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Showing 1 to 15 of 411 results Save | Export
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Craig, Paul A.; Nash, Jessica A.; Crawford, T. Daniel – Biochemistry and Molecular Biology Education, 2022
A programming workshop has been developed for biochemists and molecular biologists to introduce them to the power and flexibility of solving problems with Python. The workshop is designed to move users beyond a "plug-and-play" approach that is based on spreadsheets and web applications in their teaching and research to writing scripts to…
Descriptors: Programming Languages, Biochemistry, Molecular Biology, Data Analysis
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Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
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David, Andrew A. – American Biology Teacher, 2021
The rise of "big data" within the biological sciences has resulted in an urgent demand for coding skills in the next generation of scientists. To address this issue, several institutions and departments across the country have incorporated coding into their curricula. I describe a coding module developed and deployed in an undergraduate…
Descriptors: Programming, Programming Languages, Undergraduate Students, Biology
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Michael C. Robbins; Zhuping Li – Field Methods, 2025
The Nolan Index (NI) is a normed, quantitative measure for comparing the degree of resemblance (similarity or dissimilarity) between free listings with an Excel program for calculating it. This article enhances that effort with the addition of an R program and additional applications. Free-list resemblance measures have been used to investigate…
Descriptors: Computation, Norm Referenced Tests, Comparative Analysis, Spreadsheets
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Kao, Yvonne; Matlen, Bryan; Weintrop, David – ACM Transactions on Computing Education, 2022
The 1980s and 1990s saw a robust connection between computer science education and cognitive psychology as researchers worked to understand how students learn to program. More recently, academic disciplines such as science and engineering have begun drawing on cognitive psychology research and theories of learning to create instructional materials…
Descriptors: Computer Science Education, Cognitive Psychology, Transfer of Training, Programming
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Xiaoheng Yan; Gila Hanna – International Journal of Mathematical Education in Science and Technology, 2025
As new technological developments continue to change the educational landscape, it is not an exception in the area of proof and proving. This classroom note introduces the use of one of the trending proofs assistants -- the Lean theorem prover. We first provide a technical account of Lean, then exemplify Lean proofs in propositional logic, number…
Descriptors: Mathematics Instruction, Undergraduate Students, Mathematical Logic, Validity
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Andrea Domínguez-Lara; Wulfrano Arturo Luna-Ramírez – International Association for Development of the Information Society, 2022
The automatic code generation is the process of generating source code snippets from a program, i.e., code for generating code. Its importance lies in facilitating software development, particularly important is helping in the implementation of software designs such as engineering diagrams, in such a case, automatic code generation copes with the…
Descriptors: Programming, Coding, Computer Software, Programming Languages
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Dorodchi, Mohsen; Dehbozorgi, Nasrin; Fallahian, Mohammadali; Pouriyeh, Seyedamin – Informatics in Education, 2021
Teaching software engineering (SWE) as a core computer science course (ACM, 2013) is a challenging task. The challenge lies in the emphasis on what a large-scale software means, implementing teamwork, and teaching abstraction in software design while simultaneously engaging students into reasonable coding tasks. The abstraction of the system…
Descriptors: Computer Science Education, Computer Software, Teaching Methods, Undergraduate Students
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Lafuente, Deborah; Cohen, Brenda; Fiorini, Guillermo; Garci´a, Agusti´n Alejo; Bringas, Mauro; Morzan, Ezequiel; Onna, Diego – Journal of Chemical Education, 2021
Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks…
Descriptors: Undergraduate Students, Chemistry, Electronic Learning, Artificial Intelligence
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Grobelna, Iwona – Informatics in Education, 2020
Control systems are becoming ever more commonly used in everyday life. This is true both in industry and in the domestic domain, in the form of e.g., smart home systems. The quality of such systems can be increased by using formal verification methods, such as the model checking technique, to make sure that the designed system fulfills all user…
Descriptors: Programming Languages, Standards, Engineering, Information Systems
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Menon, Pratibha – Journal of Information Systems Education, 2023
This paper introduces a teaching process to develop students' problem-solving and programming efficacy in an introductory computer programming course. The proposed teaching practice provides step-by-step guidelines on using worked-out examples of code to demonstrate the applications of programming concepts. These coding demonstrations explicitly…
Descriptors: Introductory Courses, Programming, Computer Science Education, Feedback (Response)
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Tang, Marc – Teaching Statistics: An International Journal for Teachers, 2020
University students in other disciplines without prior knowledge in statistics and/or programming language are introduced to the statistical method of decision trees in the programming language R during a 45-minute teaching and practice session. Statistics and programming skills are now frequently required within a wide variety of research fields…
Descriptors: Statistics, Teaching Methods, Programming, Programming Languages
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Frydenberg, Mark; Mentzer, Kevin – Information Systems Education Journal, 2021
Project-based learning (PBL) engages students deeply with course concepts and empowers them to drive their own learning through the development of solutions to real-world challenges. By taking ownership of and completing a project that they designed, students develop and demonstrate creativity, critical thinking, and collaboration skills. This…
Descriptors: Learner Engagement, Student Empowerment, Active Learning, Student Projects
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Germia, Erell; Panorkou, Nicole – Mathematics Teacher: Learning and Teaching PK-12, 2020
We present a Scratch task we designed and implemented for teaching and learning coordinates in a dynamic and engaging way. We use the 5Es framework to describe the students' interactions with the task and offer suggestions of how other teachers may adopt it to successfully implement Scratch tasks.
Descriptors: Programming, Mathematical Concepts, Mathematics Instruction, Programming Languages
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Nie, Rui; Guo, Qi; Morin, Maxim – Educational Measurement: Issues and Practice, 2023
The COVID-19 pandemic has accelerated the digitalization of assessment, creating new challenges for measurement professionals, including big data management, test security, and analyzing new validity evidence. In response to these challenges, "Machine Learning" (ML) emerges as an increasingly important skill in the toolbox of measurement…
Descriptors: Artificial Intelligence, Electronic Learning, Literacy, Educational Assessment
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