Gamification is gaining popularity because it has been shown to positively influence behaviour and cognitive processes by increasing user motivation and engagement through a game-like experience. Gamification supports...
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Achieving the desired level of satisfaction for a decision- maker in any decision- making scenario is considered a challenging endeavor because minor modifications in the process might lead to incorrect findings and i...
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Achieving the desired level of satisfaction for a decision- maker in any decision- making scenario is considered a challenging endeavor because minor modifications in the process might lead to incorrect findings and inaccurate decisions. In order to maximize the decision-maker's satisfaction, this paper proposes a Single-valued Neutrosophic Geometric programming model based on pentagonal fuzzy numbers. The decision-maker is typically assumed to be certain of the parameters, but in reality, this is not the case, hence the parameters are presented as neutrosophic fuzzy values. The decision-maker, with this strategy, is able to achieve varying levels of satisfaction and dissatisfaction for each constraint and even complete satisfaction for certain constraints. Here the decision maker aims to achieve the maximum level of satisfaction while maintaining the level of hesitation and minimizing dissatisfaction in order to retain an optimum solution. Furthermore, transforming the objective function into a constraint adds one more layer to the N-dimensional multi-parametrizes and. The advantages of this multi-parametrized proposed method over the existing ones are proven using numerical examples.
The course 'Software design in Java' is a 4 ects course on object-oriented programming in the first bachelor year of the bachelor/master in Engineering Technology, jointly organized by Hasselt University and K...
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We study the data-parallel language BUTF, inspired by the F UTHARK language for array programming. We give a translation of BUTF into a version of the jr-calculus with broadcasting and labeled names. The translation i...
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We study the data-parallel language BUTF, inspired by the F UTHARK language for array programming. We give a translation of BUTF into a version of the jr-calculus with broadcasting and labeled names. The translation is both complete and sound. Moreover, we propose a cost model by annotating translated BUTF processes. This is used for a complexity analysis of the translation.
Previous research has incorporated physiological data such as heart rate and footsteps to enrich K-12 students' STEM and computing learning experiences. This qualitative study piloted a series of lessons leveragin...
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ISBN:
(纸本)9798400704239
Previous research has incorporated physiological data such as heart rate and footsteps to enrich K-12 students' STEM and computing learning experiences. This qualitative study piloted a series of lessons leveraging a novel physiological computing environment with a small group of fifth-grade girls (n=5). The purpose of this study was to understand (1) how the physiological computing lesson activities promoted changes in the students' conceptual understanding of conditional logic and variables and their diverse perspectives in computing and (2) how the students approached problem-solving and what their visual attention looked like during physiological computing. We analyzed multiple sources of data, including students' artifacts, recorded classroom conversations, think-aloud verbalizations, and eye-tracking metrics data. Data analyses revealed that the girls demonstrated an improved understanding of the two computing concepts (i.e., variables and conditional logic), employed different problem-solving strategies, and encountered common challenges such as translating the task instruction to building code with the conditional block. Eye-tracking revealed that the students rarely attended to program output during their programming and debugging processes.
Despite widespread adoption of the K-12 computerscience Standards published by the computerscience Teachers Association (CSTA) in 2017, there remain few validated assessments for computerscience that researchers an...
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In this paper, the problem of phase retrieval is addressed. Its solution is based on the Lagrange programming neural network (LPNN), which is an analog neural computational technique for solving nonlinear constrained ...
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In this paper, the problem of phase retrieval is addressed. Its solution is based on the Lagrange programming neural network (LPNN), which is an analog neural computational technique for solving nonlinear constrained optimization problems according to the Lagrange multiplier theory. The local stability of the proposed algorithm is also investigated. Furthermore, we extend the LPNN based approach to more challenging array signal processing applications, namely, when multiple vector signals with full column rank or other constraints are required to be recovered from measured magnitudes. One of the key difficulties for these challenges is pairing the separately estimated parameters, while the parameters estimated by the extended method are automatically paired. The performance of the developed algorithms is demonstrated via computer simulations.
The recent prevalence of Large Language models (LLMs), e.g., GPT-3.5 and GPT-4, has brought about a new age of man-computer symbiosis, where LLMs are employed for a litany of creative, constructive, scientific, or oth...
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In programming teaching, teachers or teaching assistants often need to spend a lot of energy helping students solve the problems they face when doing programming. It will be helpful to provide students with valuable p...
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ISBN:
(纸本)9798350376975;9798350376968
In programming teaching, teachers or teaching assistants often need to spend a lot of energy helping students solve the problems they face when doing programming. It will be helpful to provide students with valuable programming feedback, such as information on faulty lines. However, most existing algorithms do not perform well on novice programs. Therefore, considering the background in programming teaching, we proposed a novel approach combining static analysis with dynamic detection by using the correct programs submitted by previous students and coverage information for the incorrect program. In particular, the core of the static analysis module is to locate specific faulty lines through syntax tree difference comparison, which includes matching similar programs, variable mapping and replacement, and fault localization based on abstract syntax tree differences. The core of the module on dynamic detection is to perform traditional Spectrum-based Fault Localization. To evaluate the effectiveness of our proposed approach, we conducted some empirical studies on 223 student-failure programs in the real world. The experimental results indicate that our approach outperforms other baselines regarding TOP-1 and TOP-3. Furthermore, we analyzed the performance of our method on different categories of programming problems as well as the effectiveness of the combination of static analysis and dynamic detection.
computerscience II is a subject in the 2nd semester of the Bachelor's and Systems Engineering, Electrical, Electronics, and Telecommunications courses. As part of the evaluation, four tasks are included in the co...
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ISBN:
(纸本)9798350394023;9798350394030
computerscience II is a subject in the 2nd semester of the Bachelor's and Systems Engineering, Electrical, Electronics, and Telecommunications courses. As part of the evaluation, four tasks are included in the course to be performed individually by each student. From the beginning of the course, the use of Artificial Intelligence tools was introduced in different class activities, particularly ChatGPT. In this work, the activities are described and the solutions to the tasks presented by the students are evaluated. The surveys conducted with the students regarding their experience with these tools are examined.
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