Genetic programming hyperheuristic (GPHH) has recently become a promising methodology for large-scale dynamic path planning (LDPP) since it can produce reusable heuristics rather than disposable solutions. However, in...
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In large programming classes, it takes a significant effort from teachers to evaluate exercises and provide detailed feedback. In systems programming, test cases are not sufficient to assess exercises, since concurren...
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ISBN:
(纸本)9798400705328
In large programming classes, it takes a significant effort from teachers to evaluate exercises and provide detailed feedback. In systems programming, test cases are not sufficient to assess exercises, since concurrency and resource management bugs are difficult to reproduce. This paper presents an experience report on static analysis for the automatic evaluation of systems programming exercises. We design systems programming assignments with static analysis rules that are tailored for each assignment, to provide detailed and accurate feedback. Our evaluation shows that static analysis can identify a significant number of erroneous submissions missed by test cases.
GPU programming is a critical component in AI system courses, which is notoriously difficult to learn and teach, given its unique features such as massive parallelism and data movement across memory hierarchies. This ...
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ISBN:
(纸本)9798400705311
GPU programming is a critical component in AI system courses, which is notoriously difficult to learn and teach, given its unique features such as massive parallelism and data movement across memory hierarchies. This paper presents Triton-Viz, an innovative visualization toolkit that helps students learn GPU programming using Triton, one of the most widely used programming languages to develop AI applications. Triton-Viz offers an intuitive interface with interactive visualizations of GPU operations from multiple perspectives, including parallelism, memory access, and performance metrics. By integrating into educational materials, Triton-Viz enhances hands-on learning and improves comprehension of GPU programming concepts and AI algorithms in real applications, as demonstrated in a study conducted with computerscience students. The positive feedback from this study highlights the utility of Triton-Viz in educational settings and its potential to bridge the gap between the theoretical algorithm and practical implementations in AI courses.
The growing demand for skilled computer vision professionals requires effective educational approaches. This study explores a novel tool based on Virtual programming Language principles designed to enhance computer vi...
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The growing demand for skilled computer vision professionals requires effective educational approaches. This study explores a novel tool based on Virtual programming Language principles designed to enhance computer vision education, specifically in video coding. The tool leverages a user-friendly interface and a custom widget library for video exploration, enabling students to engage with video data manipulation, motion estimation simulations, and visualization of coding effects. A controlled experiment with computer vision students from a university master's program demonstrates that the tool significantly improves student motivation, knowledge acquisition, and overall learning outcomes. This study highlights the potential of such tools to revolutionize computer vision education, leading to better engagement, deeper understanding, and enhanced practical skills. Therefore, it paves the way for further exploration of similar tools in computer vision and other science, technology, engineering, and mathematics disciplines.
The effectiveness of ways of teaching in various disciplines including computerscience (CS) programming continues to be a debatable issue. In this study, we followed the Kirkpatrick training evaluation model to bette...
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ISBN:
(纸本)9783031485350;9783031485367
The effectiveness of ways of teaching in various disciplines including computerscience (CS) programming continues to be a debatable issue. In this study, we followed the Kirkpatrick training evaluation model to better understand how Explicit Instruction (EI) interventions in teaching computerprogramming to post-graduate CS students can be evaluated. This understanding can be fundamental in informing how improvements can be made in the future teaching of computerprogramming to create a better sense of quality and robustness. The aim of this study was threefold. Firstly, to provide an overview of the Kirkpatrick model. Secondly, to relate the four levels of this model to the teaching of computerprogramming. Thirdly, to evaluate the use of EI interventions as a teaching approach through the model. This study followed an integrated methodological approach where data was collected through asking questions (individual semi-structured interviews). Thematic analysis of the collected data revealed that our participants found a lot of value from the EI interventions, and hence appreciate them. Overall, the findings of this study are consistent with those of many researchers that EI is one of the effective teaching and learning strategies, not only in other disciplines, but in computerprogramming as well.
computerscience (CS) education at the university level is often challenging, particularly for students with no prior programming experience. To help scaffold students' CS learning, instructors often utilize syste...
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ISBN:
(纸本)9798400706004
computerscience (CS) education at the university level is often challenging, particularly for students with no prior programming experience. To help scaffold students' CS learning, instructors often utilize systems for automated assessment of programming assignments, where students can individually learn online using automatically generated feedback. However, despite the growing usage of these systems, learning outcomes are often mixed and not all students benefit equally from using these applications. In this study, we utilize Ordered Network Analysis (ONA) to examine data from a system for automated assessment of programming assignments and compare platform activity between novice students (N=110) achieving high (N=43) and low (N=67) scores on the final test of an introductory CS course. We identify and visualize differences in the activity patterns between the groups. High performing novice students tend to request feedback more often, while low performing students more often leave the assignment unsolved after experiencing an unsuccessful attempt. These findings show that Ordered Network Analysis can serve as a useful tool for understanding student behaviors, facilitating the design of targeted interventions that might support learners at key moments in their programming engagement towards task success.
In order to cultivate children's computational thinking, researchers have developed many excellent programming systems. Among them, the tangible programming systems combined with graphic output have been widely ac...
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In order to cultivate children's computational thinking, researchers have developed many excellent programming systems. Among them, the tangible programming systems combined with graphic output have been widely accepted because of the intuitive input method and diversified visual feedback. However, few of them support collaborative learning or programming. Little is known about children's experiences, emotional states and behaviours on collaborative programming. Motivated by this gap, we present a novel tangible and collaborative enabled programming system named Lighters, which designed for children aged 7-10 and had two types of collaboration modes (block-based and role-based). We conducted an user experiment with 24 children, and collected physiological (EDA), questionnaire, video recording and interview data for analysis. Based on our experiment results, Lighters are effective in helping children learn to program collaboratively. In addition, Lighters can mobilize children's positive emotions and enthusiasm to learn programming. Compared with block-based collaboration, role-based collaboration is more likely to stimulate children's emotional states and has a better effect on learning programming.
computerscience teaching standards for grades K-8 have been implemented in nearly all U.S. states, and the core subject area teachers (e.g., math, science, English, social studies) have been asked to integrate these ...
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computerscience teaching standards for grades K-8 have been implemented in nearly all U.S. states, and the core subject area teachers (e.g., math, science, English, social studies) have been asked to integrate these standards into their instruction. Thus, it is important that K-8 pre-service teachers of all subjects are both prepared and motivated to teach computerscience concepts-such as programming-upon entering the field. However, little is known about how pre-service teachers learn and retain programming knowledge or obtain and sustain their motivation related to programming. Maker-focused educational robotics activities have the potential to both reduce abstract cognitive load and work as motivational tools for STEM learning. The purpose of this study was to examine pre-service teachers' motivational persistence and retention of programming concepts after learning with educational robotics through maker-focused computerscience activities. Hands-on maker robotics programming activities were used to teach and motivate pre-service teachers. This quantitative study utilized repeated measures through pre-, post-, and 6-month follow-up surveys and tests. The findings indicated the pre-service teachers' programming comprehension gains exhibited on the posttest deteriorated substantially to near-baseline levels within 6 months of instruction. Conversely, pre-service teachers' motivation related to programming continued to rise after the instruction had concluded. Both the retention of comprehension of programming concepts and motivational persistence findings imply that educator preparation providers should integrate programming instruction throughout their pre-service teacher curricula and support curricular initiatives that call for the integration of computerscience instruction across pre-service teacher methods courses to reinforce computerscience learning.
Research on pair programming (PP) in education have shown a number of positive outcomes for learners, and especially novice programmers, such as enhanced learning, greater confidence in work quality, higher problem so...
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ISBN:
(纸本)9798400706004
Research on pair programming (PP) in education have shown a number of positive outcomes for learners, and especially novice programmers, such as enhanced learning, greater confidence in work quality, higher problem solving skills or enhanced interaction skills, and promotes collaborative learning. Due to these diverse advantages, pair programming in education currently follows a growing curve. Also, blended learning approaches are becoming more and more popular in education, including when learners have to learn programming. As a consequence, distributed pair programming (DPP) can be considered as a good solution to support pair programming in hybrid learning scenarios. A large number of tools from both the research community and the major integrated development environment (IDE) editors tried to study and implement DPP in their tools. However, our review of literature shows that none of them meet the requirements for delivering effective pair programming activities to novice programmers in blended learning scenarios. Based on these findings, the paper introduces a new DPP application especially designed for novice programmers. It integrates, based on some requirements identified from previous research, several features dedicated to DPP as well as other capabilities supporting extensive data collection and learning analytics. The tool has been experimented in authentic learning settings in higher education with 82 students, both in PP and DPP conditions. The experiment showed no evidence of a difference between PP and DPP on the students' perceived usability of the application, as well as on the quality of their productions.
Contribution: This study evaluates the generalizability of previously identified perceptions among engineering students of assessments in introductory programming (CS1). The students' perceptions of their instruct...
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Contribution: This study evaluates the generalizability of previously identified perceptions among engineering students of assessments in introductory programming (CS1). The students' perceptions of their instructors' and teaching assistants' (TAs) roles in these assessments are also studied, and differences based on prior programming experience, gender, and course ***: Basic programming skills are desirable also for students who are not majoring in computerscience (CS). Students' experience of assessments has not been fully *** Questions: 1) How do engineering students experience the assessment (lab assignments, midterm exam, and project) in their CS1 courses? 2) What are the students' perceptions of the TAs and instructors in relation to these assessment situations? 3) What significant differences can be found based on students' prior experience in programming, gender, and course?Methodology: Previously identified themes from an interview study worked as a framework for the formulation of 25 statements used in a survey among 137 students in six CS1 courses (second part of a mixed-method study). Descriptive statistics, Mann-Whitney U Test, and Kruskal-Wallis tests with Bonferroni corrections, were used to analyze the ***: Laboratory assignments were experienced as an opportunity to learn while the exams were viewed as predictable. The projects were perceived as authentic, although varying in difficulty, and as a huge leap from the lab assignments. Students perceived the instructors to put their touch on the course but viewed their TAs as carrying out the assessments, and experienced variations between TAs. Female students experienced these variations to a larger extent and perceived received feedback as less useful.
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