Informatics in Education

This study aims to explain the relationships between secondary school students' digital literacy, computer programming self-efficacy and computational thinking self-efficacy. The study group consists of 204 secondary school students. A relational survey model was used in the research method and three different data collection tools were used to collect data. The structural equation model was used in data analysis to reveal a model that explains and predicts the relationships between variables. According to the results of the research, it was determined that digital literacy of secondary school students affected their computer programming self-efficacy, digital literacy affected their computational thinking self-efficacy, and computer programming self-efficacy affected their computational thinking self-efficacy. It was also found that digital literacy skills have an indirect effect on secondary students' computational thinking self-efficacy on computational thinking self-efficacy.

The creative programming language Processing can be used as a generative architectural design tool, which allows the designer to write design instructions (algorithms) and compute them, obtaining graphical outputs of great interest. This contribution addresses the inclusion of this language in the architecture curriculum, within the context of digital culture and alternative approaches to how digital tools are used and learned. It studies the different processes related to Computational Thinking that are triggered in the prototyping of computer applications and that lead to creativity. The similarity between architectural design and programming is analysed, both in problem solving (abstraction, decomposition, iterative revisions -debugging-, etc.) and in the use of mechanisms of a digital nature (loops, randomness, etc.). The results of the design and testing of a pilot course are shown, in which the way of teaching, learning and using this programming language is based on the graphical representation of problems through sketches.

Computing science which focuses on computational thinking, has been a compulsory subject in the Thai science curriculum since 2018. This study is an initial program to explore how and to what extend computing science that focused on STEM education learning approach can develop pre-service teachers' computational thinking. The online STEM-based activity-Computing Science Teacher Training (CSTT) Program was developed into a two-day course. The computational thinking test (CTT) data indicated pre-service teachers’ fundamental skills of computational thinking: decomposition, algorithms, pattern recognition, pattern generalization and abstractions. The post-test mean score was higher than the pre-test mean score from 9.27 to 10.9 or 13.58 percentage change. The content analysis indicated that there were five key characteristics founded in the online training program comprised: (1) technical support such as online meeting program, equipment, trainer ICT skills (2) learning management system such as Google Classroom, creating classroom section in code.org (3) the link among policy, curriculum and implementation (4) pre-service teachers' participation and (5) rigor and relevance of how to integrate the applications of computing science into the classroom.

The Computational Thinking (CT) teaching approach allows students to practice problem-solving in a way that they can use the Computer Science mindset. In this sense, Collaborative Learning has a lot to contribute to educational activities involving the CT. This article presents the design and evaluation of a Collaborative Learning framework for the development of CT skills in students. To design the proposed strategy, several fundamental features of the Collaborative Learning concept of the literature have been studied and sketched. The strategy was applied to middle school students through a digital games programming workshop. Data were collected by three means: (1) collecting artifacts produced during activities; (2) recording of game programming sessions; and (3) applying a structured interview to students. The data analysis showed evidence that the strategy was able to mobilize Computational Thinking skills in addition to mobilizing collaborative skills in learners.

The purpose of the study is to examine the effect of unplugged coding activities carried out with middle school students on their computational thinking skills. This study employed nested-mixed design, which is a mixed research method; the data were supported by including the qualitative phase into an experimental study. In this frame, a group of 114 middle school students consisting of 5th graders were given coding training titled "Kesfet Project - I Discover Coding" by using unplugged coding content. The Computational Thinking Scale was applied to the students at the beginning and end of the training; the results obtained from the scale were analyzed by means of a paired t test. Finally, it was found out that unplugged coding activities had a positive effect on the improvement of computational thinking skills of the students. An examination of the sub-factors revealed that there is statistically no significant change in the problem solving skill despite the positive impact observed on creativity, algorithmic thinking, collaboration and critical thinking skills. Following the analysis of observation and daily data, the findings obtained revealed that the students usually displayed high levels of motivation and class participation in unplugged coding activities, they had difficulty in concretizing certain concepts as well as subjects requiring mathematical knowledge; various teaching methods and techniques were used in classes; the students liked the activities especially due to their appealing nature and their relation to daily life; however, there were occasional problems with scheduling of activities and teamwork due to over-crowded class size; the students experienced problems in achieving outcomes such as perceiving the relationship between computer science and mathematics and analyzing the given problem, and could have difficulty in associating between computer science and mathematics or between the subjects learned and the computer lesson, and in analyzing a given problem.