Development of Real-Life Problem Solving Model(CT-RLPS Model) based on Computational Thinking for Software Education

Two studies were conducted to examine the use of grounded embodied pedagogy, construction of Imaginary Worlds (Study 1), and context of instructional materials (Study 2) for developing learners' Computational Thinking (CT) Skills and Concept knowledge during the construction of digital artifacts using Scratch, a block-based programming language. Utilizing a conceptual framework for grounded embodied pedagogy called Instructional Embodiment, learners physically enacted (Direct Embodiment) and mentally simulated (Imagined Embodiment) the actions and events as presented within pre-defined Scripts. Instructional Embodiment utilizes action, perception, and environment to create a dynamic, interactive teaching & learning scenario that builds upon previous research in embodied teaching and learning. The two studies described herein examined the effects of Instructional Embodiment, Imaginary World Construction, and Context on the development of specific Computational Thinking Concepts and Skills. In particular, certain CT Concepts, such as Conditionals, Variables, Thread Synchronization, Collision Detection, & Events, and CT Skills, such as abstraction and pattern recognition, were identified and measured within the learners' individual digital artifacts. Presence and/or frequency of these Concepts and Skills were used to determine the extent of Computational Thinking development. In Study 1, fifty-six sixth- and seventh-grade students participated in a fifteen-session curricular program during the academic school day. This study examined the type of instruction and continuity of Imaginary World Construction on the development of certain CT Skills and Concepts used in a visual novel created in Scratch. Main effects were found for learners who physically embodied the pre-defined instructional materials: embodying the pre-defined Scripts led to the learners using significantly more ‘speech’ Blocks in their projects and more Absolute Positioning Blocks for ‘motion’ than those who did not physically embody the same Scripts. Significant main effects were also found for continuity of Imaginary World Construction: learners who were instructed to continue the premise of the first digital artifact (Instructional Artifact) implemented significantly more computational structures in their second digital artifact (Unique Artifact) than those who were instructed to create a Unique Artifact with a premise of their own design. In Study 2, seventy-eight sixth- and seventh-grade students participated in a seventeen-session curricular program during the academic school day. This study examined the type of instruction and context of instructional materials on the development of CT Skills and Concepts during the construction of a video game using Scratch. Similar to Study 1, findings suggest that physically embodying the actions presented within the pre-defined instructional materials leads to greater implementation of many of these same structures during individual artifact construction. The study also showed that as the pre-defined Scripts become more complex (e.g. single-threaded to multi-threaded), the effect of physical embodiment on the development of CT Skills and complex CT Concept structures becomes less pronounced. Findings from this study also suggest that Context has a significant effect on identifying & implementing the CT Skill pattern recognition: learning CT Concepts from an Unfamiliar Context had a significant positive effect on the implementation of both Broadcast/Receive couplings and Conditional Logic & Operator patterns. In sum, the findings suggest that the type of instruction, the continuity of the Imaginary World being constructed, and the context of the instructional materials all play a significant role in the learners' ability to develop certain Computational Thinking Skills and Concept knowledge. The findings also suggest that a physically embodied approach to teaching abstract concepts that is grounded in an unfamiliar context is the most effective way to integrate a grounded embodied approach to pedagogy within a formal instructional setting.

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.

Computational thinking (CT) is the crucial skill for the 21st century which is gaining increasing significance in our rapidly advancing technological world. Therefore, since the demand for CT has increased in modern education systems, Malaysia also incorporated computational thinking skills into its curriculum to align with global 21st-century educational trends. While understanding CT concepts is foundational, the ability to apply these skills effectively can vary based on training quality and individual attitudes. A few studies have examined whether CT attitudes influence CT skills. This study is conducted to investigate the relationship between trainee teachers’ perception of CT concepts and their CT skills. The study focuses on six core CT concepts: Logic, Algorithms, Decomposition, Pattern Recognition, Abstraction, and Evaluation. The study employed a correlational research design with quantitative survey method was used; items were constructed in questionnaire to acquire teachers’ perception and their knowledge about CT concept, while Bebras Challenge Tasks to assess their CT skills. 100 science trainee teachers from all IPGM over Malaysia are targeted to complete the survey form and Pearson correlation test is used to analyze the survey data. Results from this study provide insights into how CT concepts correlate with CT skills and the perceptions of trainee teachers towards CT concepts.

Computational thinking involves using computer science concepts to design systems, find solutions to problems, and understand human behavior. Recent reports recommend the addition of computational thinking into K-6 education, and computational thinking has been taught in different learning environments, including formal and informal environments, and has also been taught alongside engineering design thinking. The CDIO Initiative includes a Conceive-Design-Implement-Design process, which can be adapted for use in guiding computational thinking activities at the elementary (K-6) level. This chapter draws on a phenomenological approach to computational thinking to provide the justification and method for adapting the C-D-I-O design process for teaching K-6 computational thinking. It also describes the design requirements and methods for creating four scaffolded computational thinking activities, which are discussed in detail. For each design, the connection with computational thinking concepts and the proposed framework are provided. This chapter also includes a discussion of the scaffolding techniques between the activities, and how the fading of scaffolding was used to improve learning and confidence. By drawing upon a phenomenological approach to computational thinking, we can make rooms for different ways of knowing and representation in computational thinking education to better connect with students’ lived experiences.

At present, the concept of computational thinking is spreading in education circles around the world. From the point of view of current research and application in China, the research on the cultivation of computational thinking in K-12 education is still in the early stage. Based on the graphic programming design course of app inventor in primary and secondary schools, this study embeds computing thinking into teaching objectives and contents, constructs the teaching model of app inventor course with embedded computing thinking, and discusses how to cultivate students' computing thinking ability in teaching practice. The method provided in this paper is helpful to analyse the changes of students' computational thinking during the teaching process, and it can effectively identify teaching effects.

Computational thinking has emerged as a critical 21st-century skill, yet many secondary students in Malaysia have not been formally exposed to structured computational thinking education. This study evaluates the effectiveness of a “Basic to Advanced Computational Thinking for Secondary Students” program implemented in Melaka, Malaysia. To assess the impact of a four-day computational thinking program on secondary students’ knowledge, skills, and confidence in computational thinking concepts. A pre-post evaluation design was employed using the validated form provided by Research, Innovation, Commercialisation, and Entrepreneurship (RICE) University Technical Malaysia Melaka (UTeM) assessment instrument. Forty-eight secondary students (Forms 1-3) participated in the program, which covered introduction to computational thinking which includes Microbit, Scratch, artificial intelligence (AI), and robotics. Participants completed self-assessment questionnaires before and after the program using a 5-point Likert scale. The program demonstrated significant effectiveness across all measured competencies. Overall mean scores improved from 2.45 to 3.71 (51.3% improvement). The highest improvements were observed in knowledge acquisition (60.9%) and program relevance perception (53.2%). Female students (n=9) and male students (n=20) both showed substantial improvements, with the program successfully engaging diverse learners across different form levels. The structured computational thinking program effectively enhanced secondary students’ competencies in computational thinking. The findings support the integration of comprehensive computational thinking curricula in Malaysian secondary education to prepare students for digital literacy demands.

As a new product of the computing era, computational thinking embodies the development process of learners’ problem-solving thinking, and capturing its procedural data can provide a data basis for effective and accurate evaluation of computational thinking. To this end, this article takes the problem attributes of computational thinking as an opportunity, based on the learning behavior data generated in the problem-solving process, constructs a problem-solving model that promotes the development of computational thinking, and designs a teaching process and an intelligent training system based on this model. The effect evaluation results show that the problem-solving model can effectively promote the cultivation of students’ computational thinking. The design of the intelligent training system and the capture of learning behavior data provide a reliable basis for learners to solve problems and are a double guarantee for the development of computational thinking.KeywordsComputational thinkingProblem solving modelInstructional designComputer courses

Computational thinking (CT), which encompasses strategies for problem analysis and solution design, is highly applicable in all STEM disciplines, including computer science, for learning concepts as well as solving problems. Yet, the exposure of K-12 students to CT in many schools is practically non-existent. For students to acquire this important skill, teachers require in-depth knowledge of the problem solving strategies that define CT, and strategies for integrating CT into their lesson plans. The proposed special session will be both a tutorial on CT and an interactive session for sharing the experience and results from a CT workshop held at Columbus State University for middle and high school STEM subject teachers. This workshop, offered as a part of the ACT4STEM (Applying Computational Thinking for STEM Disciplines) project, took place in the summer of 2015. It brought together teachers from the metropolitan Columbus area in Georgia with priority given to teachers from high-need schools (as determined by the GA Department of Education [1]). The workshop introduced the participants to CT concepts and demonstrated how CT strategies of pattern recognition, generalization, problem decomposition and algorithmic thinking can be used to improve student learning of STEM concepts. The proposed special session will present sample CT modules developed for the ACT4STEM workshop in the form of a tutorial and projects and lesson plans designed by participants during the workshop. It will include interactive, hands-on activities and discussions in addition to results from the teachers' actual experiences on applying these lesson plans in their classes. This special session will benefit K12 teachers of STEM subjects interested in improving their students' comprehension of discipline related concepts and their application. Moreover, computer science faculty interested in helping K-12 teachers by organizing training sessions will gain valuable insights from the first-hand accounts of the presenters of their own experience with such an effort.

This study investigated young children’s computational thinking (CT) development by integrating ScratchJr into a programming curriculum. Twelve third graders (six males and six females) voluntarily participated in an experiment-based computer class conducted at a public elementary school in Taiwan. This study adopted a case study methodology to investigate research questions in one specific case (8-week CT educational training). A one-group quasi-experimental pretest and posttest design with the support of qualitative observation was used to examine four research topics: CT competence progress, programming behaviors in a CT framework, factors influencing CT competence, and learning responses to CT training. The quantitative results indicated that students immersing in weekly programming projects significantly improved in terms of their CT competence, which was mostly retained 1 month after completion of the class. The programming behaviors indicated that students’ CT concepts (sequence, event, and parallelism) and practice (testing and debugging as well as reusing and remixing) significantly improved. Moreover, parents’ active involvement in take-home assignments influenced students’ long-term CT competence retention. The qualitative results indicated that students enjoyed using tablet computers to learn ScratchJr programming and demonstrated various leaning behaviors in a three-stage instructional design model.

Computational thinking should be understood as problem-solving thinking, beyond its link to programming. Therefore, it is necessary to address this thought’s structure through its cognitive processes to obtain an operational definition that allows this thought’s pedagogy to be adequately addressed in the classroom, regardless its development source. In this article, five processes inherent to this thought are determined, identifying only those that are always used. These processes are operatively defined from a psychological and a pedagogical perspective. The processes are abstraction, generalization, evaluation, creation of algorithms and decomposition of the problem. The first four processes present an inherent relation to problem-solving that can be verified, while, the last one, decomposition, can be considered not fundamental in problem solving and, therefore, linked to computational thinking. The performed analysis and categorization prove that decomposition is the key and central process of computational thinking. Therefore, computational thinking teaching must always be approached from the decomposition of problems or tasks that allow the simplification of the rest of the processes involved. This should involve different resources such as programming, playing games, problem-solving, or the creation of projects.

The concept of Computational Thinking has been discussed for several decades and in recent years has been brought to the attention of the scientific community by Jeanette Wing. Her article presents Computational Thinking as “a way of solving problems, designing systems, and understanding human behavior that draws on concepts fundamental to computer science”. The importance of Computational Thinking places it among the basic skills for 21st century, together with reading, writing and calculation, that every person will have to master, so it is important to teach it already in primary school. As the invention of printing facilitated the spread of the three Rs (reading, writing and arithmetic) the technology must lead to the spread of Computational Thinking. This chapter will introduce the research on Computational Thinking and, in particular, the works on innovative computational environments, and will describe the situation of the education to CT in high school and in academic courses.

This study investigates the relationship between computational thinking performance and general school achievement and explores to see if computational thinking performance can be predicted by algebra and informatics achievement. The sample group of 775 grade 8 students was drawn from 28 secondary schools across Kazakhstan. The students responded to a Computational Thinking Performance test of 50 multiple-choice questions and Computational Thinking Scale questionnaire. The test covers the concepts: logical thinking, generalisation and abstraction. The validity and reliability of the multiple-choice questions are tested using the Item Response Theory. The Likert type questionnaire covers five factors: creativity, algorithmic thinking, cooperation, critical thinking and problem solving. School achievement results (secondary data) include scores for a number of school subjects. The results of the study showed that the multiple-choice questions are valid and a reliable tool to measure computational thinking performance of students. Algebra, general school achievement and students’ perception of their computational thinking skills were significant predictors of computational thinking performance. The results revealed no gender difference in computational thinking performance and perceptions of computational thinking. The findings regarding the relationship between computational thinking performance, the students’ general school achievement and perceptions of computational thinking skills are compared and discussed.

We experimented with the viability of using Lego Mindstorms as an alternative approach to supplement the learning of Basic Programming among novice university students. The study captured reactions and responses from ten undergraduates who had no background in Programming and were facing difficulties coping with an introductory course in Programming. Four Lego Mindstorms units were deployed to examine the participants' problem-solving and computational thinking skills. Findings indicate a high positive response (t=3.88 and p =0.004 for Problem Solving; t=-4.13 and p=0.003 for Computational thinking) to the use of Mindstorms as a strategy to encourage higher-order thinking, a critical skill in learning Programming. Participants reported clarity in understanding computational thinking concepts and claimed to be better able to articulate problem-solving tasks when prompted using Mindstorms.

The STEAM-CT approach integrates Science, Technology, Engineering, Arts, and Mathematics with Computational Thinking (CT) to help students learn how to think, design, and solve problems. It gives students hands-on, interdisciplinary experiences where they apply logic and creativity through real-world applications. The purpose of this study is to foster the development of computational thinking among Deaf students by embedding Artificial Intelligence (AI) learning within a STEAM-CT approach. This learning program consisted of three main phases: (1) exploring AI processes and tools, (2) constructing an AI system, and (3) designing AI-driven innovations. Thirty-six Deaf students from seven Deaf schools participated in this program, which aims to enhance their CT abilities and cultivate their capacity to create AI-based solutions. Students’ progress was measured using a CT framework encompassing knowledge of concepts, applied practices and perspectives. Assessments included multiple-choice tests for CT concepts, task-based rubrics for CT practices, and interviews for CT perspectives. The results showed that Deaf students gained a better understanding of CT concepts, demonstrated advanced CT practices, and exhibited strong CT perspectives. These findings suggest that AI learning through a STEAM-CT approach can effectively promote Deaf students’ computational thinking abilities.

As schools and districts across the United States adopt computer science standards and curriculum for K-12 computer science education, they look to integrate the foundational concepts of computational thinking (CT) into existing core subjects of elementary-age students. Research has shown the effectiveness of teaching CT elements (abstraction, generalization, decomposition, algorithmic thinking, debugging) using non-programming, unplugged approaches. These approaches address common barriers teachers face with lack of knowledge, familiarity, or technology tools. Picture books and graphic novels present an unexplored non-programming, unplugged resource for teachers to integrate computational thinking into their CT or CT-integrated lessons. This analysis examines 27 picture books and graphic novels published between 2015 and 2020 targeted to K-6 students for representation of computational thinking elements. Using the computational thinking curriculum framework for K-6, we identify the grade-level competencies of the CT elements featured in the books compared to the books’ target age groups. We compare grade-level competencies to interest level to identify each CT element representation as “foundational,” “on-target,” or “advanced.” We conclude that literature offers teachers a non-programming unplugged resource to expose students to CT and enhance CT and CT-integrated lessons, while also personalizing learning based on CT readiness and interest level.