Effects of a summer robotics camp on students’ STEM career interest and knowledge structure
Ahmet Tekbıyık 1 * , Demet Baran Bulut 2, Yalçın Sandalcı 3
More Detail
1 Department of Science Education, Kahramanmaraş Sütçü İmam University, Kahramanmaraş, Turkey
2 Department of Mathematics Education, Recep Tayyip Erdogan University, Rize, Turkey
3 Fatma Nuri Erkan Science and Art School, Ministry of National Education, Turkey
* Corresponding Author

Abstract

The present study focuses on the assessment of summer robotics camp designed for 7th grade students who were supposed to work on a STEM-related problem through modeling and design activities. It was exclusively investigated the effects of these activities on the STEM-related career interests and knowledge structures of students. The students were expected to develop basic robotics and design skills in the camp, and to use them in project design in the context of problem solving processes. The camp activities were designed in the alignment of P3 Task Taxonomy. A mixed design method was adapted in this study as it focused both on the effects of an experimental intervention and identification of the students’ conceptual constructs. Accordingly, simultaneous and sequential data collection techniques were used to provide satisfactory responses to the research questions. The results showed that the students the students’ career interest in engineering increased more significantly than the other STEM fields. Furthermore, word association tests that were applied before and after the camp, in order to assess the change in the students’ knowledge structures with the keywords Coding, Design, Problem, Modeling, Space, and Robot showed that the number of terms associated with these keywords were increased. In a nutshell, the education activity provided in the context of this study reinforced the students’ career interests in engineering in particular, and facilitated the development of their knowledge structures, and ability to define associations between terms.

Keywords

References

  • Ayar, M., Yalvac, B., Uğurdağ, H. F., & Şahin, A. (2013). A robotics summer camp for high school students: pipelines activities promoting careers in engineering fields. In 2013 ASEE Annual Conference. American Society for Engineering Education.
  • Bahar, M., Johnstone, A. H., & Sutcliffe. R. G. (1999). Investigation of students’ cognitive structure in elementary genetics through word association tests. Journal of Biological Education, 33, 134-141. https://doi.org/10.1080/00219266.1999.9655653
  • Barak, M., & Assal M. (2018). Robotics and STEM learning: students’ achievements in assignments according to the p3 task taxonomy-practice, problem solving, and projects. International Journal of Technology and Design Education, 28(1), 121-144. https://doi.org/10.1007/s10798‐016‐9385‐9
  • Ben-Chaim, D., Lappan, G., & Houang, R. T. (1988). The Effect of instruction on spatial visualization skills of middle school boys and girls. American Educational Research Journal, 25, 51-71. https://doi.org/10.3102/00028312025001051
  • Benitti, F. B. V. (2012). Exploring the educational potential of robotics in schools: A systematic review. Computers & Education, 58(3), 978-988. https://doi.org/10.1016/j.compedu.2011.10.006
  • Bischoff, P. J., Avery, L., Golden, C. F., & French, P. (2010). An analysis of knowledge structure, diversity and diagnostic abilities among pre-service science teachers within the domain of oxidation and reduction chemistry. Journal of Science Teacher Education, 21(4), 411–429. https://doi.org/10.1007/s10972-010-9188-x
  • Bodner, G. M. (2007). Strengthening conceptual connections in introductory chemistry courses. Chemistry Education Research and Practice, 8, 93-100. https://doi.org/10.1039/B4RP90007C
  • Cachapuz, A. F. C., & Maskill R. (1987). Detecting changes with learning in the organization of knowledge: Use of word association test to follow the learning of collision theory. International Journal of Science Education, 9, 491-504. https://doi.org/10.1080/0950069870090407
  • Carbonaro, M., Rex, M., & Chambers, J. (2004). Using LEGO robotics in a project-based learning environment. The Interactive Multimedia Electronic Journal of Computer-Enhanced Learning, 6(1). http://www.imej.wfu.edu/articles/2004/1/02/index.asp
  • Castledine, A. R., & Chalmers, C. (2011). LEGO Robotics: An authentic problem solving tool? Design and Technology Education: An International Journal, 16(3), 19-27.
  • Ching, Y. H., Yang, D., Wang, S., Baek, Y., Swanson, S., & Chittoori, B. (2019). Elementary school student development of STEM attitudes and perceived learning in a STEM integrated robotics curriculum. TechTrends, 63(5), 590-601. https://doi.org/10.1007/s11528-019-00388-0
  • Christidou, V. (2006). Greek students’ science-related interests and experiences: Gender differences and correlations. International Journal of Science Education, 28(10), 1181-1199. https://doi.org/10.1080/09500690500439389
  • Clariana, R. B. (2010). Multi-decision approaches for eliciting knowledge structure. In D. Ifenthaler, P. Pirnay-Dummer, & N. M. Seel (Eds.), Computer-based diagnostics and systematic analysis of knowledge (pp. 41-59). Springer. https://doi.org/10.1007/978-1-4419-5662-0_4
  • Cole, M., Cohen, C., Wilhelm, J., & Lindell, R. (2018). Spatial thinking in astronomy education research. Physical Review Physics Education Research, 14, 010139. https://doi.org/10.1103/PhysRevPhysEducRes.14.010139
  • Conrad, J., Polly, D., Binns, I., & Algozzine, B. (2018). Student perceptions of a summer robotics camp experience: The clearing house. Journal of Educational Strategies, 91(3), 131-139. https://doi.org/10.1080/00098655.2018.1436819
  • Creswell, J. W., & Plano Clark, V. L. (2007). Designing and conducting mixed methods research. Sage.
  • Dabney, K. P., Tai, R. H., Almarode, J. T., Miller-Friedmann, J. L., Sonnert, G., Sadler, P. M., & Hazari, Z. (2012). Out-of-school time science activities and their association with career interest in STEM. International Journal of Science Education, Part B, 2(1), 63-79. https://doi.org/10.1080/21548455.2011.629455
  • Dave, V., Blasko, D., Holliday-Darr, K., Kremer, J. T., Edwards, R., Ford, M., & Hido, B. (2010). Re-enJEANeering STEM Education: Math options summer camp. Journal of Technology Studies, 36(1), 35-45.
  • Davis, K. B., & Hardin, S. E. (2013). Making STEM fun: How to organize a STEM camp. Teaching Exceptional Children,45(4), 60–67. https://doi.org/10.1177/004005991304500408
  • Fleron, J. F. (2009). Google SketchUp: A powerful tool for teaching, learning and applying geometry. Retrieved from http://www.wsc.ma.edu/math/prime/concrete.ideas/GSUPaperNCTM.pdf
  • Furner, J., & Kumar, D. (2007). The mathematics and science integration argument: a stand for teacher education. Eurasia Journal of Mathematics, Science and Technology, 3(3), 185-189. https://doi.org/10.12973/ejmste/75397
  • Gulacar, O., Sinan, O., Bowman, C. R., & Yildirim, Y. (2015). Exploring the changes in students’ understanding of the scientific method using word associations. Research in Science Education, 45(5), 717-726. https://doi.org/10.1007/s11165-014-9443-9
  • Hammack, R., Ivey, T. A., Utley, J., & High, K. A. (2015). Effect of an engineering camp on students’ perceptions of engineering and technology. Journal of Pre-College Engineering Education Research, 5(2), 1-12. https://doi.org/10.7771/2157-9288.1102
  • Hayden, K., Ouyang, Y., Scinski, L., Olszewski, B., & Bielefeldt, T. (2011). Increasing student interest and attitudes in STEM: Professional development and activities to engage and inspire learners. Contemporary Issues in Technology and Teacher Education, 11(1), 47-69.
  • Johnstone, A. H., & Moynihan T. F. (1985). The relationship between performances in word association tests and achievement in chemistry. European Journal of Science Education, 7, 57-66. https://doi.org/10.1080/0140528850070106
  • Kastelan, I., Benito, J. R. L., Gonzalez, E. A., Piwinski, J., Barak, M., & Temerinac, M. (2014). E2LP: A unified embedded engineering learning platform. Microprocessors and Microsystems, 38(8), 933-946. https://doi.org/10.1016/j.micpro.2014.09.003
  • Kier, M. W., Blanchard, M. R., Osborne, J. W., & Albert, J. L. (2014). The development of the STEM career interest survey (STEM-CIS). Research in Science Education, 44(3), 461-481. https://doi.org/10.1007/s11165-013-9389-3
  • Kim, K., & Tawfik, A. A. (2021). Different approaches to collaborative problem solving between successful versus less successful problem solvers: Tracking changes of knowledge structure. Journal of Research on Technology in Education. https://doi.org/10.1080/15391523.2021.2014374
  • Kopcha, T. J., McGregor, J., Shin, S., Qian, Y., Choi, J., Hill, R., Mativo, J., & Choi, I. (2017). Developing an integrative STEM curriculum for robotics education through educational design research. Journal of Formative Design in Learning, 1(1), 31-44. https://doi.org/10.1007/s41686-017-0005-1
  • Koyunlu-Unlu, Z., Dokme, I., & Unlu, V. (2016). Adaptation of the science, technology, engineering, and mathematics career interest survey (STEM-CIS) into Turkish. Eurasian Journal of Educational Research, 63, 21-36. http://dx.doi.org/10.14689/ejer.2016.63.2
  • Kurtulus, A., & Uygan, C. (2010). The Effects of google SketchUp based geometry activities and projects on spatial visualization ability of student mathematics teachers. Procedia Social and Behavioral Sciences, 9, 384-389. https://doi.org/10.1016/j.sbspro.2010.12.169
  • Lavonen, J., Gedrovics, J., Byman, R, Meisalo, V., Juuti, K., & Uitto, A. (2008). Students’ motivational orientations and career choice in science and technology: A comparative investigation in Finland and Latvia. Journal of Baltic Science Education, 7(2), 86-102.
  • Lord, T. R. (1985). Enhancing the visuo‐spatial aptitude of students. Journal of Research in Science Teaching, 5, 395-405. https://doi.org/10.1002/tea.3660220503
  • Luo, W., Wei, H.-R., Ritzhaupt, A. D., Huggins-Manley, A. C., & Gardner-McCune, C. (2019). Using the S-STEM survey to evaluate a middle school robotics learning environment: Validity evidence in a different context. Journal of Science Education and Technology, 28, 429-443. https://doi.org/10.1007/s10956-019-09773-z
  • Meyer, M., Cimpian, A., & Leslie, S. J. (2015). Women are underrepresented in fields where success is believed to require brilliance. Frontiers in Psychology, 6,235. https://doi.org/10.3389/fpsyg.2015.00235
  • Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. Sage.
  • Miller, K., Sonnert, G., & Sadler. P. (2017). The influence of students’ participation in stem competitions on their interest in STEM careers. International Journal of Science Education Part B, 8(2), 95-114.
  • Ministry of National Education (2018). Turkish elementary science curriculum (Grades for 3-8).Author. Retrieved on June 28, from http://mufredat.meb.gov.tr
  • Mohr-Schroeder, M. J., Jackson, C., Miller, M., Walcott, B., Little, D. L., Speler, L., Schooler, W., & Schroeder, D. C. (2014). Developing middle school students' interests in STEM via summer learning experiences: See blue STEM Camp. School Science and Mathematics, 114(6), 291-301. https://doi.org/10.1111/ssm.12079
  • Murdock, K. L. (2009). Google SketchUp and SketchUp Pro 7 Bible. Wiley.
  • Nadelson, L. S., & Seifert, A. L. (2017). Integrated STEM defined: Context, challenges, and the future. The Journal of Educational Research, 110(3), 221-223. https://doi.org/10.1080/00220671.2017.1289775
  • Nakiboglu, C. (2008). Using word associations for assessing non major science students’ knowledge structure before and after general chemistry instruction: the case of atomic structure. Chemistry Education Research and Practice, 9, 309-322. https://doi.org/10.1039/B818466F
  • National Research Council (2011). Successful K-12 STEM education: Identifying effective approaches in science, technology, engineering, and mathematics. National Academies Press.
  • NGSS Lead States. (2013). Next Generation Science Standards: For states, by states. The National Academies Press.
  • Nugent, G., Barker, B., Grandgenett, N., & Welch, G. (2016). Robotics camps, clubs, and competitions: Results from a US robotics project. Robotics and Autonomous Systems, 75, 686-691. https://doi.org/10.1016/j.robot.2015.07.011
  • Ortiz, A. M., Bos, B., & Smith, S. (2015). The power of educational robotics as an integrated STEM learning experience in teacher preparation programs. Journal of College Science Teaching, 44(5), 42-47.
  • Pett, M. A. (1997). Nonparametric statistics for health care research. Sage.
  • Plant, A. E., Baylor, A. L., Doerr, C. E., & Rosenberg-Kima, R. B. (2009). Changing middle-school students’ attitudes and performance regarding engineering with computer-based social models. Computers and Education, 53, 209-215. https://doi.org/10.1016/j.compedu.2009.01.013
  • Prokop, P., Prokop, M., & Tunnicliffe, S. D. (2007). Is biology boring? Student attitudes toward biology. Journal of Biological Education, 42(1), 36-39. https://doi.org/10.1080/00219266.2007.9656105
  • Rafi, A., Samsudin, K. A., & Said, C. S. (2008). Training in spatial visualization: the effects of training method and gender. Educational Technology and Society, 11(3), 127-140.
  • Sen, C., Ay, Z. S., & Kiray, S. A. (2021). Computational thinking skills of gifted and talented students in integrated STEM activities based on the engineering design process: The case of robotics and 3D robot modeling. Thinking Skills and Creativity, 42, 100931. https://doi.org/10.1016/j.tsc.2021.100931
  • Sha, L., Schunn, C., & Bathgate, M. (2015). Measuring choice to participate in optional science learning experiences during early adolescence. Journal of Research in Science Teaching 52, 686-709. https://doi.org./10.1002/tea.21210
  • Shavelson, R. J. (1972). Some aspects of the correspondence between content structure and cognitive structure in physics instruction. Journal of Educational Psychology, 63, 225-234. https://doi.org/10.1037/h0032652
  • Stubbs, K., Casper, J., & Yanco, H. A. (2014). Designing evaluations for K-12 robotics education programs. In M. Khosrow-Pour (Ed.), K-12 education: concepts, methodologies, tools, and applications (pp. 1342-1364). IGI Global.
  • Tai, R., Liu, C., Maltese, A., & Fan, X. (2006). Planning early for careers in science. Science, 312(5777), 1143-1144. https://doi.org/10.1126/science.1128690
  • Thibaut, L., Ceuppens, S., De Loof, H., De Meester, J., Goovaerts, L., Struyf, A., Boeve-de Pauw, j., Dehaene, W., Deprez, J., De Cock, M., Hellinckx, L., Knipprath, H., Langie, G., Struyven, K., Van de Velde, D., Van Petegem, P., & Depaepe, F. (2018). Integrated STEM education: A systematic review of instructional practices in secondary education. European Journal of STEM Education, 3(1),1-12.
  • Wyss, V. L., Heulskamp, D., & Siebert, C. J. (2012). Increasing middle school student interest in stem careers with videos of scientists. International Journal of Environmental and Science Education, 7(4), 501-522. https://doi.org/10.20897/ejsteme/85525
  • Yan, J., Li, L., & Yin, J. (2020). Effects of MSTI summer camp program on students’ perception on STEM learning. Journal of STEM Education: Innovations and Research, 20(2), 58-64.
  • Yuen, T., Boecking, M., Stone, J., Tiger, E. P., Gomez, A., Guillen, A., & Arreguin, A. (2014). Group tasks, activities, dynamics, and interactions in collaborative robotics projects with elementary and middle school children. Journal of STEM Education, 15(1), 39-45.
  • Zhong, B., Zheng, J., & Zhan, Z. (2020). An exploration of combining virtual and physical robots in robotics education. Interactive Learning Environments. https://doi.org/10.1080/10494820.2020.1786409

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.