This study investigated patterns in the development of computational thinking and programming expertise in the context of the Exploring computerscience (ECS) program, a high school introductory CS course and professi...
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ISBN:
(纸本)9781450358903
This study investigated patterns in the development of computational thinking and programming expertise in the context of the Exploring computerscience (ECS) program, a high school introductory CS course and professional development program designed to foster deep engagement through equitable inquiry around CS concepts. Prior research on programming expertise has identified three general areas of development program comprehension, program planning, and program generation. The pedagogical practices in ECS are consistent with problem solving approaches that support the development of programming expertise. The study took place in a large urban district during the 2016-17 school year with 28 ECS teachers and 1,931 students. A validated external assessment was used to measure the development of programming expertise. The results indicate that there were medium-sized, statistically significant increases from pretest to posttest, and there were no statistically significant differences by gender or race/ethnicity. After controlling for prior academic achievement, performance in the ECS course correlated with performance on the posttest. With respect to specific programming concepts, the results also provide evidence on the progression of the development of programming expertise. Students seem to develop comprehension and planning expertise prior to expertise in program generation. In addition, students seem to develop expertise with concrete tasks prior to abstract tasks.
The following article presents and corroborates an outcome space branch-and-bound algorithm for solving the general linear multiplicative programming problem (GLMPP). In this new algorithm, GLMPP is transformed into i...
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The following article presents and corroborates an outcome space branch-and-bound algorithm for solving the general linear multiplicative programming problem (GLMPP). In this new algorithm, GLMPP is transformed into its equivalent problem by introducing auxiliary variables. To compute the tight upper bound for the optimal value of GLMPP, the linear relaxation programming problem is assembled by using bound and hull linear approximations. Furthermore, the global convergence and computational complexity of the algorithm are demonstrated. Finally, the soundness and advantage of the proposed algorithm are validated by solving a demonstrative linear multiplicative problem.
The reach of technology stretches across a wide variety of domains: from the health industry to entertainment and gaming. Software programming undoubtedly plays a major role in modern technology. Therefore, computer s...
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ISBN:
(纸本)9789819754403;9789819754410
The reach of technology stretches across a wide variety of domains: from the health industry to entertainment and gaming. Software programming undoubtedly plays a major role in modern technology. Therefore, computerscience and programming education is of the utmost importance. In our research, we aim to investigate the best approaches and languages to be used to introduce programming to students and others wishing to learn to program. Indeed, there are numerous approaches to learning programming and lots of existing research regarding these approaches. There are also numerous programming languages and types of audiences. We highlight various methods that can be used to teach programming, and how those approaches can best be matched to different programming languages and audiences. We build upon existing research to reach conclusions, and we conduct our own survey that involves computerscience students, computerscience teachers, and software development professionals. Our goal is not to promote a certain approach or to promote a particular programming language. Rather, we find correlations and provide recommendations regarding which languages are most suitable for different approaches and audiences.
With the rising emphasis on computerscience (CS) education, many states, school districts, and schools have grappled with how to address computing in the K-12 curriculum. While some approaches dedicate classroom time...
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ISBN:
(纸本)9798400704239
With the rising emphasis on computerscience (CS) education, many states, school districts, and schools have grappled with how to address computing in the K-12 curriculum. While some approaches dedicate classroom time to specific CS topics, others are attempting to infuse computing curriculum into other subjects like math and science. Preparing educators without prior CS experience to teach this integrated content is challenging. In this paper, we share programming-integrated mathematics learning (PML) modules that we developed to support teachers in learning to use programming in mathematics classrooms through argumentation. To test the effectiveness of the modules, we implemented them in a mathematics content course for elementary education majors and a mathematics pathway course for non-STEM majors. We assessed both courses as study contexts for evaluating potential PML modules to enhance teachers' knowledge and students' learning outcomes in mathematics and computerprogramming. This paper focuses on student-written reflections as data to investigate how education and non-STEM majors describe their learning through the PML modules. According to our analysis, the study participants found the PML modules to be useful in enhancing their understanding of mathematical concepts. They also described the value of learning programming in mathematics classrooms through argumentation, learning different perspectives, and helping each other understand. However, most of our student participants displayed a relatively low level of confidence in their programming abilities, specifically regarding the creation of text-based programs. Future study is needed to explore how to increase the programming self-efficacy while students learn mathematics through programming.
The advent of Large Language Models (LLMs) has created multiple challenges for the computerscience Education Community. This research project aims at integrating LLMs into Object-Oriented programming courses, by gene...
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ISBN:
(纸本)9798400706035
The advent of Large Language Models (LLMs) has created multiple challenges for the computerscience Education Community. This research project aims at integrating LLMs into Object-Oriented programming courses, by generating and evaluating new teaching methodologies and tools suitable for this paradigm's specificities.
Small, auto-gradable programming exercises provide a useful tool with which to assess students' programming skills in introductory computerscience. To reduce the time needed to produce programming exercises of si...
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ISBN:
(纸本)9798400706004
Small, auto-gradable programming exercises provide a useful tool with which to assess students' programming skills in introductory computerscience. To reduce the time needed to produce programming exercises of similar difficulty, previous research has applied a permutation strategy to existing questions. Prior work has left several open questions: is prior exposure to a question typically indicative of higher student performance? Are observed changes in difficulty due to the specific surface feature permutations applied? How is student performance impacted by the first version of a question to which they may be exposed? In this work, we pursue this permutation strategy in multiple semesters of an introductory Python course to investigate these open questions. We use linear regression models to tease out the impacts of different surface feature changes and usage conditions. Our analysis finds similar tendencies as in prior work: question versions available in study materials tend to have 5 - 11 percentage point higher scores than novel permutations and more "substantial" surface feature changes tend to produce harder questions. Our results suggest this last finding is sensitive to how evenly permutations are applied across existing questions, as the precise impact of individual permutations changes between semesters.
Beginner programmers can develop an intuitive understanding of programming by leveraging the motivating field of multimedia to visually inspect outputs and experiment with different ways to solve problems. This paper ...
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ISBN:
(纸本)9798400706035
Beginner programmers can develop an intuitive understanding of programming by leveraging the motivating field of multimedia to visually inspect outputs and experiment with different ways to solve problems. This paper presents MediaLib, a Python library designed to facilitate multimedia programming and lessen the cognitive load associated with programming for novice programmers. In addition, we designed an official MediaLib website which contains the library itself, two tutorials, and clear documentation. The tutorial clearly presents the learning objectives of each lesson and contains exercises related to MediaLib. We designed these exercises to help students gain knowledge incrementally, without requiring in-depth maths knowledge.
With the continued development of information technology and increased global cultural exchanges, translation has gained significant attention. Traditional manual translation relies heavily on dictionaries or personal...
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With the continued development of information technology and increased global cultural exchanges, translation has gained significant attention. Traditional manual translation relies heavily on dictionaries or personal experience, translating word by word. While this method ensures high translation quality, it is often too slow to meet the demands of today's fast-paced environment. computer-assisted translation (CAT) addresses the issue of slow translation speed;however, the quality of CAT translations still requires rigorous evaluation. This study aims to answer the following questions: How do CAT systems that use automated programming fare compared to more conventional methods of human translation when translating English vocabulary? (2) How can CAT systems be improved to handle difficult English words, specialised terminology, and semantic subtleties? The working premise is that CAT systems that use automated programming techniques will outperform traditional methods in terms of translation accuracy. English vocabulary plays a crucial role in translation, as words can have different meanings depending on the context. CAT systems improve their translation accuracy by utilising specific automated programs and building a translation corpus through translation memory technology. This study compares the accuracy of English vocabulary translations produced by CAT based on automatic programming with those produced by traditional manual translation. Experimental results demonstrate that CAT based on automatic programming is 8% more accurate than traditional manual translation when dealing with complex English vocabulary sentences, professional jargon, English acronyms, and semantic nuances. Consequently, compared to conventional human translation, CAT can enhance the accuracy of English vocabulary translation, making it a valuable tool in the translation industry.
programming courses can be challenging for first year university students, especially for those without prior coding experience. Students initially struggle with code syntax, but as more advanced topics are introduced...
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ISBN:
(纸本)9798400706004
programming courses can be challenging for first year university students, especially for those without prior coding experience. Students initially struggle with code syntax, but as more advanced topics are introduced across a semester, the difficulty in learning to program shifts to learning computational thinking (e.g., debugging strategies). This study examined the relationships between students' rate of programming errors and their grades on two exams. Using an online integrated development environment, data were collected from 280 students in a Java programming course. The course had two parts. The first focused on introductory procedural programming and culminated with exam 1, while the second part covered more complex topics and object-oriented programming and ended with exam 2. To measure students' programming abilities, 51095 code snapshots were collected from students while they completed assignments that were autograded based on unit tests. Compiler and runtime errors were extracted from the snapshots, and three measures - Error Count, Error Quotient and Repeated Error Density - were explored to identify the best measure explaining variability in exam grades. Models utilizing Error Quotient outperformed the models using the other two measures, in terms of the explained variability in grades and Bayesian Information Criterion. Compiler errors were significant predictors of exam 1 grades but not exam 2 grades;only runtime errors significantly predicted exam 2 grades. The findings indicate that leveraging Error Quotient with multiple error types (compiler and runtime) may be a better measure of students' introductory programming abilities, though still not explaining most of the observed variability.
Foundation models(FMs) [1] have revolutionized software development and become the core components of large software systems. This paradigm shift, however, demands fundamental re-imagining of software engineering theo...
Foundation models(FMs) [1] have revolutionized software development and become the core components of large software systems. This paradigm shift, however, demands fundamental re-imagining of software engineering theories and methodologies [2]. Instead of replacing existing software modules implemented by symbolic logic, incorporating FMs' capabilities to build software systems requires entirely new modules that leverage the unique capabilities of ***, while FMs excel at handling uncertainty, recognizing patterns, and processing unstructured data, we need new engineering theories that support the paradigm shift from explicitly programming and maintaining user-defined symbolic logic to creating rich, expressive requirements that FMs can accurately perceive and implement.
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