to increase student self-efficacy related behaviors; a critical factor when assisting students’ academic success when participating in STEM related course work.

Finally, the impact of self-efficacy to student vocational choice is of note. This is important when considering student major choice/decision making process to potential STEM related fields. Brady-Amoon & Fuertes et. al., (2011), state that, “self-rated abilities, (self-efficacy beliefs) are defined as an individual’s belief that he or she can accomplish a task or reach a current goal; and are essential to the popular notion of fit, the trait factor, and person-environment career theories,” (p. 431). The impact a student self-efficacy has on college provides support to the importance of self-efficacy traits to student’s ultimate major choice. The (1994) work of Robert Lent, Steven Brown, and Gail Hackett is an example. Their research in Vocational Choice theory and the chosen construct of Social Cognitive Career Theory, or (SCCT), provides a specific framework for understanding student vocational choices and the career decision process. The SCCT model has theoretical underpinnings found in Albert Bandera’s general social cognitive theory, emphasizing self-efficacy as a key construct of student major choice. Self-efficacy was deemed by these authors as predictive of academic career choice. Thus self-efficacy behaviors assist a student to make a decision about their choice of activities and environment, combined with personal level of effort, time expenditure, persistence, and reaction when faced with challenging obstacles or decisions.

It is this impact of student self-efficacy to academic achievement, personal success, persistence, and career/college major choice that guided the choice of self-efficacy as a core construct for examination within this study.

Purpose of StudyResults from the STEM Student Success Literacy (SSSL) survey pilot study illustrated significant relationship of specific self-efficacy attitudes to positive academic decisions, choice to change career and intended major; combined with impact of STEM major choice to degree aspiration and intention to transfer.

This study examined the influence of personal and academic self-efficacy variables to academic behaviors and career choice; combined with potential influence of student degree declaration to STEM major to degree aspirations and transfer planning.

Research QuestionsSpecific research questions posed for this study include the following:

I. What are the demographic background characteristics of students responding to the SSSL survey?

II. What are the descriptive and environmental characteristics for identified campus environment responses specific to DMACC Urban?

III. Amongst the SSSL survey respondents, is there a correlation between a student’s personal attitudes and traits; to student degree aspirations, career choice, or academic behaviors?

IV. Are there statistically significant differences in the means of STEM versus non STEM majors; to student personal attitudes, academic confidence, or academic behaviors among all SSSL respondents?

V. Are there statistically significant differences in the means of STEM versus non STEM majors; to student degree aspirations or plan for formal transfer among all SSSL respondents?

Data Source and MethodsData for this study was collected from students enrolled at five community colleges within the State of Iowa, representing the Northwest, Central, and North Central regions of the state. Students invited as study participants were identified as enrolled in STEM related courses for the fall 2011-spring 2012 academic terms. A total of 5,448 students were invited to participate, with 565 students at least partially responding to the survey, or roughly a 10% return rate. A total of 275 students completed 100% of the survey questions.

For the purpose of statistical significance, correlative and comparative analysis utilized the whole population, or all community college responses, of the survey. Descriptive statistics, pearson correlations, and independent sample t-test results are presented. The data was analyzed utilizing IBM SPSS 19.0 software.

ResultsDescriptive AnalysisOf the total student respondents, more than 70% are female, with 29.7% male. This number represented a higher female percentage than the fall 2011 total Iowa community college average enrollment of 55%.

Male

Female

29.7% 70.3%

Gender

Iowa State University School of Education 3

October 2012

Additionally, the age of survey respondents was also higher within this data aggregate, with 38.3% of students responding indicating an age of 30-55%, as compared to a median age of 20 and average age of 23 for the State of Iowa Community colleges.

In contrast, ethnicity of respondents was more diversified for survey respondents than the Iowa Community colleges averages, with 40.4% white per study participants as compared to 84% white per State of Iowa Community College enrollments (Iowa Department of Education, 2011). For this data aggregate, Asian students represented 4% of the population, African American 4%, Hispanic 2.2%, Native Hawaiian/Pacific Is .4%, two or more races 5.1%. Missing or student non responses was 43.56%; a substantial number in this data aggregate.

Of particular note for the purpose of this brief, degree aspiration for student survey respondents illustrated 89.7% of students aspire to achieve at least a bachelor’s degree or beyond, as compared to 64% of Iowa Community college students enrolled in traditional college parallel tracks (Iowa Department of Education, 2011). While comparative data for STEM career enrollments is not currently available, student survey respondents indicated that a total of 44 students or 16% were planning to major in a STEM field, with 230 students, or 83.9% not pursuing STEM at the time of survey administration.

Additionally, for choice of STEM major; 57.5% indicated science, 19.1% indicated technology, 23.4% indicated engineering, and 0% indicated math as intended majors at time of survey completion.

0

5

10

15

20

25

30

35

<18 18-24 25-29 30-40 41-55 >55

Age Category

Series1

Series2

Age

White-40.4%

Asian-4%

Black/African American-4%

Hispanic-2.2%

Native Hawaiian/PacificIs- .04%

Two or more races-5.1%

Missing (Did notRespond)-43.56%

Ethnicity

STEM Major Students

Non STEM MajorStudents

44 Students

230 Students

Number of STEM Majors

Science

Technology

Engineering

Math

57.5% 23.4%

19.1%

Science

Engineering

Technology

Choice of STEM Major



Correlation AnalysisThree sets of correlation analysis were conducted. A Pearson product-moment correlation coefficient was computed to assess the relationship between variables associated with self-efficacy and students plan for degree obtainment. Results illustrated that specific self-efficacy attitudes positively correlated with student degree aspirations. Out of these variables, two emerged as statistically significant correlations. These two variables included, (1) ‘acknowledgement completing unpleasant/challenging tasks,’ and (2) ‘personal understanding of subject matter weakness and willingness to improve’ (Table 2).

A series of correlations were also performed analyzing self-efficacy variables associated with personal attitudes to career choice decisions (Table 3). Emergent correlations illustrated first, that student acknowledgement of willingness to take on unpleasant tasks and complete an identified task correlated with a student decision to change a major due to academic difficulty. Secondly, students response to, ‘if it looks too complicated, I will not try,’ was correlated to changing ones major based on academic difficulty. Finally, self-efficacy variables associated with academic attitudes for attempting something new, but soon giving up was correlated to career/major change based on both lack of high school preparation and academic difficulty in course work. These findings suggest potential negative impacts of poor self-efficacy attitudes to career choice decisions. When considering the subject matter associated with STEM related course work, this suggests potential negative impacts for STEM degree choice and persistence.

Comparative AnalysisA comparative analysis was conducted to determine if statistical significant differences existed between two groups in the sample: students who would like to pursue a STEM major and students who would not like to pursue a major in STEM. Table 3 illustrates a comparison of STEM Majors (N=44) and Non-STEM (N=230) to both intention to transfer and degree aspiration. While students within the data aggregate identified as registered in STEM related course work, only 44 students, or 16% identified as planning to pursue a STEM related degree. This exemplifies the STEM pipeline challenge cited in the 2007 report, Rising Above the Gathering Storm.

The independent t-test illustrated significant findings between the two groups. The mean for declared STEM majors was 1.61, (SD=1.093) and for non-declared STEM majors was 2.90 (SD=1.856). The test of equality failed; however a statistical significance to the p<=.001 was noted to the intention to transfer for STEM intended major students. Thus students majoring in STEM illustrated a higher degree of tendency for transfer planning as compared to non-STEM major students within this data aggregate. Additionally, a finding of significance to the p<=.001 level was also noted for degree aspirations. Declared STEM majors illustrated a mean of 6.48 (SD= 1.355) and for non-declared STEM majors a mean of 5.55 (SD= 1.397). These findings suggest STEM majors have higher degree aspirations within this student sample set. Clearly, within this data aggregate, transfer knowledge/

degree aspiration is not an issue for STEM students, and for the retention of students into a STEM major. However, it is a clear area of concern and one that warrants a recommendation for future research to investigate specific factors associated with STEM major choice and/or persistence.

Implications for Policy and PracticeThe role of higher education, and specifically community colleges as an educational pathway for students to STEM degrees, has emerged as a national and state agenda due to the strategic and economic importance of STEM education. Within the last several years, discussion of STEM education within the state of Iowa has gained momentum and importance for educators and administrators. The creation of Governor Branstad’s new STEM initiative, the STEM advisory council, the (2011) Iowa STEM Education Roadmap, and recent (2012) Iowa STEM Policy Recommendations all combine to illustrate the importance of STEM education to the state of Iowa. An example is the new Iowa STEM Education Road Map. It states the following core vision:

“All Iowa learners, from Pre-K-adult will acquire knowledge and skills in STEM-related subjects which will provide benefits to all community members for effective citizenry and employability. Access will be ensured for all Iowa citizens with particular attention to engaging under-represented minorities in STEM study and careers. Iowa STEM education, consistently supported at the state level, will be able to rapidly incorporate new knowledge and adapt to innovations in educational practices. A well trained STEM workforce will make it possible for the State of Iowa to maintain and attract employers to the State, as well as ensure that Iowa is a key participant in the global workforce and global economy (p. 6).”

The findings of this report are a preliminary examination of 5 Iowa community colleges, emphasizing a singular construct of student self-efficacy for analysis. Results from this study illustrated statistical significance in regards to varying factors associated with a student self-efficacy and accompanying factors associated with student academic success, degree aspirations, major choice, and transfer preparation. STEM students were evidenced within this data aggregate as illustrating higher degree aspiration and transfer planning/transfer knowledge than non-STEM major students. Findings that include direct correlation of self-efficacy traits to major persistence and academic success enhance student services, instruction, influence policy development, community college strategic planning, and goals in regards to increased STEM student production in direct response to the State of Iowa’s charge. Results presented from this and future studies associated with the STEM Student Success Literacy Project (SSSL) provide opportunities for new and innovative research to enhance institutional understanding of students engaged in STEM courses, provide an opportunity to explore impacts of the construct of self-efficacy to transfer knowledge/readiness, and allow preliminary benchmarking to other Iowa community colleges.


October 2012

Table 2: Pearson Correlation of Select Self-Efficacy Attitudes and Beliefs to Student Degree Aspirations

Variable 1 2 3 4 5 6 7

When I have something unpleasant to do, I stick to it until I finish it.

Pearson Correlation

1 .399** .332** -.187**

-.314** -.240**

.118*

Sig. (2-tailed)

.000 .000 .000 .000 .000 .022

Failure makes me try harder. Pearson Correlation

.399** 1 .316** -.288**

-.368** -.307**

.073

Sig. (2-tailed)

.000

.000 .000 .000 .000 .155

I know the subjects where I am academically weak and I try to improve them.

Pearson Correlation

.332** .316** 1 -.176 -.222** -.248**

.105

Sig. (2-tailed)

.000 .000

.001 .000 .000 .041*

If something looks too complicated, I will not even bother to try it.

Pearson Correlation

-.187**

-.288**

-.176** 1 .629** .533** -.079

Sig. (2-tailed)

.000 .000 .001

.000 .000 .125

When trying to learn something new, I soon give up if I am not initially successful.

Pearson Correlation

-.314**

-.368**

-.222** .629** 1 .626** -.068

Sig. (2-tailed)

.000 .000 .000 .000

.000 .184

I avoid trying to learn new things when they look too difficult for me.

Pearson Correlation

-.240**

-.307**

-.248** .533** .626** 1 -.091

Sig. (2-tailed)

.000 .000 .000 .000 .000

.076

If there were no obstacles, what is the highest academic degree you would like to attain in your life?

Pearson Correlation

.118* .073 .105* -.079 -.068 -.091 1

Sig. (2-tailed)

.022 .155 .041 .125 .184 .076

** Correlation is significant to p<=0.01 (2 tailed) * Correlation is significant at the p<=0.05 level (2 tailed)



Table 3: Pearson Correlation Among Self-Efficacy Variables and Student’s Decision to Change Major

Variables 1 2 3 4 5 6 7 8 9

When I have something unpleasant to do, I stick to it until I finish it.

Pearson Correlation

1 .332** .291** -.138 -.307** -.241* -.049 -.219* -.002

Sig. (2-tailed)

.000 .001 .126 .001 .007 .593 .015 .984

Failure makes me try harder.

Pearson Correlation

.332** 1 .286** -.271** -.387** -.323** .124 -.083 .015

Sig. (2-tailed)

.000

.001 .002 .000 .000 .169 .359 .868

I know the subjects where I am academically weak and I try to improve them.

Pearson Correlation

.291** .286** 1 -.090 -.217* -.403** -.092 -.124 -.103

Sig. (2-tailed)

.001 .001

.318 .015 .000 .310 .169 .256

If something looks too complicated, I will not even bother to try it.

Pearson Correlation

-.138 -.271** -.090 1 .558** .525** .154 .205* -.016

Sig. (2-tailed)

.126 .002 .318

.000 .000 .088 .022 .857

When trying to learn something new, I soon give up if I am not initially successful.

Pearson Correlation

-.307** -.387** -.217* .558** 1 .659** .256* .239* .024

Sig. (2-tailed)

.001 .000 .015 .000

.000 .004 .008 .789

I avoid trying to learn new things when they look too difficult for me.

Pearson Correlation

-.241* -.323** -.403** .525** .659** 1 .134 .104 .041

Sig. (2-tailed)

.007 .000 .000 .000 .000

.138 .251 .650

Lack of high school preparation for career choice requirements

Pearson Correlation

-.049 .124 -.092 .154 .256** .134 1 .511** .051

Sig. (2-tailed)

.593 .169 .310 .088 .004 .138

.000 .576

Academic difficulty in the major course requirements for the career

Pearson Correlation

-.219* -.083 -.124 .205* .239* .104 .511** 1 -.068

Sig. (2-tailed)

.015 .359 .169 .022 .008 .251 .000

.450

Academic interests and values have changed since arriving at this college

Pearson Correlation

-.002 .015 -.103 -.016 .024 .041 .051 -.068 1

Sig. (2-tailed)

.984 .868 .256 .857 .789 .650 .576 .450

** Correlation is significant to p<=0.01 (2 tailed) * Correlation is significant at the p<= 0.05 level (2 tailed)


October 2012

Table 4: Independent Sample T Test of STEM vs. Non-STEM Identifying Majors to Transfer Intention and Degree Aspiration

t-test for Equality of Means

t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper As things stand today do you intend to transfer to a:

Equal variances assumed

-4.288 249 .000 -1.876 -.695

Equal variances not assumed

-6.025 92.141 .000** -1.709 -.862

If there were no obstacles, what is the highest academic degree you would like to attain in your life?

Equal variances assumed

4.043 272 .000** .475 1.376

Equal variances not assumed

4.128 61.777 .000 .477 1.373

** Correlation is significant to p<=0.01 (2 tailed) Bold=Failed Test for Equal Variances



ReferencesBandura, A. (1977). Self-efficacy: Toward a unifying theory of

behavioral change. Psychological Review, 84, 191–215.Bandura, A. (1993). Perceived self-efficacy in cognitive

development and functioning. Educational Psychologist, 28(2), 117-148.

Brady-Amoon, P., & Fuertes, J.N. (2011). Self-efficacy, self-rated abilities, adjustment, and academic performance.

Journal of Counseling and Development, 89(4), 431-438.Department of Education, Iowa (2011). The Annual

Condition of Iowa’s Community Colleges. Retrieved November 9th, 2011 from http://educateiowa.gov/index.php?option=com_content&view=article&id=1663&catid=183&Itemid=2471

Department of Labor, USA. (2007). The STEM workforce challenge: The role of the Public Workforce System in a national solution for a competitive science, technology, engineering, and mathematics (STEM) workforce. Retrieved November 22, 2011 from http://www.doleta.gov/youth_services/pdf/STEM_Report_4%2007.pdf

Iowa Math and Science Organization (2011). A Strategic Plan for Science, Technology, Engineering and Mathematics (STEM) Education, 2011. Retrieved June 17, 2012 from http://www.iowamathscience.org/sites/default/files/2011stemeducationroadmap_finalrc51.pdf

Lent, R.W., Brown, S. D., Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45, 79-122.

National Center for Educational Statistics (2012). Postsecondary graduation rates: 2002 (Table 23-1). The condition of education-student effort and educational progress. Retrieved from http://nces.ed.gov/programs/coe/indicator_pgr.asp

Rising Above the Gathering Storm (2007). Committee on Prospering in the Global Economy of the 21st Century: An Agenda for American Science and Technology, National Academy of Sciences, National Academy of Sciences, National Academy of Engineering, Institute of Medicine. http://www.nap.edu/catalog/11463.html. ISBN: 0-309-65442-4. PP. 1-592.

Schunk, D. H. (2003). Self-efficacy for reading and writing: Influence of modeling, goal setting and self-evaluation. Reading and Writing Quarterly: Overcoming Learning Difficulties, 19(2), 159–172.

The OCCRP Research Brief is published by the Office of Community College Research & Policy (OCCRP) in the School of Education, College of Human Sciences at Iowa State University. http://www.cclp.hs.iastate.edu

Office of Community College Research and PolicySchool of Education Iowa State UniversityN243 Lagomarcino HallAmes, Iowa

Soko S. Starobin, EditorAssistant Professor and Director of OCCRPPhone: 515-294-9121, Fax: [email protected]/research/occrp

State of Iowa Government. (2012). STEM Advisory Council. https://openup.iowa.gov/board/

STEM+Advisory+Council/194/, retrieved March, 2012.States News Service (2011). Educate to innovate: How the Obama

plan for STEM education falls short. Recovered November 24th, 2011 per http://lexisnexis.com.proxy.lib.iastate.edu:2048/Inacui2api/deliv.

Office of the Governor of Iowa, Terry Branstad (2012). Branstad, Reynolds, Allen announce Governor’s STEM Regional Advisory Boards. Retrieved June 5th, 2012 from: https://governor.iowa.gov/2012/06/branstad-reynolds-allen-announce-governor%E2%80%99s- stem-regional-advisory-boards/

AuthorsJoel D. Johnson is a doctoral candidate in the Community

College Leadership Program in the School of Education.Soko S. Starobin is an assistant professor in the School of

Education.Frankie Santos Laanan is a professor in the School of

Education.Daniel Russell is a professor in the department of Human

Development & Family Studies.

Suggested CitationJohnson, J. D., Starobin, S. S., Laanan, F. S., & Russell, D. Office of Community College Research and Policy, (2012). The influence of self-Efficacy on student academic success, student degree aspirations, and transfer planning. The OCCRP Research Brief, 7. Ames, IA: Office of Community College Research and Policy.

Documents

2012, Johnson