School systems all around Europe have in the last couple of years implemented programming into their curriculum for young students, in Sweden as a part of the mathematics subject (Skolverket, 2019). This is seen to be a way to meet a society that is becoming more digitalized by the day. But changing curriculum is only one step on the way, now more knowledge about teaching in this area is needed. The study reported on in this paper is a pilot study aiming to create an early idea about how to activate young student’s ability to use and develop computational thinking as they meet programming in school for the first time.
Research conducted in the field of teaching and learning programming often places its focus on higher education students (Lye & Koh, 2014) but research findings from older students do not necessarily apply for younger students. As a result, more research focusing on primary school students is needed.
To figure out how to teach programming, what students are supposed to learn should be established. Primary school students do not need to learn programming to become programmers. The reason is rather to develop computational thinking, since this is a skill needed in a digitalized society. The relation between programming and computational thinking need clarification since the two concepts are closely intertwined. Programming is a way to express computational thinking in the same way as writing is a way to express literacy (Voogt, Fisser, Good, Mishra, & Yadav, 2015). There is however no consensus in the field regarding the definition of computational thinking. Wing (2006) ignited a debate that has generated both theoretically and empirically based frameworks. One of those, constructed by Brennan and Resnick (2012) has been used in this pilot as theoretical framing. This was chosen since their definition of computational thinking is informed by empirical data in a setting with young students and therefore suited this context and was possible to operationalize. The framework consists of three dimensions, 1) computational concepts, 2) computational practices and 3) computational perspectives.  
Among studies conducted in primary school settings it is more common to focus on computational concepts rather than practices or perspectives (Lye & Koh, 2014). Therefore, in this pilot study the focus is on computational practices, which makes it possible to visualize what students do when they engage in programming. This can provide insights into which teaching characteristics that activates students computational thinking and help them develop it further. What is meant by computational practices will be further explained in the method section.

To expand our knowledge about how young students develop computational thinking as they meet programming in school for the first time, the following question will be answered:

Which possible teaching characteristics can help students to activate their ability to engage in computational practices?

The pilot was conducted as an intervention, consisting of four parts, 1) An unplugged activity where transformation of a story from natural language to symbols introduced students to the use of symbols and simple sequencing and looping, conducted as a whole group activity led by the teacher. 2) An unplugged activity where students had the possibility to deepen their understanding by repeating the first part but in pairs instead of together in the whole group. 3) A walk-through of a block-based environment on Ipads, showing how the program works and how it corresponds to the symbols used in part one and two. 4) A so-called making activity in the block-based environment where students worked in pairs to create their own stories, starting with a plan written on paper and then programmed from scratch in this digital environment. 22 Swedish first grade students participated in the lessons. The lessons were taught by the regular teacher and the four parts were implemented during two full school days. Two types of data were collected and analyzed: video recordings and screen recordings of the Ipads that the students used. All actions in the classroom were video recorded and during the two last parts, when students used Ipads, their screens were recorded together with the student’s conversations. The analysis focused on identifying computational practices (Brennan & Resnick, 2012) when students engaged in programming using the introduced computational concepts. The dimension computational practices contain four different practices: - Being incremental and iterative: This was identified when students moved focus between planning and programming, letting those two things inform and evolve each other. - Testing and debugging: This was identified when students realized that written code did not do the supposed work and when they experimented with code to adjust it. - Reusing and remixing: This was identified when students reused self-written code or code written of a classmate. - Abstracting and modularizing: This was identified when students wrote more than one program in one project and connected those to build a functioning unit, in this context a story. The analysis asked question about what characteristics in the teaching that made students act according to the above mentioned four computational practices.

The initial results consist of several trends and indications connected to computational thinking, and computational practices in particular. 1) Planning a programming project seems to be a vital component when students engage in making activities. Planning is an obvious component to be able to engage in being incremental and iterative, but it did also support students to engage in testing and debugging and abstracting and modularizing. 2) Creating an open setting where students are free to communicate with each other can stimulate their engagement in reusing and remixing as they then get the opportunity to inspire each other with their projects. 3) Students’ level of persistence seems to correspond with their ability to engage in computational practices. It is not a teaching characteristic as such but must be considered when planning a lesson. Previous research has pointed out the connection between persistence and testing and debugging (Falloon, 2016; Tran, 2019), but those results indicate that other practices might be affected as well. Lack of persistence can be interpreted as a reason that some students lose track of their initial plan, and therefore failing to engage in being incremental and iterative. The teaching characteristics that has been identified as potential ways to activate young students computational thinking can here only be understood as initial indications for what might be workable elements in teaching computational thinking through programming. The insights gained from the pilot will provide important guidance for further research on the subject.

Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Paper presented at the Proceedings of the 2012 annual meeting of the American educational research association, Vancouver, Canada. Falloon, G. (2016). An Analysis of Young Students' Thinking When Completing Basic Coding Tasks Using Scratch Jnr. on the iPad. Journal of Computer Assisted Learning, 32(6), 576-593. Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51-61. Skolverket. (2019). Läroplan för grundskolan, förskoleklassen och fritidshemmet 2011. Stockholm Tran, Y. (2019). Computational Thinking Equity in Elementary Classrooms: What Third-Grade Students Know and Can Do. Journal of Educational Computing Research, 57(1), 3-31. Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education: Towards an agenda for research and practice. Education Information Technologies, 20(4), 715-728.