Using self-made automata to teach STEM in early childhood teacher education

In recent decades, an increasing number of countries have integrated science, technology, engineering, and mathematics (STEM) into their curricula for early childhood education and care (ECEC). In contrast to this trend, many ECEC professionals are still reluctant about the idea of teaching STEM to young children. A reason for this might be too little experience with and knowledge about STEM. One way to tackle this problem is to address STEM in ECEC teacher education in a way that is engaging, motivating, and practical, and shows ECEC student teachers appropriate ideas for how to teach STEM in a playful and child-centred way. This case study aims to present and analyse an innovative approach to ECEC teacher training. We let the student teachers build their own automata (toys that have mechanical moving parts) to promote a better understanding of STEM. The students were highly motivated, assessed the approach as exciting and relevant, and consequently could successfully reflect on STEM content and pedagogy.


Concrete Experience
We used automata, by which we mean toys that have mechanical moving parts. This object-based learning approach (Hardie, 2015) was undertaken with a class of 31 Norwegian ECEC student teachers in the third year of their bachelor studies. A short introduction was followed by three parallel 45 minute workshops each repeated three times. In the first workshop, with an art teacher, a group of students built a crocodile or dinosaur with a scissor-arm mechanism. In the second workshop, with a mathematics teacher, they built a car with a rubber band engine. In the third workshop, with a science teacher, they explored a self-made wind turbine attached to a winch to pull objects (see  The automata that we used with the ECEC teacher students: a crocodile with a scissor-arm mechanism, a rubber band car, and a wind turbine that powers a winch.

Reflective Observation and Abstract Conceptualisation
Schön (1983) distinguishes between reflection-in-action and reflection-on-action. During the workshops, we encouraged the students to reflect in action by asking questions. For example: 'what will children learn here about physics?', 'how can you support a child that has difficulties with this task?', 'how does your experience now affect your feelings about mathematics?'. In the plenary session after the workshops, students reflected on the action that they just had experienced. These are questions the students reflected on: 'what do you think about this activity?', 'is this applicable to young children?', 'what would you have done differently?', 'do you have ideas for other automata?'. The students then had to of arts and crafts in STEM (Queen Maud University College, 2019)). We subdivided these three general categories into more specific subcategories, for example STEM was divided into the four STEM subjects, and then each subject into the STEM phenomena related to that subject. Figure 2 shows an overview of all categories and subcategories. After we categorised the utterances, we counted different things (see Table 2 in the Appendix): (1) How many utterances belong to each category? (2) How many utterances in this category were made by every student on average, at least and at most? (3) How many students made utterances in this category?

Enjoyment and perceived usefulness
The mean of the subscale 'interest/enjoyment' was 5.9 (SD = 0.6, MIN = 4.8, MAX = 6.8) with a reliability (Cronbach's alpha) of 0.84. The item with the highest score was 'this training is fun to do'. The mean of the subscale 'perceived usefulness' was 5.7 (SD = 0.8, MIN = 4.0, MAX = 7.0) with a reliability (Cronbach's alpha) of 0.89. The item with the highest score was 'I believe that this training is useful for working with STEM in kindergarten and/or primary school'. Table 1 (see Appendix) shows the mean scores for each item. The reliability of both scales is good even though the sample size is rather small. All students enjoyed the half-day seminar and perceived it as interesting and useful for their future work. Along with Deci et al. (1994, p. 132), we found that the two scales are strongly correlated (r = 0.78, p < .001).

Students' reflections
We counted a total of 355 utterances. The minimum was 12, the maximum 35, and the average 19.7 utterances per student. Every student made at least four utterances about STEM. One student made as many as 24 utterances that were related to STEM. The average was 11.4 utterances per student. This category contained 58% of all utterances.
Another 36% of all utterances were about pedagogy. The remaining 6% were about other Thiel, Lundheim, Hanssen, Moe, Vaz Rebelo Using self-made automata to teach STEM in early childhood teacher education Journal of Learning Development in Higher Education, Issue 18: October 2020 7 subjects: arts and language. Not every student wrote about these subjects. 56% of the students wrote about arts and 39% wrote about language. The following example mentions arts and language in the same utterance: 'Children learn a lot through STEM activities. They learn language, practical artistic skills, and social competence' [Utt84].