Computational Thinking Concepts Research Articles

Teaching and learning with innovative technologies and practices at primary school level.

The introduction of computer science to primary schooling age is relatively new, as traditionally it was primarily set aside for secondary and tertiary level learning (Heintz et al., 2016). Experts agree that even young children can understand fundamental concepts of computational thinking (CT), and that it is important to develop skills related to CT from a young age (Boccini et. al, 2016, p.48).
 
 Increasingly computer science is becoming a compulsory area of curriculum for many countries across the world, as reported by Bocconi et al. and there has been a recent increase in the integration of CT and computer science in mandatory education, as evidenced by the recent changes in educational curricula (p9., 2016). In New Zealand, the Technology curriculum was recently refreshed with the main revisions being the addition of CT and designing and developing digital outcomes as technological areas (Ministry of Education, 2017a). The intention of digital technologies curriculum content is to “significantly contribute to students developing the knowledge and skill they need as digital citizens and as users of digital technologies across the curriculum” (Ministry of Education, 2017b, p.3).
 
 There is also an expectation that all teachers are responsible for building capacity in digital fluency and literacy. It is the teacher's responsibility to effectively use these tools, and to in turn educate students on how to take advantage of these tools for their learning (Wright, 2010, p.46). The main rationale for introducing CT in many countries is to promote the development of 21st century skills necessary for full engagement in the digital realm (Bocconi et al., 2016, p.8).
 
 ByteEd, a New Zealand based educational resource company, have recently developed a new approach to the teaching of computer science at a primary school level that incorporates 21st century skill development. The Play Code Learn series of STEM (Science, Technology, Engineering and Mathematics) kits utilise an unplugged-to-digital methodology and explore future-focused technologies of Augmented Reality (AR) and programming.
 
 Based on the research of Bell and Vahrenhold (2018), who state unplugged activities for students engage them with lasting ideas in computer science. Integrating physical digital tasks along with unplugged tasks proves to be more beneficial for learning. The kits enable students to learn and understand digital concepts before transitioning to putting skills and knowledge into action in a digital environment.
 
 This presentation delves into the impact of the first Play Code Learn kit, Dinosaur Steps, on teaching and learning in two New Zealand classrooms. The use of an unplugged approach has proven to be advantageous to learners and highlights a significant shift in knowledge retention and the understanding of concepts, skills and literacy after using the Dinosaur Steps kit and related teaching resources during Term 4 2022.

Introducing schoolchildren to computational thinking using smartphone apps: A way to encourage enrollment in engineering education

AbstractComputational thinking is the process of solving a problem in a way that can be readily automated by a computer. Decomposition, pattern recognition, abstraction, and algorithm design are four major components of computational thinking. We conducted an experiment to study the effectiveness of smartphone apps for teaching computational thinking to 7‐year‐old children. The first experimental group was taught computational thinking using four apps, one for each component. The second experimental group was taught computational thinking using the chalk and board approach. The control group was not imparted any lesson in computational thinking. The intervention period lasted 8 weeks and was followed by a posttest and a retention test conducted after another 2 weeks. The children showed interest in learning computational thinking and could solve problems that are inspired by real‐world engineering problems during the intervention period. They could analyze and debug (77%) their own work. The performance of the children in the two experiment groups was significantly better than those in the control group in the posttest and the retention test (F = 26.470, p < .05). This means that 7‐year‐old children can learn computational thinking from suitable mediums. No significant difference was observed in the performance of the children in the posttest and the retention test (p > .05), denoting that children can retain the concepts of computational thinking. Including computational thinking lessons at the K‐12 level can encourage children to enroll in engineering programs in the future. We recommend standardization of content and development of age‐specific apps for teaching computational thinking.

Tracking Visual Programming Language-Based Learning Progress for Computational Thinking Education

Maker education that incorporates computational thinking streamlines learning and helps familiarize learners with recent advances in science and technology. Computational thinking (CT) is a vital core capability that anyone can learn. CT can be learned through programming, in particular, via visual programming languages. The conclusions of most studies were based on quantitative or system-based results, whereas we automatically assessed CT learning progress using the Scratch visual programming language as a CT teaching tool and an integrated learning tracking system. The study shows that Scratch helped teachers to diagnose students’ individual weaknesses and provide timely intervention. Our results demonstrate that learners could complete tasks and solve problems using the core CT steps. After accomplishing numerous tasks, learners became familiar with the core CT concepts. The study also shows that despite increased learning anxiety when solving problems, all learners were confident and interested in learning, and completed each task step by step.

Effectiveness of AR Board Game on Computational Thinking and Programming Skills for Elementary School Students

This study integrated the augmented reality (AR) technology into the “Coding Ocean” board game to provide players with real-time simulation of ship paths and learning scaffolds. Combined with Scratch block-based programming, an interactive learning environment is developed to assist elementary school students in learning coding skills from the unplugged board game to enhance their computational thinking concepts. The AR board game is focused on the programming concepts of sequential, and/or and loop. Through the process of treasure hunting, the basic concepts of computational thinking can be developed, i.e., abstraction, problem decomposition, pattern recognition and algorithmic thinking. In order to investigate the learning effectiveness of the AR board game on computational thinking and programming skills, a number of 51 third graders from an elementary school were recruited as research samples. The experimental group (n = 26) used the AR board game and the control group (n = 25) used the traditional board game for game-based learning. The experimental results indicate: (1) the learning effectiveness of computational thinking for the experimental group was significantly higher than that of the control group; (2) the learning achievement of the block-based programming skills for the experimental group was significantly higher than that of the control group; (3) the cognitive load of the experimental group was significantly lower than that of the control group. The AR technology can combine the unplugged board games with plugged learning modules to assist students in game-based learning, which is useful for enhancing computational thinking abilities while reducing the cognitive load.

Using Mobile Dual Eye-Tracking to Capture Cycles of Collaboration and Cooperation in Co-located Dyads

The goal of this paper is to bring new insights to the study of social learning processes by designing measures of collaboration using high-frequency sensor data. More specifically, we are interested in understanding the interplay between moments of collaboration and cooperation, which is an understudied area of research. We collected a multimodal dataset during a collaborative learning activity typical of makerspaces: learning how to program a robot. Pairs of participants were introduced to computational thinking concepts using a block-based environment. Mobile eye-trackers, physiological wristbands, and motion sensors captured their behavior and social interactions. In this paper, we analyze the eye-tracking data to capture participants’ tendency to synchronize their visual attention. This paper provides three contributions: (1) we use an emerging methodology (mobile dual eye-tracking) to capture joint visual attention in a co-located setting and replicate findings that show how levels of joint visual attention are positively correlated with collaboration quality; (2) we qualitatively analyzed the co-occurrence of verbal activity and joint visual attention in low and high performing groups to better understand moments of collaboration and cooperation; (3) inspired by the qualitative observations and theories of collaborative learning, we designed a new quantitative measure that captures cycles of collaborative and cooperative work. Compared to simple measures of joint visual attention, we found it to increase correlation coefficients with learning and collaboration scores. We discuss those results and describe how advances in analyzing sensor data can contribute to theories of collaboration. We conclude with implications for capturing students’ interactions in co-located spaces using Multimodal Learning Analytics (MMLA).

Teachers’ understanding of programming and computational thinking in primary education – A critical need for professional development

Programming and computational thinking have (re)gained an increased focus in com­pulsory education worldwide, consequently demanding teachers of various subjects to engage in the teaching and learning of the two. A recent curriculum reform in Norway emphasised the development of students’ computational skills by integrating pro­gramming into four subject domains: mathematics, natural science, music, and arts and crafts. However, these requirements come without a necessary professional develop­ment programme and are based on the presumption that all concerned teachers under­stand the concepts of programming and computational thinking and know how to teach these skills in a sound pedagogical and didactical way. Therefore, this study investigated how teachers understand programming and computational thinking and the relationship between the two concepts. We also investigated the teachers’ approaches to teaching these concepts and their need for further professional development. To address these issues, we conducted semi-structured interviews with eight primary school teachers and thematically analysed the data. Overall, the teachers reported positive attitudes towards the new curriculum and its focus on 21st-century skills, including programming and computational thinking. However, their understanding of these concepts was narrow, focused on only one of the six pertinent subskills: algorithms. Furthermore, the teachers’ teaching approaches were limited. Finally, we observed a variety of professional development processes and practices. The teachers accentuated a critical need for pro­fessional development within these domains. Our findings showed that to fulfil the curricular expectations of developing students’ computational thinking skills, increased training of primary school teachers is needed.

Scaling up a teacher development programme for sustainable computational thinking education: TPACK surveys, concept tests and primary school visits

Computational thinking (CT) education in K-12 requires extensive teacher development. This research investigates the effectiveness of a scalable and sustainable teacher development programme in promoting CT in primary education. This report presents two studies. Study 1 reports on the effectiveness of two 12-h courses using Scratch and App Inventor programming environments for CT development of teachers respectively, which involved 245 teachers from 47 primary schools. With teaching practices embedded, the programme, which used the framework of technological pedagogical content knowledge (TPACK), significantly enhanced teachers' content-related knowledge dimensions. The results indicate that the programme helped teachers develop advanced CT concepts such as data structures and procedures. Study 2, using thematic analysis, reports on CT strategies implemented in 47 schools through 94 school visits. The most mentioned strategies were the formation of teaching teams, lesson co-planning, and the integration of CT with subject teaching. The most mentioned challenges were teacher readiness, lesson time, and diversity – learners' abilities, interests, and approaches. Four types of support, including teacher development support, continuous and communal support, teaching materials support, and financial support were identified. The results suggest that a course-based programme with mixed programming environments and embedded teaching experience effectively develops teachers’ capabilities. However, continuous support for teachers in implementing the initiative after completing the programme is important, especially in addressing learner diversity and integrating CT with subject teaching.

A screen-based or physical computing unit? Examining secondary students’ attitudes toward coding

In recent years there has been a growing emphasis placed on access to computational thinking (CT) instruction for every K-12 student in the United States (U.S.). Concurrently, calls for integrating CT concepts within authentic science, technology, engineering, and mathematics (STEM) contexts have also increased. This is reflected by the inclusion of CT in the Next Generation Science Standards and the Standards for Technological and Engineering Literacy . However, methods for teaching CT concepts within secondary level STEM courses vary drastically. Physical computing, the design and programming of physical systems or devices using computational thinking skills, has become increasingly popular in the U.S. in attempts to integrate CT within authentic STEM problem-solving contexts. Despite this rise in popularity, there remains a limited but growing body of research investigating physical computing pedagogy and student learning. A mixed methods design was used in this study to examine 170 middle school students’ attitudes toward coding and after participating in either a screen-based or physical computing unit. The results indicated that students who completed the screen-based unit reported statistically greater attitudes toward the classroom applications and career/future use of computing concepts. Students in the treatment group believed that physical computing made learning computing concepts more difficult, but they preferred the hands-on learning opportunities provided by physical computing. Furthermore, male students reported higher attitudinal ratings than females regarding the influence computing would have on their future academic and career choices. This study provides implications for improving physical computing instruction and integration within STEM education contexts.

BRIDGING MAYER’S COGNITIVE THEORY OF MULTIMEDIA LEARNING AND COMPUTATIONAL THINKING IN TACKLING THE COGNITIVE LOAD ISSUES AMONG YOUNG DIGITAL NATIVES: A CONCEPTUAL FRAMEWORK

In 2020, it is undeniable the existence of digital natives in the tertiary education especially in the university. They are part of a tech-savvy generation that lead to the technological progress which always be connected and linked based on their wishes and needs without any hesitation of time and places. They are basically use a technology without guidance but how far they can manage to handle the consequences of the technology usage and problems occur, are always been questionable. It is undeniable the cruciality for a digital native to start having at least a basic of computer knowledge in managing their education and daily life. Learning about the computer science not only helps students to create programs, application or how to handle the devices, but strengthen the practice of Computational Thinking (CT). CT refers to the capacity of learners to systematically tackle unstructured tasks focused on four computing concepts such as decomposition, abstraction, pattern recognition and algorithmic thinking. The purpose of this paper is to study the relationship between CT and Mayer’s Cognitive Theory of Multimedia Learning (CTML) towards the cognitive load of the learners. This research focuses on CT concept that will be integrated with the Mayer’s CTML in designing the learning material for young digital natives. Researcher therefore proposes a conceptual framework that aims to comprehend how to facilitate the cruciality of CT concepts in Mayer’s CTML when designing the instructional learning. The proposed conceptual framework adds value in tackling the cognitive load among students, particularly in the context of the digital native generation. This paper provides several implications and highlights for further studies through comprehensive and wide-ranging literature review.

Examining Science and Technology/Engineering Educators' Views of Teaching Biomedical Concepts Through Physical Computing.

Programming and automation continue to evolve rapidly and advance the capabilities of science, technology, engineering, and mathematics (STEM) fields. However, physical computing (the integration of programming and interactive physical devices) integrated within biomedical contexts remains an area of limited focus in secondary STEM education programs. As this is an emerging area, many educators may not be well prepared to teach physical computing concepts within authentic biomedical contexts. This shortcoming provided the rationale for this study, to examine if professional development (PD) had a noticeable influence on high school science and technology and engineering (T&E) teachers’ (1) perceptions of teaching biomedical and computational thinking (CT) concepts and (2) plans to integrate physical computing within the context of authentic biomedical engineering challenges. The findings revealed a significant difference in the amount of biomedical and CT concepts that teachers planned to implement as a result of the PD. Using a modified version of the Science Teaching Efficacy Belief Instrument (STEBI-A) Riggs and Enochs in Science Education, 74(6), 625–637 (1990), analyses revealed significant gains in teachers’ self-efficacy toward teaching both biomedical and CT concepts from the PD. Further analyses revealed that teachers reported increases in their perceived knowledge of biomedical and CT concepts and a significant increase in their intent to collaborate with a science or T&E educator outside of their content area. This study provides implications for researchers and educators to integrate more biomedical and physical computing instruction at the secondary education level.

The Pedagogical Alignment of Computational Thinking to Architecture Education for the 21st Century Learners

For the 21st century learners, Millennials and Gen-Z students, the concept of Computational Thinking (CT) has been inclusively affirmed in higher education with different teaching methods and strategies. However, it has been almost a decade that Generation Z students form the main bulk of students in classrooms. And their distinct characteristics from the Millennials have necessitated rethinking educational practices, pedagogies and teaching approach to provide an optimal and holistic learning environment that meets their learning needs. In this regard, by scrutinizing the contemporary approach to the concept of Computational Thinking, this article discusses the pedagogical alignment of CT in architecture education by addressing its cognitive contributions as a mental tool for the 21st century learners. It highlights the challenges of teaching computational thinking within the current pedagogical framework in architecture education by regarding the learning preferences and attributes of Generation-Z.

Modelling Digital Competence by Combining Computational Thinking with General Learning Taxonomies

In the context of a rapid digital transformation, digital competence is now to be regarded as a fourth cultural skill complementing reading, writing, and arithmetic. In this paper, we argue that a well-structured and sound competence model is needed as a shared foundation for learning, teaching, pedagogical diagnostics and evaluative schemes in the school system. Every competence model should build upon a consistent, theoretically sound framework for teaching and learning. We consequently develop a competence model for digital competence by drawing on the concept of computational thinking as well as on general learning taxonomies. By combining different knowledge and process dimensions with essential facets of computational thinking a cube model of digital competence can be constructed. Hence, we develop and substantiate a structure model for digital competence building upon the concept of computational thinking that goes beyond the existing frameworks only focusing on the subject-related context and put this up for discussion. The next step would then be to supplement the structure model by specific learning objectives, so that developing approaches to teaching and learning digital competence will have a sound basis.

Teachers’ Perceptions of and Concerns About Integrating Computational Thinking into Science Teaching After a Professional Development Activity

Although there is a lot of interest in the development of computational thinking (CT) and the benefits it could have for every student, integrating it into science classrooms may be more difficult than traditional teaching. This can be very challenging for South African science teachers. Thus, there is an increasing need to prepare teachers and systematically engage them in professional development activities to help them learn, unlearn, relearn and restructure their thoughts, perceptions and attitudes towards integrating CT in science classrooms. This study explored teachers’ perceptions and concerns about integrating CT in science teaching. Twenty-two science teachers from innercity secondary schools in South Africa were chosen to be part of this exploratory case study. Data were collected through take-home assignments and focus group discussions containing a series of open-ended questions. The concern-based adoption model was used as a lens to understand teachers’ stages of concern. Data were analyzed using thematic analysis. It was found that sampled science teachers viewed CT as a valuable tool that can help promote learners’ data management practices and problem-solving practices, especially in reducing complex problems to researchable problems. The findings also showed that teachers intend to integrate CT into their science classrooms by refining their existing practices. However, teachers showed high informational, personal and management-related concerns regarding integrating CT in South African science classrooms: they needed more practical and contextual ideas on strategically integrating CT in their daily lessons. Conversely, teachers showed limited concern at the unrelated, consequence, collaboration and refocusing stage. This suggests a need for teacher education programmes in South Africa to focus more acutely on training pre-service teachers on how to plan and design science instruction using computational thinking concepts and practices.

Computational Thinking Process of Prospective Mathematics Teacher in Solving Diophantine Linear Equation Problems

<p style="text-align: justify;">Prospective teachers facing the 21st century are expected to have the ability to solve problems with a computer mindset. Problems in learning mathematics also require the concept of computational thinking (CT). However, many still find it challenging to solve this problem. The subjects in this study were twenty-one prospective mathematics teachers who took number theory courses, and then two research samples were selected using the purposive sampling technique. This study uses a qualitative descriptive method to describe the thinking process of prospective teachers in solving Diophantine linear equation problems. The results showed that the first subject's thought process was started by turning the problem into a mathematical symbol, looking for the Largest Common Factor (LCF) with the Euclidean algorithm, decomposition process, and evaluation. The second subject does not turn the problem into symbols and does not step back in the algorithm. The researcher found that teacher candidates who found solutions correctly in their thinking process solved mathematical problem used CT components, including reflective abstraction thinking, algorithmic thinking, decomposition, and evaluation. Further research is needed to develop the CT components from the findings of this study on other materials through learning with a CT approach.</p>

Effects of a teacher development program on teachers' knowledge and collaborative engagement, and students' achievement in computational thinking concepts

AbstractAn important educational goal for the next generation is the ability to think computationally. Cultivating K‐12 students' computational thinking (CT) requires the capacity building of teachers through teacher development programs. However, if students' learning outcomes were not assessed, it is not known whether the enhancement of teacher capacity could impact on students' learning. This study aimed to examine how a teacher development program changed teachers' content knowledge and collaborative engagement, which in turn influenced their students' learning achievement. The participants were 81 teachers and 3226 students from primary schools. We employed multi‐level modelling to study the relationships between teacher‐level variables and student achievement assessed by a CT concepts test. The teachers' content knowledge and collaborative engagement were significantly enhanced through the program, which in turn had a significant impact on student achievement. Teachers' years of teaching experience, but not their gender or whether they had majored in computer science, could also affect student achievement. The results indicate that a teacher development program can play a significant role in enhancing the teachers' CT content knowledge and collaborative engagement, which can then have a positive effect on student learning.Practitioner notesWhat is already known about this topic The cultivation of students' computational thinking (CT) in K‐12 education requires the capacity building of teachers. A teacher development program can improve teachers' knowledge and attitudes related to CT. Whether the enhancement of teacher capacity can in turn affect students' learning achievement in CT is less studied. What this paper adds We found that a teacher development program could significantly enhance teachers' knowledge in CT and their collaborative engagement in the program. Using multilevel modelling, we found further that the enhancement of teachers' knowledge and collaborative engagement could affect students' understanding of CT concepts positively. Teachers' years of teaching experience, but not their gender or whether they had majored in computer science, could also influence student achievement. Implications for practice and/or policy In designing similar teacher development programs for teachers, collaborative engagement opportunities should be provided as it can have a positive impact on student achievement. Although the majority of teachers do not have a background in computer science, a teacher development program can play a significant role in enhancing their knowledge in CT, no matter they had majored in computer science or not. The significance of the program is not limited to the development of teachers, as the enhancements of teachers' knowledge and collaborative engagement through the program can in turn have a positive impact on students' understanding of CT concepts.

Retrieval Practices Enhance Computational and Scientific Thinking Skills.

The notion of teaching experts’ habits of mind (e.g., computational thinking and scientific thinking) to novices seems to have inspired many educators and researchers worldwide. In particular, a great deal of efforts has been invested in computational thinking (CT) and its manifestations in different fields. However, there remain some troubling spots in CT education as far as how to teach it at different levels of education. The same argument applies to teaching scientific thinking (ST) skills. A remedy has been suggested to narrow CT and ST skillsets down to core cognitive competencies so they can be introduced in early and middle grades and continue to be nurtured during secondary and post-secondary years. Neuroscientists suggest that the act of (computational) thinking is strongly linked to the acts of information storage/retrieval by our brain. Plus, years of research have shown that retrieval practices promote not only knowledge retention but also inductive reasoning and deductive reasoning. Not surprisingly, these reasoning skills are core elements of both CT and ST skillsets. This article will mesh the findings of a teacher professional development with the existing literature to lay a claim that retrieval practices enhance CT and ST skills. The study offered training to secondary school teachers (n = 275) who conducted classroom action research to measure the impact of retrieval practices on teaching and learning of STEM and CT concepts. We used a quasi-experimental research design with purposeful sampling and a sequential mixed-methods approach focusing on the impact of professional development on teacher outcomes and, in turn, on student outcomes. A survey of teacher participants showed that the majority (96%) of survey respondents (n = 232) reported a good understanding of retrieval strategies, and how relevant ideas can be implemented and tested in the classroom. A large number of action research (target-control) studies by teachers (n = 122) showed that students who learned STEM and CS concepts through retrieval practices consistently scored 5–30% higher than those using the usual blocked practice. In most cases, the difference was statistically significant (p < 0.05). While the study contributes to retrieval practices literature, those looking for best practices to teach core CT and ST skills should benefit from it the most. The study concludes with some recommendations for future research based on the limitations of its current findings.

The importance of computational thinking training for primary school teachers

The importance of modern schools in developing students’ problem-solving skills, including through digital tools, is described in the article, which includes the development of basic coding skills and digital literacy, as well as the ability to solve problems and make decisions based on planning and analysis of situations. Computational thinking (CT) is built on the foundation of these abilities. The authors contend that the employment of specialized digital tools promotes the development of computational thinking and that purposeful creation of computational thinking improves teachers’ and students’ digital competence. The concept of CT, as well as existing definitions and components, are examined in this article. A list of courses from various countries’ curriculum on which CT is studied in primary school is provided. The importance of CT as a fundamental talent for everyone is underlined, and it should be developed through the integration of several disciplines to solve problems. The link between the CT components and the key competencies that should be instilled in kids as part of the primary education curriculum. The findings of a survey of more than 60 primary school teachers from various regions of Ukraine about their understanding of the concept of computational thinking and their experience in the development of skills related to all components of computational thinking in primary school students are presented. A review of open educational resources from around the world is offered to assist teachers in enhancing students’ CT skills. The strategy for putting the CT development concept into practice for future teachers and primary school teachers is offered, taking into account the ability to employ specific digital tools.

Validating a computational thinking concepts test for primary education using item response theory: An analysis of students’ responses

Although instruments for assessing students' computational thinking (CT) concepts in primary education have been developed, they have rarely been validated in terms of item response theory (IRT). We consider IRT to be a rigorous validation tool and apply it to a CT concepts test for primary education involving 13,670 students. A two-parameter logistic model was chosen over other IRT models, as it indicated an acceptable model fit and item fit. The discrimination parameters indicated that the instrument could effectively distinguish between students with various ability levels. Nominal response modelling in IRT was used to retrieve information from the students' responses, and those with a lower ability level were found to only consider one of the conditions provided, had no understanding of the repetition structure, and might have difficulties in associating a sprite with its corresponding codes. Based on ability estimates, we also found that the students’ ability in terms of CT concepts increased with grades and that boys generally performed slightly better than girls. These results suggest that the instrument can be used to examine the learning achievements of students in terms of CT concepts.

ScratchThAI: A conversation-based learning support framework for computational thinking development

Computational Thinking (CT) has been formally incorporated into the National Curriculum of Thailand since 2017, where Scratch, a block-based visual programming language, has been widely adopted as CT learning environment for primary-level students. However, conducting hands-on coding activities in a classroom has caused substantial challenges including mixed-ability students in the same class, high student-teacher ratio and learning-hour limitation. This research proposes and develops ScratchThAI as a conversation-based learning support framework for computational thinking development to support both students and teachers. More specifically, it provides learning experiences tailored to individual needs. Students can learn CT concepts and practice online coding anywhere, anytime. Moreover, through its ScratChatbot, students can ask for CT concept explanations, coding syntax or practice exercises. Additional exercises may be assigned to students based on the diagnosed individual learning difficulties in a particular topic to provide possible and timely intervention. Teachers can track learning progress and performance of the whole class as well as of individuals through the dashboard and can take suitable intervention within limited school hours. Deploying ScratchThAI to several Thai schools has enabled this research to investigate its effectiveness in a school setting. The obtained results indicated positive teacher satisfaction, better learning performance and higher student engagement. Thus, ScratchThAI contributes as a possible and practical solution to CT skill development and CT education improvement under the aforementioned challenges in Thailand.

The effects of WeDo 2.0 robot workshop on Omani grade 5 students’ acquisition of the computational thinking concepts and acceptance of the robot technology

ABSTRACT This research aimed to study the effects of the WeDo 2.0 robot workshop on grade five students’ acquisition of the computational thinking concepts (CTCs) and their acceptance of the robot technology. A quasi-experimental method, One-Group Pertest Post-test design, was used. Thirty-five grade 5 students participated in a five-day (four hours of daily training) informal robot workshop in Oman. The findings of the study showed a significant improvement in grade five students’ acquisition of CTCs after attending the robot workshop particularly in three dimensions of the CTCs: Sequential control flow, Loops, and Conditionals. and a positive acceptance of robot technology.