Despite high scores and abilities, girls lose interest in science and math throughout middle school. According to the Bureau of Labor Statistics, jobs in the computerscience research field will grow 19% by 2026; howe...
Despite high scores and abilities, girls lose interest in science and math throughout middle school. According to the Bureau of Labor Statistics, jobs in the computerscience research field will grow 19% by 2026; however, only 18% of the bachelor's degrees in computerscience are earned by women in the United States (***, 2021). New technology and inventions are being created without the benefit of more diverse perspectives and input from females. There is a need to engage girls and maintain their interest throughout middle school and beyond. Additional research needs to be conducted about the impact and best practices used during out-of-school time programs to encourage and motivate girls to stay engaged in STEM, including computerprogramming (Koch, 2014). This study investigated the relationship between middle school girls' interest in computerprogramming and the opportunities to collaborate, solve problems, and use their creativity while participating in computerprogramming activities led by female role models during the 4-H Girls Tech Challenge, an informal education program. Research questions are the following: 1) In what ways did the 4-H Girls Tech Challenge experience, which included components of problem solving, collaboration, creativity and female role models, affect the attitudes of middle school girls towards computerprogramming? 2) To what extent did the 4-H Girls Tech Challenge experience affect the attitude of middle school girls towards potentially pursuing careers related to computerscience and technology? Evidenced by other studies, experiences in which collaboration, problem solving, and creativity are present have been shown to increase knowledge about computerprogramming and engagement in STEM (Cooper & Heaverlo, 2013; Wu-Rorrer, 2019; Hayden et al., 2011). A qualitative study employing interviews with previous participants was utilized to determine how the components of collaboration, problem solving, and creativity of th
As AI-powered chatbots, notably ChatGPT, gain widespread popularity, their integration into academic settings raises concerns about preserving academic integrity. Students increasingly employ these chatbots to generat...
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Much debate surrounds the choice of programming language for teaching computerscience. Our institution's replacement of a visual programming language (RAPTOR) with a textual programming language (Python) provided...
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ISBN:
(纸本)9781450394314
Much debate surrounds the choice of programming language for teaching computerscience. Our institution's replacement of a visual programming language (RAPTOR) with a textual programming language (Python) provided a novel opportunity to explore the impacts of the programming language on students' learning and perception of programming. We conducted a randomized comparative study that involved 1083 students who took our introductory computing course in the 2019-2020 academic year. A unique aspect of our work stems from our course being a general education requirement;thus, our study includes students with a wide variety of backgrounds and majors. This report presents a comparison of student performance in each version of the course, including the impact of the programming language on underrepresented groups, and provides a summary of student feedback. Our results show that students in our introductory course performed similarly overall, but overwhelmingly perceived Python to be more valuable.
Task planning for autonomous agents has typically been done using deep learning models and simulation- based reinforcement learning. This research proposes combining inductive learning techniques with goal-directed an...
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Task planning for autonomous agents has typically been done using deep learning models and simulation- based reinforcement learning. This research proposes combining inductive learning techniques with goal-directed answer set programming to increase the explainability and reliability of systems for task breakdown and completion. Preliminary research has led to the creation of a Python harness that utilizes s(CASP) to solve task problems in a computationally efficient way. Although this research is in the early stages, we are exploring solutions to complex problems in simulated task completion.
The development of constraint solvers simplified automated reasoning about programs and shifted the engineering burden to implementing symbolic compilation tools that translate programs into efficiently solvable const...
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The development of constraint solvers simplified automated reasoning about programs and shifted the engineering burden to implementing symbolic compilation tools that translate programs into efficiently solvable constraints. We describe Grisette, a reusable symbolic evaluation framework for implementing domain-specific symbolic compilers. Grisette evaluates all execution paths and merges their states into a normal form that avoids making guards mutually exclusive. This ordered-guards representation reduces the constraint size 5-fold and the solving time more than 2-fold. Grisette is designed entirely as a library, which sidesteps the complications of lifting the host language into the symbolic domain. Grisette is purely functional, enabling memoization of symbolic compilation as well as monadic integration with host libraries. Grisette is statically typed, which allows catching programming errors at compile time rather than delaying their detection to the constraint solver. We implemented Grisette in Haskell and evaluated it on benchmarks that stress both the symbolic evaluation and constraint solving.
In the Czech version of the Bebras Challenge, programming tasks in which a programming code is built from blocks are used alongside traditional contest tasks. This paper deals with the comparison of these programming ...
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ISBN:
(纸本)9783031734731;9783031734748
In the Czech version of the Bebras Challenge, programming tasks in which a programming code is built from blocks are used alongside traditional contest tasks. This paper deals with the comparison of these programming tasks with other informatics tasks in terms of theworkload of their solvers. programming tasks can strongly attract the contestants' attention. The aim of the paper is to find out to what extent pupils pay attention to programming tasks at the expense of other tasks and how this differs for successful and unsuccessful contestants. We prepared national round tests in which there were typically two programming tasks and ten other tasks in each age category. We conducted quantitative research with a total of 184,949 respondents from the 2023 contest. We discovered that pupils spend more time on programming tasks than on the other tasks. When designing tests that include programming tasks, it is necessary to take this into account, and thus either limit the number of tasks, increase the test time, or include less challenging tasks. Our research on programming tasks revealed that, for most age categories, successful pupils ran different versions of their solution fewer times than unsuccessful ones. We also discovered that successful solvers spent more time on the task than unsuccessful solvers. The youngest pupils were the outliers in these findings. Our paper contributes to the understanding of the extent to which it is a good idea to include programming tasks in informatics contests like the Bebras Challenge.
computerscience and information technology students at Taif University develop programming skills through practical experiments. Traditional programming laboratories face challenges due to a growing number of student...
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Enhancing school mathematics with Computational Thinking (CT) and programming might be beneficial to student learning in both the fields of computing and mathematics. This doctoral research project aims to explore and...
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ISBN:
(纸本)9798400710384
Enhancing school mathematics with Computational Thinking (CT) and programming might be beneficial to student learning in both the fields of computing and mathematics. This doctoral research project aims to explore and enhance the integration of programming and CT within K-12 mathematics education. Through a two-month intervention study in a Norwegian lower secondary school, a highly modified PRIMM (Predict, Run, Investigate, Modify, and Make) framework was employed to teach programming within a lower secondary mathematics course.
Various programming languages have been used in education during the last 50 years. In this study, we investigate their popularity measured with the number of dedicated scientific publications. While some of the findi...
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ISBN:
(纸本)9781450394338
Various programming languages have been used in education during the last 50 years. In this study, we investigate their popularity measured with the number of dedicated scientific publications. While some of the findings could be expected, some are far from predictable. Also interesting are the indicated differences between the presented results and the general popularity of languages.
Aiming at solving non-convex nonlinear programming efficiently and accurately, a swarm exploring varying parameter recurrent neural network (SE-VPRNN) method is proposed in this article. First, the local optimal solut...
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Aiming at solving non-convex nonlinear programming efficiently and accurately, a swarm exploring varying parameter recurrent neural network (SE-VPRNN) method is proposed in this article. First, the local optimal solutions are searched accurately by the proposed varying parameter recurrent neural network. After each network converges to the local optimal solutions, information is exchanged through a particle swarm optimization (PSO) framework to update the velocities and positions. The neural network searches for the local optimal solutions again from the updated position until all the neural networks are searched to the same local optimal solution. For improving the global searching ability, wavelet mutation is applied to increase the diversity of particles. computer simulations show that the proposed method can solve the non-convex nonlinear programming effectively. Compared with three existing algorithms, the proposed method has advantages in accuracy and convergence time.
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