Sosialisasi Computational Thinking Mata Pelajaran Bahasa Inggris untuk Guru-Guru MI dan MTs Wilayah Lombok Tengah

Computational thinking (CT) or in Indonesian called computational thinking is a method to train thinking skills in solving problems with reasoning and analysis, initially computational thinking is always related to computers. In fact, computational computing does not teach how to use computers or things that are always related to but the thought processes used to support problem science in all disciplines, mathematics, science, social studies, and languages, in this case the socialization of CT in learning English and Indonesian. Computational thinking can teach from an early age, starting from the elementary school level (SD) or the equivalent (MI) by making questions in English and Indonesian subjects by providing examples of simple problem solving found in basic language lessons. Through this community service, you can socialize CT to MI and MTs secondary school teachers in Central Lombok, the content is so that teachers can enter or enter CT into the subject they are taught, so that students are familiar with problems solving problems by means of computational thinking , the sustainable survival of computational thinking, a problem can be resolved properly, quickly and optimally

Assessing computational thinking process using a multiple evaluation approach

This study explored the ways that the Computational Thinking (CT) process can be evaluated in a classroom environment. Thirty Children aged 10–11 years, from a primary school in London took part in a game-making project using the Scratch and Alice 2.4 applications for eight months. For the focus of this specific paper, data from participant observations, informal conversations, problem-solving sheets, semi-structured interviews and children’s completed games were used to make sense of elements of the computational thinking process and approaches to evaluate these elements in a computer game design context. The discussions around what CT consists, highlighted the complex structure of computational thinking and the interaction between the elements of artificial intelligence (AI), computer, cognitive, learning and psychological sciences. This also emphasised the role of metacognition in the Computational Thinking process. These arguments illustrated that it is not possible to evaluate Computational Thinking using only programming constructs, as CT process provides opportunities for developing many other skills and concepts. Therefore a multiple evaluation approach should be adopted to illustrate the full learning scope of the Computational Thinking Process. Using the support of literature review and the findings of the data analysis I proposed a multiple approach evaluation model where ‘computational concepts’, ‘metacognitive practices’, and ‘learning behaviours’ were discussed as the main elements of the CT process. Additionally, in order to investigate these dimensions within a game-making context, computer game design was also included in this evaluation model

Problem-Solving and Computational Thinking Practices: Lesson Learned from The Implementation of ExPRession Model

Computational thinking ability is one of today's problem-solving methods that can be applied in physics learning. However, it is not yet known by most teachers so it has not been applied optimally in learning activities. This study aims to identify students' problem-solving and computational thinking abilities in solving well-structure physics problems. The subject of this study was the eleven grade majoring in natural science of SMAN 1 Bangunrejo. This type of research is descriptive research. The data used to analyze the students' problem-solving and computational thinking abilities were obtained from the essay test. Based on the results of descriptive analysis, it can be concluded that there is a relationship between students' problem-solving abilities and students' computational thinking abilities. In making a useful description, abstraction and decomposition abilities are needed, while to determine the physics approach and specific application of physics, generalization abiliy are needed. In solving mathematical procedures, algorithm ability are needed and to find out logical progressions, debugging ability are needed

Problem-Solving and Computational Thinking Practices: Lesson Learned from The Implementation of ExPRession Model

Computational thinking ability is one of today's problem-solving methods that can be applied in physics learning. However, it is not yet known by most teachers so it has not been applied optimally in learning activities. This study aims to identify students' problem-solving and computational thinking abilities in solving well-structure physics problems. The subject of this study was the eleven grade majoring in natural science of SMAN 1 Bangunrejo. This type of research is descriptive research. The data used to analyze the students' problem-solving and computational thinking abilities were obtained from the essay test. Based on the results of descriptive analysis, it can be concluded that there is a relationship between students' problem-solving abilities and students' computational thinking abilities. In making a useful description, abstraction and decomposition abilities are needed, while to determine the physics approach and specific application of physics, generalization abiliy are needed. In solving mathematical procedures, algorithm ability are needed and to find out logical progressions, debugging ability are needed

Computational Thinking: Changes to the Human Connectome Associated with Learning to Program

Computational thinking, the ability to solve problems in the world using a logical foundation, is a fundamental skill for people in general and MIS professionals in particular. It can be argued that increased use of computational thinking can lead to better and more efficient problem solving, better decision making, and increases in productivity. Programming computer code is one type of computational thinking, and the type we address in the present research. In particular, we document changes in brain structure that occur as a person learns to program. Our results suggest that learning to program increases the structural connectivity between the frontal cortex and the anterior cingulate cortex. These results support our hypotheses about structural brain changes that result from learning to program

IMPLEMENTASI PROJECT BASED LEARNING UNTUK MENGEKSPLORASI KEMAMPUAN COMPUTATIONAL THINKING MAHASISWA

Computational Thinking (CT) or Computational Thinking is indispensable in mathematics. Programming Language courses are expected to facilitate and develop students' CT skills. The Project Base Learning (PjBL) learning model is used to see students' CT abilities. The project carried out in this PjBL learning is the making of learning media using Matlab. The media produced by the students has met the aspects of fluency in use, script accuracy, and flowchart logic. Students' CT abilities are in good category from the aspects of abstraction, logarithmic thinking, debugging / evaluation, and generalization because they have met the percentage of achievement of 82%

Analisis Kemampuan Computational Thinking Dalam Pembuatan Media Pembelajaran Matematika

The purpose of this study was to reveal the implementation of Project Base Learning (PjBL)-based learning and then analyze the Computational Thinking (CT) ability of students of the Mathematics Education Study Program, University of Muhammadiyah Malang through a learning media development project. The approach used in this research is descriptive qualitative. The subjects in this study were students who programmed the Programming Language course in semester 3. The results of the research, the projects carried out in PjBL learning were making learning media using Matlab which included the stages of needs analysis, project planning, scheduling, monitoring, testing results and evaluating carried out. very well and systematically. The media produced by students has met the aspects of fluency in use, accuracy of scripts, and flowchart logic. The student's CT ability is in a good category from the aspect of abstraction, logarithmic thinking, debugging/evaluation, and generalization because it has met the achievement percentage of 82%. In conclusion, the learning media developed based on Project Base Learning (PjBL) has been implemented well, covering aspects of smooth use and effectively increasing the Computational Thinking (CT) ability of students of the Mathematics Education Study Program, University of Muhammadiyah Malang. Keywords: Computational Thinking, Learning Media, Project Base Learnin

How computation can facilitate sensemaking about physics: A case study

We present a case study featuring a first-year bio-science university student using computation to solve a radioactive decay problem and interpret the results. In a semi-structured cognitive interview, we use this case to examine the process of sensemaking in a computational science context. We observe the student entering the sensemaking process by inspecting and comparing computational outputs. She then makes several attempts to resolve the perceived inconsistency, foregrounding knowledge from different domains. The key to making sense of the model for this student proves to be thinking about how to implement a better model computationally. This demonstrates that integrating computation in physics activities may provide students with opportunities to engage in sensemaking and critical thinking. We finally discuss some implications for instruction.Comment: 4 pages. Updated after peer review to be ready for inclusion in the PERC 2018 proceeding

Creating Science Simulations Through Computational Thinking Patterns

Computational thinking aims to outline fundamental skills from computer science that everyone should learn. As currently defined, with help from the National Science Foundation (NSF), these skills include problem formulation, logically organizing data, automating solutions through algorithmic thinking, and representing data through abstraction. One aim of the NSF is to integrate these and other computational thinking concepts into the classroom. End-user programming tools offer a unique opportunity to accomplish this goal. An end-user programming tool that allows students with little or no prior experience the ability to create simulations based on phenomena they see in-class could be a first step towards meeting most, if not all, of the above computational thinking goals. This thesis describes the creation, implementation and initial testing of a programming tool, called the Simulation Creation Toolkit, with which users apply high-level agent interactions called Computational Thinking Patterns (CTPs) to create simulations. Employing Computational Thinking Patterns obviates lower behavior-level programming and allows users to directly create agent interactions in a simulation by making an analogy with real world phenomena they are trying to represent. Data collected from 21 sixth grade students with no prior programming experience and 45 seventh grade students with minimal programming experience indicates that this is an effective first step towards enabling students to create simulations in the classroom environment. Furthermore, an analogical reasoning study that looked at how users might apply patterns to create simulations from high- level descriptions with little guidance shows promising results. These initial results indicate that the high level strategy employed by the Simulation Creation Toolkit is a promising strategy towards incorporating Computational Thinking concepts in the classroom environment