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Rucker, Ryan – Journal of Open, Flexible and Distance Learning, 2023
Online learning has risen in popularity among learners, educators, and university administrators over the last 3 decades. However, one of the biggest challenges for educators is adapting to best practices, pedagogies, tools, and technologies when delivering instruction in this environment. Because learners have choices when enrolling in a…
Descriptors: Student Satisfaction, Programming, Information Science Education, Teaching Methods
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Babak Mahjour; Andrew McGrath; Andrew Outlaw; Ruheng Zhao; Charles Zhang; Tim Cernak – Journal of Chemical Education, 2023
Data science is becoming a mainstay in research. Despite this, very few STEM graduates matriculate with basic formal training in programming. The current lesson plan was developed to introduce undergraduates studying chemistry or biology to chemoinformatics and data science in medicinal chemistry. The objective of this lesson plan is to introduce…
Descriptors: Undergraduate Students, Chemistry, Biology, Information Science
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Samson O. Adeoye; Heather Lindberg; B. Bagby; Anne M. Brown; Feras A. Batarseh; Eric K. Kaufman – NACTA Journal, 2023
Cyberbiosecurity is an emerging field at the convergence of life sciences and the digital world. As technological advances improve operational processes and expose them to vulnerabilities in agriculture and life sciences, cyberbiosecurity has become increasingly important for addressing contemporary concerns. Unfortunately, at this time,…
Descriptors: Computer Security, Biology, Biological Sciences, Labor Force Development
Arawjo, Ian Anders – ProQuest LLC, 2023
I situate computer programming as a cultural practice. I develop this perspective in two ways: exploring how programming practices can support intercultural learning, and examining how programming tools themselves embed cultural assumptions and values. For the former, I study how relationships across difference are formed over computing activities…
Descriptors: Computer Science Education, Programming, Cultural Influences, Elementary Secondary Education
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Diana Kirk; Andrew Luxton-Reilly; Ewan Tempero – ACM Transactions on Computing Education, 2025
Objectives: Code style is an important aspect of text-based programming because programs written with good style are considered easier to understand and change and so improve the maintainability of the delivered software product. However teaching code style is complicated by the existence of many style guides and standards that contain…
Descriptors: Computer Science Education, Programming, Computer Software, Teaching Methods
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Stella Xin Yin; Dion Hoe-Lian Goh; Choon Lang Quek; Zhengyuan Liu – Educational Technology & Society, 2025
With the growing popularity of computational thinking (CT) classes in K-12 schools, it is important to investigate public perceptions of these initiatives. Analyzing public discussions and opinions provides valuable insights that can inform future educational policies and reforms. In this paper, we collected questions and answers related to CT…
Descriptors: Computation, Thinking Skills, Elementary Secondary Education, Public Opinion
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Brittany Devies; Lauren Bullock; Daniel M. Jenkins; Scott J. Allen; Joanna Stanberry – New Directions for Student Leadership, 2025
This article explores the pedagogical considerations of using pop-culture podcasts as an instructional strategy in leadership development. We clarify key concepts, evaluate podcasts as an instructional tool, and provide recommendations and implications for their integration into leadership learning experiences. While an important consideration for…
Descriptors: Leadership Training, Popular Culture, Audio Equipment, Telecommunications
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Erkan Er; Gökhan Akçapinar; Alper Bayazit; Omid Noroozi; Seyyed Kazem Banihashem – British Journal of Educational Technology, 2025
Despite the growing research interest in the use of large language models for feedback provision, it still remains unknown how students perceive and use AI-generated feedback compared to instructor feedback in authentic settings. To address this gap, this study compared instructor and AI-generated feedback in a Java programming course through an…
Descriptors: Student Evaluation, Student Attitudes, Feedback (Response), Artificial Intelligence
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Erik Forsberg; Anders Sjöberg – Measurement: Interdisciplinary Research and Perspectives, 2025
This paper reports a validation study based on descriptive multidimensional item response theory (DMIRT), implemented in the R package "D3mirt" by using the ERS-C, an extended version of the Relevance subscale from the Moral Foundations Questionnaire including two new items for collectivism (17 items in total). Two latent models are…
Descriptors: Evaluation Methods, Programming Languages, Altruism, Collectivism
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Umar Alkafaween; Ibrahim Albluwi; Paul Denny – Journal of Computer Assisted Learning, 2025
Background: Automatically graded programming assignments provide instant feedback to students and significantly reduce manual grading time for instructors. However, creating comprehensive suites of test cases for programming problems within automatic graders can be time-consuming and complex. The effort needed to define test suites may deter some…
Descriptors: Automation, Grading, Introductory Courses, Programming
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Seongyune Choi; Hyeoncheol Kim – Education and Information Technologies, 2025
Attention to programming education from K-12 to higher education has been growing with the aim of fostering students' programming ability. This ability involves employing appropriate algorithms and computer codes to solve problems and can be enhanced through practical learning. However, in a formal educational setting, it is challenging to provide…
Descriptors: Foreign Countries, High School Freshmen, Programming, Artificial Intelligence
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Mark Frydenberg; Anqi Xu; Jennifer Xu – Information Systems Education Journal, 2025
This study explores student perceptions of learning to code by evaluating AI-generated Python code. In an experimental exercise given to students in an introductory Python course at a business university, students wrote their own solutions to a Python program and then compared their solutions with AI-generated code. They evaluated both solutions…
Descriptors: Student Attitudes, Programming, Computer Software, Quality Assurance
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Shu-Jie Chen; Xiaofen Shan; Ze-Min Liu; Chuang-Qi Chen – Educational Technology & Society, 2025
The introduction of programming education in K-12 schools to promote computational thinking has attracted a great deal of attention from scholars and educators. Debugging code is a central skill for students, but is also a considerable challenge when learning to program. Learners at the K-12 level often lack confidence in programming debugging due…
Descriptors: Programming, Coding, Elementary School Students, Secondary School Students
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Hanzhu Yang; Linlin Hu; Hao Wang; Yunfei Xin – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) is a cognitive approach intricately linked with core competencies in Science, Technology, Engineering, and Mathematics (STEM). Numerous studies have explored strategies to effectively integrate CT into STEM education and systematically evaluated the multidimensional impact on student learning outcomes.…
Descriptors: Integrated Activities, Computation, Thinking Skills, STEM Education
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Linjing Wu; Xuelin Xiang; Xueyan Yang; Xuan Jin; Liang Chen; Qingtang Liu – Educational Technology Research and Development, 2025
Problem-solving strategies are crucial in learning programming. Owing to their hidden nature, traditional methods such as interviews and questionnaires cannot reflect the details and differences of problem-solving strategies in programming. This study uses the Hidden Markov Model to detect and compare the problem-solving strategies of different…
Descriptors: Markov Processes, Problem Solving, Programming, Identification
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