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Direct linkDray, Kate E.; Dreyer, Kathleen S.; Lucks, Julius B.; Leonard, Joshua N. – Chemical Engineering Education, 2023
We present an educational unit to teach computational modeling, a vital part of chemical engineering curricula, through the lens of synthetic biology. Lectures, code, and homework questions provide conceptual and practical introductions to each computational method involved in the model development process, along with perspectives on how methods…
Descriptors: Engineering Education, Chemical Engineering, Teaching Methods, Units of Study
Nikola M. Luburic; Luka Z. Doric; Jelena J. Slivka; Dragan Lj. Vidakovic; Katarina-Glorija G. Grujic; Aleksandar D. Kovacevic; Simona B. Prokic – IEEE Transactions on Learning Technologies, 2025
Software engineers are tasked with writing functionally correct code of high quality. Maintainability is a crucial code quality attribute that determines the ease of analyzing, modifying, reusing, and testing a software component. This quality attribute significantly affects the software's lifetime cost, contributing to developer productivity and…
Descriptors: Intelligent Tutoring Systems, Coding, Computer Software, Technical Occupations
Yifan Zhang – ProQuest LLC, 2024
Computational thinking (CT) has been an increasing focus of research and practice since the seminal paper by Wing in 2006, especially in pre-college (K-12) education. Barr and Stephenson defined CT as a problem-solving methodology that can be automated, transferred, and applied across disciplines. With the challenges of fitting CT into already…
Descriptors: Mental Computation, Elementary Education, Problem Solving, Intellectual Disciplines
David Shilane; Nicole Di Crecchio; Nicole L. Lorenzetti – Teaching Statistics: An International Journal for Teachers, 2024
Educational curricula in data analysis are increasingly fundamental to statistics, data science, and a wide range of disciplines. The educational literature comparing coding syntaxes for instruction in data analysis recommends utilizing a simple syntax for introductory coursework. However, there is limited prior work to assess the pedagogical…
Descriptors: Programming, Data Science, Programming Languages, Coding
Alain Kuzniak; Blandine Masselin – Educational Studies in Mathematics, 2024
This paper describes how the notion of the strongly didactic contract can serve to characterize the teaching adopted to implement a task in probability. It is particularly focused on the reality of mathematical work performed by students and teachers. For this research, classroom sessions were developed in an in-service teacher training course…
Descriptors: Mathematics, Learning Theories, Teaching Methods, Teacher Education
Jeremy Jon Bro – ProQuest LLC, 2023
Secure Code Education (SCE) is the compliance requirement for many organizations in the U.S. Consequently, many U.S. companies spend large sums on programs and tooling to meet this requirement and to upskill their developers. This tooling is largely underutilized. Classes beyond the bare required minimum are often not taken advantage of, leaving…
Descriptors: Coding, Gamification, Vignettes, Programming
Melinda Lanius – PRIMUS, 2024
In this paper, I analyze the impact of culture and metaphor on cryptology education. I will compare and contrast the historically grounded metaphors of cryptology-is-warfare and encryption-is-security to a set of counter-metaphors: cryptology-is-privacy and encryption-is-communication. Using this explicit understanding of conceptual metaphor, I…
Descriptors: Figurative Language, Technology, Coding, Information Security
Yuhan Lin – ProQuest LLC, 2024
Block-based programming environments have become increasingly commonplace in computer science education. Despite a rapidly expanding ecosystem of block-based programming environments, text-based languages remain the dominant programming paradigm outside of educational contexts, motivating the transition from block-based to text-based programming.…
Descriptors: Computer Science Education, Programming, Coding, Scaffolding (Teaching Technique)
Representing DNA for Machine Learning Algorithms: A Primer on One-Hot, Binary, and Integer Encodings
Yash Munnalal Gupta; Satwika Nindya Kirana; Somjit Homchan – Biochemistry and Molecular Biology Education, 2025
This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning intervention focuses on developing practical skills in implementing these essential techniques for…
Descriptors: Science Instruction, Teaching Methods, Genetics, Molecular Biology
Sermin Metin; Damla Kalyenci; Mehmet Basaran; Emily Relkin; Büsra Bilir – Early Childhood Education Journal, 2025
The domain of early childhood education has witnessed an increasing emphasis on developing coding and computational thinking (CT) abilities. Scholarly investigations have delved into appropriate approaches for enhancing these proficiencies within early childhood classrooms. The present study aims to investigate the impact of a digital story design…
Descriptors: Early Childhood Education, Coding, Computation, Thinking Skills
W. Monty Jones; Katherine Hansen; Douglas Lusa Krug; Michael L. Schad; Nakisha Whittington; Xun Liu – Computer Science Education, 2025
Background and Context: Efforts to engage adult learners in computer science in the United States have been largely unsuccessful. While research examining the use of music for teaching computer programming with K-12 learners is emerging, little research with adult learners exists. Objective: This study evaluates the effect of computer coding…
Descriptors: Musical Composition, Computer Software, Adult Students, Student Attitudes
Download full textShi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
Dan Sun; Fan Xu – Journal of Educational Computing Research, 2025
Real-time collaborative programming (RCP), which allows multiple programmers to work concurrently on the same codebase with changes instantly visible to all participants, has garnered considerable popularity in higher education. Despite this trend, little work has rigorously examined how undergraduates engage in collaborative programming when…
Descriptors: Cooperative Learning, Programming, Computer Science Education, Undergraduate Students
Haley A. Delcher; Enas S. Alsatari; Adeyeye I. Haastrup; Sayema Naaz; Lydia A. Hayes-Guastella; Autumn M. McDaniel; Olivia G. Clark; Devin M. Katerski; Francois O. Prinsloo; Olivia R. Roberts; Meredith A. Shaddix; Bridgette N. Sullivan; Isabella M. Swan; Emily M. Hartsell; Jeffrey D. DeMeis; Sunita S. Paudel; Glen M. Borchert – Biochemistry and Molecular Biology Education, 2025
Today, due to the size of many genomes and the increasingly large sizes of sequencing files, independently analyzing sequencing data is largely impossible for a biologist with little to no programming expertise. As such, biologists are typically faced with the dilemma of either having to spend a significant amount of time and effort to learn how…
Descriptors: Artificial Intelligence, Technology Uses in Education, Training, Teaching Methods
Michael E. Ellis; K. Mike Casey; Geoffrey Hill – Decision Sciences Journal of Innovative Education, 2024
Large Language Model (LLM) artificial intelligence tools present a unique challenge for educators who teach programming languages. While LLMs like ChatGPT have been well documented for their ability to complete exams and create prose, there is a noticeable lack of research into their ability to solve problems using high-level programming…
Descriptors: Artificial Intelligence, Programming Languages, Programming, Homework
