Developing algorithmic thinking skills from an early age is becoming recognized as essential, together with computational thinking, creativity and problem-solving. Algorithmic thinking is defined as the ability to think in terms of clear and simple sequences, which might include conditions and repetitions, to solve a problem or understand a situation (Futschek, 2006; Sadykova & Il’bahtin, 2020). It can be connected to deep procedural knowledge, which involves understanding procedures, associated with comprehension, flexibility, and critical judgment (Lockwood et al., 2016). Algorithmic thinking is a key ability in Computer Science and Mathematics, but also in daily life. Teachers and curriculum developers are being challenged to foster algorithmic thinking skills starting from the preschool period (Strnad, 2018). An approach based on unplugged activities for introducing algorithmic thinking through play and games has been suggested, based on the analysis of national curricula for Early Childhood Education (Figueiredo et al., 2021). Despite the emphasis on introducing algorithmic thinking in Early Childhood Education, proposals for teacher education are still needed (Gencel et al., 2021). The project “Algorithmic Thinking Skills through Play-Based Learning for Future’s Code Literates”, under the European Union Erasmus+ Programme, is being developed by a consortium of institutions and organisations from Turkey, Italy, Portugal, Slovenia, and Croatia. Its activities include the preparation of a curriculum for integration of algorithmic thinking in preschool aimed at initial teacher education. The modules were conceived based on two main axes: a play-based approach, and the articulation between algorithmic thinking and the curricular areas of Early Childhood Education. The curriculum was developed by the partnership through a design-based research approach (Plomp et al., 2018) that included: preliminary research, development, and evaluation. The initial step was a needs analysis. The current situation regarding the integration of algorithmic thinking into Early Childhood Education in the partner countries was presented through a detailed literature review based on the descriptive needs analysis approach. Subsequently, online workshops were organised with the participation of preschool and ICT teachers, selected through purposive sampling. Teachers’ views were collected through discussions and written statements. The number of teachers participating in the workshops ranged from 46 to 200. A modular curriculum was prepared by using the data obtained through the literature reviews and the workshops. Each module presents learning outcomes, identification of content, teaching-learning activities, and assessment processes. Besides an external expert review, the evaluation includes piloting in each country. The partners have created the conditions for those pilots according to local structures and dynamics of Early Childhood Teacher Education. A minimum of 20 students will participate in the flipped learning courses in each country during the Spring semester of 2021/22. For the Portuguese case, Early Childhood Teacher Education happens at Masters/Postgraduate level, differently from all other partners (undergraduate). This has allowed the development of a second evaluation strategy. The students were invited to participate in Lesson Studies (Cajkler & Wood, 2016; Ponte et al., 2018) about algorithmic thinking in Early Childhood Education. This entailed creating a lesson plan, implementing it with a group of children (3-6 yo), and recording their learning. In a second step, the data collected was used for analysing the proposal and reformulating it accordingly. Next, the same cycle was undertaken with a different group of children for a second analysis of its potential and collection of children’s actions within the teaching (Figueiredo, Gomes, & Matos, 2021a). Each lesson study was developed by six students in a total of four lesson plans being evaluated.

This paper will analyse and report on the experience for the 24 Masters students in terms of: a) dimensions of algorithmic thinking included in the contents and didactical proposals of the lesson studies, b) didactical strategies conceived for the introduction of algorithmic thinking for children from 3 to 6 years old, c) perspectives from the student teachers about their learning on the integration of algorithmic thinking in Early Childhood Education. For the first two dimensions, the written reports, and the oral presentations with discussion of the work developed, will be the main source of data. For the third dimension, group interviews will be undertaken after the lesson study development and evaluation are finished. The written reports and the oral discussions will be analysed by three researchers independently for cross-checking of the categories found through content analysis. The cross-check will entail a discussion of categories and coding until consensus is reached. The interviews will be organized with members from different lesson study groups to maximize the variation in each discussion and use the different experiences as catalysts for the conversations. The interviews will be recorded and transcribed. Again, an independent content analysis by three researchers will be followed by cross-checking of categorization and coding. The content analysis will be guided by a phenomenographic approach (Han & Ellis, 2019), focused on the variation present in the participants’ perspectives. Participants will have the purposes and methods of the study explained to, and asked for informed consent. Participating in the course will not imply mandatory participation in the study.

Due to the novel introduction of algorithmic thinking in Early Childhood Education, research only suggests some dimensions of algorithmic thinking skills (Gencel et al., 2021; Sadykova & Il’bahtin, 2020). The study presented in this paper might contribute to the definition of content knowledge and pedagogical content knowledge that can guide and base teaching and learning of algorithmic thinking skills in this level of education. Particularly, it is expected that the dimensions included by the participants will have connections to the Portuguese curriculum which can inform how context-specific future proposals need to be. For teacher education, this set of results can help inform the contents to be included and, more importantly, connected to which courses and curricular areas. In terms of didactical strategies, the expected relevance refers to the unplugged and play-based approach that is valued in the literature. The four lesson plans and the participants’ perspectives will be valuable to evaluate how they translate to practice in Portuguese Early Childhood contexts. Again, this might be useful to inform the future inclusion of content about algorithmic thinking in teacher education. These two sets of results will also be relevant to the piloting of the modular curriculum as they can contribute with knowledge about student teachers’ appropriation and meaning of the concept of algorithmic thinking in Early Childhood Education in practice. Finally, the perspectives about learning from the participants will contribute to the research about how student teachers learn about teaching in initial teacher education, particularly from the field experiences (Arnold et al., 2014), allowing for a deeper understanding of the way future teachers experience lesson studies in Early Childhood Initial Teacher Education (Figueiredo, Gomes, & Matos, 2021b).

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