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关键词： accountability   assessment   diversity   program evaluation  

摘要： Background In the field of engineering education, assessment and evaluation have been given insufficient attention as they relate to broadening participation. We posit that this lack of attention negatively impacts our ability to develop and implement sustainable solutions at scale. Purpose The purpose of this article is to explore the presence of an assessment cycle in the literature related to broadening participation in engineering. The assessment cycle refers to the process by which assessment/evaluation is planned, enacted, and used to improve educational processes. Scope/Method The scope of this study was influenced by it being situated in a larger study focused on broadening participation of Black Americans in engineering and computer science. We completed a literature map that illuminated a subset of literature broadly related to assessment/evaluation, and subsequently conducted a systematic literature review of 33 publications reporting on assessment/evaluation efforts. Our analysis of these efforts was grounded in a six-stage assessment cycle. Results The results of this study highlight common publishing practices related to the assessment cycle in the context of broadening participation. We find that assessment/evaluation is generally published at the program level, focused on student development or academic success as a proxy for program effectiveness, and concentrated on positive claims. Conclusion There is room to significantly improve how assessment/evaluation information is published. By highlighting productive and unproductive publishing practices related to assessment/evaluation, this research has important implications for the use and publishing of assessment/evaluation, particularly as it relates to broadening participation in engineering.

关键词： Execution   Identity   Newspaper   Person reference   Categorization   Capital punishment  

摘要： Integrating a social psychological perspective into Van Leeuwen's framework of social actor representation (2008), this study investigates the ways in which various forms of person reference are selected to position executioners, executed persons, and victims in execution reports. Based on a corpus of major broadsheets in Thailand, the analysis reveals extreme and, oftentimes disturbing, labels that assign polarized identities to each group. Exclusion and impersonal nominations mystify the executioners. Oppositional functional and identification labels disparage the executed individuals by exaggerating impression of legal violation and brutality, while idealizing the victims by emphasizing innocence, vulnerability and helplessness. It is argued that the patterns therein, motivated by the retentionist ideology, are socially divisive: they work to facilitate the public's moral disengagement from feeling complicit in the execution and constitute key to normalizing the violence of state killing from that inflicted by the condemned. (C) 2021 Elsevier B.V. All rights reserved.

摘要： With #saytheirnames, the 2020 Black Lives Matters movement implores the national public to etch the names of George Floyd, Ahmaud Arbery, and Breonna Taylor into their consciousness. The fight for racial justice is a fight for attention in American popular culture. Activists push for recognition of the right to Black life, celebrities attempt to shine their spotlights on justice initiatives, and public figures debate solutions to systemic racism. The immediacy of today’s racial violence discourse parallels that of the Gilded Age and Progressive Era.

关键词： Optimization   Upper bound   Computer science   Indexes   Cybernetics   Evolutionary computation   Crossover   MOEA/D   multiobjective optimization problem (MOP)   running time analysis  

摘要： Decomposition-based multiobjective evolutionary algorithms (MOEAs) are a class of popular methods for solving the multiobjective optimization problems (MOPs), and have been widely studied in numerical experiments and successfully applied in practice. However, we know little about these algorithms from the theoretical aspect. In this paper, we present running time analysis of a simple MOEA with mutation and crossover based on the MOEA/D framework (MOEA/D-C) on five pseudo-Boolean functions. Our rigorous theoretical analysis shows that by properly setting the number of subproblems, the upper bounds of expected running time of MOEA/D-C obtaining a set of solutions to cover the Pareto fronts (PFs) of these problems are apparently lower than those of the one with mutation-only (MOEA/D-M). Moreover, to effectively obtain a set of solutions to cover the PFs of these problem, MOEA/D-C only needs to decompose these MOPs into several subproblems with a set of simple weight vectors while MOEA/D-M needs to find Omega(n) optimally decomposed weight vectors. This result suggests that the use of crossover in decomposition-based MOEA can simplify the setting of weight vectors for different problems and make the algorithm more efficient. This paper provides some insights into the working principles of MOEA/D and explains why some existing decomposition-based MOEAs work well in computational experiments.

关键词： Computer science education   Computational thinking   Problem-based learning   Elementary CS education   Block-based programming  

摘要： This study investigated how a computer science (CS) problem-based curriculum impacted elementary students' CS learning and attitudes. Four sixth-grade teachers and 200 of their students participated in the study. Researchers developed a CS curriculum in collaboration with the teachers, which consisted of two main units: (1) an introduction to block-based coding and (2) a problem-based learning (PBL) applied coding project. Overall, students significantly improved their knowledge of CT concepts after the introductory block-based coding lessons and retained that knowledge after completing the PBL activities approximately three months later. Results suggest that Event and Parallelism were challenging concepts for most of the students, whereas Loop and Sequence were easily grasped by most of the students. Further analysis based on prior knowledge levels revealed that the high-prior knowledge (HK) group outperformed the low-prior knowledge (LK) group on every measure. However, LK narrowed the gap of CT concepts after the introductory block-based coding lessons. Students also communicated relatively positive attitudes towards CS at the conclusion of the PBL unit. These results provide support for further exploring the integration of inquiry-oriented instructional strategies such as PBL to support CS instruction.

关键词： Online graduate degree   Human capital   Graduate education   Adult students   Career motivation   Computer science  

摘要： Online graduate degree programs, particularly in technical disciplines, represent a fast-growing market for higher education institutions. Yet, it is unclear how online degree programs fit within students' educational investment decisions and career goals. Based on a foundation of human capital theory, and using data from a 2017 survey of students enrolled in an online master's degree program in computer science at a highly ranked US university, this study explores how motivation for seeking an online graduate degree in computer science varies by student demographics and professional background/preparation. Results show two student markets: one for career mobility, including job advancement and/or career change, and another for skill building without consideration of mobility. Our results also show that while students come from diverse backgrounds, the primary driving factor for seeking the degree is determined by relevant professional experience. Implications for future study and online instructional design are discussed.

关键词： Complex networks   Social networking (online)   Evolution (biology)   Computer science   Forecasting   Community detection   community evolution analysis   complex networks   event-based framework   weak events  

摘要： Community evolution remains a heavily researched and challenging area in the analysis of dynamic complex network structures. Currently, the primary limitation of traditional event-based approaches for community evolution analysis is the lack of strict constraint conditions for distinguishing evolutionary events, which entails that as the cardinality of discovered events increases, so does the number of redundant events. Another limitation of existing approaches is the lack of consideration for weak events. Weak events can be generated by small changes in communities, which are empirically prevalent, and are typically not captured by traditional events. To manage these two aforementioned limitations, this research aims to formalize a weak and strong events-based framework, which includes the following newly discovered events: "weak shrink," "weak expand," "weak merge," and "weak splity" predicated on the community overlapping degree and community degree membership, this article refines these traditional strong events, as well as new constraints for weak events. In addition, a community evolution mining framework, which is based on both strong and weak events, is proposed and denoted by a weak-event-based community evolution method (WECEM). The framework can be summarized by the following: 1) communities in complex networks with adjacent time-stamps are compared to determine the community overlapping degree and community membership degree;2) the values of the community overlapping degree and membership degree meet the definition of events;and 3) weak events are effectively identified. Extensive experimental results, on real and synthetic data sets consisting of dynamic complex networks and online social networks, demonstrate that WECEM is able to identify weak events more effectively than traditional frameworks. Specifically, WECEM outperforms traditional frameworks by 22.9% in the number of discovered strong events. The detection accuracy of evolutionary events is ap

关键词： Hash functions   Image retrieval   Semantics   Training   Internet   Computer science   Concept drift   concept preserving   hashing   image retrieval   nonstationary environment  

摘要： Current hashing-based image retrieval methods mostly assume that the database of images is static. However, this assumption is not true in cases where the databases are constantly updated (e.g., on the Internet) and there exists the problem of concept drift. The online (also known as incremental) hashing methods have been proposed recently for image retrieval where the database is not static. However, they have not considered the concept drift problem. Moreover, they update hash functions dynamically by generating new hash codes for all accumulated data over time which is clearly uneconomical. In order to solve these two problems, concept preserving hashing (CPH) is proposed. In contrast to the existing methods, CPH preserves the original concept, that is, the set of hash codes representing a concept is preserved over time, by learning a new set of hash functions to yield the same set of hash codes for images (old and new) of a concept. The objective function of CPH learning consists of three components: 1) isomorphic similarity;2) hash codes partition balancing;and 3) heterogeneous similarity fitness. The experimental results on 11 concept drift scenarios show that CPH yields better retrieval precisions than the existing methods and does not need to update hash codes of previously stored images.

关键词： Computational thinking   STEAM   Game design   Computer science education  

摘要： This paper presents a game-design workshop built around a digital art installation featuring video games displayed over a real-world skyscraper to stimulate students' interest in computer science and a study testing its short-term effects on improving middle school students' computational thinking (CT) skills and attitudes towards computing. Following a STEAM approach, the workshop aimed to engage participants in age-appropriate activities that focus on CT skills through the lens of creating their own game. A web-based game design interface that allows students to code and play games as simulated on a skyscraper was developed to support the workshop's core activities. The web environment also featured step-by-step tutorials and fully functional games to promote the accessibility of the learning materials for a diverse body of students and educators around the globe. The results of the study indicated that the workshop helped students improve their CT skills and differentially influence their attitudes towards computing. In particular, the workshop experience led students from underserved community districts to lower their attitude ratings, whereas the reverse pattern was observed for students from more affluent districts. The workshop reportedly informed students' perception of computing as a profession and their appreciation of the analytical effort required for developing functional games. Qualitative analysis of artifact-based interviews indicated that students could begin to make abstractions and devise algorithms by associating variables through conditional statements while solving problems related to game development. Interview analysis also revealed that students took pride in the effort that they made during the workshop.

关键词： computer science   information technology   public health   health humanities   vaccines   machine learning  

摘要： Background: Social media has become an established platform for individuals to discuss and debate various subjects, including vaccination. With growing conversations on the web and less than desired maternal vaccination uptake rates, these conversations could provide useful insights to inform future interventions. However, owing to the volume of web-based posts, manual annotation and analysis are difficult and time consuming. Automated processes for this type of analysis, such as natural language processing, have faced challenges in extracting complex stances such as attitudes toward vaccination from large amounts of text. Objective: The aim of this study is to build upon recent advances in transposer-based machine learning methods and test whether transformer-based machine learning could be used as a tool to assess the stance expressed in social media posts toward vaccination during pregnancy. Methods: A total of 16,604 tweets posted between November 1, 2018, and April 30, 2019, were selected using keyword searches related to maternal vaccination. After excluding irrelevant tweets, the remaining tweets were coded by 3 individual researchers into the categories Promotional, Discouraging, Ambiguous, and Neutral or No Stance. After creating a final data set of 2722 unique tweets, multiple machine learning techniques were trained on a part of this data set and then tested and compared with the human annotators. Results: We found the accuracy of the machine learning techniques to be 81.8% (F score=0.78) compared with the agreed score among the 3 annotators. For comparison, the accuracies of the individual annotators compared with the final score were 83.3%, 77.9%, and 77.5%. Conclusions: This study demonstrates that we are able to achieve close to the same accuracy in categorizing tweets using our machine learning models as could be expected from a single human coder. The potential to use this automated process, which is reliable and accurate, could free valuable time a