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Lakshminarayanan, Srinivasan; Rao, N. J. – Higher Education for the Future, 2022
There are many grey areas in the interpretation of academic integrity in the course on Introduction to Programming, commonly known as CS1. Copying, for example, is a method of learning, a method of cheating and a reuse method in professional practice. Many institutions in India publish the code in the lab course manual. The students are expected…
Descriptors: Integrity, Cheating, Duplication, Introductory Courses
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Sharpe, J. P. – Physics Teacher, 2022
The Poisson distribution describes the probability of a certain number of events occurring in an interval of time when the occurrence of the individual events is independent of one another and the events occur with a fixed mean rate. Probably the best-known example of the Poisson distribution in the physics curriculum is the temporal distribution…
Descriptors: Physics, Science Instruction, Probability, Mathematics Skills
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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
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Çetinkaya-Rundel, Mine; Dogucu, Mine; Rummerfield, Wendy – Statistics Education Research Journal, 2022
Many data science applications involve generating questions, acquiring data and preparing it for analysis--be it exploratory, inferential, or modeling focused--and communicating findings. Most data science curricula address each of these steps as separate units in a course or as separate courses. Open-ended term projects, however, allow students…
Descriptors: Introductory Courses, Data Analysis, Statistics Education, Units of Study
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Lasater, Robert S.; Joseph, Anny-Claude; Cummiskey, Kevin – Teaching Statistics: An International Journal for Teachers, 2023
In this paper, we provide instructors with an approach for a classroom activity for students in an introductory data science or statistics course who have little or no statistical programming experience. We designed this activity to help students improve their statistical literacy while exploring a social justice problem-the gender wage gap. To…
Descriptors: Gender Differences, Salary Wage Differentials, Visual Aids, Statistics Education
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Li-Chen Cheng; Wei Li; Judy C. R. Tseng – Interactive Learning Environments, 2023
Programming ability is the core ability of this era and can be obtained and improved through practice. In this paper, an Automated Programming Assessment system based on Mastery learning and Peer competition (APAMP) was proposed and developed. APAMP allows students to practice repeatedly by providing immediate feedback after their programs are…
Descriptors: High School Freshmen, High School Seniors, Programming Languages, Foreign Countries
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Szlávi,Péter; Zsakó, László – Acta Didactica Napocensia, 2017
As a programmer when solving a problem, a number of conscious and unconscious cognitive operations are being performed. Problem-solving is a gradual and cyclic activity; as the mind is adjusting the problem to its schemas formed by its previous experiences, the programmer gets closer and closer to understanding and defining the problem. The…
Descriptors: Problem Solving, Programming, Mathematics, Programming Languages
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Gerják, István – Acta Didactica Napocensia, 2017
Learning computer programming for students of the age of 14-18 is difficult and requires endurance and engagement. Being familiar with the syntax of a computer language and writing programs in it are challenges for youngsters, not to mention that understanding algorithms is also a big challenge. To help students in the learning process, teachers…
Descriptors: Programming, Secondary School Students, Mathematics, Programming Languages
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Moon, Tyler; Abegaz, Tamirat; Payne, Bryson; Salimi, Abi – Journal of Cybersecurity Education, Research and Practice, 2020
Several research findings indicate that basic cyber hygiene can potentially deter the majority of cyber threats. One of the ways cybersecurity professionals can prepare users to ensure proper hygiene is to help them develop their ability to spot the difference between normal and abnormal behavior in a computer system. Malware disrupts the normal…
Descriptors: Information Security, Game Based Learning, Computer Security, Knowledge Level
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Stohlmann, Micah; Kim, Young Rae – Australian Mathematics Education Journal, 2020
Games are an everyday part of most students' lives. Games engage students and provide opportunities to foster perseverance in problem solving. When implemented in the mathematics classroom, game-based learning can have similar positive benefits. Students can enjoy mathematics and develop important life skills that will help them in their current…
Descriptors: Game Based Learning, Robotics, Educational Games, Mathematics Instruction
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Brady, Alison M. – Journal of Philosophy of Education, 2020
This paper discusses the ways in which the teacher is recognised through the formulation of evaluation frameworks which encompass criteria for so-called effective teaching and, by extension, effective learning. It argues that the emphasis on that which is 'effective', and therefore measurable, is symptomatic of an overly technicist understanding…
Descriptors: Teaching Methods, Instructional Effectiveness, Educational Philosophy, Teacher Effectiveness
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Fávero, Luiz Paulo; Souza, Rafael de Freitas; Belfiore, Patrícia; Corrêa, Hamilton Luiz; Haddad, Michel F. C. – Practical Assessment, Research & Evaluation, 2021
In this paper is proposed a straightforward model selection approach that indicates the most suitable count regression model based on relevant data characteristics. The proposed selection approach includes four of the most popular count regression models (i.e. Poisson, negative binomial, and respective zero-inflated frameworks). Moreover, it…
Descriptors: Regression (Statistics), Selection, Statistical Analysis, Models
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Mirolo, Claudio; Izu, Cruz; Lonati, Violetta; Scapin, Emanuele – Informatics in Education, 2021
When we "think like a computer scientist," we are able to systematically solve problems in different fields, create software applications that support various needs, and design artefacts that model complex systems. Abstraction is a soft skill embedded in all those endeavours, being a main cornerstone of computational thinking. Our…
Descriptors: Computer Science Education, Soft Skills, Thinking Skills, Abstract Reasoning
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Scalfani, Vincent F. – Journal of Chemical Education, 2021
The National Center for Biotechnology Information Entrez Direct (EDirect) software facilitates programmatic access to numerous biomedical, chemical, and literature databases from within a Unix terminal. EDirect has traditionally been used for command line access to NCBI data within the fields of computational biology and bioinformatics. This…
Descriptors: Biotechnology, Computer Software, Biomedicine, Biology
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Kim, Brian; Henke, Graham – Journal of Statistics and Data Science Education, 2021
One of the biggest hurdles of teaching data science and programming techniques to beginners is simply getting started with the technology. With multiple versions of the same coding language available (e.g., Python 2 and Python 3), various additional libraries and packages to install, as well as integrated development environments to navigate, the…
Descriptors: Computer Software, Data Analysis, Programming Languages, Computer Science Education
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