This study aims to provide a descriptive and bibliometric analysis of the trend of artificial intelligence (AI) application in the development of computational thinking (CT) skills in publications from 2007 to 2024. A total of 191 articles were obtained from Scopus database with certain keywords, and analyzed using Biblioshiny and VOSviewer. The results show that publications fluctuated in 2007–2014, then increased sharply since 2019, with a compound annual growth rate (CAGR) of 22.8% in the period 2019–2024. Early publications received the highest number of citations, such as in 2007 (18 citations), while recent studies show a more even distribution of citations, reflecting a shift from basic to applied research. This analysis highlights the important role of AI in enhancing CT development through learning strategies, educational technology, and cross-disciplines. The impact of AI implementation is seen in various aspects of education, such as learning strategies, educational media, and the relationship between CT and other skills. These findings demonstrate the importance of leveraging AI to support the development of CT in education, which can improve the quality of learning and enrich educational experiences globally.
This autoethnographic paper is part of a special issue trying to answer the question “How to design or choose languages for programming novices?” I will describe howmy programming language Hedy was created, how the initial design goals were formed, how my perspectives on learning and teaching changed along the way, and how Hedy changed with it. The paper also discusses how the Hedy community came to be. Hedy was initially made for my own classroom and teaching, but quickly attracted a community, which I learned a lot from. This special issue has given me a unique opportunity, after 5 years of working on Hedy, to reflect on the process and to learn from it myself, and will hopefully also allow other programming language designers to learn from.
In Education 4.0, a personalized learning process is expected, and that students are the protagonist. In this new education format, it is necessary to prepare students with the skills and competencies of the 21st-Century, such as teamwork, creativity, and autonomy. One of the ways to develop skills and competencies in students can be through block programming, which can be used with emerging technologies such as robotics and IoT and in an interdisciplinary way. Thus, block programming in High School is important because it is possible to work on aspects such as problem-solving, algorithmic thinking, among other skills (Perin et al., 2021), which are necessary in the contemporary world. Thus, our Systematic Mapping Study (SMS) aims to identify which block programming tools support of Education 4.0 in High School. Overall, 46 papers were selected, and data were extracted. Based on the results, a total of 24 identified block programming tools that can be used in high school collaboratively and playfully and with an interdisciplinary methodology. Moreover, it was possible to see that most studies address block programming with high school students, demonstrating a lack of studies that address block programming with teachers. This SMS contributed to identifying block programming tools, emerging technologies, audience (teacher or student), and learning spaces where block programming is being worked on.
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.
Computational thinking (CT) has been introduced in primary schools worldwide. However, rich classroom-based evidence and research on how to assess and support students’ CT through programming are particularly scarce. This empirical study investigates 4th grade students’ (N = 57) CT in a comparatively comprehensive and fine-grained manner by assessing their Scratch projects (N = 325) with a framework that was revised from previous studies to aim towards enhancing CT. The results demonstrate in detail the various coding patterns and code constructs the students programmed in assorted projects throughout a programming course and the extent to which they had conceptual encounters with CT. Notably, the projects indicated CT diversely, and the students altogether encountered dissimilar areas in CT. To target the acquisition of CT broadly, manifold programming activities are necessary to introduce in the classroom. Furthermore, we discuss the possibilities of applying the assessment framework employed herein to support CT education through Scratch in classrooms.