Author(s):  
Serife Nur Yildiz ◽  
Alev Ates Cobanoglu ◽  
Tarik Kisla

Scratch which is one of the block-based software for facilitating programming teaching is commonly used for beginners of learning programming. However, there is a lack of studies about the perceptions of information and communication technologies (ICT) teachers regarding the contributions of this visual programming language. Therefore, this study deals with developing a scale for measuring ICT teachers’ perceptions based on unified theory of acceptance and use of technology (UTAUT) about Scratch’s contributions in teaching programming. The sample of the study includes 265 ICT teachers from Turkish Ministry of National Education (MoNE) secondary schools who used Scratch software in their courses. According to exploratory and confirmatory factor analyses results, final version for perceptions scale of ICT teachers regarding the contributions of block-based visual programming language (Scratch) includes 28 items. The Cronbach Alpha coefficient is 0.97. This scale can help the practitioners who aims at understanding the contributions of Scratch and the other block-based visual programming languages from ICT teachers’ perspective; the researchers who wish to investigate this contribution according to various variables and the decision-makers of using Scratch in programming instruction programs.  


Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1269 ◽  
Author(s):  
Youngki Park ◽  
Youhyun Shin

Scratch and App Inventor are two of the most widely used block-based programming languages for young students. These are educational languages which allow students to program easily by dragging and dropping their code blocks. One question that arises in relation to these educational languages is which of them would be more helpful in fostering computational thinking. It is difficult to answer this question because each language has its own advantages. In this paper, we propose a novel rubric based on Dr. Scratch for assessing both Scratch and App Inventor projects in terms of computational thinking concept learning. We crawled teachers’ and students’ open and popular projects and automatically calculated their effectiveness scores with regard to learning computational thinking concepts based on our rubric. The experimental results show that (1) Scratch projects scored higher on average in Parallelism, Synchronization and Flow Control, while App Inventor projects scored higher on average in User Interactivity and Data Representation. The results also show that (2) in many cases, large programs with numerous lines of code scored high in all areas of computational thinking concepts.


Author(s):  
Agliamutdinova D.B ◽  
Besshaposhnikov N.O. ◽  
Kushnirenko A.G. ◽  
Leonov A.G. ◽  
Raiko M.V.

Around the world, the “coding is the new literacy” thesis is beginning to be shared by an increasing number of decision-makers inside and outside national education systems. This leads to the inclusion of courses on information technology, including programming, in the curricula of school and early childhood education in various countries. In Russia, with its centralized education system, the amount of programming skills that a 9th grade graduate must master was established by the federal standard in mid-2021 and includes a certain set of initial programming skills that a student must be able to demonstrate by choosing one of the 6 full-text programming languages prescribed by the standard. Our experience shows that today the programming skills provided for by the specified standard can be successfully mastered by all primary school graduates (age 11-12), and we predict that the problem of early compulsory teaching in programming will be posed by Russian legislators and solved by the Russian education system in the near future. The main thesis of this article is that the best way to systematically teach the basics of programming to beginners of all ages, including elementary school students, is to consistently use the three approaches - icon-based, block-based, and text-based - provided that there is a methodological and technological continuity of software environments that support these three approaches. This continuity can be achieved by creating a consistent family of multiple learning environments. The article describes the experience of developing and using such a family of three software environments for the system of preschool and primary education in Russia, as well as for the system of teacher training in universities.


2019 ◽  
Vol 13 (1) ◽  
pp. 1-10
Author(s):  
Radoslava Kraleva ◽  
Velin Kralev ◽  
Dafina Kostadinova

2017 ◽  
Vol 23 (4) ◽  
pp. 1483-1500 ◽  
Author(s):  
Monika Mladenović ◽  
Ivica Boljat ◽  
Žana Žanko

2020 ◽  
Vol 1 (1) ◽  
pp. 63-77 ◽  
Author(s):  
Lucas Vasconcelos ◽  
Ismahan Arslan-Ari ◽  
Fatih Ari

Learning computational skills such as programming and debugging is very important for K-12 students given the increasing need of workforce proficient in computing technologies. Programming is an intricate cognitive task that entails iteratively creating and revising programs to create an artifact. Central to programming is debugging, which consists of systematically identifying and fixing program errors. Given its central role, debugging should be explicitly taught to early childhood preservice teachers so they can support their future students’ learning to program and debug errors. In this study, we propose using eye-tracking data and cued retrospective reporting to assess preservice teachers’ cognitive strategies while debugging. Several eye-tracking studies have investigated learners’ debugging strategies though the literature lacks studies (a) conducted with early childhood preservice teachers and (b) that focus on block-based programming languages, such as Scratch. The present study addresses this gap in the literature. This study used mixed methods to triangulate quantitative findings from eye movement analysis and qualitative findings about employed debugging strategies into the creation of descriptive themes. Results showed that participants developed strategies such as simultaneous review of output and code, use of beacons to narrow down the area to be debugged, and eye fixation on output to form hypotheses. But most often, debugging was not informed by a hypothesis, which led to trial and error. Study limitations and directions for future research are discussed. 


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