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.
During the last decade, coding has come to the foreground of educational trends as a strong mean for developing students' Computational Thinking (or CT). However, there is still limited research that looks at coding and Computational Thinking activities through the lens of constructionism. In this paper, we discuss how the knowledge we already have from other thinking paradigms and pedagogical theories, such as constructionism and mathematical thinking, can inform new integrated designs for the cultivation of Computational Thinking. In this context, we explore students' engagement with MaLT (Machine Lab Turtle-sphere), an online environment of our design that integrates Logo textual programming with the affordances of dynamic manipulation, 3D graphics and camera navigation. We also present a study on how the integration of the above affordances can promote constructionist learning and lead to the development of CT skills along with the generation of meanings about programming concepts.
Coding and computational thinking have recently become compulsory skills in many school systems globally. Teaching these new skills presents a challenge for many teachers. A notable example of professional development designed using Constructionist principles to address this challenge is ScratchEd. Upon reflecting on her experiences designing and running ScratchEd, Karen Brennan identified five tensions faced by professional development providers, and proposed that these tensions could be used for scrutinising and critiquing professional development. In this paper we analyse, through the lens of Brennan's tensions, the process we have followed to design, evaluate and improve professional development. We argue that while we have experienced the same tensions, the extent to which we assess learning is a new tension that extends those identified by Brennan. There are strong reasons to assess teachers' knowledge, however, quantitative measures of learning could be at odds with Constructionism: as Papert argued in Mindstorms, constructionist educators should study their learning environments as anthropologists. Consequently, we have called this new tension the tension between anthropology and assessment.
The development of computational thinking is a major topic in K-12 education. Many of these experiences focus on teaching programming using block-based languages. As part of these activities, it is important for students to receive feedback on their assignments. Yet, in practice it may be difficult to provide personalized, objective and consistent feedback. In this context, automatic assessment and grading has become important. While there exist diverse graders for text-based languages, support for block-based programming languages is still scarce. This article presents CodeMaster, a free web application that in a problem-based learning context allows to automatically assess and grade projects programmed with App Inventor and Snap!. It uses a rubric measuring computational thinking based on a static code analysis. Students can use the tool to get feedback to encourage them to improve their programming competencies. It can also be used by teachers for assessing whole classes easing their workload.
Despite a growing effort to implement computational thinking (CT) skills in primary schools, little research is reported about what CT skills to teach at what age. Therefore, the research questions that guide this study read: (1) How is age related to students' success in computational thinking tasks? (2) How are computational thinking tasks perceived by students? (3) How do students' experience learning with respect to computational thinking? 200 primary school students between the age of 6 and 12 participated in this study. These students got introduced to two CT subjects: abstraction and decomposition. We found that age seems to be related with these concepts, with an interaction effect for gender in the abstraction task. No differences found between young and older students in the constructs perceived difficulty, cognitive load, and flow indicate that young primary school students can engage in learning these CT skills.