This innovative practice paper presents an approach to make computerscience (CS) in general and programming in particular more approachable for college students. Introductory programming classes can be difficult for ...
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ISBN:
(纸本)9798350351507
This innovative practice paper presents an approach to make computerscience (CS) in general and programming in particular more approachable for college students. Introductory programming classes can be difficult for learners;especially those without any programming background. Beginners must learn a new way of thinking, made more difficult by issues learning syntax. It's especially hard for students who lack a strong mathematics background. Observations across 3 editions of a CS0 pre-intro-programming course show that students consistently overestimate difficulties, and, come away with a stronger motivation for studying programming in the future as well as considering computerscience (CS) and data science (DS) majors, minors, and certificates as options for future study after completion. A wider variety of students consider CS-adjacent college programs, and this can have an appreciable impact on the diversity of the student body entering CS/DS programs. We have found that long term success in CS/DS is predicted by strong motivational factors. While many high school students bring a strong motivation for pursuing CS/DS due to socioeconomic factors (exposure through people they know) and availability of coursework in high school;for other students, some may not have considered CS/DS as an option due to perceived difficulty as well as steep math requirements that function as barriers-to-entry. A CS0 pre-programming course like ours explicitly centers itself as 'coding-is-fun' and encourages creativity. Students engage strongly with and are motivated to put in extra outside-of-class work required for mastery of material. We have limited evidence due to the fact that the data we have is from our small liberal arts college, however, 2 key factors make our observations and analysis valuable: 1) being a Hispanic-Serving-Institution (HSI) and an Asian-American and Native-American Pacific-Islander Serving-Institution (AANAPISI) we have a diverse student body, and 2) we are
Optimization-based scheduling in the chemical industry is highly beneficial but also highly difficult due to its combinatorial complexity. Different modeling and optimization techniques exist, each with individual str...
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Optimization-based scheduling in the chemical industry is highly beneficial but also highly difficult due to its combinatorial complexity. Different modeling and optimization techniques exist, each with individual strengths. We propose Benders decomposition to integrate mixed-integer linear programming (MILP) and discrete-event simulation (DES) to solve flow shop scheduling problems with makespan minimization objective. The basic idea is to generate valid Benders cuts based on sensitivity information of the DES sub problem, which can be found in the critical paths of DES solutions. For scaled literature flow shops, our approach requires at least an order of magnitude fewer iterations than a genetic algorithm and provides optimality gap information. For a realworld case study, our approach finds good solutions very quickly, making it a powerful alternative to established methods. We conclude that the Benders-DES algorithm is a promising approach to combine rigorous MILP optimization capabilities with high-fidelity DES modeling capabilities.
Internship experiences allow students to authentically participate in industry while still obtaining mentorship and development opportunities. The Morehouse Center for Broadening Participation in Computing, in collabo...
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Much work has been done to give semantics to probabilistic programming languages. In recent years, most of the semantics used to reason about probabilistic programs fall in two categories: semantics based on Markov ke...
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ISBN:
(数字)9783031308291
ISBN:
(纸本)9783031308284;9783031308291
Much work has been done to give semantics to probabilistic programming languages. In recent years, most of the semantics used to reason about probabilistic programs fall in two categories: semantics based on Markov kernels and semantics based on linear operators. Both styles of semantics have found numerous applications in reasoning about probabilistic programs, but they each have their strengths and weaknesses. Though it is believed that there is a connection between them there are no languages that can handle both styles of programming. In this work we address these questions by defining a two-level calculus and its categorical semantics which makes it possible to program with both kinds of semantics. From the logical side of things we see this language as an alternative resource interpretation of linear logic, where the resource being kept track of is sampling instead of variable use.
Smart contracts are computer programs designed to automate legal agreements. They are usually developed in a high-level programming language, the most popular of which is Solidity. Every day, hundreds of thousands of ...
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INTRODUCTION: Even while studying programming languages is essential for science and technology education, some students, especially novices, may find it challenging. One reason might be that these pupils are unable t...
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INTRODUCTION: Even while studying programming languages is essential for science and technology education, some students, especially novices, may find it challenging. One reason might be that these pupils are unable to comprehend programming basics, notably the usage of selective and repeated structures (loops), which are too complex and abstract for them to ***: programming structured applications requires understanding the relationship between variable-operators and declarations, so a more intuitive and practical visualization technique is needed. In view of this, this article presents an augmented reality (AR) learning system using a DF-RA mobile application that offers visual representation and interactivity to help college students in entry-level computerscience-related majors learn to program structured applications using dynamic and interactive ***: In order to examine the influences of said Augmented Reality-enhanced system on student learning, an experiment will be carried out within the group with 34 university students. All students used both an augmented reality enhanced version and a conventional paper version (classic methodology with paper flowcharts).RESULTS: The expected results is that the augmented reality version through the DF-RA mobile application made students have a better learning efficiency than the traditional paper system. In addition, the system enhanced with Augmented Reality also made students have improved perceptions in terms of system usability, flow experience, and usage ***: Experimental findings were analyzed to demonstrate that the augmented reality learning system increases students' motivation to study structured programming fundamentals and their practical competence.
programming Languages are fundamental courses for computerscience students. C++ is one of these programming languages, and it is important because it is not only a procedure language but also it is an Object-Oriented...
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Identifying misconceptions in student programming solutions is an important step in evaluating their comprehension of fundamental programming concepts. While misconceptions are latent constructs that are hard to evalu...
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We compare software engineering education for traditional computerscience and software engineering degree programs with the needs of robotics software engineering, concluding that technical engineering degrees need t...
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We compare software engineering education for traditional computerscience and software engineering degree programs with the needs of robotics software engineering, concluding that technical engineering degrees need to emphasize social aspects of software engineering, group work, and weigh advantages and disadvantages between different solution options.
Many studies have shown the efficacy of pair programming for students learning to program. However, most of these studies have taken place in an in-person environment, where the driver and navigator are physically sha...
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ISBN:
(纸本)9781450394338
Many studies have shown the efficacy of pair programming for students learning to program. However, most of these studies have taken place in an in-person environment, where the driver and navigator are physically sharing a keyboard and screen and can communicate verbally and non-verbally. With the increase in online learning, especially during the COVID-19 pandemic. It is important to know whether these results generalize to an online environment. In this work, we develop a methodology to replicate existing pair programming research in a remote context. Students can fulfill the same driver and navigator roles and share access to a single IDE. However, communication is limited to video chat, and participants can never physically interact. This will allow us to replicate various studies, evaluating the efficacy, perceptions, impacts, and perceptions of solo vs. pair programming. An initial study of 116 students enrolled in an introduction to programming course validated our experimental setup and showed that pair programming positively impacted the completion and correctness of programming exercises in an online environment. With 67.3% of pair programming submissions passing at least one test case, vs. 55.3% in the solo programming condition, and 63.5% of pair programming submissions passing all test cases vs. 45.0% of solo submissions (p < 0.02). This work validates our experimental design and shows promise that future work will be able to replicate many additional pair-programming studies in an online environment.
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