Journal of Science Education and Technology

, Volume 25, Issue 6, pp 833–845 | Cite as

Measuring Student Career Interest within the Context of Technology-Enhanced STEM Projects: A Cross-Project Comparison Study Based on the Career Interest Questionnaire

  • Karen Peterman
  • Ruth Kermish-Allen
  • Gerald Knezek
  • Rhonda Christensen
  • Tandra Tyler-Wood


This article describes Energy for ME and Going Green! Middle Schoolers Out to Save the World, two Science, Technology, Engineering, and Mathematics (STEM) education programs with the common goal of improving students’ attitudes about scientific careers. The authors represent two project teams, each with funding from the National Science Foundation’s ITEST program. Using different approaches and technology, both projects challenged students to use electricity monitoring system data to create action plans for conserving energy in their homes and communities. The impact of each project on students’ career interests was assessed via a multi-method evaluation that included the Career Interest Questionnaire (CIQ), a measure that was validated within the context of ITEST projects and has since become one of the instruments used most commonly across the ITEST community. This article explores the extent to which the CIQ can be used to document the effects of technology-enhanced STEM educational experiences on students’ career attitudes and intentions in different environments. The results indicate that the CIQ, and the Intent subscale in particular, served as significant predictors of students’ self-reported STEM career aspirations across project context. Results from each project also demonstrated content gains by students and demonstrated the impact of project participation and gender on student outcomes. The authors conclude that the CIQ is a useful tool for providing empirical evidence to document the impact of technology-enhanced science education programs, particularly with regard to Intent to purse a STEM career. The need for additional cross-project comparison studies is also discussed.


Energy Career attitudes Outcomes 


  1. Abell S (2007) Handbook of research on science education. Lawrence Erlbaum Associates, MahwahGoogle Scholar
  2. Baird JR, Penna C (1992) Survey research. In: Baird JR (ed) Shared adventure: a view of quality teaching and learning (Second report of the teaching and learning science in schools project). Monash University, Melbourne, pp. 185–274Google Scholar
  3. Bandura A, Barbaranelli C, Caprara GV, Pastorelli C (2001) Self-efficacy beliefs as shapers of children’s aspirations and career trajectories. Child Dev 72(1):187–206CrossRefGoogle Scholar
  4. Bencze L, Alsop S (2014) Activist science and technology education (2014 edition). Springer, New YorkGoogle Scholar
  5. Bowdich S (2009) Analysis of research exploring culturally responsive curricula in Hawaii. In: Paper presented to the Hawaii Educational Research Association Annual Conference, 7 February 2009Google Scholar
  6. Brown AL (1992) Design experiments: theoretical and methodological challenges in creating complex interventions in classroom settings. J Learn Sci 2(2):141–178CrossRefGoogle Scholar
  7. Buldu M (2006) Young children’s perceptions of scientists: a preliminary study. Educ Res 48(1):121–132CrossRefGoogle Scholar
  8. Bybee RW (2010) Advancing STEM education: a 2020 vision. Technol Eng Teach, 70(6):30–35. Retrieved from
  9. Chawla L, Cushing DF (2007) Education for strategic environmental behavior. Environ Educ Res 13(4):437–452CrossRefGoogle Scholar
  10. Christensen R, Knezek G (2013) Contrasts in student perceptions of STEM content and careers. In: McBride R, Searson M (eds), Proceedings of society for information technology & teacher education international conference 2013. AACE, Chesapeake, pp. 2048–2053. Retrieved from
  11. Christensen R, Knezek G (2015) Active learning approaches to integrating technology into middle school science classrooms: reconceptualizing a middle school science curriculum based on 21st century skills. In: Ge X, Ifenthaler D, Spector JM (eds) Full steam ahead: emerging technologies for STEAM. Springer Academic, New YorkGoogle Scholar
  12. Christensen R, Knezek G, Tyler-Wood T (2014) Student perceptions of science, technology, engineering and mathematics (STEM) content and careers. Comput Hum Behav 34:173–186. doi:10.1016/j.chb.2014.01.046 CrossRefGoogle Scholar
  13. Covitt BA (2004) Motivation in environmental education: Supporting middle school students’ motives for helping the Chesapeake Bay (Ph.D.). University of Michigan, United States – Michigan. Retrieved
  14. Davidson DM (1995) What does integration of science and mathematics really mean? School Sci Math 95(5):226–230CrossRefGoogle Scholar
  15. DeVellis RF (1991) Scale development. Sage Publications, Newbury ParkGoogle Scholar
  16. Dierking LD (2010) A comprehensive approach to fostering the next generation of science, technology, engineering, and mathematics (STEM) education leaders. New Educator 6(3):297–309CrossRefGoogle Scholar
  17. George P, Stevenson C, Thomason J, Beane J (1992) The middle school and beyond. Association for Supervision and Curriculum Development, AlexandriaGoogle Scholar
  18. Gottfredson L (1981) Circumscription and compromise: a developmental theory of occupational aspirations. J Couns Psychol 28(6):545–579CrossRefGoogle Scholar
  19. Heilbronner NN (2011) Stepping onto the STEM pathway. J Educ Gifted 34(6):876–899Google Scholar
  20. Keeley P (2009) Elementary science education in the K-12 system. NSTA Reports. Retrieved
  21. Kermish-Allen R, Peterman K, Macdonald S, Thompson R, Winner B (2015) Student and teacher teams using high resolution electricity monitoring to create local change. J Sustain EducGoogle Scholar
  22. Kier MW, Blanchard MR, Osborne JW, Albert JL (2014) The development of the STEM career interest survey (STEM-CIS). Res Sci Educ 44(3):461–481CrossRefGoogle Scholar
  23. Knezek G, Christensen R, Tyler-Wood T (2011) Contrasting perceptions of STEM content and careers. Contemp Issues Technol Teach Educ, 11(1). Retrieved
  24. Knezek G, Christensen R, Tyler-Wood T, Periathiruvadi S (2013) Impact of environmental power monitoring activities on middle school student perceptions of STEM. Sci Educ Int 21(1):98–123Google Scholar
  25. Knezek G, Christensen R, Tyler-Wood T, Gibson D (2015) Gender differences in conceptualizations of STEM career interest: complementary perspectives from data mining, multivariate data analysis and multidimensional scaling. J STEM Educ 16(4):13–19Google Scholar
  26. Lederman N (1997) The nature of science: Naturally? School Sci Math 97(1):1–2CrossRefGoogle Scholar
  27. Maltese AV, Tai RH (2011) Pipeline persistence: examining the association of educational experiences with earned degrees in STEM among U.S. students. Sci Educ 95(5):877–907CrossRefGoogle Scholar
  28. Malyn-Smith J, Hasselbring J, Haydon K, Jacobs P (2011) Kermish-Allen R (2011) Building STEM career pathways for technology-enabled youth. Proc Soc Inf Technol Teach Educ Int Conf 1:4128–4129Google Scholar
  29. Meier A (2009) National geographic vampire power test. Retrieved
  30. Meinhold JL, Malkus AJ (2005) Adolescent environmental behaviors can knowledge, attitudes, and self-efficacy make a difference? Environ Behav 37(4):511–532. doi:10.1177/0013916504269665 CrossRefGoogle Scholar
  31. Mills, L. (2013). Middle school predictors of STEM career interest: indicators of STEM career interest among public middle school students in the United States (Unpublished doctoral dissertation). University of North Texas, DentonGoogle Scholar
  32. Nakhleh MB, Krajcik JS (1993) A protocol analysis of the influence of technology on students’ actions, verbal commentary, and thought processes during the performance of acid-base titrations. J Res Sci Teach 30(9):1149–1168. doi:10.1002/tea.3660300911 CrossRefGoogle Scholar
  33. National Research Council (2011) Assessing 21st century skills: summary of a workshop. Retrieved from
  34. National Science Board (2009) Building a sustainable energy future: U.S. actions for an effective energy economy transformation. National Science Foundation. Retrieved
  35. Oh YJ, Jia Y, Lorentson M, LaBanca F (2013) Development of the educational and career interest scale in science, technology, and mathematics for high school students. J Sci Educ Technol 22(5):780–790CrossRefGoogle Scholar
  36. Palmer DH (1997) Investigating students’ private perceptions of scientists and their work. Res Sci Technol Educ 15(2):173–184CrossRefGoogle Scholar
  37. Powers AL (2004) An evaluation of four place-based education programs. J Environ Educ 35(4):17–32CrossRefGoogle Scholar
  38. Reid-Griffin A, Carter G (2008) Uncovering the potential: the role of technologies on science learning of middle school students. Int J Sci Math Educ 6(2):329–350. doi:10.1007/s10763-007-9105-8 CrossRefGoogle Scholar
  39. Rittmayer A, Beier M (2008) Overview: self-efficacy in STEM. SWE-AWE CASEE OverviewsGoogle Scholar
  40. Romine W, Sadler TD, Presley M, Klosterman ML (2014) Student interest in technology and science (sits) survey: development, validation, and use of a new instrument. Int J Sci Math Educ 12(2):261–283CrossRefGoogle Scholar
  41. Sadler PM, Sonnert G, Hazari Z, Tai R (2012) Stability and volatility of STEM career interest in high school: a gender study. Sci Educ 96(3):411–427CrossRefGoogle Scholar
  42. Schunk DH, Meece JR, Pintrich PR (2013) Motivation in education: theory, research, and applications, 4th edn. Pearson, BostonGoogle Scholar
  43. Schusler TM, Krasny ME (2010) Environmental action as context for youth development. J Environ Educ 41(4):208–223. doi:10.1080/0095896090347980 CrossRefGoogle Scholar
  44. Super DE (1969) Vocational development theory. Couns Psychol 1:2–30CrossRefGoogle Scholar
  45. Tai RH, Liu QC, Maltese AV, Fan X (2006) Planning early for careers in science. Science 312:1143–1144CrossRefGoogle Scholar
  46. Tyler-Wood T, Knezek G, Christensen R (2010) Instruments for assessing interest in STEM content and careers. J Technol Teach Educ 18(2):341–363Google Scholar
  47. U.S. Department of Energy (2011) When to turn off personal computers. Retrieved

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Karen Peterman Consulting, Co.DurhamUSA
  2. 2.Maine Math and Science AllianceAugustaUSA
  3. 3.Department of Learning TechnologiesUniversity of North TexasDentonUSA
  4. 4.Institute for the Integration of Technology into Teaching and LearningUniversity of North TexasDentonUSA

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