266
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Robot illustrated: Exploring elementary students’ perceptions of robots via the draw-a-robot test

ORCID Icon, ORCID Icon, &
Received 26 Feb 2023, Accepted 28 Jun 2023, Published online: 11 Jul 2023

References

  • Appel, M., Izydorczyk, D., Weber, S., Mara, M., & Lischetzke, T. (2020). The uncanny of mind in a machine: Humanoid robots as tools, agents, and experiencers. Computers in Human Behavior, 102, 274–286. https://doi.org/10.1016/j.chb.2019.07.031
  • 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
  • Burdett, E. R. R., Ikari, S., & Nakawake, Y. (2022). British children’s and adults’ perceptions of robots. Human Behavior and Emerging Technologies, 2022, 1–16. https://doi.org/10.1155/2022/3813820
  • Capobianco, B. M., Diefes-Dux, H. A., Mena, I., & Weller, J. (2011). What is an Engineer? Implications of elementary school student conceptions for engineering education. Journal of Engineering Education, 100(2), 304–328. https://doi.org/10.1002/j.2168-9830.2011.tb00015.x
  • Carless, D., & Lam, R. (2014). The examined life: Perspectives of lower primary school students in Hong Kong. Education 3-13, 42(3), 313–329. https://doi.org/10.1080/03004279.2012.689988
  • Chambers, D. W. (1983). Stereotypic images of the scientist: The draw-a-scientist test. Science Education, 67(2), 255–265. https://doi.org/10.1002/sce.3730670213
  • Chang, H.-Y., Lin, T.-J., Lee, M.-H., Lee, S. W.-Y., Lin, T.-C., Tan, A.-L., & Tsai, C.-C. (2020). A systematic review of trends and findings in research employing drawing assessment in science education. Studies in Science Education, 56(1), 77–110. https://doi.org/10.1080/03057267.2020.1735822
  • Chen, Y., Zhang, X., Bao, Y., & Hu, L. (2022). Exploring elementary students’ perceptions of robots: The draw-a-robot test. In 2022 4th International Conference on Computer Science and Technologies in Education (CSTE). https://doi.org/10.1109/CSTE55932.2022.00052
  • Chu, S.-T., Hwang, G.-J., & Tu, Y.-F. (2022). Artificial intelligence-based robots in education: A systematic review of selected SSCI publications. Computers and Education, 3, 100091. https://doi.org/10.1016/j.caeai.2022.100091
  • Cox, M. V., & Parkin, C. E. (1986). Young children’s human figure drawing: Cross-sectional and longitudinal studies. Educational Psychology, 6(4), 353–368. https://doi.org/10.1080/0144341860060405
  • Duit, R. (1996). Preconceptions and misconceptions. In De Corte, E., & Weinert, F. (Eds.), International encyclopedia of developmental and instructional psychology (pp. 455–459). Elsevier.
  • Edwards, A., Edwards, C., Spence, P. R., Harris, C., & Gambino, A. (2016). Robots in the classroom: Differences in students’ perceptions of credibility and learning between “teacher as robot” and “robot as teacher. Computers in Human Behavior, 65, 627–634. https://doi.org/10.1016/j.chb.2016.06.005
  • Edwards, A., Edwards, C., Westerman, D., & Spence, P. R. (2019). Initial expectations, interactions, and beyond with social robots. Computers in Human Behavior, 90, 308–314. https://doi.org/10.1016/j.chb.2018.08.042
  • Eklund-Myrskog, G. (1998). Students’ conceptions of learning in different educational contexts. Higher Education, 35(3), 299–316. https://doi.org/10.1023/A:1003145613005
  • Finson, K. D., Beaver, J. B., & Cramond, B. L. (1995). Development and field test of a checklist for the draw-a-scientist test. School Science and Mathematics, 95(4), 195–205. https://doi.org/10.1111/j.1949-8594.1995.tb15762.x
  • Gunes, H., & Kucuk, S. (2022). A systematic review of educational robotics studies for the period 2010–2021. Review of Education, 10(3), 3381. https://doi.org/10.1002/rev3.3381
  • Haney, W., Russell, M., & Bebell, D. (2004). Drawing on education: Using drawings to document schooling and support change. Harvard Educational Review, 74(3), 241–272. https://doi.org/10.17763/haer.74.3.w0817u84w7452011
  • Haring, K. S., Mougenot, C., Ono, F., & Watanabe, K. (2014). Cultural differences in perception and attitude towards robots. International Journal of Affective Engineering, 13(3), 149–157. https://doi.org/10.5057/ijae.13.149
  • Harrison, L. J., Clarke, L., & Ungerer, J. A. (2007). Children’s drawings provide a new perspective on teacher–child relationship quality and school adjustment. Early Childhood Research Quarterly, 22(1), 55–71. https://doi.org/10.1016/j.ecresq.2006.10.003
  • Hsieh, W.-M., & Tsai, C.-C. (2018). Learning illustrated: An exploratory cross-sectional drawing analysis of students’ conceptions of learning. The Journal of Educational Research, 111(2), 139–150. https://doi.org/10.1080/00220671.2016.1220357
  • Hsieh, W.-M., & Tsai, C.-C. (2017). Exploring students’ conceptions of science learning via drawing: A cross-sectional analysis. International Journal of Science Education, 39(3), 274–298. https://doi.org/10.1080/09500693.2017.1280640
  • Hsin, C.-T., Liang, J.-C., Hsu, C.-Y., Shih, M., Sheu, F.-R., & Tsai, C.-C. (2019). Young children’s conceptions of learning: A cross-sectional study of the early years of schooling. The Asia-Pacific Education Researcher, 28(2), 127–137. https://doi.org/10.1007/s40299-018-0419-9
  • Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159. https://doi.org/10.2307/2529310
  • Lee, M.-H., Johanson, R. E., & Tsai, C.-C. (2008). Exploring Taiwanese high school students’ conceptions of and approaches to learning science through a structural equation modeling analysis. Science Education, 92(2), 191–220. https://doi.org/10.1002/sce.20245
  • Liu, M., & Chiang, F.-K. (2020). Middle school students’ perceptions of engineers: A case study of Beijing students. International Journal of Technology and Design Education, 30(3), 479–506. https://doi.org/10.1007/s10798-019-09513-9
  • Mallik, A., Sabouri, P., Ghosh, S., & Kapila, V. (2020). Assessing the effects of a robotics workshop with draw-a-robot test. In 2020 ASEE Virtual Annual Conference Content Access Proceedings. https://doi.org/10.18260/1-2–34182
  • Mead, M., & Métraux, R. (1957). Image of the scientist among high-school students. Science, 126(3270), 384–390. https://doi.org/10.1126/science.126.3270.384
  • Ministry of Education of the People’s Republic of China. (2020). Information technology curriculum standards for general high school (2020-year Edition). Retrieved from http://www.moe.gov.cn/srcsite/A26/s8001/202006/t20200603_462199.html
  • Ministry of Education of the People’s Republic of China. (2022). Information Technology Curriculum Standards for Compulsory Education (2022-year Edition). Retrieved from http://www.moe.gov.cn/srcsite/A26/s8001/202204/W020220420582361024968.pdf
  • National Center for Educational Technology. (2021). Artificial Intelligence and Literacy Framework for Elementary and Secondary Schools. Retrieved from https://www.ncet.edu.cn/u/cms/www/202112/24125027deqs.pdf
  • Ortega-Ruipérez, B., & Lázaro Alcalde, M. (2022). Teachers’ perception about the difficulty and use of programming and robotics in the classroom. Interactive Learning Environments, 2022, 1–12. https://doi.org/10.1080/10494820.2022.2061007
  • Papert, S. (1993). The children’s machine: Rethinking school in the age of the computer. Basic Books.
  • Piaget, J. (1971). Developmental stages and developmental processes. In D. R. Green, M. P. Ford, & G. B. Flamer (Eds.), Measurement and Piaget. McGraw-Hill.
  • Ray, C., Mondada, F., & Siegwart, R. (2008). What do people expect from robots? In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems. https://doi.org/10.1109/IROS.2008.4650714
  • Relkin, E., de Ruiter, L. E., & Bers, M. U. (2021). Learning to code and the acquisition of computational thinking by young children. Computers & Education, 169, 104222. https://doi.org/10.1016/j.compedu.2021.104222
  • Richardson, J. T. E. (1999). The concepts and methods of phenomenographic research. Review of Educational Research, 69(1), 53–82. https://doi.org/10.3102/00346543069001053
  • Sagala, R., Umam, R., Thahir, A., Saregar, A., & Wardani, I. (2019). The effectiveness of stem-based on gender differences: The impact of physics concept understanding. European Journal of Educational Research, 8(3), 753–761. https://doi.org/10.12973/eu-jer.8.3.753
  • Samaras, G., Bonoti, F., & Christidou, V. (2012). Exploring children’s perceptions of scientists through drawings and interviews. Procedia - Social and Behavioral Sciences, 46, 1541–1546. https://doi.org/10.1016/j.sbspro.2012.05.337
  • Savela, N., Turja, T., Latikka, R., & Oksanen, A. (2021). Media effects on the perceptions of robots. Human Behavior and Emerging Technologies, 3(5), 989–1003. https://doi.org/10.1002/hbe2.296
  • Schiff, D. (2022). Education for AI, not AI for Education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 32(3), 527–563. https://doi.org/10.1007/s40593-021-00270-2
  • Selwyn, N., Boraschi, D., & Özkula, S. M. (2009). Drawing digital pictures: An investigation of primary pupils’ representations of ICT and schools. British Educational Research Journal, 35(6), 909–928. https://doi.org/10.1080/01411920902834282
  • 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
  • Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158. https://doi.org/10.1016/j.edurev.2017.09.003
  • Steinke, J., Lapinski, M. K., Crocker, N., Zietsman-Thomas, A., Williams, Y., Evergreen, S. H., & Kuchibhotla, S. (2007). Assessing media influences on middle school–aged children’s perceptions of women in science using the draw-a-scientist test (DAST). Science Communication, 29(1), 35–64. https://doi.org/10.1177/1075547007306508
  • Su, J., & Yang, W. (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education, 3, 100049. https://doi.org/10.1016/j.caeai.2022.100049
  • Sullivan, A., & Bers, M. U. (2019). Investigating the use of robotics to increase girls’ interest in engineering during early elementary school. International Journal of Technology and Design Education, 29(5), 1033–1051. https://doi.org/10.1007/s10798-018-9483-y
  • Sullivan, A., & Bers, M. U. (2016). Girls, boys, and bots: Gender differences in young children’s performance on robotics and programming tasks. Journal of Information Technology Education: Innovations in Practice, 15, 145–165. https://doi.org/10.28945/3547
  • Sullivan, F. R. (2008). Robotics and science literacy: Thinking skills, science process skills and systems understanding. Journal of Research in Science Teaching, 45(3), 373–394. https://doi.org/10.1002/tea.20238
  • Symington, D., & Spurling, H. (1990). The ‘Draw a Scientist Test’: Interpreting the data. Research in Science & Technological Education, 8(1), 75–77. https://doi.org/10.1080/0263514900080107
  • Szczepanowski, R., Cichoń, E., Arent, K., Sobecki, J., Styrkowiec, P., Florkowski, M., & Gakis, M. (2020). Education biases perception of social robots. European Review of Applied Psychology, 70(2), 100521. https://doi.org/10.1016/j.erap.2020.100521
  • Trujillo Castro, A., Martínez Reyes, M., & Soberanes-Martín, A. (2022). Instructional design to foster computational thinking using educational robotics. In Research anthology on computational thinking, programming, and robotics in the classroom (pp. 60–78). IGI Global. https://doi.org/10.4018/978-1-6684-2411-7.ch004
  • Tsai, C.-C. (2004). Conceptions of learning science among high school students in Taiwan: A phenomenographic analysis. International Journal of Science Education, 26(14), 1733–1750. https://doi.org/10.1080/0950069042000230776
  • Tsai, C.-C., Jessie Ho, H. N., Liang, J.-C., & Lin, H.-M. (2011). Scientific epistemic beliefs, conceptions of learning science and self-efficacy of learning science among high school students. Learning and Instruction, 21(6), 757–769. https://doi.org/10.1016/j.learninstruc.2011.05.002
  • Wang, C., Shen, J., & Ran, H. (2022). Imagining robots of the future: Examining sixth-graders’ perceptions of robots through their literary products. Journal of Research on Technology in Education, 2022, 1–26. https://doi.org/10.1080/15391523.2022.2030264
  • Wang, H.-Y., & Tsai, C.-C. (2012). An exploration of elementary school students’ conceptions of learning: A drawing analysis. The Asia-Pacific Education Researcher, 21, 610–617.
  • Williams, R., Park, H. W., & Breazeal, C. (2019, May 2). A is for Artificial Intelligence. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3290605.3300677
  • Xia, L., & Zhong, B. (2018). A systematic review on teaching and learning robotics content knowledge in K-12. Computers & Education, 127, 267–282. https://doi.org/10.1016/j.compedu.2018.09.007
  • Xu, Z., Ritzhaupt, A. D., Umapathy, K., Ning, Y., & Tsai, C.-C. (2021). Exploring college students’ conceptions of learning computer science: A draw-a-picture technique study. Computer Science Education, 31(1), 60–82. https://doi.org/10.1080/08993408.2020.1783155
  • Yang, W. (2022). Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation. Computers and Education, 3, 100061. https://doi.org/10.1016/j.caeai.2022.100061
  • Yeh, H.-Y., Tsai, Y.-H., Tsai, C.-C., & Chang, H.-Y. (2019). Investigating students’ conceptions of technology-assisted science learning: A drawing analysis. Journal of Science Education and Technology, 28(4), 329–340. https://doi.org/10.1007/s10956-019-9769-1

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.