Fostering computational thinking with simulated 3D robots in secondary education

Integrated computing uses computing tools and concepts to support learning in other disciplines while giving all students opportunities to experience computer science. Integrated computing is often motivated as a way to introduce computing to students in a low-stakes environment, reducing barriers to learning computer science, often especially for underrepresented groups. This study explored integrated computing activities implemented in US schools to examine which programming and CT concepts they teach and whether those concepts differed across contexts. We gathered data on 262 integrated computing activities from in-service K-12 teachers and 20 contextual factors related to the classroom, the teacher, and the school. Our analysis revealed that programming and CT concepts were inversely related to five contextual factors, such that factors predicting more CT concepts also predicted fewer programming concepts. These factors reflected school resources, such that wealthier schools used activities with more CT concepts and fewer programming concepts. In addition, factors related to underrepresented groups often related to fewer concepts being taught in activities. School racial composition was the only factor of the 20 that had a relationship with both types of concepts in the same direction-students from underrepresented groups used activities with fewer CT and programming concepts. Our findings suggest that, although integrated computing can potentially introduce computing to a broader audience, we must evaluate what these activities are teaching and to whom. Another primary contribution of this work is an open-access dataset about integrated computing activities, the concepts that they teach, and the contextual factors around their use.

Embedding technological tools in learning and providing learning environment that can support wider use of technology to equip students with computational thinking have become the trend in education. Computational thinking is a mental skill that can be acquired through coding activity. Various educational programming tools and coding software have been developed to help school children learn programming and coding at different levels including young children in preschool. This research aims to explore the use of ScratchJr, an educational programming tool in supporting young children learn programming principles and concepts. We found that ScratchJr that is developed with icon-based graphical programming blocks is a suitable educational programming tool for young children. The research findings provide insightful information for us to enrich the teaching modules for young children to progressively learn programming principles and concepts, and to acquire computational thinking.KeywordsComputational thinkingIcon-based graphical programming blocksProgrammingScratchJrYoung children

Background. Learning programming is a cognitively demanding field of study accompanied with various difficulties. Although there is a high demand in the market for programmers, software analysts and engineers, a high dropout rate is recorded in relevant fields of study. Serious games are a promising means of engaging students in learning programming by giving them more incentives and making the process of learning programming concepts and languages more entertaining. Aim. This article introduces a new serious game called PY-RATE ADVENTURES, which aims to assist young students in their introduction to the basic programming concepts using Python. The game does not have any prerequisites and is suitable for players with no previous knowledge of programming. This article aims to present important information regarding the analysis, design and pilot evaluation of PY-RATE ADVENTURES. Method. The game was evaluated by 31 people that had recently graduated or were students of an Interdepartmental Programme of Postgraduate Studies in Information Systems. The participants voluntarily played the game and answered a questionnaire based on the MEEGA+ model, after their hands on experience with the game. This questionnaire’s purpose was to evaluate PY-RATE ADVENTURES in terms of perceived player experience and short-term learning. Results. The participants positively evaluated the game almost in all the elements of player experience. Furthermore, the majority of the users consider that the game helped them to learn basic programming concepts in Python and stated that they would prefer to learn programming with this game rather than other teaching methods. Conclusion. The positive results of the pilot evaluation give us the motivation to proceed and evaluate the game with students in secondary education, in order to extract stronger and generalisable conclusions regarding the impact of the game as an educational tool for learning programming concepts.

New generations are using and playing with mobile and computer applications extensively. These applications arethe outcomes of programming work that involves skills, such as computational and algorithmic thinking. Learningprogramming is not easy for students children. In recent years, academic institutions like theMassachusetts Institute of Technology (MIT) and hi-tech companies, such as Google and Khan Academy, haveintroduced online environments to facilitate the teaching and learning of programming. Most of these programmingenvironments are web-based, and interactive and are supported with visual multimedia features. Therefore, they havebecome easy to use, very attractive and helpful for teaching children how to program and to develop theiralgorithmic and computational thinking skills. The proposed presentation will describe research that examined theteaching of a course to primary school children based on three on-line interactive environments: "Plastelina" for logicgames, "Code with Anna and Elsa" via the Hour of Code project block-oriented programming environment, forblock programming and "Turtle Academy" for textual programming in the Logo language. The current researchincluded the development, implementation and evaluation of the course at an elementary school. In addition, it wasaimed at investigating the pupils' attitudes toward the learning of computer programming, both before and afterparticipation in the course. The results revealed that the pupils' attitudes towards programming remained positivealso also after the participation in the course. It was also found that programming improved children's problemsolving skills.

This article describes the design and implementation of the course Introduction to Computational Thinking (PC-01) for primary and secondary education. The course introduces the “concepts” and core “processes” of Computational Thinking using a visual programming environment. The design of the course PC-01 includes a set of multimedia content, learning tools and technologies that help teachers and students in the teaching-learning process. These tools allow the teacher the successful delivery of the course content as well as the individual/collective monitoring of students' progress in the course. Students have access to their progress throughout the course and participate in creative and collaborative tasks. This course also serves to introduce transversely educational technologies to many students of primary and secondary education. The technological environment integrates the online teaching resources and the methodological tools of the course. The course uses Scratch 2.0 as the programming environment and Moodle as the learning platform. At present the course is being implemented in public schools in the Dominican Republic.

Enhancing elementary school students' computational thinking and programming learning with graphic organizers

In the light of the involvement of information and communication technologies, Teaching the concepts of computer science, programming and algorithms has become necessary.We study in this article the approach of computational thinking and then we develop this approach through a descriptive methodology based mainly on the specification and algorithms and achieve the concepts of computational thinking called Relational Algorithmic thinking Approach and highlight the effectiveness of this methodology in education.

<p>The recent advancement in computational thinking (CT) research has reported numerous learning benefits to school-age children. The long-standing perceived difficulty of computer programming has challenged the acquisition of CT skills from programming education. Several block-based programming environments (BBPEs) have been developed to reduce this difficulty and enhance active engagement in computational-related activities. Although numerous studies have examined students’ level of interactions during block-based programming modality (BPM) activities, a major gap in the literature is the paucity of research evidence reporting the association between these interactions and CT. This study, therefore, investigates the association between interaction patterns during BPM activities and CT skills. The present study employed a longitudinal approach where the same participants were observed over eight weeks. Thirty-five, second-year-level computer science and computer education students (mean age: 19.8; male = 23, female = 12) from a research university in Nigeria were recruited. Their computational activities over the study periods were video-recorded. The participants’ CT skills were collected using the computational thinking test and the computational thinking scale. Findings indicate four interaction patterns: learner–learner, learner–content, learner–teacher, and learner–distractor. Learner–learner and learner–content were prevalent. The interaction patterns significantly predict CT skills although significant differences exist across gender, cognitive load, spatial ability, and programming proficiency. The research has provided opportunities for educators to integrate BBPEs in learning programming and CT concepts. Although such integration is likely to occur with the help of strong educational policies, teachers are encouraged to cultivate the spirit of collaboration in students during programming activities.</p>

This study investigated minority students’ learning in programming. The variables, including self-efficacy, computational thinking, and learning performance were the focus of this study. This study explored the relationships of creative self-efficacy, learning self-efficacy, computational thinking, and learning performance among minority undergraduate students. The influence of creative self-efficacy, learning self-efficacy, and computational thinking on learning performance was explored. The participants were minority students from a HBCU institution in the southeastern United States. Quantitative approaches were performed to analyze the collected data. The results indicated that self-efficacy, learning self-efficacy, and computational thinking were positively correlated with learning performance. Learning self-efficacy and computational thinking were significant predictors of learning performance among minority students.

Programming has received extensive attention for the embodiment of computational thinking (CT) skills. However, the lack of in‐depth research on the characteristics of college students' CT skills in text‐based programming learning has resulted in the unknown distribution characteristics and evolution patterns of their CT skills, which cannot effectively constitute an effective tracking analysis of their CT skills, thus affecting the cultivation of creative thinking and problem‐solving skills for them. Therefore, the purpose of the paper is to explore the characteristics of college students' CT skills through text‐based programming work and discover the overall characteristics, individual differences and evolutionary patterns of their CT skills on the relation between text‐based programming and CT skills through data analysis. It was found that there are roughly five categories of CT difference and four major categories with nine subcategories of CT evolution among college students. The results showed that the Control and Data skills were the students' dominant skills. In contrast, Algorithm skills were relatively weak. Only about 1/3 of the students had the phenomenon of continuous skill improvement, and programming learning did not have a significant impact on the improvement of CT skills for some students. Finally, we propose several suggestions for CT skills development strategies in response to the students' characteristics in CT skills. The study can not only fill the gaps of the current study but also identify the evolutionary characteristics of students' CT skills, which can effectively intervene in college students' programming learning and help improve their CT skills.

The study examined the effect of teaching text-based programming with a physical programming tool on secondary school students’ computational thinking skills and self-efficacy perceptions. The study was conducted according to a sequential explanatory design as a mixed method research. The study group consisted of 85 secondary school students. Within the scope of the study, a physical programming tool called Micro:bit was used to teach Python programming for a period of 6 weeks. Data were collected using the Self-Efficacy Perception Scale for Computational Thinking Skill, Bebras: International Challenge on Informatics and Computational Thinking Tasks, tests focused on programming tool, concepts, and processes, and through semi-structured interview questioning. According to the findings obtained from pretests and posttests, a significant and positive difference was found in the students’ computational thinking skills and self-efficacy perceptions towards computational thinking skill. As a result of having received instruction in programming, the students satisfactorily learnt the required programming concepts and processes. Through learning Python programming with a physical programming tool, the students not only gained the skills required to write appropriate syntax, and to test and debug code, but they also learnt programming concepts such as variables, conditional expressions, loops, and functions.

The graphics calculator (GC) is a hand-held technology. With it, students visualize and understand concepts in mathematics and science better. It also allows them to make real-world connections, binding together advanced graphing functionality and conceptual science, technology, engineering, arts and mathematics (STEAM). As they gain a deeper understanding of abstract concepts, they acquire creative and critical thinking and problem- solving skills they need to reach greater academic successes. In learning, GC plays several roles in increasing students’ computational thinking and procedural skills. Despite being a learning tool that satisfies science and mathematics curriculum needs, the calculator often has been used as an add-on to traditional teaching methodology rather than central and in more integrated ways. This study looks into the potential of developing computational thinking skills using GC technology. The data of the study was obtained from secondary sources through a systematic review method. The study showed that GC seems to be effective tools to practice STEAM education as well as to develop students’ computational thinking through analysing and decompose real problem as well as engaging in the abstraction process and developing an algorithm using coding. The findings provides justifications on the impact of GC in developing computational thinking skills thereby maximizing the pedagogical benefits to students.

A systematic review of integrating computational thinking in early childhood education

Artificial intelligence (AI) literacy is a global strategic objective in education. However, little is known about how AI should be taught. In this paper, 46 studies in academic conferences and journals are reviewed to investigate pedagogical strategies, learning tools, assessment methods in AI literacy education in K-12 contexts, and students’ learning outcomes. The investigation reveals that the promotion of AI literacy education has seen significant progress in the past two decades. This highlights that intelligent agents, including Google’s Teachable Machine, Learning ML, and Machine Learning for Kids, are age-appropriate tools for AI literacy education in K-12 contexts. Kindergarten students can benefit from learning tools such as PopBots, while software devices, such as Scratch and Python, which help to develop the computational thinking of AI algorithms, can be introduced to both primary and secondary schools. The research shows that project-based, human–computer collaborative learning and play- and game-based approaches, with constructivist methodologies, have been applied frequently in AI literacy education. Cognitive, affective, and behavioral learning outcomes, course satisfaction and soft skills acquisition have been reported. The paper informs educators of appropriate learning tools, pedagogical strategies, assessment methodologies in AI literacy education, and students’ learning outcomes. Research implications and future research directions within the K-12 context are also discussed.

Linking sustainable development with computational thinking promotes high-impact problem solving, integrating fundamental concepts of computer programming. This study analyzed the relationship between computational thinking and the Sustainable Development Goals (SDGs) using text mining and data visualization techniques. A text mining method was employed to analyze computational thinking and its sub-competencies (decomposition, pattern recognition, abstraction and algorithm) appearances in the OSDG Community dataset, consisting of 32,120 text fragments labeled with the associated SDG. Results revealed that computational thinking and its subcompetencies: decomposition, pattern recognition, abstraction, and algorithm, were frequently linked to SDGs 4 (quality education), SDG 5 (gender equality), SDG 6 (clean water and sanitation), and SDG 11 (sustainable cities and communities). The findings demonstrate the potential of computational thinking to provide innovative solutions to global problems and support the achievement of the SDGs. The study can be of value to stakeholders in the social, governmental, academic and business sectors interested in sustainable development and educational innovation in the application of computational thinking.