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Preservice science teachers coding science simulations: epistemological understanding, coding skills, and lesson design

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ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT 2022年第4期70卷 1517-1549页

作者： Vasconcelos, Lucas Kim, ChanMin Univ South Carolina 820 Main St Columbia SC 29208 USA Penn State Univ 304 Fischer Rd State Coll PA 16801 USA

National and state science learning standards urge K-12 educators to offer authentic Science, Technology, Engineering, and Mathematics learning experiences. One way to fulfill this goal is to prepare preservice science teachers to integrate computer science skills, such as coding, into science education learning contexts that can benefit from it. This study implemented coding in Scientific Modeling Lessons (CS-ModeL) in a science teacher education course. CS-ModeL is the name of an instructional module and of an online tool, and they aim to support preservice science teachers' use of coding in scientific modeling and lesson design. Preservice teachers used block-based coding to create science simulations, performed analogous physical experiments, and designed lessons in which they support scientific modeling with coding. This mixed methods study investigated if and how participation in CS-ModeL affected preservice teachers' epistemological understanding of scientific models and modeling along with their understanding of computer science concepts. This study also examined coding-enhanced scientific modeling activities in their designed lessons. Results showed an overall improvement in participants' epistemological understanding of models and modeling, and in their understanding of computer science concepts. Participants' lessons featured activities in which block-based coding simulations are used either as a research tool or as an exploration tool. Additionally, most lessons targeted computer science practices, but not concepts. It was also found that participants' lessons were not aligned with their epistemological understanding of models and modeling. Study limitations, implications for research and practice, and directions for future research are discussed.

关键词： Scientific models Scientific modeling block-based coding Epistemological understanding coding concepts Lesson design

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Learned Image Compression using Adaptive block-wise Encoding and Reconstruction Network 53

Learned Image Compression using Adaptive Block-wise Encoding...

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IEEE International Symposium on Circuits and Systems (IEEE ISCAS)

作者： Zhao, Zhenghui Jia, Chuanmin Wang, Shanshe Ma, Siwei Yang, Jiansheng Peking Univ Sch EE & CS Dept Comp Sci Beijing 100871 Peoples R China Peking Univ Sch Math Sci LMAM Beijing 100871 Peoples R China Peking Univ Informat Technol R&D Innovat Ctr Shaoxing 312000 Peoples R China

ISBN: (纸本)9781728192017

In this paper, a flexible and adaptive block-wise image compression architecture with restoration network is proposed to improve the rate-distortion (R-D) performance of learned image compression. In contrast to existing learned compression algorithms which perform the image based transform coding, our approach splits the input image into non-overlapped blocks and compresses each block adaptively based on their local content characteristics. To reduce the artifacts caused by the block partitioning, block fusion network is subsequently proposed to overcome the drawbacks of block-wise independent coding. Further, quantization fine-tuning training process is proposed and utilized to reduce the difference of quantization operations between the training process and testing process. Experimental results show that the proposed network architecture has the ability to obtain significant coding gain compared with existing conventional compression standards including Versatile Video coding (VVC) and achieves comparable R-D performance with state-of-the-art learned image codec using less parameters.

关键词： Learned image compression block-based coding restoration network

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Accessible Computer Science for K-12 Students with Hearing Impairments 1

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14th International Conference on Universal Access in Human-Computer Interaction (UAHCI) part of the 22nd International Conference on Human-Computer Interaction (HCI)

作者： Das, Meenakshi Marghitu, Daniela Jamshidi, Fatemeh Mandala, Mahender Howard, Ayanna Auburn Univ Auburn AL 36830 USA Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (数字)9783030491086

ISBN: (纸本)9783030491079;9783030491086

An inclusive science, technology, engineering and mathematics (STEM) workforce is needed to maintain America's leadership in the scientific enterprise. Increasing the participation of underrepresented groups in STEM, including persons with disabilities, requires national attention to fully engage the nation's citizens in transforming its STEM enterprise. To address this need, a number of initiatives, such as AccessCSforALL, Bootstrap, and CSforAll, are making efforts to make Computer Science inclusive to the 7.4 million K-12 students with disabilities in the U.S. Of special interest to our project are those K-12 students with hearing impairments. American Sign Language (ASL) is the primary means of communication for an estimated 500,000 people in the United States, yet there are limited online resources providing Computer Science instruction in ASL. This paper introduces a new project designed to support Deaf/Hard of Hearing (D/HH) K-12 students and sign interpreters in acquiring knowledge of complex Computer Science concepts. We discuss the motivation for the project and an early design of the accessible block-based Computer Science curriculum to engage D/HH students in hands-on computing education.

关键词： Accessibility American Sign Language block-based coding

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Learning to teach coding through argumentation

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COMPUTERS AND EDUCATION OPEN 2022年 3卷

作者： Kim, ChanMin Gleasman, Cory Boz, Tugba Park, Hyejin Foutz, Timothy Penn State Univ Coll Educ Learning Design & Technol Educ Psychol State Coll PA 16801 USA Tennessee Technol Univ Coll Educ Curriculum & Instruct Cookeville TN USA Dublin City Univ Sch STEM Educ Innovat & Global Studies Dublin Ireland James Madison Univ Dept Math & Stat Harrisonburg VA USA Univ Georgia Coll Engn Sch Environm Civil Agr & Mech Eng Athens GA 30602 USA

For computer science to be for all students, coding needs to be integrated within existing curricula for authentic and interdisciplinary computer science learning. The present study examined the use of transformative pedagogy of teaching coding through argumentation, specifically focusing on how teachers conceptualized teaching coding through argumentation. Fourteen elementary teachers learned coding and argumentation in a semester-long professional learning course. Participating teachers' coding knowledge, views of coding, and beliefs about using argumentation in teaching coding were examined. A concurrent triangulation mixed methods design was used. Quantitative data included coding exams and surveys and qualitative data included interviews and course artifacts. Study findings include: (a) there were sustained groups with more complete coding knowledge and less complete coding knowledge throughout the semester, (b) coding was often viewed as a means to create another modality for other subject teaching with no difficulty of integration, (c) a few teachers articulated their beliefs about using argumentation in teaching coding with concrete relational connection to coding, and (d) teachers who consistently exhibited more complete coding knowledge conceptualized teaching coding with argumenta-tion in more concrete ways.

关键词： Computing education Elementary teacher education Robot programming block-based coding Argumentation

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coding in scientific modeling lessons (CS-ModeL)

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ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT 2020年第3期68卷 1247-1273页

作者： Vasconcelos, Lucas Kim, ChanMin Univ South Carolina 820 Main St Columbia SC 29208 USA Penn State Univ 304 Fischer Rd State Coll PA 16801 USA

Learning standards for K-12 science education emphasize the importance of engaging students in practices that scientists perform in their profession. K-12 teachers are expected to engage students in scientific modeling, which entails constructing, testing, evaluating, and revising their own models of science phenomena while pursuing an epistemic goal. However, conceptualizing models of unobservable science phenomena without support is daunting for students. We propose that creating science simulations with block-based coding in Scratch is a promising approach to support student's scientific modeling and learning to code. However, research indicates that preservice and in-service science teachers often hold a deficient understanding of scientific modeling instruction, and lack experience teaching with coding. Professional learning on use of block-based coding in scientific modeling instruction is needed though such interdisciplinary research is scarce. In this paper, we review pertinent literature and propose five guidelines for teacher educators striving to offer such professional learning. The guidelines informed the design and development of coding in scientific modeling lessons (CS-ModeL), which is a module and an online tool for scaffolding teachers' learning to code science simulations, and to integrate simulation coding activities into scientific modeling lessons, respectively. We discuss how guidelines informed the design and development of CS-ModeL, as well as plans for future research.

关键词： Scientific modeling Epistemic agency block-based coding Simulations STEM teaching

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Agile Curriculum Development: Computational Modeling COVID-19 21

Agile Curriculum Development: Computational Modeling COVID-1...

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Proceedings of the 52nd ACM Technical Symposium on Computer Science Education

作者： Madeline Hinckle Veronica Catete Nicholas Lytle Tiffany Barnes Eric Wiebe North Carolina State University Raleigh NC USA

ISBN: (纸本)9781450380621

Computational modeling provides an excellent vehicle for raising scientific awareness of emergent and topical phenomena such as COVID-19. Now more than ever, it is crucial to provide students with factual information about how diseases spread and how their own actions can impact that spread. In order to both encourage computational thinking skills and build scientific knowledge of the COVID-19 pandemic, we have created a series of programming activities through which students construct their own computational models based on the emerging scientific consensus around COVID-19. Students are able to model everyday situations such as being in a crowded area or going to stores while unknowingly infected, and immediately see the consequences of those actions. By including accurate scientific variables such as the reproductive number of the virus, incubation period, and period of communicability, students are able to create their own epi-curves that demonstrate the severity of the disease and provide students with visual representation of how quickly COVID-19 spreads. We also use the scientific model and associated modeling activities to reinforce best practices at home and in the community. Finally, this curriculum development effort demonstrates how block-based computational modeling activities lend themselves to agile curricular re-design around emerging and topics of local interest

关键词： middle grades block-based coding computational modeling k-12

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SPATIALLY ADAPTIVE IMAGE COMPRESSION USING A TILED DEEP NETWORK 24

SPATIALLY ADAPTIVE IMAGE COMPRESSION USING A TILED DEEP NETW...

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24th IEEE International Conference on Image Processing (ICIP)

作者： Minnen, D. Toderici, G. Covell, M. Chinen, T. Johnston, N. Shor, J. Hwang, S. J. Vincent, D. Singh, S. Google Inc 1600 Amphiteatre Pkwy Mountain View CA 94043 USA

ISBN: (纸本)9781509021758

Deep neural networks represent a powerful class of function approximators that can learn to compress and reconstruct images. Existing image compression algorithms based on neural networks learn quantized representations with a constant spatial bit rate across each image. While entropy coding introduces some spatial variation, traditional codecs have benefited significantly by explicitly adapting the bit rate based on local image complexity and visual saliency. This paper introduces an algorithm that combines deep neural networks with quality-sensitive bit rate adaptation using a tiled network. We demonstrate the importance of spatial context prediction and show improved quantitative (PSNR) and qualitative (subjective rater assessment) results compared to a non adaptive baseline and a recently published image compression model based on fully-convolutional neural networks.

关键词： Image Compression Neural Networks block-based coding Spatial Context Prediction

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HEVC-based DEblockING FILTER WITH RAMP PRESERVATION PROPERTIES

HEVC-BASED DEBLOCKING FILTER WITH RAMP PRESERVATION PROPERTI...

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IEEE International Conference on Image Processing

作者： Andrey Norkin Ericsson Research

ISBN: (纸本)9781479957521

The paper presents an HEVC-based deblocking filter that improves perceptual quality of reconstructed video on the content that exhibits a lot of chaotic motion, such as water, fire or smoke while providing similar quality on "normal" video content, such as the content with linear motion. The filter is also capable of efficiently suppressing block artifacts in smooth areas with slowly changing samples intensity. The objective performance of the proposed deblocking filter is on average similar to the HEVC deblocking.

关键词： Deblocking HEVC Subjective quality block-based coding Video compression

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HEVC Deblocking Filter

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2012年第12期22卷 1746-1754页

作者： Norkin, Andrey Bjontegaard, Gisle Fuldseth, Arild Narroschke, Matthias Ikeda, Masaru Andersson, Kenneth Zhou, Minhua Van der Auwera, Geert Ericsson Res S-16489 Stockholm Sweden Cisco Syst Norway N-1366 Lysaker Norway Panason Res & Dev Ctr D-63255 Langen Germany Sony Corp Technol Dev Grp Tokyo 1418610 Japan Texas Instruments Inc Syst & Applicat Res & Dev Ctr Dallas TX 75243 USA Qualcomm Technol Inc San Diego CA 92121 USA

This paper describes the in-loop deblocking filter used in the upcoming High Efficiency Video coding (HEVC) standard to reduce visible artifacts at block boundaries. The deblocking filter performs detection of the artifacts at the coded block boundaries and attenuates them by applying a selected filter. Compared to the H.264/AVC deblocking filter, the HEVC deblocking filter has lower computational complexity and better parallel processing capabilities while still achieving significant reduction of the visual artifacts.

关键词： block-based coding deblocking video coding video filtering video processing

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HEVC deblocking filtering and decisions

HEVC deblocking filtering and decisions

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Conference on Applications of Digital Image Processing XXXV

作者： Norkin, Andrey Andersson, Kenneth Fuldseth, Arild Bjontegaard, Gisle Ericsson Res Stockholm Sweden Cisco Syst Oslo Norway

ISBN: (纸本)9780819492166

The emerging High Efficiency Video coding (HEVC) standard uses a block-based coding scheme, which may cause blocking artifacts, especially at lower bitrates. An adaptive in-loop deblocking filter is used in the standard to reduce visible artifacts at block boundaries. The deblocking filter detects artifacts at the block boundaries and attenuates them by applying a selected filter. This paper will present deblocking decisions and filtering operations that are used in HEVC.

关键词： deblocking video coding video processing block-based coding filtering

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