Wing’s (2006) appeal to computer scientists to share the treasures of their domain with everybody represents a seminal juncture in computational thinking (CT) discourse. At the centre of Wing’s proposition, lies the claim that inherent practices and concepts in computer science could be harnessed for problem-solving in other domains. Since ‘most educators regard problem-solving as the most important learning outcome for life’ (Jonassen, 2000, p. 63), the linkage between CT and problem-solving resonated within the educational community and policymakers. For instance, CT has been included as a learning dimension in the national curricula of the European Ministries of Education (Bocconi et al., 2016) and the Next Generation Science Standards in the United States (National Research Council, 2013). Also, considered an essential 21st century skill, large-scale comparative studies such as the International Computer and Information Literacy Study (ICILS) and Programme for International Student Assessment (PISA) have also incorporated CT in their assessment frameworks (Fraillon et al., 2019; Organisation for Economic Co-operation and Development, 2018).
Besides problem-solving, CT is associated with several educational and social benefits like collaboration, critical thinking, self-management, confidence, mathematical thinking, natural language literacy, reasoning, creativity, metacognition, communication, and positive attitudes (Denner et al., 2019; Popat & Starkey, 2019; Scherer et al., 2019). Wing’s (2006) viewpoint likened the importance of CT with time-honoured literacies of reading, writing, and arithmetic. Though debatable, prospects of CT have necessitated enquiries on the nature and acquisition of CT. Whilst not exhaustive, these include interests in CT’s conceptualization (Ezeamuzie & Leung, 2022; Shute et al., 2017), assessment (Korkmaz et al., 2017; Román-González et al., 2017), and development across educational settings like teacher education (Yadav et al., 2018), high schools (Yin et al., 2020), middle schools (Berland & Wilensky, 2015), primary schools (Kong et al., 2018; Pellas, 2023), early childhood (Bers et al., 2014), undergraduates (Ezeamuzie et al., 2022), and special needs (González-González et al., 2019).
Most empirical enquiries on CT focused on instructional strategies (e.g., Hsu et al., 2018; Lye & Koh, 2014; Scherer et al., 2020), learning environments (e.g., Noh & Lee, 2020; Zhang & Nouri, 2019) and other micro-level learners’ attributes such as gender, attitude, age, programming experience (e.g., Authors, 2022b; Sun et al., 2022) and emotions (Pellas, 2023). But, there are wider community contexts such as government educational policies, home environment, school characteristics and classroom settings that may influence students’ CT skills (Fraillon et al., 2019). Policies adopted at the national, provincial, and school levels play critical roles in shaping educational outcomes. For instance, Hanushek et al. (2013) discovered that granting schools autonomy enhanced the mathematics and science achievements of students in developed economies. How the wider community structures such as the national or local educational policies enhance or inhibit CT development constitutes a critical gap in the CT discourse. To close this gap, this study examines how educational policies could support CT development. Students’ CT achievements and educational policy data of the participating nations were captured in the ICILS large-scale comparative study (Fraillon et al., 2019; Fraillon et al., 2020b). The validated big data, which is open and free, contains invaluable data for uncovering the impact of educational policies on the development of CT – a 21st century problem-solving skill for everybody.
Research Question – How do the basic and technology-related educational policies predict learners’ CT achievement? The analysis will focus on the following 12 policy features: start age of compulsory education (X1), length of compulsory education (X2), policy direction (X3), autonomy in governance for public schools (X4), autonomy in governance for private schools (X5), curriculum emphasis on CT topics (X6), support for digital learning (X7), mandate for ICT assessment (X8), plans for 1:1 computing @ school (X9), plans to support student with ICT (X10), plans to provide ICT resources (X11) and plan to support teachers with ICT (X12).