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Lucy D'Agostino McGowan; Travis Gerke; Malcolm Barrett – Journal of Statistics and Data Science Education, 2024
This article introduces a collection of four datasets, similar to Anscombe's quartet, that aim to highlight the challenges involved when estimating causal effects. Each of the four datasets is generated based on a distinct causal mechanism: the first involves a collider, the second involves a confounder, the third involves a mediator, and the…
Descriptors: Statistics Education, Programming Languages, Statistical Inference, Causal Models
Carscadden, Kelly; Martin, Andrew – International Journal of Higher Education, 2022
An essential skill for STEM undergraduates is the ability to understand the world by manipulating, visualizing, and analyzing data to make or evaluate claims. Current online debate, without peer-reviewed literature, explores which of two common R syntax environments (base R or tidyverse) is best for teaching novice R users. In an in-person…
Descriptors: Biology, Undergraduate Students, Programming Languages, Teaching Methods
Fu, Qian; Zheng, Yafeng; Zhang, Mengyao; Zheng, Lanqin; Zhou, Junyi; Xie, Bochao – Educational Technology Research and Development, 2023
Providing appropriate feedback is important when learning to program. However, it is still unclear how different feedback strategies affect learning outcomes in programming. This study designed four different two-step programming feedback strategies and explored their impact on novice programmers' academic achievement, learning motivations, and…
Descriptors: Feedback (Response), Academic Achievement, Novices, Programming
Weiss, Charles J. – Biochemistry and Molecular Biology Education, 2022
This article reports a workshop from the 2021 IUBMB/ASBMB Teaching Science with Big Data conference held virtually in June 2021 where participants learned to explore and visualize large quantities of protein PBD data using Jupyter notebooks and the Python programming language. This activity instructs participants using Jupyter notebooks, Python…
Descriptors: Visual Aids, Programming Languages, Data Analysis, Science Instruction
Nongkhai, Lalita Na; Wang, Jingyun; Mendori, Takahiko – International Association for Development of the Information Society, 2022
This paper proposes the design of an ontology of multiple programming languages and give three examples to show the methodology. Our ontology aims to summarize the core of computational thinking logic by elaborating the concepts of three object-oriented programming languages in the industry: Python, Java, and C#. Therefore, the construction of the…
Descriptors: Programming Languages, Computer Science Education, Intelligent Tutoring Systems, Thinking Skills
Qing Yu; Kun Yu; Baomin Li – Journal of Educational Computing Research, 2025
Computer programming is regarded as an important skill for the future. However, many K-12 students face challenges and difficulties in learning traditional text-based programming. Block-based visual programming (BVP) can reduce the difficulty of learning programming and is seen as a potential programming education tool. Nevertheless, the effects…
Descriptors: Programming, Computer Science Education, Visual Aids, Outcomes of Education
Dayal, Vikram – International Journal of Mathematical Education in Science and Technology, 2023
Epidemiological models have enhanced relevance because of the COVID-19 pandemic. In this note, we emphasize visual tools that can be part of a learning module geared to teaching the SIR epidemiological model, suitable for advanced undergraduates or beginning graduate students in disciplines where the level of prior mathematical knowledge of…
Descriptors: Biology, Visual Aids, Epidemiology, Science Instruction
Teimourzadeh, Aria; Kakavand, Samaneh; Kakavand, Benjamin – Marketing Education Review, 2023
In the era of big data, many business organizations consider data analytics skills as important criteria in the acquisition of qualified applicants. As numerous managerial decisions in the field of marketing are becoming evidence-based, business schools have integrated case studies about different stages of data analytics such as problem…
Descriptors: Marketing, Teaching Methods, Programming Languages, Data Analysis
Yamashita, Koichi; Fujioka, Ryota; Kogure, Satoru; Noguchi, Yasuhiro; Konishi, Tatsuhiro; Itoh, Yukihiro – Research and Practice in Technology Enhanced Learning, 2017
Pointers are difficult learning targets for novice learners of C programming. For such difficult targets, introducing a system visualizing program behaviors is generally expected to support learners to understand the targets. However, visualization in existing systems often conceals the concrete value of variables such as pointers; the way in…
Descriptors: Programming, Visual Aids, Memory, Teaching Methods
Del Toro, Israel; Dickson, Kimberly; Hakes, Alyssa S.; Newman, Shannon L. – American Biology Teacher, 2022
Increasingly, students training in the biological sciences depend on a proper grounding in biological statistics, data science and experimental design. As biological datasets increase in size and complexity, transparent data management and analytical methods are essential skills for undergraduate biologists. We propose that using the software R…
Descriptors: Undergraduate Students, Biology, Statistics Education, Data Analysis
Enhancement of the Command-Line Environment for Use in the Introductory Statistics Course and Beyond
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
Tan, Song Wei Benjamin; Naraharisetti, Pavan Kumar; Chin, Siew Kian; Lee, Lai Yeng – Journal of Chemical Education, 2020
The advance of digital technology presents an opportunity to equip students with relevant skill sets as "Scientists of the Future" who are able to utilize knowledge at the interface between various disciplines. In this technology report, an open source programming language is used to automate a simple laboratory experiment commonly…
Descriptors: Programming Languages, Science Instruction, Chemistry, Computer Science Education
Myint, Leslie; Hadavand, Aboozar; Jager, Leah; Leek, Jeffrey – Journal of Statistics Education, 2020
We performed an empirical study of the perceived quality of scientific graphics produced by beginning R users in two plotting systems: the base graphics package ("base R") and the ggplot2 add-on package. In our experiment, students taking a data science course on the Coursera platform were randomized to complete identical plotting…
Descriptors: Statistics, Randomized Controlled Trials, Teaching Methods, Courseware
Maruyama, Ryoga; Ogata, Shinpei; Kayama, Mizue; Tachi, Nobuyuki; Nagai, Takashi; Taguchi, Naomi – International Association for Development of the Information Society, 2022
This study aims to explore an educational learning environment that supports students to learn conceptual modelling with the unified modelling language (UML). In this study, we call the describing models "UML programming." In this paper, we show an educational UML programming environment for science, technology, engineering, art, and…
Descriptors: Case Studies, Programming Languages, Learning Processes, Models
Boustedt, Jonas – Computer Science Education, 2012
The software industry needs well-trained software designers and one important aspect of software design is the ability to model software designs visually and understand what visual models represent. However, previous research indicates that software design is a difficult task to many students. This article reports empirical findings from a…
Descriptors: Foreign Countries, Computer Software, Computer Science Education, Programming
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