Although it was used by Papert in 1996 for the first time, nobody had a clear understanding of what computational thinking (CT) was until Wing presented and defined it in 2006. Wing (2006) outlined the basic definition of CT as a way of “solving problems, designing systems and understanding human behavior by drawing on the concepts of computer science”. In 2021, we still do not have a full consensus on its definition, but CT has been widely accepted as a key 21st century skill. When it comes to integrating CT into school curricula, Science, Technology, Engineering, and Mathematics (STEM) subjects have been considered as the most appropriate places and there is abundance of research on its integration (Jona et al., 2014; Weintrop et al., 2016). Although CT can also be taught outside the context of computer science through cross-curricular integration, there is sparse literature on English language teaching (ELT) (Jacob et al., 2018). That is mostly because teaching computational thinking to English learners brings its own challenges in terms of content, cognitive and linguistic demands, and widespread stereotyping against certain groups of learners (Jacob et al., 2018).

Despite the fact that language learners experience difficulties with computational literacy, they will have several benefits by integrating CT through literacy. Teachers can directly incorporate computer science into their instruction through instructional practices such as using ‘pseudocode’ to write algorithms that can then be translated into actual (Malan & Leitner, 2007), agent-based game creation (De Souza et al., 2011), programming languages such as Scratch, and Storytelling Alice (Burke, O'Byrne, & Kafai, 2016). On the one hand integrating CT into language learning creates a number of opportunities for learners; on the other hand it causes many obstacles especially for the students from culturally and linguistically diverse backgrounds. Therefore, developing a curriculum for English language subject requires special attention from writing objectives to creating evaluation activities. For instance, while designing an instructional practice for an English language learning setting, this situation should be considered and what type of linguistic scaffolds and supports are needed should be determined. Computer science problems involve multiple solutions, which makes computational thinking difficult to assess (Fuller et al., 2007). English learners may face linguistic challenges in articulating their own problem-solving processes and solutions, but these ineffective or mistaken solutions may lead to one of many potentially correct solutions (Wing, 2006). Teacher misperceptions and faulty beliefs about these students may result in misdiagnosing errors in a student’s work when the student is, in fact, practicing novel and innovative approaches to problem solving (Ryoo, Lee, Sandoval, & Goode, 2013).

In the light of above mentioned issues, this current study was conducted in order to provide an overview of the applications of CT in ELT settings. For this purpose, the purpose, scope, theoretical basis, and findings of existing articles and conference papers in the selected databases that focus on CT and ELT were investigated thoroughly. In this study, we conducted a systematic review with the purposes to reflect on prior studies by focusing on one aspect of the literature, the applications of CT in ELT settings. The following research questions formed the basis of this review. However, the analysis is still ongoing and we will cover results of the first research question. All the results will be shared in the Conference.

1. What instructional techniques are used or suggested to introduce CT in ELT settings?
2. What kinds of suggestions are made for other ELT settings?

We searched two widely used and comprehensive digital databases to ensure the search to cover all the relevant literature and journals: Web of Science and Scopus. We first collected all journal articles with the extract key phrase “computational thinking” alone in the titles of each manuscript and “English language teaching” in the all fields of each manuscript. We did not use any alternative keywords related to the fields such as computing, programming, and coding, as we focused on CT as a distinct concept. We included both articles and conference papers in order not to miss any recent development and study in the field. Our initial search yielded 50 papers in the Web of Science database and 444 papers in Scopus database. In particular, we used the following inclusion criteria to select articles that are (a) using “computational thinking” in the title of the paper, (b) “English language teaching” in any part of the paper (such as title, abstract, keywords, or main text); (c) peer-reviewed journal articles and conferences papers; (d) available in full-text; (e) written in English. After the initial search, not to miss any paper we examined the references of the selected articles by utilizing a snowball method. Based on the reduction of articles following the inclusion and exclusion criteria by the authors, the number of studies was reduced to 9 papers in the final review. For data analysis, we used content analysis and coded the literature by systematically classifying the texts into categories (Fraenkel, Wallen, & Hyun, 2015). To extract information from each selected article in accordance with the research questions, a coding scheme was developed and an Excel spreadsheet was used to store and analyze all data.

Based on the systematic review of the selected articles and conference papers findings are reported in accordance with the research questions. It is possible to examine the articles and conference papers in two sections. In the first section, there are research-based studies which took an instructional technique and applied it in an educational setting. In the second section, there are review studies which answered the question of how to utilize CT in ELT settings and then suggested several techniques. For the first research question, it has been determined that Scratch is the most common programming tool that was used for introducing CT in ELT settings (Moreno-Leon & Robles, 2015; Parsazadeh, Cheng, Wu, & Huang, 2020; Weng & Wong, 2017; Wolz, Stone, Pearson, Pulimood, & Switzer, 2011; Zhou, 2018). Scratch is a graphical programming language which is created by the Lifelong Kindergarten Group at the MIT Media Lab. It allows students aged from 8 to 16 to program their own interactive stories, games and animations and then share what they create with others in the Scratch community online (Weng & Wong, 2017). Another technique that was presented by two studies is modeling (Howell, Jamba, Kimball, Sanchez-Ruiz, 2011; Sabitzer, Demarle-Mausel, & Jarnig, 2018). As modeling is a good tool for storytelling, a learning method for different subjects where information and learning contents are embedded in stories, it is considered suitable for ELT settings (Sabitzer, Demarle-Mausel, & Jarnig, 2018). Linguistics scaffolding is the last technique that was presented by two studies (Jacob, Nguyen, & Tofel-Grehl, 2018; Jacob, Nguyen, Richardson, & Warschauer, 2019). As the vocabulary in the language used for describing CT processes is distinct from everyday language, it is important that teachers consider students’ oral and written language development in learning CT through linguistics scaffolding (Jacob, Nguyen, & Tofel-Grehl, 2018).

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