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Measuring Acceptance of block-based coding Environments

TECHNOLOGY KNOWLEDGE AND LEARNING 2023年第1期28卷 241-251页

作者： Toma, Radu Bogdan Univ Burgos Fac Educ Dept Specif Didact C Villadiego S-N Burgos 09001 Spain

The development of computational thinking skills is attracting attention worldwide. The use of visual or block-based coding in primary schools has gained momentum. Yet, students' acceptance of such coding environments has been neglected in the literature. This study presents a measurement instrument that will allow pursuing such an endeavor. The Technology Acceptance Model was used as a guiding framework. A panel of eight experts and a purposive sample of 315 elementary school students (Mage = 10.18 years, SD = 1.13) were recruited. Inter-rater agreement between experts (75-100%) confirmed the content validity of the items. Exploratory factor analysis resulted in a three-factor solution of 12 items measuring perceived usefulness, perceived ease of use, and attitudes towards visual coding. Inspection of the correlation matrix provided evidence of convergent and discriminant validity. Cronbach's alpha (.75-.82), McDonald's omega (.68-.83), and Spearman-Brown's split-half coefficients (.67-.80) provided evidence of reliability. Overall, findings support the validity and reliability of the proposed instrument. Its use can shed light on students' acceptance of different block-based coding environments.

关键词： block-based coding Visual coding Computational thinking Instrument Acceptance Validity and reliability

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Automated Structural Evaluation of block-based coding Assignments 2023

Automated Structural Evaluation of Block-based Coding Assign...

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54th Annual ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE TS)

作者： Damle, Param Bull, Glen Watts, Jo Nguyen, N. Rich Univ Virginia Charlottesville VA 22904 USA

ISBN: (纸本)9781450394338

As computer science is integrated into a wider variety of fields, block-based programming languages like Snap!, which assemble code with visual blocks rather than text syntax, are increasingly used to teach computational thinking (CT) to students from diverse backgrounds. Although automated evaluators (autograders) for programming assignments usually focus on runtime efficiency and output accuracy, effective evaluation of a student's CT skills requires assessing coding best practices, such as decomposition, abstraction, and algorithm design. While autograders are commonplace for text languages like Python, we present a machine learning approach to assess how effectively block-based code demonstrates understanding of CT fundamentals. Our dataset consists of Snap! programs written by students new to coding and evaluated by instructors using a CT rubric. We explore how to best transform these programs into low-dimensional features to allow encapsulation and repetition patterns to emerge. Experimentation involves comparing the effectiveness of a suite of clustering models and similarity metrics by analyzing how directly automated feedback correlates to the course staff's manual evaluation. Lastly, we demonstrate the practical application of the autograder in a classroom setting and discuss scalability and feasibility in other domains of CS education.

关键词： clustering visual programming block-based coding student assessment computational thinking machine learning

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Preparing preservice teachers to use block-based coding in scientific modeling lessons

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INSTRUCTIONAL SCIENCE 2020年第6期48卷 765-797页

作者： Vasconcelos, Lucas Kim, ChanMin Univ South Carolina Dept Educ Studies Wardlaw Coll Educ 820 Main St Columbia SC 29208 USA Penn State Univ Coll Educ Learning Design & Technol 314D Keller Bldg University Pk PA 16802 USA

Scientific modeling and coding are critical skills to be integrated into K-12 instruction. Research has shown that preservice teachers are often ill-prepared for teaching scientific modeling, and lack opportunities to learn coding within teacher education programs. The present study reports the implementation of an instructional module and online system, called coding in Scientific Modeling Lessons (CS-ModeL), which was designed to scaffold preservice science teachers' learning to code simulations and design scientific modeling lessons that feature simulation coding. In this study, we examined preservice teachers' epistemic discourse during simulation coding, perceptions of coding for future teaching, and coding-enhanced scientific modeling lessons. This was a qualitative single case study that involved six participants enrolled in a science teacher education course. Participants worked in pairs during scientific modeling activities, and each pair was considered an embedded unit within the single case. Data sources included transcripts of screen recordings captured during simulation coding, transcripts of individual semi-structured interviews, and lessons in which participants used simulation coding as part of scientific modeling activities. Qualitative thematic analysis was conducted. Findings revealed that participants' epistemic discourse led to correction of science misconceptions. However, lack of debugging and conflict argumentation skills detracted from their epistemic discourse quality. Participants perceived coding as a beneficial skill for K-12 students though they voiced concerns about teaching with coding unassisted. Participants failed to design truly interdisciplinary and authentic scientific modeling activities including simulation coding. Study limitations and future research directions are discussed.

关键词： Preservice teachers Professional learning Scientific modeling block-based coding Simulations Epistemic discourse

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block-based Learned Image coding with Convolutional Autoencoder and Intra-Prediction Aided Entropy coding 35

Block-based Learned Image Coding with Convolutional Autoenco...

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Picture coding Symposium (PCS)

作者： Yuan, Zhongzheng Liu, Haojie Mukherjee, Debargha Adsumilli, Balu Wang, Yao NYU Tandon Sch Engn Dept Elect & Comp Engn Brooklyn NY 11201 USA Nanjing Univ Sch Elect Sci & Engn Nanjing Jiangsu Peoples R China Google Res Mountain View CA USA

ISBN: (纸本)9781665425452

Recent works on learned image coding using autoencoder models have achieved promising results in rate-distortion performance. Typically, an autoencoder is used to transform an image into a latent tensor, which is then quantized and entropy coded. based on a work by Ball ' e et al., we adapted the autoencoder with a hyperprior model to code images in a block-based approach. When the autoencoder model is directly applied to code small image blocks, spatial redundancy in the larger image cannot be fully utilized, resulting in a decrease in rate-distortion performance. We propose a method to utilize border information in the entropy coding of latent and hyper-latent tensors, which has achieved promising results. We show that using intra-prediction to help entropy coding is more effective than applying a convolutional autoencoder with hyper priors to intra-prediction residual blocks.

关键词： block-based coding deep learning intraprediction learned image compression

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Learned Image Compression With Efficient Cross-Platform Entropy coding

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2025年第1期15卷 72-82页

作者： Yang, Runyu Liu, Dong Wu, Feng Gao, Wen Univ Sci & Technol China Key Lab Brain Inspired Intelligent Percept & Cogni MOE Hefei 230027 Peoples R China Peking Univ Sch Comp Sci Beijing 100871 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China

Learned image compression has shown remarkable compression efficiency gain over the traditional image compression solutions, which is partially attributed to the learned entropy models and the adopted entropy coding engine. However, the inference of the entropy models and the sequential nature of the entropy coding both incur high time complexity. Meanwhile, the neural network-based entropy models usually involve floating-point computations, which incur inconsistent probability estimation and decoding failure in different platforms. We address these limitations by introducing an efficient and cross-platform entropy coding method, chain coding-based latent compression (CC-LC), into learned image compression. First, we leverage the classic chain coding and carefully design a block-based entropy coding procedure, significantly reducing the number of coding symbols and thus the coding time. Second, since CC-LC is not based on neural networks, we propose a rate estimation network as a surrogate of CC-LC during the end-to-end training. Third, we alternately train the analysis/synthesis networks and the rate estimation network for the rate-distortion optimization, making the learned latent fit CC-LC. Experimental results show that our method achieves much lower time complexity than the other learned image compression methods, ensures cross-platform consistency, and has comparable compression efficiency with BPG. Our code and models are publicly available at https://***/Yang-Runyu/CC-LC.

关键词： Image coding Estimation Entropy coding Entropy Computational modeling Training Symbols Transforms Circuits and systems Time complexity block-based coding chain coding cross-platform consistency entropy coding learned image compression

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Perceptual Quality-Oriented Rate Allocation via Distillation from End-to-End Image Compression

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ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 2024年第7期20卷 1–22页

作者： Yang, Runyu Liu, Dong Ma, Siwei Wu, Feng Gao, Wen Univ Sci & Technol China 443 Huangshan Rd Hefei 230027 Anhui Peoples R China Peking Univ 5 Yiheyuan Rd Beijing 100871 Peoples R China Peng Cheng Lab 2 Xingkeyi St Shenzhen 518055 Peoples R China

Mainstream image/video coding standards, exemplified by the state-of-the-art H.266/VVC, AVS3, and AV1, follow the block-based hybrid coding framework. Due to the block-based framework, encoders designed for these standards are easily optimized for peak signal-to-noise ratio (PSNR) but have difficulties optimizing for the metrics more aligned to perceptual quality, e.g., multi-scale structural similarity (MS-SSIM), since these metrics cannot be accurately evaluated at the small block level. We address this problem by leveraging inspiration from the end-to-end image compression built on deep networks, which is easily optimized through network training for any metric as long as the metric is differentiable. We compared the trained models using the same network structure but different metrics and observed that the models allocate rates in different ratios. We then propose a distillation method to obtain the rate allocation rule from end-to-end image compression models with different metrics and to utilize such a rule in the block-based encoders. We implement the proposedmethod on the VVC reference software-VTMand the AVS3 reference software-HPM, focusing on intraframe coding. Experimental results show that the proposed method on top of VTM achieves more than 10% BD-rate reduction than the anchor when evaluated withMS-SSIM or LPIPS, which leads to concrete perceptual quality improvement.

关键词： AVS3 block-based coding end-to-end image compression H.266/VVC perceptual quality rate allocation

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UAE Parents’ Awareness of the Importance of Programming to Primary Students, and Their Perspectives Towards It: A Quantitative Study 1

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7th BUiD Doctoral Research Conference, BDRC 2023

作者： Elsawah, Wafaa Faculty of Education The British University in Dubai Dubai United Arab Emirates

ISBN: (数字)9783031561214

ISBN: (纸本)9783031561207

Purpose: Highlight programming’s importance and explore parental views on its inclusion in UAE primary schools. Methodology: Employing a quantitative approach, the study surveyed 499 UAE parents with primary school children. Their perspectives on programming and their children’s attitudes towards it were gauged. Findings: UAE’s primary school programming education needs reform, necessitating enhanced parental and student awareness. Implications: Educational policymakers should prioritize programming as a core subject, backed by this study. It adds to the literature on programming’s value, highlighting parental awareness’s impact on student attitudes. Originality/Value: This research contributes practical and academic insights, guiding potential expansion. Educational leaders, especially in primary schools, can use these findings to improve programming education. © The Author(s) 2024.

关键词： block-based coding coding programming TAM

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Revisiting Analogical Reasoning in Computing Education: Use of Similarities Between Robot Programming Tasks in Debugging

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JOURNAL OF EDUCATIONAL COMPUTING RESEARCH 2023年第5期61卷 1036-1063页

作者： Kim, ChanMin Dinc, Emre Lee, Eunseo Baabdullah, Afaf Zhang, Anna Y. Belland, Brian R. Penn State Univ University Pk PA USA

Analogical reasoning is considered to be a critical cognitive skill in programming. However, it has been rarely studied in a block-based programming context, especially involving both virtual and physical objects. In this multi-case study, we examined how novice programming learners majoring in early childhood education used analogical reasoning while debugging block code to make a robot perform properly. Screen recordings, scaffolding entries, reflections, and block code were analyzed. The cross-case analysis suggested multimodal objects enabled the novice programming learners to identify and use structural relations. The use of a robot eased the verification process by enabling them to test their analogies immediately after the analogy application. Noticing similar functional analogies led to noticing similarities in the relation between block code as well as between block code and the robot, guiding to locate bugs. Implications and directions for future educational computing research are discussed.

关键词： computing education robot programming and debugging analogical reasoning novice programming learners block-based coding

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Barriers to programming education in UAE primary schools: a qualitative review from ICT teachers’ perspectives

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Discover Education 2023年第1期2卷 1-16页

作者： Elsawah, Wafaa Hill, Christopher British University in Dubai Dubai United Arab Emirates

Purpose: Demonstrate the importance of programming, discuss the pedagogical philosophy of how programming is taught, identify the barriers to the proper implementation of programming education in United Arab Emirates (UAE) primary schools, and find solutions to overcome these barriers. Methodology: The study adopted a qualitative approach. Thirteen ICT teachers, from different schools in the UAE, were interviewed to investigate their perception of the teaching of programming to primary students. Findings: The good application of programming education in UAE schools is yet to be accomplished. There is a need to reform the teaching of programming in primary schools in the UAE and to raise awareness about it and its importance in the school domain (school principals, teachers, and students). Implications: One significant implication is that teaching programming should be taken seriously by educational policymakers and school leaders as a core subject that should be taught to all students. The study also contributed to the growing body of literature on the value of programming skills and the role of the appropriate curriculum in developing these skills. Originality/value: This study provides new insights at both practical and scholarly levels. It can shed light on the field's expansion prospects. The outcomes of this study may assist educational policymakers in better implementing programming education, particularly in primary school. Moreover, it helps teachers better prepare for the problems that primary students may encounter with learning programming in schools. © The Author(s) 2023.

关键词： block-based coding coding Computational thinking Programming TAM

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Tangible-MakeCode: Bridging Physical coding blocks with a Web-based Programming Interface for Collaborative and Extensible Learning 25

Tangible-MakeCode: Bridging Physical Coding Blocks with a We...

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2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： Yu, Jin Garg, Poojita Synn, DoangJoo Oh, HyunJoo Interactive Computing Georgia Institute of Technology Atlanta GA United States University of Washington Seattle WA United States Georgia Institute of Technology Atlanta GA United States Industrial Design & Interactive Computing Georgia Institute of Technology Atlanta GA United States

ISBN: (纸本)9798400713941

Tangible programming engages children through hands-on and collaborative learning but often lacks integration with widely used programming platforms, which limits their extensibility and relevance in existing educational contexts. To address this, we propose Tangible-MakeCode (T-MC), a system that combines physical coding blocks with MakeCode. T-MC enables students, including beginners in coding, to design and program interactive wireless communication projects. Students assemble the blocks, capture an image with a webcam, and convert it into code for MakeCode, which they can simulate and upload to their micro:bit boards. We describe the iterative design of T-MC, informed by participatory design workshops with 53 children and feedback from expert interviews with six teachers. A pilot study with 21 children (ages 12-14;M=10, F=11) demonstrates that T-MC is an engaging and inclusive tool that empowers beginners to contribute to team projects by providing an accessible platform for prototyping ideas. © 2025 Copyright held by the owner/author(s).

关键词： block-based coding Collaborative Learning Educational Technology Iterative Prototyping MakeCode Participatory Design Tangible Programming

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