Development Of Computational Thinking Skills Research Articles

Computational Thinking with a Multi-literacy Model Using Interactive PowerPoint Media: An Experiment in Elementary Schools

Elementary school students need to acquire computational thinking as a crucial skill in the digital age. Similar to mathematical skills, computational thinking is a fundamental competence in digital literacy. It is used to solve problems in learning. One approach is to facilitate children’s learning by emphasizing computational thinking, such as using the multi-literacy model with interactive PowerPoint slides. This study aimed to assess and characterize the influence of multi-literacy models aided by interactive PowerPoint media on the development of computational thinking skills in elementary school students, considering their prior knowledge. Involving a total sample of 56 4th-grade elementary school students, this quantitative study employed a 3 x 2 factorial design. The sample included 14 students in the high group, 28 in the medium group, and 14 in the high group. The research revealed that the implementation of a multi-literacy learning approach, assisted by interactive PowerPoint media, significantly enhances student’s acquisition and improvement of computational thinking skills. This is because children can develop computational thinking skills in an enjoyable environment using PowerPoint media. Another study revealed that students in the high group performed much better on average when it came to learning computational thinking skills. Meanwhile, the average gain of computational thinking skills in the medium group was only slightly different from that of the low group. Keywords: computational thinking, multi-literacy model, interactive PowerPoint media

Primary school students' perceptions and developed artefacts and language from learning coding and computational thinking using the 3C model

AbstractBackgroundA resurgence in teaching coding in primary school classrooms has led to a pedagogical swing towards using physical computing and coding to develop students' use of algorithms, computational thinking, and problem‐solving skills. Two obstacles impede the optimal development of these objectives: the availability of a suitable pedagogy and an instructional sequencing model for primary school teachers to effectively present coding and computational thinking concepts and skills to students in alignment with their developmental stage.ObjectiveThis study aims to address both obstacles by introducing the 3C Model, a newly developed instructional sequence grounded in established pedagogies and designed to effectively teach coding and computational thinking skills to primary school students based on their developmental stage.MethodsThe qualitative study employed two data sources to triangulate findings, using: (1) semi‐structured interviews and thematic analysis to investigate 11 primary school students' perceptions of their learning experiences with the 3C Model, and (2) researcher observations along with reflections of the students' developed and demonstrated learning through the method of knowing‐in‐action, reflection‐in‐action, and reflection‐on‐action.Results and ConclusionsThe findings of this study fill a gap in the existing literature by demonstrating that the pedagogical and sequential approach embedded in the 3C Model not only enhanced students' engagement levels but also resulted in improved curriculum learning outcomes. The 3C Model provides teachers with a coherent and age‐appropriate instructional structure. It uses physical computing devices and digital coding platforms to introduce coding concepts, furthering the development of computational thinking skills in primary school students beyond mere procedural and rote learning.ImplicationsThe study holds important implications for practical applications, as it addresses an absence in the literature of an established pedagogy and instructional sequencing model for effectively teaching coding and computational thinking concepts and skills to primary school students. Drawing on established pedagogical and developmental learning theories, the 3C Model provides primary school teachers with an engaging, age‐appropriate instructional method that avoids decontextualised teaching and surface‐based learning. Instead, it encourages collaborative student work and contextualised learning, steering away from isolated and generic approaches.

Estimating Computational Thinking Ability Using Tablets and Electronic Pens

This study proposes a method to estimate a computational thinking ability utilizing handwritten logs. The development of computational thinking skills to build a plan to organize solutions is crucial from an early age. The methods for cultivating these abilities in elementary education are still in the developmental stages. The proposed method analyzes hand-drawing logs obtained through tablets and electronic pens. Participants are assigned illustration tasks utilizing the layer functionality. The transition among layers objectively assesses whether individuals solve tasks in a perspective manner according to a plan. In an experiment involving 24 students and graduate students, an application with seven layers is employed to assign a 20-minute task of replicating a car illustration. From the results, it turns out we can estimate computational thinking abilities from hand-drawing logs. In addition to that, the results reveal the characteristic way of using and holding the pen that occurs when one has a planning perspective unique to computational thinking. This research promotes the ongoing exploration of methodologies for assessing computational thinking skills, particularly in the context of elementary education. It contributes to fostering computational thinking abilities in younger ages.

Proximal Policy Optimization-Based Reinforcement Learning and Hybrid Approaches to Explore the Cross Array Task Optimal Solution

In an era characterised by rapid technological advancement, the application of algorithmic approaches to address complex problems has become crucial across various disciplines. Within the realm of education, there is growing recognition of the pivotal role played by computational thinking (CT). This skill set has emerged as indispensable in our ever-evolving digital landscape, accompanied by an equal need for effective methods to assess and measure these skills. This research places its focus on the Cross Array Task (CAT), an educational activity designed within the Swiss educational system to assess students’ algorithmic skills. Its primary objective is to evaluate pupils’ ability to deconstruct complex problems into manageable steps and systematically formulate sequential strategies. The CAT has proven its effectiveness as an educational tool in tracking and monitoring the development of CT skills throughout compulsory education. Additionally, this task presents an enthralling avenue for algorithmic research, owing to its inherent complexity and the necessity to scrutinise the intricate interplay between different strategies and the structural aspects of this activity. This task, deeply rooted in logical reasoning and intricate problem solving, often poses a substantial challenge for human solvers striving for optimal solutions. Consequently, the exploration of computational power to unearth optimal solutions or uncover less intuitive strategies presents a captivating and promising endeavour. This paper explores two distinct algorithmic approaches to the CAT problem. The first approach combines clustering, random search, and move selection to find optimal solutions. The second approach employs reinforcement learning techniques focusing on the Proximal Policy Optimization (PPO) model. The findings of this research hold the potential to deepen our understanding of how machines can effectively tackle complex challenges like the CAT problem but also have broad implications, particularly in educational contexts, where these approaches can be seamlessly integrated into existing tools as a tutoring mechanism, offering assistance to students encountering difficulties. This can ultimately enhance students’ CT and problem-solving abilities, leading to an enriched educational experience.

An Investigation of In-service Teachers’ Perceptions and Development of Computational Thinking Skills in a Graduate Emerging Technologies Course

This study investigated in-service teachers’ perceptions and development of computational thinking (CT) skills in an online graduate emerging technologies course. Participants perceived that they increased their CT problem-solving and creativity skills and decreased their collaborative learning and critical thinking skills. Additionally, teachers increased their CT test scores after taking the course. Most teachers used CT terminology correctly (i.e., algorithms and decomposition). However, only 59% correctly described abstraction and pattern recognition, while most teachers did not mention debugging. The authors call on teacher educators to address in-service teachers’ knowledge gaps in their CT skills and select appropriate strategies for CT preparation.

Multiplayer Serious Games Supporting Programming Learning

Computational thinking (CT) is crucial in education for providing a multifaceted approach to problem-solving. However, challenges exist such as supporting teachers' knowledge of CT and students' desire to learn it, particularly for non-technical students. To combat these challenges, Computer Supported Collaborative Learning (CSCL) has been introduced in classrooms and implemented using a variety of technologies, including serious games, which have been adopted across several domains aiming to appeal to various demographics and skill levels. This research focuses on a Collaborative Multiplayer Serious Game (MSG) for CT skill training. The architecture is aimed at young students and is designed to aid in the learning of programming and the development of CT skills. The purpose of this research is to conduct an empirical study to assess the multiplayer game gameplay mechanics for collaborative CT learning. The proposed game leverages a card game structure and contains complex multi-team multi-player processes, allowing students to communicate and absorb sequential and conditional logics as well as graph routing in a 2D environment. A preliminary experiment was conducted with four fourth-graders and eight sixth-graders from a French school in Morocco who have varying levels of understanding of CT. Participants were split into three groups each with two teams and were required to complete a 16-question multiple-choice quiz before and after playing the same game to assess their initial structural programming logics and the effectiveness of the MSG. Questionnaires were collected along with an interview to gather feedback on their gaming experiences and the game’s role in teaching and learning. The results demonstrate that the proposed MSG had a favourable effect on the participants’ test scores as the scores of 4 of the teams increased and 1 remained the same. All students performed well on the sequential and conditional logics, which was significantly better than the achievement of the Bebras test of the graph routing. Furthermore, according to the participants, the game provides an appealing environment that allows players to immerse themselves in the game and the competitive aspect of the game adds to its appeal and helps develop teamwork, coordination, and communication skills.

Development and preliminary testing of the AlgoPaint Unplugged Computational Thinking Assessment for Preschool Education

The concept, development and assessment of computational thinking have increasingly become the focus of research in recent years. Most of this type of research focuses on older children or adults. Preschool age is a sensitive period when many skills develop intensively, so the development of computational thinking skills can already begin at this age. The increased interest in this field requires the development of appropriate assessments. Currently, there are only a limited number of computational thinking assessments for preschool children. Based on this shortcoming, an assessment tool, named AlgoPaint Unplugged Computational Thinking Assessment for Preschool, was created addressed for 4-7 years old children. It is a paperpencil-based test, which examines the following computational thinking domains: algorithms and debugging. Regarding computational concepts, simple instructions, simple and nested loops, and conditionals are included in the test. For the preliminary testing, AlgoPaint test was applied by 11 preschool teachers with 56 preschool age children. The test was also evaluated by 6 experts in algorithmic thinking working at universities. Based on the feedback given by the teachers and the experts, and the results of the children, AlgoPaint Computational Thinking Test was revised and completed. The revised version of the test is included in the appendix of the paper.

The effect of an unplugged coding course on primary school students' improvement in their computational thinking skills

AbstractBackgroundToday, computational thinking (CT), which is considered to be a form of literacy, has taken its place in the ICT curriculum of many countries at the K‐12 level. Therefore, there is a need for more evidence with regards to a theoretical and practical understanding of CT skills’ development of K‐12 students.ObjectivesThe purpose of the study was to investigate the effect of an unplugged coding course on primary school students’ development of CT skills, differences in their CT skills in terms of socio‐demographics such as gender, computer ownership, daily computer use, and home Internet access, and the relationship between their CT and 21st century skills.MethodsThe research was based a quasi‐experimental design with one‐group pretest‐posttest with follow‐up. The CT skills of 212 third and fourth grade students at a public primary school of Turkey were measured with a CT Skills Test before, after, and about ten weeks following having attended an unplugged coding course.Results and ConclusionsThe results of the study showed that the unplugged coding course statistically significantly improved the participants’ CT skills, specifically in algorithmic design, abstraction, evaluation, decomposition, and generalization. Moreover, the findings indicated that primary school students’ CT skills were not associated with their socio‐demographics. In addition, the students’ CT skills were found to be positively and statistically significantly correlated with their collaboration and communication skills.ImplicationsThis study contributes to understanding of the effects of unplugged activities on the development of primary school students’ CT skills, which is beneficial to teaching practices for CT skills in the primary education.

The Development of Computational Thinking and Mathematics Problem Solving Skills Through Mathematics Modelling Activities

The latest TIMSS report highlighted that secondary school students from Malaysia did not perform well in this global assessment on mathematics achievement. Some studies have pointed out that students’ mathematics achievement can be improved by equipping them with computational thinking. Therefore, this study examined the development of computational thinking skill and mathematics problem-solving skills via mathematics modelling activities among secondary students in Malaysia. The research instrument used for the assessment of computational thinking was adapted from UK Berbras Challenges and CAS Barefoot Team from United Kingdom. In addition, rubrics for development of mathematics problem solving skill was adapted from Polya problem solving model. This study adopted qualitative approach and the modelling activities were conducted for six weeks. The activities were introduction of modelling, individual modelling task and group modelling task. Data were also collected based on results of computational thinking test and mathematics test. Data from observation and interviews were analyzed, and the scores obtained from both tests were compared and analyzed as well. Based on the findings of the study, it could be concluded that the students progressed at different levels during the development of their computational thinking skill and mathematics problem-solving competency via mathematics modelling activities. These results indicated that mathematics modelling activities can be conducted at schools to improve students’ performance in Mathematics.

Exploring Gender Differences in Computational Thinking Learning in a VR Classroom: Developing Machine Learning Models Using Eye-Tracking Data and Explaining the Models

Understanding existing gender differences in the development of computational thinking skills is increasingly important for gaining valuable insights into bridging the gender gap. However, there are few studies to date that have examined gender differences based on the learning process in a realistic classroom context. In this work, we aim to investigate gender classification using students’ eye movements that reflect temporal human behavior during a computational thinking lesson in an immersive VR classroom. We trained several machine learning classifiers and showed that students’ eye movements provide discriminative information for gender classification. In addition, we employed a Shapley additive explanation (SHAP) approach for feature selection and further model interpretation. The classification model trained with the selected (best) eye movement feature set using SHAP achieved improved performance with an average accuracy of over 70%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$70\\%$$\\end{document}. The SHAP values further explained the classification model by identifying important features and their impacts on the model output, namely gender. Our findings provide insights into the use of eye movements for in-depth investigations of gender differences in learning activities in VR classroom setups that are ecologically valid and may provide clues for providing personalized learning support and tutoring in such educational systems or optimizing system design.

Computational Thinking and User Interfaces: A Systematic Review

Contribution: This document presents a systematic bibliographic review that demonstrates the need to conduct research on how the user experience impacts the development of computational thinking. Background: In the field of computer science, computational thinking is defined as a method that enhances problem-solving skills, system design, and human behavior understanding. Over the last few decades, several tools have been proposed for the development of computational thinking skills; however, there is no area of study that evaluates the implications or the impact that these types of platforms have on users belonging to any knowledge area. Research Question: Do user interfaces influence the development of computational thinking skills? Methodology: To address this issue, a systematic review of the literature was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology for analyzing and evaluating scientific publications. Findings: The results show that despite the dearth of literature on the subject, the specific design of a user interface has a significant impact on the development of computational thinking. Bearing the above in mind, it is necessary to conduct research that delves more deeply into the effects caused by the technologies that are used to develop computational thinking, this being a line of research that is worthy of consideration.

Coding with Block Programming Languages in Educational Robotics and Mobiles, Improve Problem Solving, Creativity & Critical Thinking Skills

The purpose of the article is to highlight how students' computational thinking, which is a critical thinking skill, can be developed through educational robotics and programming. It is a fun and engaging learning activity that encourages students to collaborate, delve into a problem, construct knowledge, and cultivate critical thinking. Educational robotics is therefore an innovative teaching tool, which contributes to the implementation of the above goal and follows the principles of building, specifically the construction of knowledge (Mikropoulos & Bellou, 2010). It develops students' critical thinking, strengthens their mental models, and activates known learning mechanisms leading them to a deeper level of understanding and assimilation of knowledge, which cannot be accomplished with traditional teaching methodologies. It has also been proven to be able to help students solve complex problems as well as contribute to the development of computational thinking skills (Atmatzidou & Demetriadis, 2014), which should characterize the entire literate population and complement the other three basic reading skills, writing, and mathematics (Mavroudis, Petrou & Fesakis, 2014).

A simple interactive robot to promote computational thinking

This paper described the functionalities of a simple robot adopted in the classroom to promote computational thinking (CT) in the context of the project PeCOT—computational thinking with tangible objects. This robot, similar to some commercial educational robots, was developed to be used in primary education classroom contexts (second, third, and fourth grades) by children between 8 and 10 years old. PeCOT is a pedagogical intervention project and research project that will run over the next 2 years. The aim of this paper is to present the robot, how it works, and some activities that can be implemented in the educational context to promote CT skills, including learning in different subject areas, such as mathematics or natural science. Thus, we begin by presenting a general description of the robot. Next, we identify activities and formalize the programming steps for each of the activities. Finally, we discuss the potential that the robot and the proposed activities may have to promote the development of CT skills.

Employing Mobile Technologies to Investigate the Association Between Abstraction Skills and Performance in Environmental Studies in Early Primary School

In the modern digital era, the impressive development of mobile technologies has entailed the reformation of orientations, dispositions and stances in education, changing the dominant approaches to learning. In this article, we introduce the novel idea of the synergistic development of computational thinking skills and environmental awareness in the early primary school years, by employing mobile technologies.

Evaluation of Computational Thinking using four educational robots with primary school students in Peru

The Development of Computational Thinking skills in elementary school students can be done through different activities, with or without the use of computers or technological devices. In this sense, the use of programmable robots brings many of the advantages of educational robotics for teaching fundamental aspects of Computing. This paper describes an educational intervention that evaluates the use of four educational robot models to improve Computational Thinking with primary school students in the Huancavelica region in Peru, South America. This Peruvian region is known for its low human development rates, where the population still faces some important barriers regarding access to education and technology. The study was conducted with 6 to 13 years-old children for four weeks. Computational Thinking was evaluated using computational concepts like sequences, cycles, events, parallelism, conditionals, operators, and data manipulation. The evaluation results showed that children preferred robots that have more interaction, connectivity, and programming features, and they could contribute significantly to the development of Computational Thinking skills.

The CT-cube: A framework for the design and the assessment of computational thinking activities

Computational thinking is a fundamental competence that is being introduced in K-12 and succeeding curricula worldwide. Despite this huge effort, many computational thinking models in the literature do not explicitly take into consideration the pupils’ age and the developmental nature of computational thinking skills. Furthermore, many existing computational thinking models are focused on the internal thinking processes of the individuals, failing to explicitly consider the situated nature, in terms of social context and artefactual environment, that usually characterise tasks that require computational thinking to be solved. In this paper, we present a framework for the design, realisation, analysis, and assessment of computational thinking activities, called CT-cube. The CT-cube allows to extend existing computational thinking models to consider the life-long development of computational thinking skills in individuals, from childhood to adult age, and to take into consideration the situated nature of computational thinking activities. We use the CT-cube to design an unplugged task, called Cross Array Task (CAT), allowing to assess the algorithmic skills of K-12 pupils and we show how the CT-cube can be used in this case to illustrate the development of this competence along the entire compulsory school path, considering a sample of 109 pupil aged 3 to 16 in Switzerland.

Incorporation of Computational Thinking Practices to Enhance Learning in a Programming Course

The development of computational thinking skills is essential for information management, problem-solving, and understanding human behavior. Thus, the aim of the experience described here was to incorporate computational thinking practices to improve learning in a first Python programming course using programming tools such as PSeInt, CodingBat, and the turtle graphic library. A quasi-experimental methodological design was used in which the experimental and control groups are in different academic semesters. Exploratory mixed research was carried out. The control and experimental group consisted of 41 and 36 students, respectively. The results show that with the use of support programming tools, such as PSeInt, CodingBat, Python turtle graphic library, and the incorporation of computational thinking practices, the experimental group students obtained better learning results. It is concluded that student performance and motivation in university programming courses can be improved by using proper tools that help the understanding of programming concepts and the skills development related to computational thinking, such as abstraction and algorithmic thinking.

Foundation Phase teachers’ experiences of teaching the subject, coding, in selected Western Cape schools

Several teachers have recently started introducing coding into their teaching in primary schools. This comes on the back of the emerging prominence of educational technology and the teaching of computational skills at school level, in light of the country’s policy commitment to the Fourth Industrial Revolution. Coding has been punted as 1 of 2 essential subjects to be launched in schools countrywide from 2020; the other being robotics. In this article we focus on the implementation of coding as a subject in selected Foundation Phase classes in the Western Cape. We aim to gain an understanding of coding as a subject from the perspective of teachers who are implementing this very new subject in the Foundation Phase. We specifically discuss the experiences and challenges of teachers who have been teaching the subject over the last few years, based on in-depth qualitative interviews with 4 Foundation Phase teachers. Overall, we provide a set of considerations for the optimal implementation of coding as a subject in Foundation Phase in South African schools. The participants’ experiences highlight the challenges associated with implementation, teachers’ pedagogical skills and competences, and resource requirements. We raise the following areas that need to be addressed for the successful implementation of coding: professional development addressing teaching methodologies on the development of computational thinking skills in young learners, providing support for teachers, addressing time constraints in the teaching of the subject, and providing resources.

A Collaborative Learning Framework for Computational Thinking Development through Game Programming

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.

Measuring Acceptance of Block-Based Coding Environments

The development of computational thinking skills is attracting attention worldwide. The use of visual or block-based coding in primary schools has gained momentum. Yet, students' acceptance of such coding environments has been neglected in the literature. This study presents a measurement instrument that will allow pursuing such an endeavor. The Technology Acceptance Model was used as a guiding framework. A panel of eight experts and a purposive sample of 315 elementary school students (Mage = 10.18 years, SD = 1.13) were recruited. Inter-rater agreement between experts (75–100%) confirmed the content validity of the items. Exploratory factor analysis resulted in a three-factor solution of 12 items measuring perceived usefulness, perceived ease of use, and attitudes towards visual coding. Inspection of the correlation matrix provided evidence of convergent and discriminant validity. Cronbach’s alpha (.75–.82), McDonald’s omega (.68–.83), and Spearman-Brown’s split-half coefficients (.67–.80) provided evidence of reliability. Overall, findings support the validity and reliability of the proposed instrument. Its use can shed light on students' acceptance of different block-based coding environments.