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.

This study investigates the effect of programming courses on the computational thinking (CT) skills of elementary school students and the learning effectiveness of students from different backgrounds who are studying programming. We designed a OwlSpace programming course into an elementary school curriculum. Students in fourth and fifth grades were taught the fundamentals of programming. We measured and analyzed the effectiveness of their CT skills and self-efficacy in CT. The researchers analyzed the changes in the CT of different gender, different grade, and different past experience students in programming courses and then made specific recommendations for information technigy teachers and related units. The results demonstrate that students learned and improved their CT skills by taking OwlSpace programming course. Additionally, gender, grade, and past experience are found to have no impact on the students’ learning that means the course can improve students ability without limited any characteristics.

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 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.

Information and communications technologies today are used in virtually any university course when students prepare their papers. ICT is also needed after people are graduated from university and enter the job market. This author is an instructor in the field of informatics related to health care and social sciences at the Riga Stradins University. In practice, he has found that after completing informatics courses (IC) at the university level, students and practicing specialists at various levels find it hard to decide on what data processing method to use in order to interpret extracted results in the relevant area of specialisation. There are various data processing methods in the literature, presented individually and without adequate linkages. The author has found in practice that when such assignments are handled, there is closer linkage among data processing methods than the literature would suggest.