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.
This study reports the findings of a program that aims to develop pre-service science teachers’ computational problem-solving skills and views on using information and communications technology in science education. To this end, pre-service science teachers were trained on computational thinking, computational problem solving, designing an algorithm, and Python coding, and then they were asked to solve problem situations determined within the science education program using the computational problem-solving process. The study was conducted in a faculty of education in Turkey and carried out conducted in an elective course in the spring semester of the 2019 - 2020 academic year (in an online platform due to the Covid-19 Pandemic). 38 pre-service science teachers were included in the study. In this process, pre-service science teachers’ conceptual development levels regarding computational thinking and their views regarding the use of ICT in schools were collected quantitatively. The development of computational problem-solving skills of pre-service science teachers was scored by a rubric developed in this study. According to the analyzes, pre-service science teachers increased knowledge of computational thinking (t = -5,969, p = .000), enhanced views regarding the use of ICT in schools (t = -2,436, p = .020), and developed computational problem-solving skills (χ2(2) = 9.000, p = 0,011). These findings have the potential to provide evidence on how computational problem-solving skills can be integrated into science teacher education programs.
Due to technological advancements, robotics is findings its way into the classroom. However, workload for teachers is high, and teachers sometimes lack the knowledge to implement robotics education. A key factor of robotics education is peer learning, and having students (near-)peers teach them robotics could diminish workload. Therefore, this study implemented near-peer teaching in robotics education. 4 K10-11 secondary school students were teachers to 83 K5-6 primary school students. The intervention included 4 3-hour robotics lessons in Dutch schools. Primary school students completed a pre- and post-intervention questionnaire on their STEM-attitudes and near-peer teaching experience, and a report on their learning outcomes. Interaction with near-peer teachers was observed. After the lessons, a paired-samples t-test showed that students had a more positive attitude towards engineering and technology. Students also reported a positive near-peer teaching experience. Conventional content analysis showed that students experienced a gain in programming and robotics skill after the lessons, and increased conceptual understanding of robotics. The role the near peer teachers most frequently fulfilled was formative assessor. Near-peer teachers could successfully fulfil a role as an engaging information provider. This study shows that near-peer teachers can effectively teach robotics, diminishing workload for teachers. Furthermore, near-peer robotics lessons could lead to increased STEM-attitudes.
Research trends on computational thinking (CT) and its learning strategies are showing an increase. The strategies are varying, for example is using games to provide enjoyment, engagement, and experience. To improve the high level of immersion and presence of game objects, learning strategies through games can be improved by virtual reality (VR) technology and its application. However, a systematic review that specifically discusses game based in VR (GBiVR) settings is lacking. This paper reports previous studies systematically about the strategies used to learn CT through games and VR applications. 15 papers were selected through Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. As the result, this study proposes a conceptual framework for designing a strategy to learn CT through GBiVR settings. The framework consists of critical aspects of variables that can be considered in the learning environment like game elements, VR features, and CT skills. All the aspects are discussed below.
Nowadays, solving problems is substantial for the social relationship human. Computational Thinking (CT) emerges as an interdisciplinary thought process encompassing mental abilities to help students solve and understand problems. Researchers invest in the methodological proposal of activities aimed at CT stimulation, educational approaches, and the conception of technologies that support these activities’ execution. Educational Robotics (ER) is one of these technologies that stand out at different educational levels to favor teamwork, logical thinking, and creativity, skills intimately articulated with the computing paradigm. The main objective of this work is to investigate the impact of ER activities on CT development and subjects learning in the Technical and Vocational Education in High School. For this, we accomplished a study of intervention research type with students and teachers analyzing quantitative and qualitative aspects. The results indicate that the introduction of ER can favor students in the development of CT skills and learning High School subjects.
Integrating computational thinking into K-12 Education has been a widely explored topic in recent years. Particularly, effective assessment of computational thinking can support the understanding of how learners develop computational concepts and practices. Aiming to help advance research on this topic, we propose a data-driven approach to assess computational thinking concepts, based on the automatic analysis of data from learners’ computational artifacts. As a proof of concept, the approach was applied to a Massive Open Online Course (MOOC) to investigate the course’s effectiveness as well as to identify points for improvement. The data analyzed consists of over 3300 projects from the course participants, using the Scratch programming language. From that sample, we found patterns in how computational thinking manifests in projects, which can be used as evidence to guide opportunities for improving course design, as well as insights to support further research on the assessment of computational thinking.
When we “think like a computer scientist,” we are able to systematically solve problems in different fields, create software applications that support various needs, and design artefacts that model complex systems. Abstraction is a soft skill embedded in all those endeavours, being a main cornerstone of computational thinking. Our overview of abstraction is intended to be not so much systematic as thought provoking, inviting the reader to (re)think abstraction from different – and perhaps unusual – perspectives. After presenting a range of its characterisations, we will explore abstraction from a cognitive point of view. Then we will discuss the role of abstraction in a range of computer science areas, including whether and how abstraction is taught. Although it is impossible to capture the essence of abstraction in one sentence, one section or a single paper, we hope our insights into abstraction may help computer science educators to better understand, model and even dare to teach abstraction skills.
Problem-solving and critical thinking are associated with 21st century skills and have gained popularity as computational thinking skills in recent decades. Having such skills has become a must for all ages/grade levels. This study was conducted to examine the effects of grade level, gender, chronotype, and time on computational thinking skills. To this end, the study was designed to follow a longitudinal research model. Participants were 436 secondary school students. Computational thinking test scores were collected from the students at certain time intervals. Results indicate that computational thinking skills are independent of gender, time, and chronotype but differ significantly depending on grade level. The interaction between grade level and time of testing also has a significant impact on computational thinking skills. The difference in grade level can be interpreted as taking an information technologies course increases computational thinking. The results suggest that such courses should be promoted to children at a young age. The joint effect of gender, grade level, and chronotype were not statistically significant and it is recommended to conduct future studies to investigate this result.
This study aims to provide a deeper understanding about the Bebras tasks, which is one of the computational thinking (CT) unplugged activities, in terms of age level, task category, and CT skills. Explanatory sequential mixed method was adopted in the study in order to collect data according to the research questions. The participants of the study were 113,653 school students from different age levels. Anonymous data was collected electronically from the Turkey 2019 Bebras challenge. Factor analysis was employed to reveal the construct validity to determine how accurately the tool measured the abstract psychological characteristics of the participants. In addition, the item discrimination index was calculated to measure how discriminating the items in the challenge were. Qualitative data gathered through the national Bebras workshop was analysed according to content analysis. The findings highlighted some interesting points about the implications of the Bebras Challenge for Turkey, which are discussed in detail. Furthermore, common problems of Bebras tasks are identified and possible suggestions for improvement are listed.