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Justin Gambrell; Eric Brewe – Physical Review Physics Education Research, 2024
Computational thinking in physics has many different forms, definitions, and implementations depending on the level of physics or the institution it is presented in. To better integrate computational thinking in introductory physics, we need to understand what physicists find important about computational thinking in introductory physics. We…
Descriptors: Physics, Introductory Courses, Science Instruction, Thinking Skills
Carlos Sandoval-Medina; Carlos Argelio Arévalo-Mercado; Estela Lizbeth Muñoz-Andrade; Jaime Muñoz-Arteaga – Journal of Information Systems Education, 2024
Learning basic programming concepts in computer science-related fields poses a challenge for students, to the extent that it becomes an academic-social problem, resulting in high failure and dropout rates. Proposed solutions to the problem can be found in the literature, such as the development of new programming languages and environments, the…
Descriptors: Cognitive Ability, Computer Science Education, Programming, Instructional Materials
Phillips, A. M.; Gouvea, E. J.; Gravel, B. E.; Beachemin, P. -H.; Atherton, T. J. – Physical Review Physics Education Research, 2023
Computation is intertwined with essentially all aspects of physics research and is invaluable for physicists' careers. Despite its disciplinary importance, integration of computation into physics education remains a challenge and, moreover, has tended to be constructed narrowly as a route to solving physics problems. Here, we broaden Physics…
Descriptors: Physics, Science Instruction, Teaching Methods, Models
Fung, Tze-ho; Li, Wing-yi – Practical Assessment, Research & Evaluation, 2022
Rough set theory (RST) was proposed by Zdzistaw Pawlak (Pawlak,1982) as a methodology for data analysis using the notion of discernibility of objects based on their attribute values. The main advantage of using RST approach is that it does not need additional assumptions--like data distribution in statistical analysis. Besides, it provides…
Descriptors: Gifted, Metacognition, Learning Strategies, Programming Languages
Thompson, JaCoya; Arastoopour Irgens, Golnaz – Journal of Statistics and Data Science Education, 2022
Data science is a highly interdisciplinary field that comprises various principles, methodologies, and guidelines for the analysis of data. The creation of appropriate curricula that use computational tools and teaching activities is necessary for building skills and knowledge in data science. However, much of the literature about data science…
Descriptors: Data Analysis, Middle School Students, Statistics Education, Student Centered Learning
Ali Al Ghaithi; Behnam Behforouz – Journal of Educators Online, 2024
The current study attempted to measure the impact of using an interactive WhatsApp bot designed using Python language programming in grammar learning. To this end, sixty Omani pre-intermediate English proficiency learners were the sample population of this study to act as a control and experimental group, with an equal number of students in each…
Descriptors: Grammar, Programming Languages, English (Second Language), Second Language Learning
Maciej M. Syslo – Informatics in Education, 2024
The first books in Polish about the Pascal programming language appeared in the late 1970s, and were soon followed by a Polish translation of Niklaus Wirth's book "Algorithms + Data Structures = Programs." At that time, many efforts were made to prepare teachers to teach informatics in schools, and Pascal was one of the topics taught,…
Descriptors: Programming Languages, Information Science Education, Algorithms, Foreign Countries
Hao, Jiangang; Ho, Tin Kam – Journal of Educational and Behavioral Statistics, 2019
Machine learning is a popular topic in data analysis and modeling. Many different machine learning algorithms have been developed and implemented in a variety of programming languages over the past 20 years. In this article, we first provide an overview of machine learning and clarify its difference from statistical inference. Then, we review…
Descriptors: Artificial Intelligence, Statistical Inference, Data Analysis, Programming Languages
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
Chan, Shiau-Wei; Looi, Chee-Kit; Ho, Weng Kin; Kim, Mi Song – Journal of Educational Computing Research, 2023
The importance of computational thinking (CT) as a 21st-century skill for future generations has been a key consideration in the reforms of many national and regional educational systems. Much attention has been paid to integrating CT into the traditional subject classrooms. This paper describes a scoping review of learning tools for integrating…
Descriptors: Thinking Skills, 21st Century Skills, Teaching Methods, Research Reports
Schwab-McCoy, Aimee; Baker, Catherine M.; Gasper, Rebecca E. – Journal of Statistics and Data Science Education, 2021
In the past 10 years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university faculty teaching data science courses and…
Descriptors: Statistics Education, Higher Education, College Students, Teaching Methods
Hadjistassou, Stella; Louca, Petros; Joannidou, Shaunna; Molina Muñoz, Pedro Jesus – Research-publishing.net, 2021
This paper delves into the underlying phases involved in designing, developing, and deploying Augmented Reality (AR) applications and game-based scenarios that will be implemented during intercultural exchanges among students in two different academic institutions in Sweden and Cyprus. Building on principles of design-based research (Barab &…
Descriptors: Computer Simulation, Exchange Programs, Game Based Learning, Intercultural Communication
Rubleske, Joseph; Fletcher, Travis; Westerfeld, Brett – Journal of Instructional Pedagogies, 2020
Electronic sports (e-sports) can be defined as digital games played competitively for an audience (Hodge et al., 2017). With a global consumer base of roughly 450 million people and projected 2019 revenues of US$1.1 billion, the e-sports industry continues to grow (Pannekeet, 2019). Behind this growth is a thriving ecosystem which includes…
Descriptors: Computer Games, Athletics, Data Collection, Data Analysis
Neelima Bhatnagar; Victoria Causer; Michael J. Lucci; Michael Pry; Dorothy M. Zilic – Information Systems Education Journal, 2024
Data analytics is a rapidly growing field that plays a crucial role in extracting valuable insights from large volumes of data. A data analytics practicum course provides students with hands-on experience in applying data analytics techniques and tools to real-world scenarios. This practicum is intended to serve as a bridge between the student's…
Descriptors: Statistics Education, Data Analysis, Practicums, Education Work Relationship
Johnson, Marina E.; Misra, Ram; Berenson, Mark – Decision Sciences Journal of Innovative Education, 2022
In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…
Descriptors: Bayesian Statistics, Programming Languages, Artificial Intelligence, Data Analysis

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