Journal of Science Education and Technology

, Volume 24, Issue 6, pp 898–909 | Cite as

Alignment of Hands-on STEM Engagement Activities with Positive STEM Dispositions in Secondary School Students

  • Rhonda Christensen
  • Gerald Knezek
  • Tandra Tyler-Wood


This study examines positive dispositions reported by middle school and high school students participating in programs that feature STEM-related activities. Middle school students participating in school-to-home hands-on energy monitoring activities are compared to middle school and high school students in a different project taking part in activities such as an after-school robotics program. Both groups are compared and contrasted with a third group of high school students admitted at the eleventh grade to an academy of mathematics and science. All students were assessed using the same science, technology, engineering and mathematics (STEM) dispositions instrument. Findings indicate that the after-school group whose participants self-selected STEM engagement activities, and the self-selected academy of mathematics and science group, each had highly positive STEM dispositions comparable to those of STEM professionals, while a subset of the middle school whole-classroom energy monitoring group that reported high interest in STEM as a career, also possessed highly positive STEM dispositions comparable to the STEM Professionals group. The authors conclude that several different kinds of hands-on STEM engagement activities are likely to foster or maintain positive STEM dispositions at the middle school and high school levels, and that these highly positive levels of dispositions can be viewed as a target toward which projects seeking to interest mainstream secondary students in STEM majors in college and STEM careers, can hope to aspire. Gender findings regarding STEM dispositions are also reported for these groups.


STEM dispositions Positive outcomes Secondary school level 



This research was funded in part by the NSF ITEST Grants #0833706, #1030865 and #1312168.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standard

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.


  1. Abell S (2007) Handbook of research on science education. Lawrence Erlbaum Associates, MahwahGoogle Scholar
  2. Akinoglu O, Tandogan RO (2007) The effects of problem-based active learning in science education on students’ academic achievement, attitude and concept learning. Eurasia J Math Sci Technol Educ 3(1):71–81Google Scholar
  3. Dunn-Rankin P et al (1971) Norming and scoring the school attitude survey (SAI) (A final report to the Hawaii State Department of Education), University of Hawaii, Education Research and Development Center, HonoluluGoogle Scholar
  4. American Association of University Women (2010) Why so few? Women in science, technology, engineering, and mathematics. American Association of University Women, WashingtonGoogle Scholar
  5. Aschbacher PR, Ing M, Tsai SM (2013) Boosting student interest in science. Kappan Mag 95(2):47–51CrossRefGoogle Scholar
  6. 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, Australia, pp 185–274Google Scholar
  7. Banning J, Folkestad JE (2012) STEM education related dissertation abstracts: a bounded qualitative meta-study. J Sci Educ Technol 21(6):730–741CrossRefGoogle Scholar
  8. Beaton AE, Martin MO, Mullis IVS, Gonzalez EJ, Smith TA, Kelly DL (1996) Science achievement in the middle school years. Boston College, Chestnut HillGoogle Scholar
  9. Bialo ER, Sivin-Kachala J (1996) The effectiveness of technology in schools: a summary of recent research. Sch Libr Media Q 25(1):51–57Google Scholar
  10. Bisland M, Kekelis L, McCreedy D, Koster E, Gupta P, Roman C (2011). Science museum roundtable. Discussion at the NCWIT K-12 Alliance Summit, New YorkGoogle Scholar
  11. Bonwell C, Eison J (1991) Active learning: creating excitement in the classroom. AEHE-ERIC Higher Education Report No. 1., Jossey-Bass, WashingtonGoogle Scholar
  12. Bybee RW (2010). Advancing STEM education: a 2020 vision. Technol Eng Teach 70(6):30–35. Retrieved from
  13. Ceci SJ, Williams WM, Barnett SM (2009) Women’s underrepresentation in science: sociocultural and biological considerations. Psychol Bull 135(2):218–261CrossRefGoogle Scholar
  14. Christensen R, Knezek G (2001) Equity and diversity in K-12 applications of information technology: key instructional design strategies (KIDS) project findings for 2000–2001 (Year Two Report), Institute for the Integration of Technology into Teaching and Learning (IITTL), Denton, TXGoogle Scholar
  15. 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 and teacher education international conference 2013 AACE, Chesapeake, VA, pp 2048–2053. Retrieved 2 Jan 2014 from
  16. Christensen R, Knezek G, Tyler-Wood T (2014a) 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
  17. Christensen R, Knezek G, Tyler-Wood T, Gibson D (2014b) Longitudinal analysis of cognitive constructs fostered by STEM activities in middle school students. Knowl Manag E-Learning 6(2):103–122Google Scholar
  18. Christensen R, Knezek G, Tyler-Wood T (2015) Dispositions of teachers in STEM enrichment programs. In: Proceedings of the Hawaii international conference on education, Honolulu, HIGoogle Scholar
  19. Cohen J (1988) Statistical power analysis for the behavioral sciences, 2nd edn. Lawrence Earlbaum Associates, HillsdaleGoogle Scholar
  20. Davidson DM (1995) What does integration of science and mathematics really mean? Sch Sci Math 95(5):226–230CrossRefGoogle Scholar
  21. DeVellis RF (1991) Scale development. Sage Publications, Newbury ParkGoogle Scholar
  22. Dewey J (1938) Experience and education. A touchstone book. Kappa Delta Pi, New YorkGoogle Scholar
  23. Dweck C (2006) Is math a gift? Beliefs that put females at risk. In: Ceci SJ, Williams WM (eds) Why aren’t more women in science? Top researchers debate the evidence. American Psychological Association, Washington, pp 47–55Google Scholar
  24. Ebenezer JV, Zoller U (1993) Grade 10 students’ perceptions of and attitudes toward science teaching and school science. J Res Sci Teach 30(2):175–186CrossRefGoogle Scholar
  25. Gallagher S (1997) Problem-based learning: Where did it come from, what does it do and where is it going? J Educ Gifted 29(4):332–362Google Scholar
  26. George P, Stevenson C, Thomason J, Beane J (1992) The middle school and beyond. Association for Supervision and Curriculum Development, AlexandriaGoogle Scholar
  27. Ghanbari S (2014) STEAM: the wave of the future embedded in ideals of the past. STEAM J 1(2):17Google Scholar
  28. Halverson HG (2011) The trouble with bright girls. Huffington Post, March 1. Accessed 1 Mar 2011
  29. Heemskerk IMCC, Brink AM, Volman MLL, ten Dam GTM (2005) Inclusiveness and ICT in education: a focus on gender, ethnicity and social class. J Comput Assist Learn 21(1):1–16CrossRefGoogle Scholar
  30. Heilbronner NN (2011) Stepping onto the STEM pathway. J Educ Gifted 34(6):876–899Google Scholar
  31. Holden JP, Lander ES, Varmus H (2010). Prepare and inspire: K-12 education in science, technology, engineering and math (STEM) for America’s future (Executive Report). Presidents’ Council of Advisors on Science and Technology, WashingtonGoogle Scholar
  32. Keeley P (2009) Elementary science education in the K-12 system. NSTA Reports. Retrieved from
  33. Knezek G, Christensen R (1998) Internal consistency reliability for the teachers’ attitudes toward information technology (TAT) questionnaire. In: McNeil S, Price J, Boger-Mehall S, Robin B, Willis J (eds) Proceedings of the society for information technology in teacher education annual conference, Society for Information Technology in Teacher Education, Bethesda, MD pp 831–836Google Scholar
  34. Knezek G, Christensen R (2009) CFB high school student technology report spring 2009. Unpublished manuscriptGoogle Scholar
  35. Knezek G, Christensen R, Tyler-Wood T (2011) Contrasting perceptions of STEM content and careers. Contemp Issues Technol Teach Educ 11(1):92–117Google Scholar
  36. 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 24(1):98–123Google Scholar
  37. Knezek G, Christensen R, Tyler-Wood T (2014) Going green! Middle schoolers out to save the world (MSOSW). National Science Foundation Award 1312168 Annual ReportGoogle Scholar
  38. Knezek G, Christensen R, Tyler-Wood T (2015) Teacher dispositions toward science, technology, engineering and mathematics (STEM). In: Proceedings of society for information technology and teacher education international conference 2015, Association for the Advancement of Computing in Education (AACE), Chesapeake, VA, pp 1362–1368Google Scholar
  39. Lederman N (1997) The nature of science: Naturally? Sch Sci Math 97(1):1–2CrossRefGoogle Scholar
  40. Lent RW, Sheu H, Schmidt J, Brenner BR, Wilkins G, Brown SD, Gloster CS, Schmidt LC, Lyons H, Treisteman D (2005) Social cognitive predictors of academic interests and goals in engineering: utility for women and students at historically black universities. J Couns Psychol 52(1):84–92CrossRefGoogle Scholar
  41. Maltese AV, Tai RH (2011) Pipeline persistence: examining the association of educational experiences with earned degrees in STEM among US students. Sci Educ 95(5):877–907CrossRefGoogle Scholar
  42. Milner AR, Sondergeld TA, Demir A, Johnson CC, Czerniak CM (2012) Elementary teachers’ beliefs about teaching science and classroom practice: an examination of pre-post NCLB testing in science. J Sci Teach Educ 23(2):111–132CrossRefGoogle Scholar
  43. Modi K, Schoenberg J, Salmond K (2012) Generation STEM: what girls say about science, technology, engineering and math. The Girl Scout Research InstituteGoogle Scholar
  44. Myers RE, Fouts JT (1992) A cluster analysis of high school science classroom environments and attitude toward science. J Res Sci Teach 29:929–937CrossRefGoogle Scholar
  45. National Research Council (2012) A framework for K-12 science education: practices, crosscutting concepts, and core ideas. The Academies Press, WashingtonGoogle Scholar
  46. Nguyen HHH, Ryan AMM (2008) Does stereotype threat affect test performance of minorities and women? A meta-analysis of experimental evidence. J Appl Psychol 93(6):1314–1334CrossRefGoogle Scholar
  47. Osborne J, Simon S, Collins S (2003) Attitudes towards science: a review of the literature and its implications. Int J Sci Educ 25(9):1049–1079CrossRefGoogle Scholar
  48. Potvin P, Hasni A (2014) Analysis of the decline in interest towards school science and technology from grades 5 through 11. J Sci Educ Technol 23(6):784–802CrossRefGoogle Scholar
  49. 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
  50. Sundberg MD, Dini ML, Li E (1994) Decreasing course content improves student comprehension and attitudes toward science in freshman biology. J Res Sci Teach 31:679–693CrossRefGoogle Scholar
  51. Super DE (1969) Vocational development theory. Couns Psychol I:2–30CrossRefGoogle Scholar
  52. Tai RH, Liu QC, Maltese AV, Fan X (2006) Planning early for careers in science. Science 312:1143–1144CrossRefGoogle Scholar
  53. Talton EL, Simpson RD (1987) Relationships of attitude toward classroom environments with attitude toward and achievement in science among tenth grade biology students. J Res Sci Teach 24(6):507–525CrossRefGoogle Scholar
  54. 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
  55. United States Department of Education (2006) The condition of education. National Center for Education Statistics, US Government Printing Office, WashingtonGoogle Scholar
  56. Walton GM, Spencer SJ (2009) Latent ability: grades and test scores systematically underestimate the intellectual ability of negatively stereotyped students. Psychol Sci 20(9):1132–1139CrossRefGoogle Scholar
  57. Zaichkowsky JL (1985) Measuring the involvement construct. J Consum Res 12(3):341–352CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Institute for the Integration of Technology into Teaching and LearningUniversity of North TexasDentonUSA

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