Stem learning in primary education by means of highly visualised digital applications

Autor: Fanchamps, L.J.A., Kreijns, C.
Přispěvatelé: Gómez Chova, Luis, López Martinez, Augustín, Candel Torres, Ignacio
Jazyk: angličtina
Rok vydání: 2022
Zdroj: Fanchamps, L J A & Kreijns, C 2022, Stem learning in primary education by means of highly visualised digital applications . in L Gómez Chova, A López Martinez & I Candel Torres (eds), INTED 2022 Proceedings : 16th annual International Technology, Education and Development Conference . IATED Academy, Valencia, pp. 3050-3058, 16th International Technology, Education and Development Conference, Valencia, Spain, 7/03/22 . https://doi.org/10.21125/inted.2022
Popis: Understanding core concepts underlying science, technology, engineering and mathematics (STEM) is an important focus area for students in primary education. However, research showed a number of issues surrounding STEM education undermining its effectivity. These issues pertain to students’ lack of motivation for STEM subjects, the pre- and misconceptions regarding STEM processes, and the application of knowledge and skills in every day practice. Therefore, the STEM learning environment must invite, should illustrate and facilitate learning while removing preconceptions and avoid misconceptions. Furthermore, integrating meaningful, attractive materials can motivate students in STEM subjects. This sets demands on the STEM learning environment to offer students the opportunity to acquire knowledge that can be directly transferred to everyday practice in an easily accessible manner. To this end, we purport that digital learning environments that take a visual approach to STEM processes in which underlying variables can be controlled and manipulated via a computer interface can generate positive STEM learning outcomes. The current study investigated whether highly visual STEM learning environments can represent STEM-concepts and -processes in such a way that students understand how one variable affects the other.One hundred primary school students were recruited as participants for our study conducted in the second half of 2020. They were assigned to two experimental groups and a control group. The first experimental group used the STEM visual learning environment as implemented by the rather innovative Flui.Go digital environment. The second experimental group used a commercial science box. The control group had the tradition form of STEM education. Students’ attitude towards technology, students’ fascination and valuing science, and understanding of science and physics concepts were measured at the start and after the intervention.The findings indicated that the Flui.Go group developed and improved skills that elevated the positive effects provided by using a digital STEM-learning environment and, by means of its highly visualized character, were able to optimize the link between theory and practice. Flui.Go caused a progression in scientific thinking and enhanced the use of a systematic approach in addition to an increased inspiration for science and technology. Flui.Go also motivated students to maintain focus and enthusiasm for a longer period of time as well as an increased level of involvement and creativity, with productive collaboration and strong responsibility. The findings also revealed that there was for both experimental groups an increase on all dependent variables when compared with the control group. In addition, a significant effect was established due to the influence of Flui.Go on students' attitudes towards technology. This in a direct comparison with students who applied the commercial science box. Finally, Flui.Go established a strong increase in students' fascination and appreciation for science as well as in their understanding of scientific and physical concepts.Our conclusion is that the findings of our study can help teachers to increase their knowledge, skills and pedagogical approach in order to effectively apply and implement digital STEM education using a highly visual environment during their lessons.
Databáze: OpenAIRE