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摘要： The unexamined power and prejudice embedded within technologies and societies has led to direct harm to individuals of color, minoritized groups, and the US ideal of a multi-racial democracy. Rather than an accident of AI or a "glitch" of the system, these inequities highlight the invisible and oppressive architecture - a "New Jim Code" (Benjamin, 2019) - encoded into the bones of the technology. At the same time, computer science education has grown considerably over the last decade. We ask how can educators address embedded injustice within the K-12 CS education? Using information asymmetry (Hippel, 2005) as a conceptual framing, we argue for the need to address racialized and patriarchal biases through curricular design and teaching in CS. We argue for a participatory and community centered approach to CS curricula which facilitates community co-designed CS, centers criticality, and fosters civic education within CS.

关键词： Competency-based   Computer science   Computational thinking   Micro-credentials   Pre-service teachers   Teacher education  

摘要： Teacher preparation programs are essential to ensure pre-service teachers are equipped with the skills and knowledge necessary to teach in the PK-12 learning environment, but are rooted in a traditional paradigm of a compacted curriculum with little room for more content. The addition of Computational Thinking (CT) becomes one more thing to add to a packed schedule and integration of CT into established courses takes major redesign of courses. One university in Maryland, U.S. developed a CT focused micro-credential for K-8 pre-service and in-service teachers. In examining pre- and post-content surveys, reflection journal entries and lesson plans, pre-service teachers report CT and pedagogical content growth in their awareness and integration of CT in their lives and future classrooms. Results indicate a CT micro-credential could be an innovative solution to adding CT content to an over-packed, pre-service curriculum. In addition, CT micro-credential courses increased pre-service teachers' knowledge and self-awareness to the feasibility to proficiently implement CT across all courses.

关键词： Punishment   Criminal justice   Capital punishment  

摘要： The introduction of rewards for the conviction of serious criminals fundamentally transformed English criminal justice. The prospect of rewards totalling up to 140 pound encouraged additional prosecutions, more full (as opposed to partial) guilty verdicts, and more death sentences. In the process, in a series of largely unintended consequences, two fundamental pillars of early-modern justice were undermined: reliance on the public to prosecute, and the death penalty to deter crime. Policing agents began to play a much more important role in apprehending criminals, while the high level of executions contributed to growing doubts about the efficacy of capital punishment.

关键词： Students  

摘要： Proposing a justice-centered CS education.

关键词： Metadata  

摘要： DBLP is the largest open-access repository of scientific articles on computer science and provides metadata associated with publications, authors, and venues. We retrieved more than 6 million publications from DBLP and extracted pertinent metadata (e.g., abstracts, author affiliations, citations) from the publication texts to create the DBLP Discovery Dataset (D3). D3 can be used to identify trends in research activity, productivity, focus, bias, accessibility, and impact of computer science research. We present an initial analysis focused on the volume of computer science research (e.g., number of papers, authors, research activity), trends in topics of interest, and citation patterns. Our findings show that computer science is a growing research field (≈15% annually), with an active and collaborative research community. While papers in recent years present more bibliographical entries in comparison to previous decades, the average number of citations has been declining. Investigating papers’ abstracts reveals that recent topic trends are clearly reflected in D3. Finally, we list further applications of D3 and pose supplemental research questions. The D3 dataset, our findings, and source code are publicly available for research purposes. © 2022, CC BY-SA.

关键词： Heterogeneous catalysis   Applied mathematics   Method development   Bioenergy   Computer science  

摘要： Mechanistic understanding of large molecule conversion and the discovery of suitable heterogeneous catalysts have been lagging due to the combinatorial inventory of intermediates and the inability of humans to enumerate all structures. Here, we introduce an automated framework to predict stable configurations on transition metal surfaces and demonstrate its validity for adsorbates with up to 6 carbon and oxygen atoms on 11 metals, enabling the exploration of similar to 10(8) potential configurations. It combines a graph enumeration platform, force field, multi-fidelity DFT calculations, and first-principles trained machine learning. Clusters in the data reveal groups of catalysts stabilizing different structures and expose selective catalysts for showcase transformations, such as the ethylene epoxidation on Ag and Cu and the lack of C-C scission chemistry on Au. Deviations from the commonly assumed atom valency rule of small adsorbates are also manifested. This library can be leveraged to identify catalysts for converting large molecules computationally.

关键词： Positive experiences about science   Core competency   Achievement  

摘要： The purpose of this study is to investigate the effects of learning using computer-based science inquiry program. To this end, the three lessons computer-based science inquiry were developed in domain of material's properties. The developed program was put into K middle school located in Seoul and the effects were verified. For the experimental group, the three lessons computer-based science inquiry related to the separation of mixture were introduced, and for the comparison group, the contents presented in the textbook were introduced as a teacher-centered teaching method. To verify the effects of the program, 2-way ANCOVA was performed on positive experiences about science and science core competency, and 2-way ANOVA was performed on academic achievement. As a result of the study, there were significant differences between the two groups in positive experiernces about science and scientific core competencies and academic achievement (p<.05), and group*gender interaction effect was only significant in academic achievement (p<.05). From the results of this study, we could see the possibility of using a computer-based science inquiry program as a chemistry teaching method that enables sustainable scientific inquiry.

关键词： Dynamical systems   Learning algorithms   Network models   Computer science   Statistics  

摘要： Neural generative models can be used to learn complex probability distributions from data, to sample from them, and to produce probability density estimates. We propose a computational framework for developing neural generative models inspired by the theory of predictive processing in the brain. According to predictive processing theory, the neurons in the brain form a hierarchy in which neurons in one level form expectations about sensory inputs from another level. These neurons update their local models based on differences between their expectations and the observed signals. In a similar way, artificial neurons in our generative models predict what neighboring neurons will do, and adjust their parameters based on how well the predictions matched reality. In this work, we show that the neural generative models learned within our framework perform well in practice across several benchmark datasets and metrics and either remain competitive with or significantly outperform other generative models with similar functionality (such as the variational auto-encoder). Brain-inspired neural generative models can be designed to learn complex probability distributions from data. Here the authors propose a neural generative computational framework, inspired by the theory of predictive processing in the brain, that facilitates parallel computing for complex tasks.

关键词： Internet of Things   Real-time systems   Numerical models   Sensors   Computer science   Time-frequency analysis   Time measurement   Age of Information (AoI)   budget constraint   information update   Internet of Things (IoT)  

摘要： Age of Information (AoI) has become a new performance metric that quantifies the freshness of information in the Internet of Things (IoT). To optimize the AoI, the latest information should be frequently sampled and timely updated by source nodes (SNs), which, however, contradicts with the fact that the resources of both the SNs and destination node are limited. To consider this issue, this article formulates a more general multisource information update problem, taking into account both the budget constraint of destination node and the limited sampling/updating capabilities of the SNs. Besides that, two different sampling models, named sampling-predetermined and sampling-at-will models, have been studied, respectively. Particularly, for the information update problem under the sampling-predetermined model, we prove that it is an NP-hard problem. Then, we propose a greedy algorithm to select the appropriate SNs, and theoretically analyze the bound of the AoI achieved by the proposed algorithm. For the sampling-at-will model, we theoretically derive the minimum AoI that can be achieved under given number of updates, based on which, we design an optimal SNs selection and updating time determination mechanism, to achieve the minimum AoI. Finally, we conduct simulations to evaluate the effectiveness of the proposed algorithms.

摘要： Using responses from a large respondent-initiated online survey, we find that the career interests of many current and aspiring computer scientists in the United States diverge from a popular and official depiction of computer scientists' interests used for career and workforce development worldwide. Distinct profiles of career interests emerged from the data. These profiles suggest that many women in the field value social and artistic expression in a way not currently recognized by established depictions of computer scientists' interests. Better capturing the diversity of interests in computer science might help to boost women's, and men's, engagement in this STEM field.