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关键词： Computational thinking   Academic performance   Computer science   School curricula  

摘要： Teaching computational thinking (CT) has become a priority for educators and policymakers tasked with educating and training students for future jobs which are predicted to be increasingly automated. Recent research on effective instructional interventions for developing computational thinking skills, including algorithmic and critical thinking, problem-solving, creativity, and cooperativity, suggests that teaching and learning CT can improve student academic performance. In fact, the extant literature is quite sanguine about the topic of CT. However, few studies have attempted to establish a relationship between CT skills and academic performance. In the present cross-sectional study, we employ path analysis to model the structural relationship between selfreported CT skills and academic performance of a sample of 81 computer science undergraduates enrolled at a Southwestern American university. We found few direct relationships between CT skills and academic performance. We only find a significant positive relationship between creativity and academic performance and a significant negative relationship between cooperativity and academic performance. Our findings are surprising considering the abundant research promoting computational thinking as a key component of 21st century skills. The findings call for further in-depth analysis of computational thinking and the influence on students' learning and learning outcomes. We discuss our results with respect to recent educational mandates for including CT and instructional alignment in school curricula. Our findings contribute to the existing discussion by helping to clarify the relationship between CT skills and academic performance in higher education.

关键词： Improving classroom teaching   Pedagogical issues   Secondary education   Teaching   learning strategies  

摘要： A new school subject, Leaving Certificate Computer Science, was introduced in September 2018 into Irish schools in a period of curriculum reform and change. Drawing on concepts of teacher agency and learner agency, and viewed through a figurational sociology lens, this paper explored the realities of teaching LCCS and the role teacher agency and learner agency played in such enactment. Through a case study design, four teachers were interviewed in a focus group semistructured manner. To delve deeper into the pedagogical approaches used in LCCS, a further one teacher and their nine students were interviewed. The findings highlight an influential relationship (positive and negative, encouraging and discouraging) between teachers' agentic decisions in their process of achieving teacher agency and the students process of achieving learner agency. The paper offers a figurational viewpoint of the relationship between teacher agency and learner agency through a constructed Figure. We explicitly argue that the responsibility should not be placed on the teacher and student in achieving agency (as a product) but it is a combination of the teacher and the students and the other interdependent relationships within their figurations, alongside contextual factors, and educational social processes, which determine the fluctuation of the process of achieving teacher and learner agency. The paper provides considerations for computer science teacher education.

关键词： artificial intelligence   human intelligence   robotics   autonomous machines   computer science   artificial neural network   human brain  

摘要： Artificial intelligence is one of the most trending topics in the field of Computer Science which aims to make machines and computers 'smart'. There are multiple diverse technical and specialized research associated with it. Due to the accelerating rate of technological changes, artificial intelligence has taken over a lot of human jobs and is giving excellent results that are more efficient and effective, than humans. However, a lot of time there has been a concern about the following: will artificial intelligence surpass human intelligence in the near future? Are computers' ever accelerating abilities to outpace human jobs and skills a matter of concern? The different views and myths on the subject have made it even a more than just a topic of discussion. In this research paper, we will study the existing facts and literature to understand the true definitions of artificial intelligence (AI) and human intelligence (HI) by classifying each of its types separately and analyzing the extent of their full capabilities. Later, we will discuss the possibilities if AI eventually can replace human jobs in the market. Finally, we will synthesize and summarize results and findings of why artificial intelligence cannot surpass human intelligence completely in the future.

关键词： Student leadership   K-12   district policy implementation   broadening participation   leadership  

摘要： Computer Science education (CSed) often aims to position youth as designers, creators, and those with a voice in their world. But do youth have opportunities to design, create, and have voice around the shape of their CSed learning experiences? In this study, we explore ways that school districts engage youth to contribute to the shaping and enactment of their CS instructional systems, efforts districts make to have these leadership roles create impact within these systems, and the tensions associated with these processes. Through in depth analysis of five district case studies, our findings highlight variance around the nature of leadership roles, how access to leadership roles is structured, student autonomy within and ownership over leadership roles, how roles reach into and index differential power over instructional systems, and how district processes of scaffolding and infrastructuring mediate the ultimate impact that students in these roles are able to have on CS instructional systems. Findings also surfaced ways that district actors dealt with a number of tensions associated with student leadership within CS instructional systems. This study provides educators, administrators, and researchers with an expansive view of the potential for students to play legitimate roles within the context of system-wide instructional efforts around CS, and aims to expand conceptions of 'equitable computer science'-up to this point largely conceived of through the lenses of access to, participation in, and experiences of CS learning-to focus on equity as also being about who has 'a seat at the table' when it comes to CS.

关键词： conceptions of programming learning (CoPL)   approaches to programming learning (APL)   phenomenographic analysis   computer science (CS)   non-computer science (non-CS)  

摘要： Programming learning has become an essential literacy for computer science (CS) and non-CS students in the digital age. Researchers have addressed that students' conceptions of learning influence their approaches to learning, and thus impact their learning outcomes. Therefore, we aimed to uncover students' conceptions of programming learning (CoPL) and approaches to programming learning (APL), and analyzed the differences between CS and non-CS students. Phenomenographic analysis was adopted to analyze 31 college students (20 CS-related, and 11 not) from northern Taiwan. Results revealed six categories of CoPL hierarchically: 1. memorizing concepts, logic, and syntax, 2. computing and practicing programming writing, 3. expressing programmers' ideas and relieving pressure, 4. applying and understanding, 5. increasing one's knowledge and improving one's competence, and 6. seeing in a new way. Four categories of APL were also found, namely: 1. copying from the textbook, teachers, or others, 2. rote memory, 3. multiple exploration attempts, and 4. online or offline community interactions. Furthermore, we found that most CS students held higher level CoPL (e.g., seeing in a new way) than non-CS students. However, compared with non-CS students, CS students adopted more surface approaches to learning programming, such as copying and rote memory. Implications are discussed.

关键词： Data mining  

摘要： The main objective of the present study was to develop a data mining model to identify employability patterns of graduates. The model aims to improve job placement rate related to vocational training. This study is in response to concerns about employability of professionals. The KDD (Knowledge Discovery in Databases) methodology was used with defined and simplified stages, algorithms, decision tree techniques, neural networks, and regressions to determine the interaction of graduates in the work environment. The neural network algorithm was adjusted for accuracy, precision, sensitivity, execution time, performance, and data and results interpretation for the generated model. In conclusion, the significant predictor variables were: 1) use of knowledge and skills in the current job, 2) the graduation year and if graduates searched for jobs after graduation, and 3) currently employed (dependent variable). © 2021 Centro de Informacion Tecnologica. All rights reserved.

关键词： Entropy   Control systems   Uncertainty   Dynamical systems   Computer science   Aerospace electronics   Trajectory   Communication channel   data rate constrained feedback   entropy   invariance   networked control systems  

摘要： We introduce a novel notion of invariance feedback entropy to quantify the state information that is required by any controller that enforces a given subset of the state space to be invariant. We establish a number of elementary properties, e.g., we provide conditions that ensure that the invariance feedback entropy is finite and show for the deterministic case that we recover the well-known notion of entropy for deterministic control systems. We prove the data rate theorem, which shows that the invariance entropy is a tight lower bound of the data rate of any coder controller that achieves invariance in the closed loop. We analyze uncertain linear control systems and derive a universal lower bound of the invariance feedback entropy. The lower bound depends on the absolute value of the determinant of the system matrix and a ratio involving the volume of the invariant set and the set of uncertainties. Furthermore, we derive a lower bound of the data rate of any static, memoryless coder controller. Both lower bounds are intimately related and for certain cases it is possible to bound the performance loss due to the restriction to static coder controllers by 1 bit/time unit. We provide various examples throughout the article to illustrate and discuss different definitions and results.

关键词： Feature extraction   Image reconstruction   Hyperspectral imaging   Search problems   Three-dimensional displays   Computer science   Band selection (BS)   channel attention   hyperspectral images (HSIs)   position attention  

摘要： Due to the existence of noise and spectral redundancies in hyperspectral images (HSIs), the band selection (BS) is highly required and can be achieved through the attention mechanism. However, existing BS methods fail to consider global interaction between the spectral information and spatial information in a nonlinear fashion. In this letter, we propose an end-to-end unsupervised dual-attention reconstruction network for BS (DARecNet-BS). The proposed network employs a dual-attention mechanism, i.e., position attention module (PAM) and channel attention module (CAM), to recalibrate the feature maps and subsequently uses a 3-D reconstruction network to restore the original HSI. This way, the long-range nonlinear contextual information in spectral and spatial directions is captured, and the informative band subset can be selected. Experiments are conducted on three well-known hyperspectral data sets, i.e., Indian Pines (IP), University of Pavia (UP), and Salinas (SA), to compare existing BS approaches, and the proposed DARecNet-BS can effectively select less redundant bands with comparable or better classification accuracy. The source code will be made publicly available at https://***/ucalyptus/DARecNet-BS.

摘要： By the early 1970s, work by Noam Chomsky (Benjamin Franklin Medal, 1999) and his colleagues provided strong evidence for a formal characterization of the syntax of human languages. While most linguists believed that a similar characterization of the semantics of language was possible, there was little consensus about its form. Two conflicting views had emerged;to quote a contemporaneous paper by Partee, "One approach, generative semantics, was founded in part on the conviction that semantic and syntactic rules could not be separated in any principled way.... The other, interpretive semantics, maintains the distinction between syntactic rules as formation rules and semantic rules as interpretive rules, but does not posit any systematic relation between them." In parallel, a third approach, a novel formal account of semantics based on strict compositionality and model theory had emerged in the work of the logician Richard Montague, even though it violated commonsense notions of meaning in key instances and provided only the weakest mechanisms to handle purely syntactic phenomena. In this context, Barbara Partee first interpreted Montague's ideas to the community of linguists, finding a way to get linguists past its considerable mathematical difficulty, and then fused Montague's work with interpretive semantics to propose a specific architecture for the syntax-semantics system that has supported accounts of a remarkably wide range of semantic phenomena. In the past 50 years, Partee's approach has become the dominant account of meaning within linguistics. Partee has also trained two generations of students in this new field of formal semantics, and these students collectively provide major intellectual leadership across this field today. The fundamental ideas of formal semantics as envisioned by Partee, particularly the notion of a compositional, declarative semantics running on the output of a deep syntactic analysis, have also played an important although indirect rol

关键词： Social network large-scale decision-making (SN-LSDM)   Punishment-driven consensus reaching model (PDCRM)   Trust-constrained K-means clustering (TCop-Kmeans) algorithm   Trust loss   Social capital selection  

摘要： Clustering and consensus reaching are two crucial processes for solving social network large-scale decision-making (SN-LSDM) problems. This paper explores the moderating effect of trust on the decision-making process, which is decomposed into examining the influence of trust constraint on clustering and the influence of trust loss on consensus reaching. We hold that low-trust experts are not suitable to be assigned to the same subgroup, even though their preferences are sufficiently similar. We propose a punishment-driven consensus reaching model for SN-LSDM problems. The model contains two main stages. In Stage 1, a trust-constrained K-means clustering algorithm is presented, which can overcome the defect of grouping low-trust experts caused by traditional clustering methods based on preference similarity. Then, a weight-determining method combining the size, cohesion, and overall trust degree of a subgroup is proposed. In Stage 2, a punishment-driven consensus reaching process is designed, which identifies four categories of consensus scenarios (high-high, high-low, low-high, low-low) through consensus measures and trust measures. Different adjustment strategies are established, and the moderating effect of trust loss on consensus reaching and consensus cost is investigated. Finally, both a case study on social capital selection in public-private partnership projects and a comparative analysis are implemented to reveal the feasibility and advantages of the clustering algorithm and consensus reaching model proposed in this paper. (C) 2021 Elsevier B.V. All rights reserved.