STEAM Career Interest Instrument

1. Alana S. Phillips
Jennifer Miller
University of North Texas
Career Interests of Students in a
STEAM Camp

2. Summer STEAM Camp Experience

3. Research Questions
 Are STEM career interests of males different
from females?
 Are STEM career interests different by age
group?
 What are the primary factors that influence a
career choice?

4. Population
3
12
6
8
5
3
1
0
2
4
6
8
10
12
14
8 9 10 11 12 13 14
Age
N = 38
27
11
0
10
20
30
M F
Age

5. Instrument
 STEM Career Interest Questionnaire
(Knezek & Christensen, 2009)
 Twelve questions, Likert-type responses
– 1= strongly disagree to
– 5 = strongly agree
 Three parts
– Supports (Part 1)
– Education (Part 2)
– Career (Part 3)

6. Instrument (cont’d)
1. I would like to have a career in science.
2. My family is interested in the science courses I take.
3. I would enjoy a career in science.
4. My family has encouraged me to study science.
5. I will make it into a good college and major in an area
needed for a career in science.
6. I will graduate with a college degree in a major area
needed for a career in science.

7. Instrument (cont’d)
7. I will have a successful professional career and make
substantial scientific contributions.
8. I will get a job in a science-related area.
9. Some day when I tell others about my career, they will
respect me for doing scientific work.
10. A career in science would enable me to work with others
in meaningful ways.
11. Scientists make a meaningful difference in the world.
12. Having a career in science would be challenging.

8. RESULTS

9. Reliability
 Cronbach’s Alpha (α) = .91 (Excellent)
 Subscales (α)
– Supports = .78 (Good)
– Education = .87 (Good)
– Career = .73 (Good)

10. Validity
 Total Variance of Three Factors 74.03%
 Communality values of all variables
exceeded .65 (considered high)
 Age and Family Factor (p=.039,Cohen’s d
=.62)

11. Analysis by Age Group
Factor/Age Group N Mean
Std.
Deviation
Sig
between
grps
Cohen’s
d
Supports (Part 1)
Younger 22 3.31 1.11
Older 16 3.77 0.76
Total 38 3.5 0.99 1.63 0.483
Education (Part 2)
Younger 22 3.44 1.07
Older 16 3.76 0.67
Total 38 3.58 0.92 0.303 0.358
Career (Part 3)
Younger 22 3.91 1.01
Older 16 4.29 0.68
Total 38 4.07 0.9 1.99 0.441

12. Analysis by Gender
Factor/Gender N Mean
Std.
Deviation
Sig
between
grps
Cohen’s
d
Supports
Male 28 3.41 1.11
Female 10 3.75 0.51
Total 38 3.5 0.99 0.361 0.393
Education
Male 28 3.54 1.03
Female 10 3.68 0.57
Total 38 3.58 0.92 0.693 0.168
Career
Male 28 3.95 0.92
Female 10 4.4 0.77
Total 38 4.07 0.9 0.179 0.53

13. Results
 Means on the subscales appeared higher for
older students than younger and higher for
females than males.
 Item 4, “My family has encouraged me to
study science” was rated much more
positively by the younger students.

14. Discussion
 Limitations of the study
– Population
– No pre/post test
 Future research

15. References
 Cohen, J. (1988). Statistical power analysis for the behavioral
sciencies. Routle
 DeVellis, R. F. (2011). Scale development: Theory and applications
(Vol. 26). Sage.
 Knezek, G. & Christensen, R. (2009). Career Interest
Questionnaire, Retrieved from
http://www.iittl.unt.edu/IITTL/newiittl/STEM/ CareerInterestQ.pdf
 MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999).
Sample size in factor analysis. Psychological methods, 4(1), 84.
 Tyler-Wood, T., Knezek, G., & Christensen, R. (2010). Instruments
for assessing interest in STEM content and careers. Journal of
Technology and Teacher Education, 18(2), 345-368.

16. Conclusion
Questions?