Skip to main content

Advertisement

SpringerLink
Log in

An analysis of the impact of student–scientist interaction in a technology design activity, using the expectancy-value model of achievement related choice

  • Published:
International Journal of Technology and Design Education Aims and scope Submit manuscript

Abstract

Many education initiatives in science and technology education aim to create enthusiasm among young people to pursue a career in Science, Technology, Engineering, and Mathematics (STEM). Research suggests that personal interaction between secondary school students and scientists could be a success factor, but there is a need for more in-depth research on the actual effects of science education initiatives. This paper describes an in-depth, qualitative assessment of a technology design activity, using as a theoretical framework the expectancy-value model of academic choice Eccles and Wigfield (Annu Rev Psychol 53:109–132, 2002). A core element in the studied education initiative is the interaction between secondary school students and scientists. Semi-structured interviews were conducted with participating students and analysed qualitatively to disentangle the factors in their motivation to participate in this initiative and their experiences and memories gathered during participation. Last, this paper reflects on the use of the expectancy-value model for in-depth assessments of science education initiatives. Results show that interest-enjoyment values and attainment values are most important in the students’ motivation to participate in the studied activity. These values are connected to educational principles of authentic practice, and of providing meaningful contexts for scientific concepts. Furthermore, results show that the interaction between students and scientists is not automatically a success factor. Disappointment in this interaction, can cast a shadow on students’ whole experience. This leads us to propose to include an additional factor in the expectancy-value model of achievement related choice: educational environment, including ‘personal interaction’ as an element. Adding this factor would—in our opinion—create an even better framework for in-depth assessment of science education initiatives.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Bennett, J., Hogarth, S., & Lubben, F. (2003). A systematic review of the effects of context-based and Science-Technology-Society (STS) approaches in the teaching of secondary science. London: EPPI-Centre, Social Science Research Unit Institute of Education University of London.

    Google Scholar 

  • Bøe, M. V., Henriksen, E. K., Lyons, T., & Schreiner, C. (2011). Participation in science and technology: Young people’s achievementrelated choices in late-modern societies. Studies in Science Education, 47(1), 37–72. doi:10.1080/03057267.2011.549621.

    Article  Google Scholar 

  • Boeije, H. (2010). Analysis in qualitative research. London: SAGE Publications.

    Google Scholar 

  • Braund, M., & Reiss, M. (2006). Towards a more authentic science curriculum: The contribution of out-of-school learning. International Journal of Science Education, 28(12), 1373–1388. doi:10.1080/09500690500498419.

    Article  Google Scholar 

  • Cohen, L., Manion, L., & Morrisson, K. (2007). Research methods in education (6th ed.). London: Routledge.

    Google Scholar 

  • Deci, E. L., Ryan, R. M., & Leonard, B. (1980). The empirical exploration of intrinsic motivational processes. Advances in experimental social psychology (Vol. 13, pp. 39–80): Academic Press.

  • Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109–132.

    Article  Google Scholar 

  • Herrington, J., Reeves, T. C., Oliver, R., & Woo, Y. (2004). Designing authentic activities in web-based courses. Journal of Computing in Higher Education, 16(1), 3–29.

    Article  Google Scholar 

  • Jenkins, E., Jensen, F., & Henriksen, E. K. (2010). IRIS working document no. 5.1: Recruitment initiatives and choice of STEM higher education: Review of theoretical perspectives and empirical findings regarding recruitment initiatives inside and outside school (IRIS, Trans.) (pp. 59).

  • Jones, G., Taylor, A., & Forrester, J. H. (2011). Developing a scientist: A retrospective look. International Journal of Science Education, 33(12), 1653–1673. doi:10.1080/09500693.2010.523484.

    Article  Google Scholar 

  • Meece, J., Wigfield, A., & Eccles, J. (1990). Predictors of math anxiety and its influence on young adolescents’ course enrollment intentions and performance in mathematics. Journal of Educational Psychology, 82(1), 60–70.

    Article  Google Scholar 

  • OECD. (2008). Encouraging student interest in science and technology studies OECD (Ed.) (pp. 134). Retrieved from http://www.keepeek.com/Digital-Asset-Management/oecd/science-and-technology/encouraging-student-interest-in-science-and-technology-studies_9789264040892-en doi:10.1787/9789264040892-en.

  • QSR International Pty Ltd. (2010). NVivo qualitative data analysis software (version 9).

  • Rutherford, F. J. (1993). Hands-on: A means to an end. 2061 Today, 3(1), 5.

  • Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development and well-being. American Psychologist, 55(1), 68–78.

    Article  Google Scholar 

  • Sadler, T. D., Burgin, S., McKinney, L., & Ponjuan, L. (2010). learning science through research apprenticeships: A critical review of the literature. Journal of Research in Science Teaching, 47(3), 235–256.

    Google Scholar 

  • Salas-Morera, L., Cejas-Molina, M., Olivares-Olmedilla, J., Climent-Bellido, M., Leva-Ramírez, J., & Martínez-Jiménez, P. (2012). Improving engineering skills in high school students: a partnership between university and K-12 teachers. International Journal of Technology and Design Education,. doi:10.1007/s10798-012-9223-7.

    Google Scholar 

  • Schuurbiers, D., Blomjous, M., Osseweijer, P. (2006). chapter in In J. M. C. Donhong & B. Schiele (Eds.), At the human scale: international practices in science communication. Bejing: Science Press Beijing.

  • Silverman, D. (2006). Interpreting qualitative data—Methods for analyzing talk, text and interaction (3rd ed.). Londen: SAGE Publication.

    Google Scholar 

  • Snape, P., & Fox-Turnbull, W. (2013). Perspectives of authenticity: Implementation in technology education. International Journal of Technology and Design Education, 23(1), 51–68. doi:10.1007/s10798-011-9168-2.

    Article  Google Scholar 

  • Stake, R. E. (1995). The art of case study research. Thousand Oaks, CA: SAGE Publications Inc.

    Google Scholar 

  • Wall, K. (2010). United Nations Educational Scientific and Cultural Organization. Engineering: Issues challenges and opportunities for development. Paris: UNESCO (United Nations EducationalScientific and Cultural Organization).

  • Wigfield, A., & Eccles, J. S. (1992). The development of achievement task values—A theoretical analysis. Developmental Review, 12(3), 265–310. doi:10.1016/0273-2297(92)90011-P.

    Article  Google Scholar 

  • Wigfield, A., & Eccles, J. S. (2002). The development of competence beliefs, expectancies for succes, and achievement values from childhood through adolescence. In A. Wigfield & J. Eccles (Eds.), Development of achievement motivation (pp. 91–120). San Diego: Academic press.

    Chapter  Google Scholar 

Download references

Acknowledgments

This article is part of a PhD-research project of the CSG Centre for Society and Life Sciences carried out within the research programme of the Kluyver Centre for Genomics of Industrial Fermentation in The Netherlands at the Delft University of Technology, Department of Biotechnology, Section Biotechnology and Society (BTS), funded by the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO).

Author information

Authors and Affiliations

  1. Section Biotechnology and Society, Department of Biotechnology, Faculty of Applied Sciences, Delft University of Technology, Julianalaan 67, 2628 BC, Delft, The Netherlands

    Anne-Lotte Masson, Tanja Klop & Patricia Osseweijer

Authors
  1. Anne-Lotte Masson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tanja Klop
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Patricia Osseweijer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anne-Lotte Masson.

Appendix: questions for students

Appendix: questions for students

General information: to be filled in by interviewer

Name:

Project:

Year of participation:

Supervisor from school:

Participating scientist:

Number of students in group:

Reached the finals: yes/no

Won the finals: yes/no

  1. 1.

    How did you find out about Imagine?

    1. a.

      Why did you choose to participate?

    2. b.

      Did you consider other options for your general end-project?

  2. 2.

    How did you choose your topic from the list of proposals?

    1. a.

      Did you search for information on the different topics before making a decision?

    2. b.

      Did you discuss your choice with your supervisor from school?

  3. 3.

    How did you choose which developing country to situate your project in?

    1. a.

      How did you find the information you needed?

    2. b.

      Did you find this difficult?

    3. c.

      Did you like this element?

    4. d.

      Did anyone help you with this (teachers, scientist)?

  4. 4.

    Can you tell me what happened during the practical experiment?

    1. a.

      What kind of experiment did you do?

    2. b.

      How did you come up with the idea to do that experiment?

    3. c.

      Where did you carry out the experiment?

    4. d.

      Who helped you (the most) in this?

  5. 5.

    Can you tell me about the interaction with the scientist?

  6. 6.

    Can you tell me about your planning and the cooperation within the group?

    1. a.

      How was the work divided?

    2. b.

      How did you put all the pieces together?

  7. 7.

    What are the demands for a general end-project at your school (hours, subjects, number of students)?

  8. 8.

    Do you see a difference between your work and other students who did a ‘normal’ general end-project?

  9. 9.

    How much time did you invest in Imagine?

    1. a.

      Was this comparable to other students?

  10. 10.

    What did you like best in Imagine?

    1. a.

      Why?

  11. 11.

    What did you like least?

    1. a.

      Why?

  12. 12.

    What did you learn from doing Imagine?

  13. 13.

    What would you change in Imagine?

    1. a.

      Why?

  14. 14.

    What did you do at school besides the regular mandatory lessons (students council etc.)?

  15. 15.

    What do you think of when you think of biotechnology/Life Sciences?

    1. a.

      Can you give me an example from everyday life?

    2. b.

      Do you think there was biotechnology/Life Sciences in your project?

    3. c.

      Has participating in Imagine changed your image of biotechnology/Life Sciences?

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Masson, AL., Klop, T. & Osseweijer, P. An analysis of the impact of student–scientist interaction in a technology design activity, using the expectancy-value model of achievement related choice. Int J Technol Des Educ 26, 81–104 (2016). https://doi.org/10.1007/s10798-014-9296-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10798-014-9296-6

Keywords

Search

Navigation