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关键词： Service-Learning   Computational Thinking   Information Literacy   STEM Education   Higher Education   China  

摘要： Service-Learning (S-L) has been recognized as a promising educational strategy in higher education in China. This study explores the integration of an academic S-L component within a Computer Science curriculum at a university on China's east coast, focusing on student experiences. We thematically analyzed qualitative data encompassing reflection reports and final essays from 53 enrolled undergraduates, transcripts from 11 semi-structured interviews with students, and community feedback. The findings illuminate the multifaceted benefits of embedding S-L in Computer Science education. Students not only acquired theoretical knowledge but also developed crucial cognitive skills through practical, real-world service experiences. The S-L component was instrumental in enhancing students' connections with peers, service recipients, and the broader community, fostering a deep sense of engagement and empathy. Additionally, the study highlights the role of academic S-L in stimulating creativity and student empowerment in the rapidly evolving domains of information technology and higher education.

关键词： Codes   Chatbots   Maintenance engineering   Software development management   Software   Computer bugs   Urban areas   Computer science   Accuracy   Source coding   Empirical study   ChatGPT   self-verification   code generation   code completion   program repair  

摘要： With the increasing utilization of large language models such as ChatGPT during software development, it has become crucial to verify the quality of code content it generates. Recent studies proposed utilizing ChatGPT as both a developer and tester for multi-agent collaborative software development. The multi-agent collaboration empowers ChatGPT to produce test reports for its generated code, enabling it to self-verify the code content and fix bugs based on these reports. However, these studies did not assess the effectiveness of the generated test reports in validating the code. Therefore, we conduct a comprehensive empirical investigation to evaluate ChatGPT's self-verification capability in code generation, code completion, and program repair. We request ChatGPT to (1) generate correct code and then self-verify its correctness;(2) complete code without vulnerabilities and then self-verify for the presence of vulnerabilities;and (3) repair buggy code and then self-verify whether the bugs are resolved. Our findings on two code generation datasets, one code completion dataset, and two program repair datasets reveal the following observations: (1) ChatGPT often erroneously predicts its generated incorrect code as correct, its vulnerable completed code as non-vulnerable, and its failed program repairs as successful during its self-verification. (2) The self-contradictory hallucinations in ChatGPT's behavior arise: (a) ChatGPT initially generates code that it believes to be correct but later predicts it to be incorrect;(b) ChatGPT initially generates code completions that it deems secure but later predicts them to be vulnerable;(c) ChatGPT initially outputs code that it considers successfully repaired but later predicts it to be buggy during its self-verification. (3) The self-verification capability of ChatGPT can be enhanced by asking the guiding question, which queries whether ChatGPT agrees with assertions about incorrectly generated or repaired code and vulnerabil

关键词： Contractive autoencoders   interactive prognosis   nonlinear degradation model   remaining useful life (RUL)   turbofan engines  

摘要： Uncertainty quantification of the remaining useful life (RUL) for degraded systems under the big data era has been a hot topic in recent years. A general idea is to execute two separate steps: deep-learning-based health indicator (HI) construction and stochastic process-based degradation modeling. However, there exists a critical matching defect between the constructed HI and a degradation model, which seriously affects the RUL prediction accuracy. Toward this end, this article proposes an interactive prognosis framework between deep learning and a stochastic process model for the RUL prediction. First, we resort to stacked contractive autoencoders to fuse multiple sensor information of historical systems for constructing the HI in a typical unsupervised manner. Then, considering the nonlinear characteristic of the constructed HI, an exponential-like degradation model is introduced to construct its degradation evolving model, and theoretical expressions of the prediction results are derived under the concept of the first hitting time. Furthermore, we design an optimization objective function by integrating the HI construction and degradation modeling for the RUL prediction. To minimize the designed objective function of the proposed interactive prognosis framework, a gradient descent algorithm is employed to update the model parameters. Based on the well-trained interactive prognosis model, we can obtain the HI of a field system from stacked contractive autoencoders with sensor data and the probability density function (pdf) of the predicted RUL on the basis of the estimated parameters. Finally, the effectiveness and superiority of the proposed interactive prognosis method are verified by two case studies associated with turbofan engines.

关键词： Peer feedback   UTAUT   Technology acceptance   Achievement goals   Learning   Computer science  

摘要： Computer-supported peer feedback offers great potential to enhance students' learning. Yet, students sometimes do not use computer-supported peer feedback opportunities, which partially can be the result of low technology acceptance. The UTAUT-model specifies performance expectancy, effort expectancy, and facilitating conditions as decisive factors for the intention to use a technology. From a motivational perspective, however, it can be expected that also students' achievement goals have an impact on the intention to use an online peer feedback tool. Therefore, we investigated the effects of learning approach, appearance approach, appearance avoidance, work avoidance and relational goals (besides performance expectancy, effort expectancy and facilitating conditions) on 155 computer science students' intentions and actual use of an online peer feedback tool and their performance in an end-of-course exam. Results of path modelling the longitudinal, student and log-data informed data showed that students' intentions predicted actual use, which predicted exam performance. Learning approach goals positively predicted the intention to use the tool, while performance and work avoidance goals did not predict intentions. Relational goals, however, negatively predicted intentions and end-of-course performance, shedding light on the importance of students' social motivations when using online peer feedback tools in their studies (e.g., peer feedback might be perceived as a social threat). Thus, the results point to the importance of an appropriate framing of online peer feedback tool use in educational settings as a learning opportunity and to reduce students' possible concerns about their social relationships when using online peer feedback tools.

关键词： Representation learning   Iterative methods   Optimization   Computer science   Accuracy   Imputation   Diffusion processes   Incomplete multi-view clustering (IMVC)   latent structure-aware view recovery (LaSA)   cross view graph diffusion regularization  

摘要： Incomplete multi-view clustering (IMVC) presents a significant challenge due to the need for effectively exploring complementary and consistent information within the context of missing views. One promising strategy to tackle this challenge is to recover missing views by inferring the missing samples. However, such approaches often fail to fully utilize discriminative structural information or adequately address consistency, as it requires such information to be known or learnable in advance, which contradicts the incomplete data setting. In this study, we propose a novel approach called Latent Structure-Aware view recovery (LaSA) for the IMVC task. Our objective is to recover missing views through discriminative latent representations by leveraging structural information. Specifically, our method offers a unified closed-form formulation that simultaneously performs missing data inference and latent representation learning, using a learned intrinsic graph as structural information. This formulation, incorporating graph structure information, enhances the inference of missing data while facilitating discriminative feature learning. Even when intrinsic graph is initially unknown due to incomplete data, our formulation allows for effective view recovery and intrinsic graph learning through an iterative optimization process. To further enhance performance, we introduce an iterative consistency diffusion process, which effectively leverages the consistency and complementary information across multiple views. Extensive experiments demonstrate the effectiveness of the proposed method compared to state-of-the-art approaches.

关键词： Tensors   Graphics processing units   Indexes   Sparse matrices   Arithmetic   Registers   Computer science   Single instruction multiple data   Optimization   Memory management   Bit optimization   GPU   sparse tensor contraction (SpTC)   sparse tensor format   tensor core  

摘要： Sparse tensor contraction (SpTC) is an important operator in tensor networks, which tends to generate a large amount of sparse high-dimensional data, placing higher demands on the computational performance and storage bandwidth of the processor. Using GPUs with powerful arithmetic characteristics is a reliable choice for accelerating SpTC, however, the high dimensionality and sparsity of tensor makes GPU-accelerated SpTC operators suffer from the difficulties of low computational intensity and high memory consumption. The recent introduction of Tensor Core Units (TCUs) on GPUs brings even more powerful arithmetic, which exacerbates the memory wall problem. To cope with the challenges, this paper proposes a new BCB format that linearizes the indices of multidimensional blocks to reduce block index accesses and uses a bitmap to store the distribution of non-zero elements in a block to reduce the storage overhead. A parallel blocking algorithm of BCB-SpTC is designed to divide the binary linear indices into free and contracted indexes to improve the pairing overhead of computational tasks. Then based on the characteristic computation method of TCUs, the proprietary filling method of TCUs is designed to overcome the inefficiency of parallel computation of sparse data on TCUs. Finally, experimental results on the A100 dataset show that BCB-SpTC improves the acceleration ratio by 1.1x to 21.3x over the existing SpTC GPU method.

关键词： Rural students   Robotics   Curricular integration   Self-efficacy   Social science  

摘要： Integrating computer science (CS) content into existing STEM curricula emerges as a viable solution to broadening rural students' participation in CS, but rural students have a significant proficiency gap in science and mathematics. By focusing on an English language arts course as the context for CS integration, this exploratory study examined the impact of a robotics-based intervention integrated into a high school language arts class on rural students' CS self-efficacy. A convergent mixed methods design was applied to collect and analyze qualitative and qualitative data separately. Quantitative results confirmed that the integrated robotics-based intervention significantly improved rural students' CS self-efficacy. Qualitative findings provided insights on how embodied learning and mastery experience facilitated by the robotics-based intervention fostered rural students' CS self-efficacy. The findings from the two sources of data were integrated, shedding light on the potential of curricular integration in language arts classes for broadening rural student participation in CS education.

关键词： Schedules   Employment   Estimation   Software   Costs   Collaboration   Surveys   Reviews   Project management   Instruments   Computer science (CS)   drafting   linked courses   project schedule management   technical communication (TC)   time estimation   writing and communication processes  

摘要： Background: Students in technical communication classes need to develop expert-like competence in project schedule management to prepare for academic and career success. We address two aspects of project schedule management-estimating time and estimating the number of drafts-that affect undergraduate computer science students in linked computer science-technical communication courses as they prepare documents for their client-based team project. Literature review: Our research considers three areas (developing expert-like behaviors, estimating time, and estimating the number of drafts) that students need to address in their coursework with complex, client-based problems. Research question: What percentage of students accurately estimate, overestimate, or underestimate the time needed to complete project tasks in face-to-face and hybrid sections? We define accurately estimating time as an expert-like behavior and categorize both generating documents and estimating the number of drafts as project tasks. Research methodology: To discuss this research question, we introduce the participants, explain our informed consent, describe our survey instrument for collecting data, and detail our research design. Results/discussion: We present student estimations in two categories: estimated versus actual time to complete assignments and the number of estimated versus actual drafts completed. We learn that students misjudge the amount of time and the number of drafts needed to complete a project, suggesting that technical communication coursework can better prepare students in developing these competencies.

关键词： Electromagnetic interference   Education   Training   Interviews   Guidelines   Computer science   Stakeholders   Computer students   curriculum development   educational programs  

摘要： Contribution: This study advances the understanding of English as a medium of instruction (EMI) in computer science education by exploring computer instructors' perspectives. Its unique contribution lies in a qualitative approach that uncovers the practical implications for policy and practice in the educational context. Background: The rationale for this study is the increasing global adoption of EMI in higher education, particularly in technical fields like computer science. The need to examine the real-world application and challenges of EMI, from the perspective of those directly involved in teaching, establishes its broad relevance. Intended Outcomes: The intended outcomes are to provide evidence-based recommendations for the EMI policy development and to enhance the quality of computer science education. The study aims to inform policy makers and educators about effective strategies and practices, ensuring a more successful implementation of EMI policies that cater to both instructors' and students' needs. Application Design: The study employs a qualitative methodology, utilizing semi-structured interviews with computer instructors. This design was chosen to deeply explore instructors' experiences, beliefs, and strategies in EMI contexts, thus providing rich, contextualized insights into the practical aspects of the EMI policy implementation. Findings: The findings reveal several key challenges in implementing EMI, including limited English proficiency among instructors and students, and a lack of clear teaching and assessment guidelines. The study also identifies effective management strategies used by instructors, such as incorporating students' mother tongue and adapting personal teaching methods. These findings highlight the need for comprehensive policy planning and support for instructors in EMI programs.

关键词： Computing identity   Underrepresented minorities   Computer science   Women   African Americans  

摘要： This paper offers a synthesis on computing identity and the experiences of women and minoritized populations in computing and computer science in higher education. Examining computing identity and its role in the computing experiences of minoritized undergraduates can help us better understand ways to engage and support women and minoritized individuals in the computing field thus increasing participation and persistence of these groups in computing. In this article, we present a review of research literature on computing identity within the experiences of women and minoritized undergraduate students in computing. The research questions guiding this work are: (1) What research literature exists about computing identity?, (2) According to existing literature, what are the experiences of women and racially minoritized undergraduates in computing (e.g., persons who identify as Black, Hispanic/Latinx, Indigenous people)?, and (3) What theoretical frameworks are used to guide existing computing identity literature? Emergent themes include the need to focus on exposure to computing, persistence, career expectations, and engagement. While there is no consensus on a computer identity framework, there is research guided by social cognitive career theory, social identity theory, and practice theory. We conclude that computing identity, including its multiple conceptualizations, offers multiple opportunities for informing and broadening participation of minoritized populations in computing. Future research should include further conceptual exploration of computing identity.