Objectives. The increasing demand for computing skills has led to a rapid rise in the development of new computerscience (CS) curricula, many with the goal of equitably broadening the participation of underrepresente...
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Objectives. The increasing demand for computing skills has led to a rapid rise in the development of new computerscience (CS) curricula, many with the goal of equitably broadening the participation of underrepresented students in CS. While such initiatives are vital, factors outside of the school environment also play a role in influencing students' interests. In this article, we examined the effects of students' perceived parental support on their interest in computerprogramming and explored the mechanisms through which this effect may have been established as students participated in an introductory CS instructional unit. Participants. This instructional unit was implemented with upper primary (grade 5) school students and was designed to broaden trajectories for participation in CS. The participants in the current study (N = 170) came from six classrooms in two rural schools in the western United States. Study Method. The seven-week instructional unit began with students playing a commercial CS tabletop board game that highlighted fundamental programming concepts and transitioned to having students create their own board game levels in the block-based programming language, Scratch. Further, because the board game could be taken home, the instructional unit offered opportunities to involve the family in school-based CS activities. To investigate the effect of students' perception of parental (specifically father and mother) support on their interest in and self-efficacy to pursue CS, we surveyed students before and after the unit's implementations and explored the structural relationship of the data using structural equation modeling. Results. We present three findings. First, the combined effect of students' perceived mother's and father's support measured prior to the implementation (pre-survey) predicted students' self-efficacy (Standardized Estimate ((3) = 0.37, standard error = 0.010, p <.001) and interest in computerprogramming (Standardized Estimate ((3)
programming is becoming a key subject in early education globally, with surging problems of how computerscience can become a subject for children of all ages and backgrounds. Problems of implementing new technologies...
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programming is becoming a key subject in early education globally, with surging problems of how computerscience can become a subject for children of all ages and backgrounds. Problems of implementing new technologies in the old curricula have long been noted, and lately, concern over computerscience education goals is often too narrow and skills-based without concerns for the critical educational potential. This study follows the change process of two case preschool departments implementing programming with a floor robot across a seven-month design process. Mixed analytical techniques based on activity theory are used to examine the tensions, conflicts and development of pedagogical alternatives. The studies show the strenuous change processes involving local transformations toward a child-centred, inclusive early computerscience education and development of projects centring making, children's exploration, tinkering and play as key parts of the learning process. It discusses how the considerable change processes enabled pedagogical solutions coherent with important concepts in computerprogramming and how computing education can build on child-centred pedagogies through local adaptations and age-appropriate designs.
Fault localization is to identify faulty program *** a large number of fault localization ap-proaches in the literature,coverage-based fault localization,especially spectrum-based fault localization(SBFL),has been int...
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Fault localization is to identify faulty program *** a large number of fault localization ap-proaches in the literature,coverage-based fault localization,especially spectrum-based fault localization(SBFL),has been intensively studied due to its effectiveness and *** the rich literature,almost all existing fault local-ization approaches and studies have been conducted on imperative programming languages such as Java and C,leaving a gap in other programming *** this paper,we aim to study fault localization approaches for the functional pro-gramming paradigm,using the Haskell language as a *** the best of our knowledge,we build up the first dataset on real Haskell projects,including both real and seeded *** dataset enables the research of fault localiza-tion for functional *** it,we explore fault localization techniques for *** particular,as is typical for SBFL approaches,we study methods for coverage collection and formulae for suspiciousness score computation,and care-fully adapt these two components to Haskell considering the language features and characteristics,resulting in a series of adaption ***,we design a learning-based approach and a transfer learning based approach to take ad-vantage of data from imperative *** approaches are evaluated on our dataset to demonstrate the promises of the direction.
Algot is a visual, live programming language for computerscience education that uses a novel implementation of programming by demonstration. Recent experimental studies indicate that Algot is effective for teaching f...
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ISBN:
(纸本)9798400706035
Algot is a visual, live programming language for computerscience education that uses a novel implementation of programming by demonstration. Recent experimental studies indicate that Algot is effective for teaching foundational computerscience concepts in secondary and tertiary education. In this proposed ITiCSE session, we will give a brief demonstration of how Algot works and how it can be used to implement algorithms that are typically taught in CS1, such as sorting and searching. Our primary intention is to help practitioners in the ITiCSE audience determine if Algot could be appropriate for their own classrooms.
The purpose of this article is to historize the definition of computerscience, particularly the characteristic ambiguity of the discipline toward the computer. This ambiguity is foundational to computerscience and h...
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The purpose of this article is to historize the definition of computerscience, particularly the characteristic ambiguity of the discipline toward the computer. This ambiguity is foundational to computerscience and has its roots in the response of university computer centers to the commercialization of computing in the mid-1950s. University computing experts developed an understanding of the activity of computing disentangled from the computer itself, a conceptual shift that went together with a parallel process of dematerialization of the notion of computer. These transformations were facilitated by the ascendance of a high modernist agenda in the sciences in the United States. University computing experts embraced the high modernist agenda and developed analogies across programs, notations, and a notion of the computer now understood as a model of computation. This immaterial conflation of notations, programs, and representations of the machine, would become one of the core tenets of computerscience.
The performance of seven large language models (LLMs) in generating programming code using various prompt strategies, programming languages, and task difficulties is systematically evaluated. GPT-4 substantially outpe...
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The performance of seven large language models (LLMs) in generating programming code using various prompt strategies, programming languages, and task difficulties is systematically evaluated. GPT-4 substantially outperforms other LLMs, including Gemini Ultra and Claude 2. The coding performance of GPT-4 varies considerably with different prompt strategies. In most LeetCode and GeeksforGeeks coding contests evaluated in this study, GPT-4, employing the optimal prompt strategy, outperforms 85 percent of human participants in a competitive environment, many of whom are students and professionals with moderate programming experience. GPT-4 demonstrates strong capabilities in translating code between different programming languages and in learning from past errors. The computational efficiency of the code generated by GPT-4 is comparable to that of human programmers. GPT-4 is also capable of handling broader programming tasks, including front-end design and database operations. These results suggest that GPT-4 has the potential to serve as a reliable assistant in programming code generation and software development. A programming assistant is designed based on an optimal prompt strategy to facilitate the practical use of LLMs for programming.
Fairness in assessment is as important as validity and reliability. When question or paper choice is used in an assessment it is important that the various routes are comparable so that fairness to all students is mai...
Fairness in assessment is as important as validity and reliability. When question or paper choice is used in an assessment it is important that the various routes are comparable so that fairness to all students is maintained. Previous literature on question choice suggests that offering choice often leads to significant differences in exam performance by route, sometimes by several marks. This dissertation compares the five possible routes through a computerscience A-level assessment. One paper was responded to using a choice of five different programming languages and it was possible that not all languages were equally accessible to students or equally applicable to the exam paper tasks. Test bias was evaluated using recently developed IRT-based differential test functioning procedures that were developed to assess unfairness due to demographic characteristics. These enabled a detailed test-level, sub-section, and item-level analysis at various levels of student ability. Some small differences between two routes were found but overall, the assessment behaved in a fair and equitable manner. It is likely that this was achieved through careful question design and the strict application of a common paper and generic mark scheme. It is recommended that the performance of the programming paper is monitored in future exam series. A few anomalies observed in the data suggested the possibility that classroom experience might have had more of an impact on students' performances than programming language choice. This suggests that there is a need for research targeted at better understanding how teachers are preparing their students for the exam, and how the students are approaching the paper. While choice has not led to unfairness in this analysis, concerns around the use of choice in assessment remain. Further research is proposed to look at the impact of choice on exam fairness in a broader selection of subjects that do not use generic questions or mark schemes. In additi
The aim of this case study is to provide a detailed description of the first university-level programming and computerscience training in Hungary, which started in 1957 at the University of Szeged. The program began ...
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ISBN:
(纸本)9783030291600;9783030291594
The aim of this case study is to provide a detailed description of the first university-level programming and computerscience training in Hungary, which started in 1957 at the University of Szeged. The program began due to the strenuous efforts of Professor Laszlo Kalmar, who is considered to be "the father of computerscience in Hungary". The aim of this study is to add to the literature on Kalmar's work, focusing on his activities in the field of computerscience education, and at the same time, to add a detailed study from the Eastern Bloc to the history of computerscience education.
The integration of artificial intelligence (AI) into computerscience (CS) education is evolving, yet its specific application in database instruction remains underexplored. This systematic review analyzes 31 empirica...
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The integration of artificial intelligence (AI) into computerscience (CS) education is evolving, yet its specific application in database instruction remains underexplored. This systematic review analyzes 31 empirical studies published between 2020 and 2025, examining how AI applications support teaching and learning in CS, with an emphasis on database education. Following the PRISMA methodology, the review categorizes AI applications according to instructional design models, roles, actions, benefits, and challenges. Findings indicate that AI tools, particularly chatbots, intelligent tutoring systems, and code generators, effectively support personalized instruction, immediate feedback, and interactive problem-solving across CS and database-specific contexts. However, challenges persist, including AI inaccuracies, biases, student dependency in AI, and academic integrity risks. The review also identifies a shift in programming education as AI reshapes software development practices, prompting a need to align curricula with evolving industry expectations. Despite growing attention to AI applications in programming education, database-related research remains limited. This review highlights the necessity for further empirical investigations specifically in database instruction, including more extensive studies addressing AI-driven pedagogical strategies and their long-term impacts. The results suggest that careful integration of AI tools can complement traditional instruction, emphasizing the critical role of human educators in achieving meaningful and effective learning outcomes.
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