Programming teaching is currently included in a wide range of academic and technical courses mostly due to technological advances. Despite the fact that this approach is reaching more and more students, the literature has described a set of limitations in the acquisition of this complex learning and presented microworlds as a possible solution. Although they have been closely associated with constructivist models combined with the 4C/ID model, they have shown promising results in recent studies. This chapter explores the use of microworlds associated with the 4C/ID model to facing the learning difficulties on programming in technical courses. It also presents a set of practical examples that the reader could put into practice.
TopIssues On Programming Learning
The difficulties inherent in programming teaching and learning are not new. Studies from the 1980s already announced its complexity (e.g. Mayer, 1988; Disjkstra, 1989). However, the problem has remained so far, in part because the focus of researchers and teachers on the searching for solutions is often directed to classroom tools.
The development of solutions should begin with a global understanding of the programming learning process. Several authors suggest that one of the causes of students' difficulties is the complex syntax of their first programming language (Gomes, Henriques & Mendes, 2008; Price, Hirst, Johnson, Petre & Richards, 2002; Silva, Lima, Raposo & Júnior, 2018), which may be related to the selection of the first language offered to students that would typically be more appropriate for professional use than for beginners (Jenkins, 2002; Costa, 2019).
Another restraint pointed out by the literature is related to the lack of students' skills in problem solving and logical and abstract reasoning, required by programming learning (Dann, Cooper & Pausch, 2000; Gomes, Henriques and Mendes, 2008; Gal -Ezer & Harel, 1998; Silva et al., 2018), that puts in evidence some difficulties in the application of theoretical contents to practical situations (Gal-Ezer & Harel, 1998).
Moons and Backer (2013) indicated two pertinent studies within the scope of students' programming skills. In the case of the study by McCracken et al. (2001), they evaluated the programming skills of the 227 first year students in Computer Science. The evaluation results showed an average of 22.9 out of 110. In the study of Lister et al. (2004), 600 students from seven countries responded to a 20-choice multiple-question test with two types of questions, (the first was to indicate the outcome of running a program and the second was to complete the missing piece of code in the program). The results showed that over a quarter of the students failed the most elementary questions.