and Y.W. [, Galteri, L.; Seidenari, L.; Bertini, M.; Del Bimbo, A. Abstraction in learning is the process of taking away or removing certain characteristics of a complex problem to reduce it to its most essential components. Copyright Learning.com 2023. All articles published by MDPI are made immediately available worldwide under an open access license. [. We will share this in the workshop and discuss under the pattern recognition lens. Computational thinking is a problem-solving skill that develops an algorithm, or series of steps to perform a task or solve a problem. White, G. L. (2001). You ask your smart speaker what the weather will be that 2022 has been an exciting year at Learning.com! and Z.D. 694711. the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, In Proceedings of the Seventh IEEE International Conference on Computer Vision, Kerkyra, Greece, 2027 September 1999; Volume 2, pp. One system might simply record present and absent. In computational thinking, one of the integral steps to the problem-solving process is pattern recognition. Students generalize chord progressions for common musical genres into a set of general principles they can communicate. Learn how this concept can be integrated in student learning. In this process, pattern recognition is Digital literacy refers to the knowledge and ability to use technology effectively and responsibly. What's Next? After Jeanette Wing in 2006 described computational thinking (CT) as a fundamental skill for everyone just like reading or arithmetic, it has become a widely discussed topic all over the world. It might be a new pattern that occurs several times in your own program, or it might exist elsewhere in other programs. As technology advances and adapts faster and Computational thinking is problem-solving. What are the patterns we can recognize? [, Fabbri, C.; Islam, M.J.; Sattar, J. Cognitive fit: An empirical study of recursion and iteration. EasyTech Wins Tech & Learning Awards of Excellence: Best of 2022, How One School District is Driving Digital Wellness in Students (& How to Join), What is Digital Literacy: Definition and Uses in Daily Life, Texas Technology Standards: Big Changes Need Big Solutions, Definition of Computer Science, Computational Thinking and Coding, Get Creative with Professional Development for Technology Integration. Author to whom correspondence should be addressed. Berman, D.; Treibitz, T.; Avidan, S. Diving into haze-lines: Color restoration of underwater images. (1988). (eds) Teaching Coding in K-12 Schools. Computational Thinking Steps: In order to make predictions using computational thinking, we need to define three steps related to the problem and its solution: I should add a little caveat here: these rules for computational thinking are all well and good but theyre not really rules, per se; instead, think of them more like well-intentioned heuristics, or rules of thumb. The pattern types have a similar solution and once you create an algorithm for each you may see some similarities, however recognizing the pattern type of the question helps to create the solution. Students develop laws and theorems by looking at similar formulas and equations. Google Scholar. [. Papadakis, S., Kalogiannakis, M., Orfanakis, V., & Zaranis, N. (2019). We will examine this in more detail with the lens of pattern recognition. Learn more about abstraction in computational thinking by downloading our free guide for educators: The Ultimate Guide to Computational Thinking for Educators. It hides the underlying complexity in a programming language, which makes it simpler to implement algorithms and communicate with digital tools. The study aimed to evaluate the results of a computational thinking (CompThink) and learning management model using a flipped classroom (FC), combined with critical thinking problem-solving (CTPS . All of these required the people behind them to think about big, broad, and complex concepts; to break down the problem and to experiment; and to find patterns amongst the experimentations; and to eventually abstract this concrete knowledge to package it into these sterile statements that shelter us from the complexity and difficulty waded through to arrive at this law. This paper proposes a fast and efficient underwater image enhancement model based on conditional GAN with good generalization ability using aggregation strategies and concatenate operations to take full advantage of the limited hierarchical features. This face was recognized in this photo by pattern recognition. The results show that our model produces better images, and has good generalization ability and real-time performance, which is more conducive to the practical application of underwater robot tasks. We can represent parts of a system in general terms, including Variables, Constants, Key Processes, repeated Processes, Inputs and Outputs. Learn more about abstraction in computational thinking by downloading our free guide for educators: The Ultimate Guide to Computational Thinking for Educators, How to Help Students Improve Pattern Recognition Skills, 3 Important Additions to Digital Literacy for Students in 2023. The green and blue light with a shorter wavelength will travel farther [, Many scholars have carried out in-depth research on the scattering phenomenon of light propagating in the medium. Retrieved February 24, 2022, from http://rigaux.org/language-study/diagram.html. They constitute a way of reasoning or thinking logically and methodically about solving any problem in any area! The details of the hierarchical attention encoder (HAE) are shown in, For the discriminator, we use a Markov discriminator [, The conditional generative adversarial network introduces additional auxiliary information and can learn the mapping. Underwater image enhancement with a deep residual framework. Using UICM (color measurement index), UISM (sharpness measurement index), UIConM (contrast measurement index) as the evaluation basis. Prat, C., Madhyastha, T., Mottarella, M., & Kuo, C. (2020). Working memory differs from long-term memory in . Pattern abstraction is hiding the complexities of one pattern from another. Making predictions based on identified patterns. 67236732. Abstraction enables us to remove all unnecessary detail from our problem and then solve the problem using a model. When a patient discusses symptoms with a doctor or undergoes a series of tests, the results are compared against known patterns to quickly identify types of infections or injuries that may be causing the symptoms and to apply corresponding solutions to the diagnoses. While pattern recognition is most commonly discussed as a step in computational thinking, we automatically use pattern recognition in our everyday lives. ; Wang, Z.; Paul Smolley, S. Least squares generative adversarial networks. % [, Akkaynak, D.; Treibitz, T. Sea-thru: A method for removing water from underwater images. Many people use face recognition in photos when posting to social media. Students conduct a survey of peers and analyze the data to note the key findings, create visualizations, present the findings. Cognitive load theory and the format of instruction. Jason Zagami . We apply the FE-GAN model to real and artificially synthesized underwater image datasets, process paired and unpaired distorted images, and compare them with the corresponding ground truth images. xJSmSr!@67gQ Ai In computational thinking, decomposition and pattern recognition break down the complex, while abstraction figures out how to work with the different parts efficiently and accurately. In this section, we chose a relatively complete set of real and artificial synthetic underwater images to test the enhancement effect of the proposed model. https://doi.org/10.3390/electronics12051227, Han J, Zhou J, Wang L, Wang Y, Ding Z. FE-GAN: Fast and Efficient Underwater Image Enhancement Model Based on Conditional GAN. This is Abstraction; the student search functionality is hidden away from the rest of the system. Cho, Y.; Jeong, J.; Kim, A. Model-assisted multiband fusion for single image enhancement and applications to robot vision. x}YaHao=3\u_D(n@2|E?400 F/>Kf9YU`Hldz,yw;?^CO=|~w~{/5n;p;6:6`~N9qs} A single chess Knight is able to move on a small cross-shaped board. In Proceedings of the 2017 IEEE International Conference on Computational Photography (ICCP), Stanford, CA, USA, 1214 May 2017; pp. What is the best way to present the information. How to Help Students Improve Pattern Recognition Skills, 3 Important Additions to Digital Literacy for Students in 2023. Why Is Computational Thinking Important for Students? Lets look at how to actually find such a computational solution with the caveat that individual steps will be customized as different problems will require different detailed approaches. A sequential network can avoid frequently visiting additional nodes, which is beneficial for speeding up inference and reducing memory consumption. In recent years, many learning-based methods used, Structural reparameterization is used in our encoder to speed up inference. 1996-2023 MDPI (Basel, Switzerland) unless otherwise stated. One way to think about information is data in some context. Although computational thinking isnt a formal methodology for reasoning, it does encompass some basic principles that are useful in all fields and disciplines. Computational problems, in general, require a certain mode of approach or way of thinking. Generalization like this allows us to identify characteristics that are common across seemingly disparate models, thus allowing us to adapt a solution from one domain to a supposedly unrelated domain. We can also codify this information in some knowledge-based system that is curated using knowledge management techniques. Conceptualization, J.H. Computational thinking is the process of defining a step-by-step solution to a complex problem or to achieve a specific goal. The object detection test was performed before and after the FE-GAN processing. Decomposition and pattern recognition broke down the complex, and abstraction figures out how to work with the different parts efficiently and accurately. It allows us to thus prioritize information about the system under examination. In software engineering and computer science, abstraction is a technique for arranging complexity of computer systems. [. In this paper, we proposed an underwater image enhancement model based on a conditional generative adversarial network. QT%^[g5XM.GTFySXX;S$[+?D@_[6E[jmYWNM~jxIoVx2I#UP$0mq'J"e'i[t4B/vdZciYh;'@3B$u$Wq|"60(puvCU In the Aquarium Combined dataset, there are seven types of targets to be detected: fish, jellyfish, penguin, puffin, shark, starfish, and stingray. In this dataset, part of the images are collected by seven different camera equipment; the other part comes from images captured in YouTube videos. a student will typically study a 2-year course. This is similar to travelling public transport problems. Li, Y.; Lu, H.; Zhang, L.; Li, J.; Serikawa, S. Real-time visualization system for deep-sea surveying. 49524956. In Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, 2229 October 2017; pp. Zhao, J.; Mathieu, M.; LeCun, Y. Energy-based generative adversarial network. The elements can be broken down into inputs, processes and outputs. Outside of this, she has also led professional development for teachers in both English and Arabic and served as the primary editor for several university professors writing both book chapters and journal articles. There is not a single reference to "algorithmic thinking" or "computational thinking". Please note, this is not a comprehensive listing but is representative. ; data curation, L.W. However, these skills, such as pattern recognition, decomposition, abstraction, generalization . Li, H.; Zhuang, P. DewaterNet: A fusion adversarial real underwater image enhancement network. Different loss functions based on texture and content are combined with weights to constrain the generator and discriminator. I can identify and describe problems and processes. Article metric data becomes available approximately 24 hours after publication online. ; Zhao, X.; Cosman, P.C. Han, M.; Lyu, Z.; Qiu, T.; Xu, M. A review on intelligence dehazing and color restoration for underwater images. In Early childhood development: Concepts, methodologies, tools, and applications (pp. If we put data in the context of some logic-based reasoning structure, we can reach some conclusion based on the evidence; this conclusion becomes our usable information that can form the basis of actionable knowledge. 101 0 obj <>/Filter/FlateDecode/ID[]/Index[69 59]/Info 68 0 R/Length 141/Prev 560346/Root 70 0 R/Size 128/Type/XRef/W[1 3 1]>>stream A Feature Nayar, S.K. Cognitive characteristics of learning Java, an object-oriented programming language. Video Technol. https://doi.org/10.3390/electronics12051227, Subscribe to receive issue release notifications and newsletters from MDPI journals, You can make submissions to other journals. Abstraction in coding and computer science is used to simplify strings of code into different functions. Why Is Computational Thinking Important for Students? Compared with the original distorted image, the processed image has a more natural tone and increased brightness, so the target in the image is clearer and easier to identify. This is a preview of subscription content, access via your institution. Here we used mAP (mean average precision) as a reference metric. Silberman, N.; Hoiem, D.; Kohli, P.; Fergus, R. Indoor segmentation and support inference from rgbd images. Social Studies: Students coalesce the most important details shared in articles about a specific current event and write a brief about the event. Students coalesce the most important details shared in articles about a specific current event and write a brief about the event. Let's examine some patterns in these recipes - in general terms. Abstraction principle (computer programming). Given a generated image, Since we resized the image before the experiment, the values of. Patricia is grumpy and wants to build one dam in each neighbourhood that will cause trouble. We will relate these examples to modern solutions that deal with many more data items. Information not needed is gender, age and date of birth as all this will be obtained from the student search. These images were taken in a poor light environment, and the overall number of this dataset is small, which brings a certain degree of difficulty to training. You ask your smart speaker what the weather will be that 2022 has been an exciting year at Learning.com! ; Constants - this will be something that is likely to remain fixed for a while, e.g. ?C6"C <6)6OOn^bqE+8mNy !m^lb7;|uty~>aK%Eo,X[glz3:]+70a!lWbR3X+~C6iK7-;C^\42760Ijq/7b;=wna"l@ C2f/~+.TO#E"p{; " 86nv=l1=7aGuj5/'zNLO(9Dtr*iQ=:!)fv8X"gJ}&R-/;`;9M{Kz&+_2y(ce W!%nNq>N$$y&cj%g}taG|I$>hHfko]pwIL@("(W;`%cslyLbU A couple of examples are iPad apps for junior school, and Blooms Taxonomy. [, Spier, O.; Treibitz, T.; Gilboa, G. In situ target-less calibration of turbid media. Sinha, A., & Vessey, I. The information needed will be surname only. Ever find yourself saying, 'where have I seen this before', could be a significant step in computational thinking. Can you identify all the general terms that you would need for this program to securely manage your timetable and your homework? UIQM expresses as follows: In the ImageNet dataset, we randomly selected 5500 pairs of images for training and the remaining 628 pairs for testing. Cognition and Instruction, 8(4), 293332. Using a public data set we will examine patterns in data and visualize or describe the patterns. Once you have decomposed a complex problem, it helps to look for similarities or 'patterns' in . All rights reserved. Check out our articles on decomposition, pattern recognition, and algorithmic thinking. Experiments on different datasets show that the enhanced image can achieve higher PSNR and SSIM values, and the mAP value also achieved significant results in the object detection task. [. We dont care HOW they do them only that they work. Your task is to create the algorithm that will have the knight visit each square without going off the board. HIGHLIGHTS who: Kay-Dennis Boom and colleagues from the (UNIVERSITY) have published the research work: Education and Information Technologies (2022) 27:8289-8310 Relationships between computational thinking and the quality of computer programs, in the Journal: (JOURNAL) what: This study examines the relationship between different forms of computational thinking and two different measures of . Zhou, Y.; Yan, K.; Li, X. With the research and application of AUVs (autonomous underwater vehicles) and ROVs (remote operated vehicles), ocean exploration has achieved many breakthrough results. A . Can you think of any abstraction in each one? 2023 Springer Nature Switzerland AG. Your alarm on your smart phone wakes you in the morningthats powered by computer science. As it sounds, pattern recognition is all about recognizing patterns. For instance, we may recognize that an upcoming timed traffic light has turned yellow. Of course not, your computer just turns itself on. Li, C.; Anwar, S.; Porikli, F. Underwater scene prior inspired deep underwater image and video enhancement. Pattern recognition is an essential tool in computational thinking in computer science as well as in everyday life. Abstraction is an essential part of computational thinking. In Proceedings of the Proc. Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive Several aspects should be taken into consideration, such as FLOPs, number of parameters, and inference time during deploying on resource-limited devices. We will look at searching algorithms later on in the course. These rules, in turn, can directly inform the final algorithm well use in the second step of constructing the computational solution. 853862. Pattern recognition in computational thinking uses the identification of similarities within a particular data set or sequence to simplify understanding and resolution of a problem or goal. Vision in bad weather. Pattern recognition is prominent in medicine, where identifying patterns helps to diagnose and cure diseases as well as to understand and prevent disease. For This helps to simplify or break down the problem to make it easier to resolve. Abstraction helps students return to the larger problem that prompted this whole computational . If youre able to make repeated, precise, quantitative predictions, it implies that whichever model youve used or whichever mode of thinking youve employed, its actually working and should likely be re-employed. In Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, 2229 October 2017; pp. permission provided that the original article is clearly cited. Unit 4 Programming by Suba Senthilnathan Assignment 1 - Content of Programming Explain how computational thinking skills Decomposition breaks down problems into smaller, more manageable parts. Such systems are known as Information Management Systems (IMS). This process occurs through filtering out irrelevant information and identifying whats most important. a creative chef for a series of smaller problems. %%EOF Li, C.; Guo, J.; Guo, C. Emerging from water: Underwater image color correction based on weakly supervised color transfer. Our web-based curriculum for grades K-12 engages students as they learn keyboarding, online safety, applied productivity tools, computational thinking, coding and more. 234241. Pattern recognition as part of computational thinking is the process of identifying patterns in a data set to categorize, process and resolve the information more effectively. This is based on pattern recognition, similar to fingerprints. To further verify the generalization ability of FE-GAN, we selected 990 images from the artificially synthesized dataset for testing and compared them with the corresponding ground truth images. The publicly available dataset used in this research can be obtained through the following link: The authors would like to thank the Key R&D plan of Shandong Province (2020JMRH0101), National Deep Sea Center. Pattern recognition in computational thinking uses the identification of similarities within a particular data set or sequence to simplify understanding and resolution of a problem or goal. Learn how this concept can be integrated in student learning. More specifically, it is a set of skills and processes that enable individuals to navigate complex Were excited to share that Learning.coms EasyTech has won in this years Tech & Learning Awards of Excellence: Best of 2022 in the Primary Technology is undoubtedly a fixture in students lives. A teacher wants to look up details about a specific student. It can also expand the difference between the features of different objects in the image, improve the image quality, enrich the amount of information, and strengthen the recognition effect. Science: Students develop laws and theorems by looking at similar formulas and equations. 770778. You are accessing a machine-readable page. The application scenarios of most existing models are still very restricted, and it is rare to achieve good results in both real and synthetic underwater image datasets. [. All representations of a thing are inherently abstract. Panetta, K.; Gao, C.; Agaian, S. Human-visual-system-inspired underwater image quality measures. Will the data patterns provide a part of the solution to the problem? To summarise abstraction is the gathering of the general characteristics we need and the filtering out of the details and characteristics that we do not need.. A website providing comprehensive coverage of computer programming. Another system might record, present, planned absence, unplanned absence and late. While the phrase computational thinking contains the word computational, it has applications far outside computer science. For the Mixed dataset, we selected Test-R90 (90 paired images) and Test-C60 (60 unpaired images) as the test sets of paired and unpaired images respectively and compared them with the same methods in qualitative evaluation. It works by establishing a level of complexity on which a person interacts with the system, suppressing the more complex details below the current level. [, For the existing synthetic and real underwater image datasets, many GAN-based methods have been proven to have achieved good results in underwater image enhancement. [, Johnson, J.; Alahi, A.; Fei-Fei, L. Perceptual losses for real-time style transfer and super-resolution. In Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada, 2730 September 2015; pp. Due to the limitation of memory, all pictures were resized to. %PDF-1.4 Simultaneously, our model conducted qualitative and quantitative analysis experiments on real underwater images and artificial synthetic image datasets respectively, which effectively demonstrates the generalization ability of the model. Cognitive load during problem solving: Effects on learning. Based on HAE and DRB, we construct a fast and efficient underwater image enhancement network. All authors have read and agreed to the published version of the manuscript. In this process, pattern recognition is Digital literacy refers to the knowledge and ability to use technology effectively and responsibly. Chen, R.; Cai, Z.; Cao, W. MFFN: An underwater sensing scene image enhancement method based on multiscale feature fusion network. However, the training process of GAN is usually unstable. It then connects each decomposed problem to establish a complete solution. To quantitatively analyze the enhancement effect of the FE-GAN model on the paired underwater image, we choose PSNR (peak signal-to-noise ratio) and SSIM (structural similarity) as reference indicators. Abstraction in computational thinking is a technique where we split individual parts of the program down into imaginary black boxes that carry out operations. Computational thinking is a problem-solving skill set that is used to tackle problems in computer science. Computational thinking is the process of defining a step-by-step solution to a complex problem or to achieve a specific goal. Seeing is understanding: The effect of visualisation in understanding programming concepts. Jaffe, J.S. For example, if youre faced with writing a large, complex paper, you might choose to tackle it by decomposing the paper into smaller sub-sections and tackling each of those separately. 22232232. More specifically, it is a set of skills and processes that enable individuals to navigate complex Were excited to share that Learning.coms EasyTech has won in this years Tech & Learning Awards of Excellence: Best of 2022 in the Primary Technology is undoubtedly a fixture in students lives. Pattern generalisation is spotting things that are common between patterns. Like the other elements of computational thinking, abstraction occurs inherently and can be addressed throughout the curriculum with students. Draw a series of animals. This can be seen further here. Underwater optical imaging: The past, the present, and the prospects. enables us to navigate complex problems more effectively while helping to find relevance and clarity at scale. Languages: Students create a personal guide that dictates when to use the formal and informal you in Spanish class or the two to know verbs in French, which, mind you, always confounded me. https://doi.org/10.1007/978-3-031-21970-2_26, Shipping restrictions may apply, check to see if you are impacted, http://rigaux.org/language-study/diagram.html, Tax calculation will be finalised during checkout. Its very clever.. Computer science is the study of computational processes and information processes. Using the cognitive walkthrough to improve the design of a visual programming experiment. Generalization can help us to organize ideas or components, as we do when we classify some animals as vertebrates and others as invertebrates. Each participant at this workshop may have used Google Maps to arrive here today the algorithm generated to provide you the detailed instructions is based on pattern recognition. This process occurs through filtering out the extraneous and irrelevant in order to identify whats most important and connects each decomposed problem. As we saw above, Computational Thinking is an iterative process composed of three stages: Lets list the details of the five computational thinking principles and the accompanying computer science ideas and software engineering techniques that can come into play for each of these three steps. Once you have decomposed a complex problem, it helps to look for similarities or 'patterns' in each segmented part of the problem. We can also generalize to form a big picture that ignores some of the inessential details. Correspondence to Du, Z.; Liu, D.; Liu, J.; Tang, J.; Wu, G.; Fu, L. Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution. In 1994, four Software engineers, nicknamed the Gang of Four, Erich Gamma, Richard Helm, Ralph Johnson and John Vlissides, published a book on design patterns which formalised patterns in software use. This process uses inductive thinking and is needed for transferring a particular problem to a larger class of similar problems. Ever find yourself saying, 'where have I seen this before', could be a significant step in computational thinking. Consider the student search system, it can be represented using the following terms: Think back to your student planner program from Lesson 1. >/)gU)FOW_s U}Bgw5]\0QOo, \rz0gx1Ato{C -T/~3IjdzjXM'l2%50TpY?.G/-SYrUT5Af7. This will give us a list of students with the specific surname, but the information brought back would include their first, middle and last name, and their year of registration. Identifying patterns means that there is probably an existing solution already out there. 797819). In computational thinking, one of the integral steps to the problem-solving process is pattern recognition. To further improve the quality of the generated image, we introduce the pixel-level and image-level loss functions into the objective function formulation. captured are operated to obtain the clear images as the desired output [. IPMGAN: Integrating physical model and generative adversarial network for underwater image enhancement. hbbd```b`` Although the brightness and details of the image enhanced by FE-GAN were restored partially, there is still a large gap from the image style under natural light, which is also the focus of future research. >> ty G ~i-*hd h"uZX{LQ!fbW " z(vW49s7$nZAax9A'21@R%B [, Yi, Z.; Zhang, H.; Tan, P.; Gong, M. Dualgan: Unsupervised dual learning for image-to-image translation. 127 0 obj <>stream Now from this general knowledge of patterns in cats, we could draw the general outline of a cat. hko Abstraction means hiding the complexity of something away from the thing that is going to be using it. Here, we selected UCycleGAN [, The application of underwater image enhancement technology to underwater detection equipment is an important research direction. [, Ding, X.; Zhang, X.; Ma, N.; Han, J.; Ding, G.; Sun, J. Repvgg: Making vgg-style convnets great again. For example, if youre driving on the freeway and you notice cars bunching together in the left lane down the road, you might decide to change into the right lane. Hambarde, P.; Murala, S.; Dhall, A. UW-GAN: Single-image depth estimation and image enhancement for underwater images. Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. Electronics 2023, 12, 1227. 27942802. If the problem deals with a complex system, you might break the system down into a bunch of smaller sub-components.