PENERAPAN MODEL CREATIVE PROBLEM SOLVING BERBASIS WEB UNTUK MENINGKATKAN COMPUTATIONAL THINKING SISWA

Computational thinking merupakan keterampilan yang akan perlu dikuasai dari pendidikan untuk dapat menyelesaikan masalah yang ada di dunia teknologi digital yang merupakan salah satu kemampuan untuk memecahkan masalah dengan pola pikir komputasi. Beberapa penelitian mengungkapkan kemampuan pemecahan masalah di Indonesia masih relative rendah, dari hasil uji coba terbatas hanya memperoleh rata-rata 0,23. Tujuan penelitian ini, untuk menerapkan model pembelajaran Creative Problem Solving berbasis website untuk meningkatkan computational thinking siswa. Penelitian ini menggunakan media berbasis website sebagai sarana dalam penelitian dengan hasil yang ingin dicapai yaitu peningkatan kemampuan computational thinking siswa dan tanggapan siswa mengenai media dengan model creative problem solving. Didukung dengan model pembelajaran creative problem solving. Penelitian ini menerapkan metode Smart Learning Environment Establishment Guidline (SLEEG) dengan desain penelitian One Group Pretest Posttest. Berdasarkan penelitian yang dilakukan, kemampuan computational thinking siswa meningkat setelah digunakan media dalam pembelajaran. Hal ini terbukti rata-rata nilai gain sebesar 0,50. Respon siswa mengenai media memperoleh nilai rata-rata persentase 81% dengan kriteria “Sangat Baik”. Dapat disimpulkan bahwa penerapan pembelajaran dengan creative problem solving berbasis website dapat meningkatkan kemampuan computational thinking siswa. Teaching and learning process are becoming more challenging in line with the development of 21st century learning education. In an increasingly modern technological era, education needs to be aligned with current needs. Computational thinking is a skill that needs to be mastered from education to be able to solve problems that exist in the world of digital technology which is one of the abilities to solve problems with a processed mindset. Several studies reveal that problem-solving abilities in Indonesia are still relatively low, from the results of limited trials only obtaining an average of 0.23. The purpose of this research is to apply the website-based Creative Problem Solving learning model to improve students' computational thinking skills. This study uses website-based media as a means of research with the results to be achieved, namely increasing students' computational thinking skills and student responses regarding media with creative problem solving models. Supported by a creative problem solving learning model. This study applies the Smart Learning Environment Establishment Guideline (SLEEG) method with the One Group Pretest Posttest research design. Based on the research conducted, students' computational thinking abilities increased after using media in learning. This is proven by the average gain value of 0.50. Student responses regarding the media obtained an average proportion of 81% with the "Very Good" criterion. It can be concluded that the application of learning based on the Creative Problem Solving website can improve students' computational thinking abilities

Adaptive Augmented Reality Serious Game to Foster Problem Solving Skills

This paper describes the design of an adaptive intelligent augmented reality serious game which aims to foster problem solving skills in young learners. Studies show that our students lack computational thinking skills in high school, which raises the need to establish new methods to develop these skills in our younger learners. We believe that problem solving skills are the fundamental skills of computational thinking and are critical for STEM, in addition to a broad range of other fields. Therefore we decided to focus on those meta-cognitive skills acquired to foster problem solving, such as strategic knowledge. The game described in this paper provides a unique adaptive learning environment that aims to develop learners’ meta-cognitive skills by utilizing augmented reality technology, believable pedagogical agents and intelligent tutoring modules. It offers a great user experience and entertainment which we hope will encourage learners to invest more time in the learning process. This paper describes the architecture and design of the game from the viewpoint of educational pedagogies and frameworks for serious game design

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

Fostering computational thinking skills : a didactic proposal for elementary school grades

There is a growing presence of technology in the daily lives of elementary school students, with a recent exponential rise due to the constraints of remote teaching during the COVID-19 pandemic. It is important to understand how the education system can contribute to helping students develop the required skills for technological careers, without neglecting its obligation to create conditions that allow them to acquire transversal skills and to enable them to exercise full citizenship. The integration of Educational Robotics and block programming activities in collaborative learning environments promotes the development of computational thinking and other ICT skills, as well as critical thinking, social skills, and problem solving. This paper presents a theoretical proposal of a didactic sequence for the introduction to educational robotics and programming with Scratch Jr. It is composed of three learning scenarios, designed for elementary school teaching. Its main goal is to create conditions that favour the development of computational thinking in a collaborative learning environment. With increasing complexity and degree of difficulty, all the tasks root from a common problem: How can we create an algorithm that programs the robot/sprite to reach a predetermined position?info:eu-repo/semantics/publishedVersio

Diogene-CT: tools and methodologies for teaching and learning coding

Computational thinking is the capacity of undertaking a problem-solving process in various disciplines (including STEM, i.e. science, technology, engineering and mathematics) using distinctive techniques that are typical of computer science. It is nowadays considered a fundamental skill for students and citizens, that has the potential to affect future generations. At the roots of computational-thinking abilities stands the knowledge of computer programming, i.e. coding. With the goal of fostering computational thinking in young students, we address the challenging and open problem of using methods, tools and techniques to support teaching and learning of computer-programming skills in school curricula of the secondary grade and university courses. This problem is made complex by several factors. In fact, coding requires abstraction capabilities and complex cognitive skills such as procedural and conditional reasoning, planning, and analogical reasoning. In this paper, we introduce a new paradigm called ACME (“Code Animation by Evolved Metaphors”) that stands at the foundation of the Diogene-CT code visualization environment and methodology. We develop consistent visual metaphors for both procedural and object-oriented programming. Based on the metaphors, we introduce a playground architecture to support teaching and learning of the principles of coding. To the best of our knowledge, this is the first scalable code visualization tool using consistent metaphors in the field of the Computing Education Research (CER). It might be considered as a new kind of tools named as code visualization environments

Spice-up your coding lessons with the ACME approach

It is nowadays considered a fundamental skill for students and citizens the capacity of undertaking a problem-solving process in various disciplines (including STEM, i.e. science, technology, engineering and mathematics) using distinctive techniques that are typical of computer science. These abilities are usually called Computational Thinking and at the roots of them stands the knowledge of coding. With the goal of encouraging Computational Thinking in young students, we discuss tools and techniques to support the teaching and the learning of coding in school curricula. It is well known that this problem is complex due to the fact that it requires abstraction capabilities and complex cognitive skills such as procedural and conditional reasoning, planning, and analogical reasoning. In this paper, we present ACME (“Code Animation by Evolved Metaphors”) that stands at the foundation of the Diogene-CT code visualization environment and methodology. We discuss visual metaphors for both procedural and object-oriented programming. Based on them, we introduce a playground architecture to support teaching and learning of the principles of coding. To the best of our knowledge, this is the first scalable code visualization tool using consistent metaphors in the field of Computing Education Research (CER)

Diogene-CT: tools and methodologies for teaching and learning coding

AbstractComputational thinking is the capacity of undertaking a problem-solving process in various disciplines (including STEM, i.e. science, technology, engineering and mathematics) using distinctive techniques that are typical of computer science. It is nowadays considered a fundamental skill for students and citizens, that has the potential to affect future generations. At the roots of computational-thinking abilities stands the knowledge of computer programming, i.e. coding. With the goal of fostering computational thinking in young students, we address the challenging and open problem of using methods, tools and techniques to support teaching and learning of computer-programming skills in school curricula of the secondary grade and university courses. This problem is made complex by several factors. In fact, coding requires abstraction capabilities and complex cognitive skills such as procedural and conditional reasoning, planning, and analogical reasoning. In this paper, we introduce a new paradigm called ACME ("Code Animation by Evolved Metaphors") that stands at the foundation of the Diogene-CT code visualization environment and methodology. We develop consistent visual metaphors for both procedural and object-oriented programming. Based on the metaphors, we introduce a playground architecture to support teaching and learning of the principles of coding. To the best of our knowledge, this is the first scalable code visualization tool using consistent metaphors in the field of the Computing Education Research (CER). It might be considered as a new kind of tools named as code visualization environments

Computer Science Education at The Claremont Colleges: The Building of an Intuition

In this thesis, I discuss how the undergraduate computer scientist is trained, and how they learn what I am calling computational intuition. Computational intuition describes the methodology in which computer scientists approach their problems and solve them through the use of computers. Computational intuition is a series of skills and a way of thinking or approaching problems that students learn throughout their education. The main way that computational intuition is taught to students is through the experience they gain as they work on homework and classwork problems. To develop computational intuition, students learn explicit knowledge and techniques as well as knowledge that is tacit and harder to teach within the lectures of a classroom environment. Computational intuition includes concepts that professors and students discuss which include “computer science intuition,” “computational thinking,” general problem solving skills or heuristics, and trained judgement. This way of learning is often social, and I draw on the pedagogy of cognitive apprenticeship to understand the interactions between the professors, tutors, and other students help learners gain an understanding of the “computer science intuition.” It is this method of thinking that computer scientists at the Claremont Colleges have stated as being one of the most essential items that should be taught and gained throughout their education and signals a wider understanding of computer science as a field

Subgoals, Problem Solving Phases, and Sources of Knowledge: A Complex Mangle

Educational researchers have increasingly drawn attention to how students develop computational thinking (CT) skills, including in science, math, and literacy contexts. A key component of CT is the process of abstraction, a particularly challenging concept for novice programmers, but one vital to problem solving. We propose a framework based on situated cognition that can be used to document how instructors and students communicate about abstractions during the problem solving process. We develop this framework in a multimodal interaction analysis of a 32-minute long excerpt of a middle school student working in the PixelBots JavaScript programming environment at a two-week summer programming workshop taught by undergraduate CS majors. Through a microgenetic analysis of the process of teaching and learning about abstraction in this excerpt, we document the extemporaneous prioritization of subgoals and the back-and-forth coordination of problem solving phases. In our case study, we identify that (a) problem solving phases are nested with several instances of context-switching within a single phase; (b) the introduction of new ideas and information create bridges or opportunities to move between different problem solving phases; (c) planning to solve a problem is a non-linear process; and (d) pedagogical moves such as modeling and prompting highlight situated resources and advance problem solving. Future research should address how to help students structure subgoals and reflect on connections between problem solving phases, and how to help instructors reflect on their routes to supporting students in the problem solving process.Comment: ACM Student Research Competition (SRC) submission in Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE '19); 3 pages; Poster: https://docs.google.com/drawings/d/1OrfWGp7-o8sI7KJyx4-leY-A8TioXP1IQFKNBDceht4/edit?usp=sharin