During the past two decades, computational thinking (CT) has gained renewed international interest with many countries taking policy initiatives to integrate it in their general education curricula (Bocconi et al., 2022). CT is broadly conceptualised as a problem-solving approach which draws on the concepts fundamental to computer science (Wing, 2006). In order to ensure successful integration of CT, teachers with necessary CT competence are a vital factor. However, there is empirical evidence pointing out that teachers struggle to understand what CT is and how to integrate it into teaching (Kravik et al., 2022; Nordby et al., 2022). Thus, teacher education becomes a crucial point for producing a sustainable pipeline of teachers equipped with the required CT skills (Yadav et al., 2017). Research suggests that preservice teachers should not only gain CT content knowledge but also pedagogical content knowledge to successfully teach CT (Ottenbreit-Leftwich et al., 2022). In line with this argument scholars suggest that CT needs to be integrated not only into educational psychology courses but also into methods courses for preservice teachers to gain both content knowledge and pedagogical content knowledge (Yadav et al., 2017). CT integration into subject /methods courses at preservice teacher education is an underexplored area where there is a need for more knowledge and would thus be the focus of this study.

Previous research in CT integration into teacher education comprises research reporting interventions aiming to integrate CT in both education technology courses (Yadav et al., 2017), educational technology methods courses (e.g. Umutlu, 2021), and science methods courses (Jaipal-Jamani & Angeli, 2017; Adler & Kim, 2018) and mathematics methods courses (Gadanidis et al., 2017). Programming, particularly block-based programming appears to be the most popular vehicle for developing CT skills among preservice teachers (Umutlu, 2021). Instructional strategies employing robotics (Jaipal-Jamani & Angeli, 2017) and modelling (Adler & Kim, 2018) are also utilized to promote CT skills in preservice teachers. Although there exist some studies that report the efficacy of interventions on CT integration into subject courses, there is a lack of studies demonstrating how CT is actually implemented in subject courses in teacher education. Our study aims to investigate how CT is implemented in mathematics and science courses at preservice education by drawing on data from interviews conducted with teacher educators. The findings will be important particularly to teacher educators and researchers in and beyond the European context.

The context of the study is Norway where a new primary and secondary school curriculum has been implemented, through which CT is integrated into several existing subjects including mathematics and science primarily through the integration of programming into these subjects (Ministry of Education and Research, 2019). Since CT is integrated into existing subjects in the school curriculum, teacher education should also prepare prospective teachers to teach accordingly. Our focus of the study is mathematics and science. By integrating CT into mathematics and science, content learning can be facilitated simultaneously providing meaningful contexts to apply CT (Weintrop et al., 2016). The following research question will guide our research:

How is computational thinking integrated into existing mathematics and science preservice teacher education courses?

Theoretical framework:

There are multiple definitions and frameworks for CT (Wing, 2006; Weintrop et al., 2016; Brennan & Rensnick, 2012) and there is no consensus on a basic definition. Since this study focuses on mathematics and science, we chose the CT in mathematics and science taxonomy developed by Weintrop et al. (2016). In this taxonomy, there are four major categories – data practices, modelling and simulation practices, computational problem-solving practices, systems thinking practices – each of which is composed of five to seven practices.  

This study is designed as a qualitative study. Semi-structured interviews were conducted with 17 teacher educators (nine in mathematics and eight in science) who are currently working at a 1-7 teacher education programme which prepares preservice teachers to teach in grades 1-7 (ages 6-13) in Norway. After conducting 17 interviews we realised that we have reached the data saturation point in relation to our research question. The sample consisted of teacher educators affiliated to eight teacher education institutions out of the ten public teacher education institutions that offer 1-7 teacher education in Norway. Since not all teacher educators use CT in their teaching, the sample was selected purposively to recruit teacher educators who have incorporated CT in their teaching. The interviews were conducted on Zoom by the first author, and each interview lasted for approximately 45 minutes. Written consent was obtained from the participants prior to holding the interviews. The audio recordings were transcribed verbatim by the first author using F4transkript. Thematic analysis was employed as the analysis method using a theory driven, deductive approach. We follow the six phases of conducting a thematic analysis described by Braun and Clarke (2006) which are 1) familiarising with the data, 2) generating initial codes, 3) searching for themes, 4) reviewing potential themes, 5) defining and naming themes and 6) producing the report. All three authors read the transcripts to familiarise themselves with the data. Then, an operationalisation of Weintrop et al.’s CT taxonomy was agreed upon. Next, the three authors independently conducted coding of three randomly selected interviews, followed by some necessary justifications of the operationalisation of the CT taxonomy before coding all 17 interviews. Sub-themes and candidate themes emerged during the coding process. The candidate themes are being revisited to review and refine the themes.

In the preliminary analysis of interview data, three candidate themes emerged- analog programming, block-based programming, modelling and robotics. Analog programming Mathematics teacher educators stated that they start their CT and programming teaching with analog programming using some unplugged activities. Most of the activities they described focused on algorithmic thinking- performing a task in a logical sequence of steps and especially convincing the preservice teachers the importance of precision of instructions to obtain the desired end result. Moreover, mathematics teacher educators underscored the place of algorithms in mathematics. Block-based programming Mathematics teacher educators’ accounts revealed that from analog programming they make a quick transition to programming activities which were mostly block based programming. Programming is the solid context preservice teachers get to apply their CT skills. The examples they provided were mostly associated with geometry, however, they stated that probability, numbers are also areas that are suited for CT integration. Modelling and robotics Robotics is employed by both mathematics and science teacher educators in their teaching. In science, the typical examples of CT integration given by science teacher educators included creating artefacts either making robots or making models with Scratch. Comparing the examples of teaching learning situations given by teacher educators, it is evident that in mathematics, programming was employed as a tool to learn deeply about mathematical concepts via problem-solving, for example, creating a polygon in Scratch, while in science, programming was often used to solve a larger problem, for example, by making a model that illustrate a larger concept/ phenomenon such as the solar system. The science programming activities described by the science teacher educators were predominantly in the form of group projects which continued for several sessions. This kind of projects involved different practices that came under the four categories in the Weintrop taxonomy.

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