Article Preview
TopIntroduction
The power of computers stems from their ability to represent our physical reality as a virtual world and their capacity to follow instructions with which to manipulate that world (K–12 Computer Science Framework, 2016). Ideas, images, and information can be translated into bits of data and processed by computers to create apps, animations etc. Games and apps that teach programming skills are even available on smartphones (Papadakis, Kalogiannakis & Zaranis, 2017a).
In recent years, Computational Thinking (CT) and related concepts (e.g. coding, programming, algorithmic thinking) have been promoted by educational stakeholders as skills that are as fundamental for all as numeracy and literacy (Benton, Hoyles, Kalas, & Noss, 2017; Bocconi, Chioccariello, Dettori, Ferrari, & Engelhardt, 2016; Papadakis & Kalogiannakis, 2008; Papadakis, Kalogiannakis, Zaranis, & Orfanakis, 2016). A number of prominent institutions and industry inside and outside Europe (Papadakis, 2016) have intervened in the debate about the introduction of CT skills in compulsory education (Royal Society, Académie des Sciences, Informatics Europe and the Association of Computing Machinery (ACM), Working Group on Informatics Education) (Bocconi et al., 2016). Additionally, computing and mathematical occupations are projected to be among the fastest-growing of any occupational group, with 1.3 million job openings in computing-related fields projected by 2022 (Richards, & Terkanian, 2013).
Although, in general, it is agreed that CT and programming are not overlapping sets (Wing, 2006) programming can make CT concepts concrete and become a tool for learning. Despite this widespread interest in developing CT skills among schoolchildren due to the fact that the role and significance of computing has increased in society and the economy (Kalogiannakis, 2010; Wilson, Sudol, Stephenson, & Stehlik, 2010; Papadakis, Kalogiannakis, & Zaranis, 2016b) student motivation to enrol in computing fields is in decline (Karakus, Uludag, Guler, Turner, & Ugur, 2012). A reason is that novices face many barriers when learning to program a computer, including the need to learn both a new syntax and a model of computation (Hundhausen, Farley, & Brown, 2009; Xinogalos, Satratzemi, & Malliarakis, 2017). The language syntax, the seemingly esoteric punctuation and formatting rules that must be followed when composing programs, can be a serious barrier for novice programmers (Weintrop & Wilensky, 2015).
As Guzdial (2004, p. 152) states the target in introductory courses is toward making programming more interesting, more relevant, and more powerful for students-novices. Different kinds of activities – game creation, robot programming, and storytelling - have been proposed for different educational levels, obviously with different complexity (Bocconi et al., 2016; Papadakis & Orfanakis, 2017). In an attempt to increase interest in computer science (CS), much effort has been made developing tools, activities and preliminary learning materials, both for younger children (Zaranis, Kalogiannakis & Papadakis, 2013; Papadakis, Kalogiannakis & Zaranis, 2016a; 2017b) and for high schools and universities (Meerbaum-Salant, Armoni, & Ben-Ari, 2013). Research has shown that NPEs (Novice Programming Environments) or ILEs (Initial Learning Environments) play an important role in attracting and retaining new programmers’ interest in computing as they manage to engage students and improve their attitudes towards CS (Papadakis, Kalogiannakis, Orfanakis, & Zaranis, 2014; Orfanakis & Papadakis, 2014; 2016).