Due to the probability characteristics of quantum mechanism, the combination of quantum mechanism and intelligent algorithm has received wide attention. Quantum dynamics theory uses the Schr?dinger equation as a quant...
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Due to the probability characteristics of quantum mechanism, the combination of quantum mechanism and intelligent algorithm has received wide attention. Quantum dynamics theory uses the Schr?dinger equation as a quantum dynamics equation. Through three approximation of the objective function, quantum dynamics framework(QDF) is obtained which describes basic iterative operations of optimization algorithms. Based on QDF, this paper proposes a potential barrier estimation(PBE) method which originates from quantum mechanism. With the proposed method, the particle can accept inferior solutions during the sampling process according to a probability which is subject to the quantum tunneling effect, to improve the global search capacity of optimization *** effectiveness of the proposed method in the ability of escaping local minima was thoroughly investigated through double well function(DWF), and experiments on two benchmark functions sets show that this method significantly improves the optimization performance of high dimensional complex functions. The PBE method is quantized and easily transplanted to other algorithms to achieve high performance in the future.
Contemporary computer architecture comprises multicomputer settings. Multiple computers provide the facility of high performance to implement multiple threads that are faster and concurrently with different processors...
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This dissertation research explores the potential of using learning analytics to improve programming education. The research goals include replicating previous research through studying heterogeneous groups of student...
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ISBN:
(纸本)9798400701399
This dissertation research explores the potential of using learning analytics to improve programming education. The research goals include replicating previous research through studying heterogeneous groups of students at upper secondary schools over several months. The expected contribution of this dissertation is to provide insights into how learning analytics can identify struggling students.
Contribution: This article proposes a new theoretical model with a goal to develop future human computational thinking (CT) in foundational computerscience (CS) education. The model blends six critical types of think...
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Contribution: This article proposes a new theoretical model with a goal to develop future human computational thinking (CT) in foundational computerscience (CS) education. The model blends six critical types of thinking, i.e., logical thinking, systems thinking, sustainable thinking, strategic thinking, creative thinking, and responsible thinking into the design of a first-year undergraduate programming course. The study describes a creative blended pedagogy that embeds the proposed model into the course plan. Background: The emergence of artificial intelligent systems such as large language models from a knowledge provider perspective, coupled with a gradual change in post-pandemic outlook of education challenge the relevance and raises concerns about the future of education. The 21st-century human CT requirements, viz., learning to code (skill) and thinking computationally (competency), will be inadequate in the future. Moreover, there is substantial evidence which shows that most introductory programming courses fail to integrate critical elements like ethics and responsibility as part of the course. Intended Outcomes: The authors anticipate experiential learning models such as this has immense potential to future-proof CS education, as well as make future software engineers responsible citizens. Application Design: The proposed model blends six types of thinking into the design and activities of the course. The underlying theoretical basis of these activities revolve around three key principles: 1) experiential learning;2) self-reflection;and 3) peer learning. Findings: This case study from a liberal educational institution in India qualitatively shows evidence of students developing six critical elements of thinking that shapes their future CT ability.
How should dynamic programming be taught to students experiencing it for the first time? Dynamic programming is a sophisticated programming technique that exercises many aspects of computerscience in concert. Because...
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ISBN:
(纸本)9781450394338
How should dynamic programming be taught to students experiencing it for the first time? Dynamic programming is a sophisticated programming technique that exercises many aspects of computerscience in concert. Because of the deep technical complexity therein, building effective lessons is challenging. In this work we propose a worked example model for teaching dynamic programming that centers around a midterm exam in which the solutions are provided to the students weeks in advance. 35 students were surveyed about their experiences learning dynamic programming with and without this model.
HighP5 is a new high-level parallel programming language designed to help software developers to achieve three objectives simultaneously: programmer productivity, program portability, and superior program performance....
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Learning programming is a multifaceted process shaped by diverse factors, including effectively utilizing self-regulation of learning (SRL) skills. However, students frequently require a certain level of support to ef...
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ISBN:
(纸本)9798400704239
Learning programming is a multifaceted process shaped by diverse factors, including effectively utilizing self-regulation of learning (SRL) skills. However, students frequently require a certain level of support to effectively engage in SRL, prompting a question regarding the optimal means of providing such assistance. The current literature is limited in identifying which types of support are most effective, and it's also noted that some students do not benefit from its usage. The underlying causes remain underexplored, and a deeper understanding of this phenomenon can offer insights into improving the design of regulatory support. This research is situated within this scope and was guided by the following research questions: RQ1) How does the use of self-regulation of learning support differ among students with high and low-performance levels? RQ2) How do students use and evaluate the self-regulation of learning support? Fifty-four students enrolled in an online introductory programming course participated in this investigation. The findings indicate that higher-performance students made more extensive use of the provided regulatory support, implying the potential utilization of this resource as a learning aid. Simultaneously, it's noted that some students either avoided or utilized this support to a lesser extent, underscoring that the mere provision of resources is insufficient for their effective usage. A qualitative analysis revealed some factors that might have influenced this behavior.
Contribution: A problem-solving approach (PSA) model derived from major computational thinking (CT) concepts. This model can be utilized to formulate solutions for different algorithmic problems and translate them int...
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Contribution: A problem-solving approach (PSA) model derived from major computational thinking (CT) concepts. This model can be utilized to formulate solutions for different algorithmic problems and translate them into effective active learning methods. Background: Different teaching approaches for programming are widely available;however, being able to formulate an algorithmic solution computationally and then transform it into code is essential for students. Research Questions: What are the effective teaching approaches for fostering the development of problem-solving and programming skills? How do CT concepts contribute to the formulation of a PSA model for programming problems and its translation into an effective teaching method? How can an effective teaching method that utilizes the PSA model be identified and distinguished from other approaches? Methodology: A preliminary study pointed out the difficulties experienced when teaching programming, inspiring the formulation of a PSA model that used CT concepts. An experimental study on problem-based and game-based programming workshops that utilized the PSA model through sorting algorithms was performed on experimental groups consisting of 30 students each. A syntax-based programming workshop consisting of 30 students was used as the control group. All the participants were recruited through a pretest that incorporated basic programming questions. The participants had to answer a posttest after the workshop. Findings: The results showed that the participants exhibited no significant difference between the pretest and posttest for the syntax-based learning (SBL). However, there is a significant difference between the pretest and posttest of both the problem-based learning (PBL) and the game-based learning (GBL) workshops. There was no significant difference significant difference for the pretest scores of all three workshops. The analysis of the posttest further confirmed that the experimental groups (PBL and GBL)
In the context of classification, robustness verification of a neural network is the problem which consists in determining if small changes of inputs lead to a change of their assigned classes. We investigate such a p...
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ISBN:
(纸本)9783031609237;9783031609244
In the context of classification, robustness verification of a neural network is the problem which consists in determining if small changes of inputs lead to a change of their assigned classes. We investigate such a problem on binarized neural networks via an integer linear programming perspective. We namely present a constraint generation framework based on disjunctive programming and complete descriptions of polytopes related to outputs of neuron pairs. We also introduce an alternative relying on specific families of facet defining inequalities. Preliminary experiments assess the performance of the latter approach against recent single neuron convexification results.
In 2022, the release of ChatGPT marked a significant advancement in the use of Artificial Intelligence (AI) chatbots, particularly impacting fields like computerscience and education. The ability to generate code sni...
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In 2022, the release of ChatGPT marked a significant advancement in the use of Artificial Intelligence (AI) chatbots, particularly impacting fields like computerscience and education. The ability to generate code snippets using AI chatbots has introduced new opportunities and challenges in teaching programming. However, there is limited agreement on how students integrate them into their learning processes. This study aims to explore how students utilize AI chatbots in the "Object-Oriented programming" course and examine the relationship between chatbot usage and academic performance. To address this, 231 students completed a survey assessing the frequency and manner of chatbot usage. Descriptive statistical methods were employed to analyze usage and perceptions, while Spearman's correlation was used to investigate the connection between chatbot usage and course performance. Results indicated that students primarily relied on AI chatbots for programming tasks. Interestingly, students' performance negatively correlates with the reported frequency of using these tools. These findings provide valuable insights for programming educators, offering a better understanding of students' perceptions and use of AI chatbots. This knowledge can inform strategies for integrating these tools effectively into computerscience education.
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