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...
详细信息
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.
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...
详细信息
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.
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...
详细信息
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.
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...
详细信息
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.
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...
详细信息
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...
详细信息
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...
详细信息
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.
Current programming practices rely heavily on the use of APIs (Application programming Interfaces) and frameworks. However, APIs can be challenging to learn and use. Existing research focuses on specific barriers prog...
详细信息
Current programming practices rely heavily on the use of APIs (Application programming Interfaces) and frameworks. However, APIs can be challenging to learn and use. Existing research focuses on specific barriers programmers encounter while learning APIs, providing a fragmented understanding of the process. In this paper, we analyze the holistic process of twelve programmers learning the React JS API using sensemaking theory as a guiding framework for qualitative coding of behaviors. We describe how these API learners moved through sensemaking stages and how they interacted with information during each sensemaking stage. Our results highlighted programmers' tendency to seek understanding when they encountered problems.
Integer linear programming (ILP) is a fundamental research paradigm in algorithms. Many modern algorithms to solve structured ILPs efficiently follow one of two main approaches. The first one is to prove a small upper...
详细信息
ISBN:
(纸本)9783031521126;9783031521133
Integer linear programming (ILP) is a fundamental research paradigm in algorithms. Many modern algorithms to solve structured ILPs efficiently follow one of two main approaches. The first one is to prove a small upper bound on the support size of the ILP, which is the number of variables taking non-zero values in an optimal solution, and then to only search for ILP solutions of small support. The second one is to apply an augmentation algorithm using Graver elements to an initial feasible solution obtained from a small proximity bound for the ILP, which is the distance between an optimal solution of the ILP and that of its LP relaxation. Our first contribution are new lower bounds for the support size of ILPs. Namely, we discover a connection between support sizes and an old number-theoretic conjecture by Erdos on subset-sum distinct sets. Further, we improve the previously best lower bounds on the support size of ILPs with m constraints and largest absolute value Delta of any coefficient in the constraint matrix from Omega(mlog(Delta)) to Omega(mlog(root m Delta)). This new lower bound asymptotically matches the best-known upper bounds. Our second contribution are new bounds on the size of Graver elements and on the proximity for ILPs. We first show nearly tight lower and upper bounds for g(1)(A), the largest 1-norm parallel to g parallel to(1) of any Graver basis element g of the constraint matrix A. Then we show that the proximity of any ILP in standard form with support size s is bounded by s center dot c(1)(A), where c(1)(A) is the largest 1-norm parallel to c parallel to(1) of any circuit c of A. This improves over the known proximity bound of n center dot g(1)(A), as s and c(1)(A) can be much smaller than n and g(1)(A), respectively.
Contribution: This study demonstrates the efficacy of an ecological belonging intervention in a first-year engineering programming course to increase belonging for Black, Latinx, and Indigenous (BLI) students and clos...
详细信息
Contribution: This study demonstrates the efficacy of an ecological belonging intervention in a first-year engineering programming course to increase belonging for Black, Latinx, and Indigenous (BLI) students and close academic equity ***: Introductory programming courses are often challenging for students and can shape belonging in engineering. BLI students may be particularly susceptible to interpreting struggle as confirmation that they do not belong in predominantly white spaces, which can negatively influence academic *** Questions: "What are the effects of an ecological belonging intervention on BLI students' feelings of belonging within their first-year engineering course?" and "What are the effects of an ecological belonging intervention on BLI students' performance on a weekly computerprogramming assignment?"Methodology: The intervention was implemented with 691 students in Spring 2022 and was designed to normalize the struggle to address threats to belonging and close equity gaps in BLI students' academic performance. A pre-/post-semester survey measuring belonging was analyzed using repeated-measures ANOVA, and pass/fail academic records were analyzed using logistic ***: The targeted belonging intervention for BLI engineering students can help to address issues of isolation and academic confidence that negatively impact individuals' sense of belonging and academic performance.
暂无评论