When students procrastinate on programming assignments, it can hinder the quality of their code and negatively impact their grades. In contrast, when students actively delay working on assignments to prepare to code (...
详细信息
ISBN:
(纸本)9798400704239
When students procrastinate on programming assignments, it can hinder the quality of their code and negatively impact their grades. In contrast, when students actively delay working on assignments to prepare to code (e.g., reading or seeking help), it can be an effective self-regulated learning (SRL) strategy beneficial to programming performance. However, distinguishing active delay from procrastination is methodologically challenging. To address this, we tracked what students did when they behaviorally delayed starting an assignment. Most students prepared to code by using multiple course resources across programming assignments. We found that many students delayed starting to code by seeking help in the Q&A platform, and this was beneficial to the quality of their code. Also, some pre-coding activities were related to behavioral delay in starting to code, but benefitted students' grades, and thus may indicate active delay, but not all pre-coding activities were beneficial. By considering pre-coding activities, we gain a comprehensive view of students' approach to coding in CS education.
The article is devoted to the formation of professional and special competencies of future information technology specialists in the field of programming. The authors of the article propose to study programming throug...
详细信息
This preliminary study investigates the impact of a collaborative guided inquiry learning (CGIL) approach on the retention and performance of underrepresented racial minority (URM) students in an Object-Oriented progr...
详细信息
ISBN:
(纸本)9798400704239
This preliminary study investigates the impact of a collaborative guided inquiry learning (CGIL) approach on the retention and performance of underrepresented racial minority (URM) students in an Object-Oriented programming course at a Hispanic-serving institution. The study showed that this teaching method significantly improved academic performance for both URM and non-URM students, with no notable differences in retention rates. Student surveys highlight the method's effectiveness in promoting communication and collaboration skills, which are the foundations of inclusion and diversity in the workplace. The results also show that it was fairly easy to replicate the positive learning experiences across multiple sections of a course. This approach can potentially increase retention, improve performance, and promote diversity within the computerscience discipline, contributing to a more inclusive and skilled workforce in the technology industry.
Understanding students' testing processes in a CS1 course is crucial in helping instructors of introductory courses determine the necessary content to teach. Prior work highlights the importance of teaching testin...
详细信息
ISBN:
(纸本)9798400705328
Understanding students' testing processes in a CS1 course is crucial in helping instructors of introductory courses determine the necessary content to teach. Prior work highlights the importance of teaching testing practices to students, as there is concern for students' testing abilities upon graduation of an university CS program. Given that testing is an implicit programming process, we aim to examine how students in CS1 go about testing their code in programming assignments. Because of the consistent research showing the achievement gap between students with and without prior experience in introductory classes, our analysis also aims to understand specific differences in testing processes between the two groups. Leveraging a dataset of over 300 students with over 50,000 snapshots of student code during their development process, we applied metrics related to incremental testing and determined the usage of diagnostic print statements and the usage of designing test cases beyond the given tests (in which we refer to as 'custom test cases'). A large majority of the students used neither diagnostic print statements nor custom test cases in their programming assignments. Additionally, the three testing practices we examined do not seem to significantly contribute to the achievement gap due to prior experience to students' success, suggesting a need for further investigation into which practices do account for that success.
In this study, we assess the efficacy of employing the ChatGPT language model to generate solutions for coding exercises within an undergraduate Java programming course. ChatGPT, a large-scale, deep learning-driven na...
详细信息
ISBN:
(纸本)9798400701382
In this study, we assess the efficacy of employing the ChatGPT language model to generate solutions for coding exercises within an undergraduate Java programming course. ChatGPT, a large-scale, deep learning-driven natural language processing model, is capable of producing programming code based on textual input. Our evaluation involves analyzing ChatGPT-generated solutions for 80 diverse programming exercises and comparing them to the correct solutions. Our findings indicate that ChatGPT accurately generates Java programming solutions, which are characterized by high readability and well-structured organization. Additionally, the model can produce alternative, memory-efficient solutions. However, as a natural language processing model, ChatGPT struggles with coding exercises containing non-textual descriptions or class files, leading to invalid solutions. In conclusion, ChatGPT holds potential as a valuable tool for students seeking to overcome programming challenges and explore alternative approaches to solving coding problems. By understanding its limitations, educators can design coding exercises that minimize the potential for misuse as a cheating aid while maintaining their validity as assessment tools.
LLMs trained in the understanding of programming syntax are now providing effective assistance to developers and are being used in programming education such as in generation of coding problem examples or providing co...
详细信息
ISBN:
(纸本)9783031630279;9783031630286
LLMs trained in the understanding of programming syntax are now providing effective assistance to developers and are being used in programming education such as in generation of coding problem examples or providing code explanations. A key aspect of programming education is understanding and dealing with error message. However, 'logical errors' in which the program operates against the programmer's intentions do not receive error messages from the compiler. In this study, building on existing research on programming errors, we first define the types of logical errors that can occur in programming in general. Based on the definition, we propose an effective approach for detecting logical errors with LLMs that makes use of relations among error types in the Chain-of-Thought and Tree-of-Thought prompts. The experimental results indicate that when such logical error descriptions in the prompt are used, the average classification performance is about 21% higher than the ones without them. We also conducted an experiment for exploiting the relations among errors in generating a new logical error dataset using LLMs. As there is very limited dataset for logical errors such benchmark dataset can be very useful for various programming related applications. We expect that our work can assist novice programmers in identifying the causes of code errors and correct them more effectively.
This paper describes a novel methodology for implementing allpass digital phase compensator (DPC) using the generalized linear-fractional programming (LFP) along with the regularization technique. The allpass DPC desi...
详细信息
ISBN:
(纸本)9798350381771;9798350381764
This paper describes a novel methodology for implementing allpass digital phase compensator (DPC) using the generalized linear-fractional programming (LFP) along with the regularization technique. The allpass DPC design is first stated as a generalized LFP problem, and then it is converted to a regularized minimization problem. This conversion changes the equality constraint in the generalized LFP to an inequality constraint and also adds an extra term to the objective function. The resulting problem reduces to a regularized minimization problem, which can be tackled by using linear programming (LP). That is, the regularized minimization problem reduces to an LP with only inequality design constraints. An allpass DPC example is used to demonstrate that solving the regularized LP yields an optimal solution. The design accuracy and stability issue are also revealed.
The CC2020 Report highlights the importance of transitioning from knowledge-based to competency-based CS education. Given that proficient programming is considered a foundational skill for CS majors, some researchers ...
详细信息
ISBN:
(纸本)9798400705311
The CC2020 Report highlights the importance of transitioning from knowledge-based to competency-based CS education. Given that proficient programming is considered a foundational skill for CS majors, some researchers have developed top-down qualitative frameworks for assessing programming competency. However, the lack of quantitative competency models makes it challenging to conduct competency-oriented assessments in CS courses, especially for introductory programming courses such as CS1. To address this challenge, our study tracks the learning activities of 209 students in a CS1 course, including 10 formative tests and 44590 code submissions. The five-channel learning sequences (score, engagement, code metrics, programming skills, coding style) are established to capture the knowledge, skill, and dispositions of the CS1 competency model for each student, with profiles in each channel characterized by five indicators: mean values, entropy, turbulence, proficiency, and resilience. This approach enables multi-dimensional competency assessment with visualization throughout the learning process, providing timely guidance for both teaching and learning. This work is a preliminary exploration in CS1 towards quantitative programming competency models in CS education via integrating multidimensional data, employing appropriate data granularity, and visualizing observable patterns.
With the growing demand for computational skills in the job market, it's imperative that lower secondary school students grasp basic programming concepts such as repetition, modularity, conditionals, and variables...
详细信息
ISBN:
(纸本)9798400706035
With the growing demand for computational skills in the job market, it's imperative that lower secondary school students grasp basic programming concepts such as repetition, modularity, conditionals, and variables. Yet, many students perceive computerscience as daunting and irrelevant. Physical computing offers a promising solution to this motivational gap. It enhances intrinsic motivation, self-efficacy, and positive attitudes towards technology. Moreover, they engage students who may not identify as typical programmers and foster essential computational thinking skills. This research investigates the efficacy of employing the same educational robot in different contexts, such as music, images, colors, and simple video games, while teaching basic programming concepts. We call this approach "multi-context physical computing" to emphasize the focus on the different application scenarios. We believe that this could benefit students for two reasons. Firstly, by presenting the same concept across different contexts, learners can better grasp the essence of the concept, disentangling it from extraneous contextual associations. Secondly, catering to individual interests by offering diverse contexts may enhance motivation, consequently fostering improved learning outcomes, as predicted by the expectancy-value theory. In order to assess the benefits of the multi-context approach on learning outcomes and motivation, we will compare it to a more traditional single-context approach centered on robot locomotion in a randomized controlled study.
暂无评论