Digital literacy is considered to be crucial for social and professional participation. Hence, several projects have been launched in school, as well as extracurricular activities to promote digital literacy in middle...
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Digital literacy is considered to be crucial for social and professional participation. Hence, several projects have been launched in school, as well as extracurricular activities to promote digital literacy in middle school. They aim, among other things, to increase interest in the so-called STEM subjects (science, technology, engineering, and mathematics), which include computerscience. Interest in a topic is described in the literature as a crucial factor for learning success and career choice. Still, there is a potential for current research on the expression and distribution of interest in computerscience. Therefore, this study aims to address this research gap by examining interest in computerscience. The exploration of interest is expanded to include gender aspects and pupils' dispositions. Given the significantly lower number of women studying in STEM fields, there is a particular focus on an improved understanding of the interests of female pupils as early as middle school. Moreover, the literature suggests that pupils' dispositions should also be considered in instructional design to achieve stable interest. In this context, the following two dispositions shine out in literature and are therefore focused on in this article: first, interest in contextual, people-related topics (mainly found among women), and second, interest in factual, object-related topics (mainly found among men). In summary, this study investigates how pupils' interest in computerscience is expressed before and after a programming intervention and how it is distributed across gender and dispositions. Therefore, the study surveyed 8th-grade pupils (N = 114) about their preferences and assessed their interest in computerscience before and after an intervention with unplugged materials and playful robots. Results show that all groups of pupils find computerscience interesting, and the intervention slightly increased interest. Girls show a marginally lower interest in computerscience
Automatic test paper design is critical in education to reduce workloads for educators and facilitate an efficient teaching process. However, current designs fail to satisfy the realistic teaching requirements of educ...
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Code quality is an important aspect of programming, as quality code is easier to maintain, and code maintenance makes up the majority of software cost. For that reason, code quality should be emphasized in programming...
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ISBN:
(纸本)9798400706004
Code quality is an important aspect of programming, as quality code is easier to maintain, and code maintenance makes up the majority of software cost. For that reason, code quality should be emphasized in programming education. Previous work has identified many code quality defects commonly made by students. However, the current state lacks a clear organization and prioritization of these defects. In this paper, we propose an organization framework for code quality defects, presenting a catalog that describes 80 defects, with a specific focus on defects frequently encountered in code by novice programmers. To determine which defects are worth pointing out to students, we conducted a survey among 72 educators, who rated the priority with which each defect should be reported to a student. These presented results serve multiple purposes: they facilitate comparison across various research studies, support the advancement of software tools, and offer inspiration for programming education.
Novice programmers can greatly improve their understanding of challenging programming concepts by studying worked examples that demonstrate the implementation of these concepts. Despite the extensive repositories of e...
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ISBN:
(纸本)9798400705328
Novice programmers can greatly improve their understanding of challenging programming concepts by studying worked examples that demonstrate the implementation of these concepts. Despite the extensive repositories of effective worked examples created by CS education experts, a key challenge remains: identifying the most relevant worked example for a given programming problem and the specific difficulties a student faces solving the problem. Previous studies have explored similar example recommendation approaches. Our research introduces a novel method by utilizing deep learning code representation models to generate code vectors, capturing both syntactic and semantic similarities among programming examples. Driven by the need to provide relevant and personalized examples to programming students, our approach emphasizes similarity assessment and clustering techniques to identify similar code problems, examples, and challenges. This method aims to deliver more accurate and contextually relevant recommendations based on individual learning needs. Providing tailored support to students in real-time facilitates better problem-solving strategies and enhances students' learning experiences, contributing to the advancement of programming education.
In this paper, we propose hardware acceleration to improve a performance of scripting programming languages for embedded developments. Scripting programming languages enable more efficient software developments and sc...
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Background: and Context: computerprogramming is increasingly being taught to young children worldwide. Quality programming curricula are needed to enable students to explore computerscience concepts and develop a po...
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Background: and Context: computerprogramming is increasingly being taught to young children worldwide. Quality programming curricula are needed to enable students to explore computerscience concepts and develop a positive attitude towards programming. However, few studies have been conducted on the available curricula for young learners. Objective: This study aims to provide an evidence-based, public, and free computerscience curriculum for early childhood education by investigating the efficacy of the CAL-ScratchJr curriculum, among second graders. Method: A cluster-randomized controlled trial involving 11 schools and 21 second-grade classrooms was conducted to examine the impact of the 24-lesson curriculum on students' coding proficiency and computational thinking. Findings: The results indicated that the CAL-ScratchJr curriculum intervention had a medium positive effect on second graders' coding skills, but no significant impact on computational thinking. Implications: Results caution against incorporating disconnected abstract computational thinking practices in education. The features of the curriculum were discussed.
Acquiring programming skills is daunting for most learners and is even more challenging in heavily attended courses. This complexity also makes it difficult to offer personalized feedback within the time constraints o...
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Acquiring programming skills is daunting for most learners and is even more challenging in heavily attended courses. This complexity also makes it difficult to offer personalized feedback within the time constraints of instructors. This study offers an approach to predict programming weaknesses in each learner to provide appropriate learning resources based on machine learning. The machine learning models selected for training and testing and then compared are and Decision Trees. During the comparison based on the features of prior knowledge, time spent, and GPA, Logistic Regression was found to be the most accurate. Using this model, the programming weaknesses of each learner are identified so that personalized feedback can be given. The paper further describes a controlled experiment to evaluate the effectiveness of the personalized programming feedback generated based on the model. The findings indicate that learners receiving personalized programming feedback achieve superior learning outcomes than those receiving traditional feedback. The implications of these findings are explored further, and a direction for future research is suggested.
Instructors in computerscience classes often need to decide between having students use real programming tools to provide practical experience and presenting them with simpler educational interfaces to reduce their c...
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ISBN:
(纸本)9783031723148;9783031723155
Instructors in computerscience classes often need to decide between having students use real programming tools to provide practical experience and presenting them with simpler educational interfaces to reduce their cognitive load. Our work investigates the trade-offs between these approaches, by comparing student learning from two offerings of an introductory Python class across several community colleges in the U.S. In the first offering (N = 219), students used a real IDE (Visual Studio Code) throughout the entire course. In the second offering (N = 166), students used a simplified in-browser code editor, with no setup, for the first three modules and transitioned to Visual Studio Code in the subsequent modules. Our results showed that the second offering led to better learning than the first offering in the first three modules with the in-browser code editor. Moreover, students in both offerings performed similarly in a subsequent module in which they performed local development with Visual Studio Code, suggesting that the ability to use a real IDE was not harmed by the initial use of the in-browser code editor. In addition, we found that students in both offerings improved in their levels of self-efficacy with the course's learning objectives at the end of the class. Finally, we identified that the revisions made in the second offering benefited full-time students more than part-time students. We conclude with a discussion of the trade-offs between employing realistic programming tools and simplified coding environments, as well as suggestions for making introductory computerscience classes more effective and accessible.
Since 2021 the proliferation of generative artificial intelligence tools, notably ChatGPT, has experienced considerable diffusion, particularly within the context of higher education institutions. Both lecturers and s...
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ISBN:
(纸本)9783031832093;9783031832109
Since 2021 the proliferation of generative artificial intelligence tools, notably ChatGPT, has experienced considerable diffusion, particularly within the context of higher education institutions. Both lecturers and students have embraced the use of ChatGPT to support academic and student activities. This study examines the influence of ChatGPT on the teaching and learning of programming from the perspective of lecturers and students. Using the Faculty of computerscience at the Technical University of Manabi as the case study, semi-structured interviews were conducted with students from introductory, intermediate, and advanced programming courses, as well as with lecturers teaching programming subjects, exploring dimensions of usability, user experience, benefits, challenges, and ethical implications. Findings show that ChatGPT has the potential to enhance understanding of concepts and practical problem-solving in programming. However, it may also foster technological dependency and dishonest academic practices if not properly monitored and guided. The implications of this study are both theoretical and practical, as it presents evidence concerning the students' ability to discern accuracy of answers provided by ChatGPT, while providing understanding into how ChatGPT influences the academic development of programming in university courses. This can serve as a basis for designing teaching strategies and educational policies in higher education institutions.
programming nowadays has become an important tool in various scientific fields, not only in terms of software engineering but also for knowledge acquisition. In this regard, we analyze epistemic programming as an inte...
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ISBN:
(纸本)9798400704239
programming nowadays has become an important tool in various scientific fields, not only in terms of software engineering but also for knowledge acquisition. In this regard, we analyze epistemic programming as an interdisciplinary, cognitive perspective on programming, enabling programmers to gain insights into individual interests. As a first step towards implementing epistemic programming in computing education, we assess, whether novice programmers can utilize epistemic programming as a means of gaining insights and exploring their interests with the help of a worked example. Therefore, we report on findings from a study, analyzing eye-tracking data, screen recordings, and transcripts from retrospective think-aloud interviews. The results indicate that the participants were able to engage in a data-driven epistemic programming process and to gain individual insights. They used the given worked example - especially at the beginning of the process - by adopting code and then adapting it according to their interests, following different approaches. The study thus provides some first indications that engaging in epistemic programming with the support of worked examples can serve as a way of individualized knowledge acquisition - also for programming novices - and thus illustrates a new perspective on computing education for all.
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