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Dan Sun; Fan Ouyang; Yan Li; Chengcong Zhu; Yang Zhou – Journal of Computer Assisted Learning, 2024
Background: With the development of computational literacy, there has been a surge in both research and practice application of text-based and block-based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major…
Descriptors: Computer Science Education, Programming, Computer Literacy, Comparative Analysis
Velez, Martin – ProQuest LLC, 2019
Software is an integral part of our lives. It controls the cars we drive every day, the ships we send into space, and even our toasters. It is everywhere and we can easily download more. Software solves many real-world problems and satisfies many needs. Thus, unsurprisingly, there is a rising demand for software engineers to maintain existing…
Descriptors: Computer Science Education, Programming, Introductory Courses, Computer Software
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Damar Rais; Zhao Xuezhi – Journal on Mathematics Education, 2024
Python programming is widely employed in educational institutions worldwide. Within the "Merdeka Belajar" curriculum context, this programming is recognized as a suitable vehicle for mathematics instruction, significantly influencing students' motivation and learning outcomes, particularly following periods of educational hiatus. This…
Descriptors: Student Motivation, Learning Motivation, Programming Languages, Student Attitudes
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Gerbing, David W. – Journal of Statistics and Data Science Education, 2021
R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…
Descriptors: Statistics Education, Teaching Methods, Introductory Courses, Programming Languages
UK Department for Education, 2024
This report sets out the findings of the technical development work completed as part of the Use Cases for Generative AI in Education project, commissioned by the Department for Education (DfE) in September 2023. It has been published alongside the User Research Report, which sets out the findings from the ongoing user engagement activity…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Software, Computational Linguistics
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Xie, Benjamin; Loksa, Dastyni; Nelson, Greg L.; Davidson, Matthew J.; Dong, Dongsheng; Kwik, Harrison; Tan, Alex Hui; Hwa, Leanne; Li, Min; Ko, Andrew J. – Computer Science Education, 2019
Background and Context: Current introductory instruction fails to identify, structure, and sequence the many skills involved in programming. Objective: We proposed a theory which identifies four distinct skills that novices learn incrementally. These skills are tracing, writing syntax, comprehending templates (reusable abstractions of programming…
Descriptors: Programming, Skill Development, Computer Science Education, Instructional Design
Rebecca Smith – ProQuest LLC, 2019
In recent years, computer science has become a cornerstone of modern society. As a result, enrollment in undergraduate computer science programs has expanded rapidly. While the influx of talent into the field will undoubtedly lead to countless technological developments, this growth also brings new pedagogical challenges. Educational resources,…
Descriptors: Computer Science Education, Individualized Instruction, Interaction, Learning Experience
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Veerasamy, Ashok Kumar; D'Souza, Daryl; Laakso, Mikko-Jussi – Journal of Educational Technology Systems, 2016
This article presents a study aimed at examining the novice student answers in an introductory programming final e-exam to identify misconceptions and types of errors. Our study used the Delphi concept inventory to identify student misconceptions and skill, rule, and knowledge-based errors approach to identify the types of errors made by novices…
Descriptors: Computer Science Education, Programming, Novices, Misconceptions
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Elkin, Mollie; Sullivan, Amanda; Bers, Marina Umaschi – Computers in the Schools, 2016
KIBO is a developmentally appropriate robotics kit for young children that is programmed using interlocking wooden blocks; no screens or keyboards are required. This study describes a pilot KIBO robotics curriculum at an urban public preschool in Rhode Island and presents data collected on children's knowledge of foundational programming concepts…
Descriptors: Programming, Preschool Children, Robotics, Developmentally Appropriate Practices
Polo, Blanca J. – ProQuest LLC, 2013
Much research has been done in regards to student programming errors, online education and studio-based learning (SBL) in computer science education. This study furthers this area by bringing together this knowledge and applying it to proactively help students overcome impasses caused by common student programming errors. This project proposes a…
Descriptors: Computer Science Education, Programming, Online Courses, Electronic Learning
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Munoz de la Pena, D.; Gomez-Estern, F.; Dormido, S. – Computers & Education, 2012
In this paper we present a web-based innovative education tool designed for automating the collection, evaluation and error detection in practical exercises assigned to computer programming and control engineering students. By using a student/instructor code-fusion architecture, the conceptual limits of multiple-choice tests are overcome by far.…
Descriptors: Engineering Education, Multiple Choice Tests, Programming, Engineering
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Rodrigo, Ma. Mercedes T.; Andallaza, Thor Collin S.; Castro, Francisco Enrique Vicente G.; Armenta, Marc Lester V.; Dy, Thomas T.; Jadud, Matthew C. – Journal of Educational Computing Research, 2013
In this article we quantitatively and qualitatively analyze a sample of novice programmer compilation log data, exploring whether (or how) low-achieving, average, and high-achieving students vary in their grasp of these introductory concepts. High-achieving students self-reported having the easiest time learning the introductory programming…
Descriptors: Programming, High Achievement, Introductory Courses, Qualitative Research
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
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Jadud, Matthew C. – Computer Science Education, 2005
Syntactically correct code does not fall from the sky; the process that leads to a student's first executable program is not well understood. At the University of Kent we have begun to explore the "compilation behaviours" of novice programmers, or the behaviours that students exhibit while authoring code; in our initial study, we have…
Descriptors: Introductory Courses, Programming, Student Behavior, Educational Technology
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