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Jule Scheper; Robin Leuppert; Daniel Possler; Anna Freytag; Sophie Bruns; Julia Niemann-Lenz – Journalism and Mass Communication Educator, 2025
Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…
Descriptors: Journalism Education, Programming Languages, Statistical Analysis, Data Analysis
Miedema, Daphne; Fletcher, George; Aivaloglou, Efthimia – ACM Transactions on Computing Education, 2023
Prior studies in the Computer Science education literature have illustrated that novices make many mistakes in composing SQL queries. Query formulation proves to be difficult for students. Only recently, some headway was made towards understanding why SQL leads to so many mistakes, by uncovering student misconceptions. In this article, we shed new…
Descriptors: Computer Science Education, Novices, Misconceptions, Programming Languages
Scharl, Anna; Zink, Eva – Large-scale Assessments in Education, 2022
Educational large-scale assessments (LSAs) often provide plausible values for the administered competence tests to facilitate the estimation of population effects. This requires the specification of a background model that is appropriate for the specific research question. Because the "German National Educational Panel Study" (NEPS) is…
Descriptors: National Competency Tests, Foreign Countries, Programming Languages, Longitudinal Studies
Lasser, Jana; Manik, Debsankha; Silbersdorff, Alexander; Säfken, Benjamin; Kneib, Thomas – Teaching Statistics: An International Journal for Teachers, 2021
Data and its applications are increasingly ubiquitous in the rapidly digitizing world and consequently, students across different disciplines face increasing demand to develop skills to answer both academia's and businesses' increasing need to collect, manage, evaluate, apply and extract knowledge from data and critically reflect upon the derived…
Descriptors: Introductory Courses, Data, Interdisciplinary Approach, Programming Languages
Felderer, Barbara; Blom, Annelies G. – Sociological Methods & Research, 2022
The ease at which online paradata can be captured in web surveys seems to increase social researchers' desire to collect such data. Yet little attention is paid to whether respondents actually approve of their collection. This article, therefore, studies online survey respondents' acceptance of automatically collecting their geographical…
Descriptors: Data Collection, Online Surveys, Geographic Location, Individual Characteristics
Lezhnina, Olga; Kismihók, Gábor – International Journal of Research & Method in Education, 2022
In our age of big data and growing computational power, versatility in data analysis is important. This study presents a flexible way to combine statistics and machine learning for data analysis of a large-scale educational survey. The authors used statistical and machine learning methods to explore German students' attitudes towards information…
Descriptors: Student Attitudes, Scientific Literacy, Numeracy, Foreign Countries
Eric Schätz; Alke Martens – International Association for Development of the Information Society, 2023
Due the wideness of the term Physical Computing, there is a need for a better structure of this topic. This paper is about an approach of structuring this field by finding attributes of different physical computing devices which can be used in class. Those attributes are meant to enforce teachers as well as researchers to analyze different devices…
Descriptors: Computer Use, Handheld Devices, Telecommunications, Teaching Methods
Podworny, Susanne; Hüsing, Sven; Schulte, Carsten – Statistics Education Research Journal, 2022
Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…
Descriptors: Statistics Education, Programming, Programming Languages, Data Analysis
Förster, Anna; Dede, Jens; Udugama, Asanga; Förster, Alexander; Helms, Daniel; Kniefs, Louis; Müller, Julia; Gerken, Lars; Richter, Franziska; Kulmann, Jan – Education Sciences, 2021
In this paper, we present our experience with redesigning an introductory computer science course for (electrical) engineers with blended learning concepts. It is a large mandatory course with eight credit points over the course of two semesters, where first year electrical engineers learn how to program with Arduino, C and Python. Additionally,…
Descriptors: Blended Learning, Introductory Courses, Required Courses, Computer Science Education
Krüger, Ralph – Interpreter and Translator Trainer, 2022
This paper intends to illustrate the didactic potential of Python-based Jupyter notebooks in teaching translation technology, machine translation in particular, to translation students. It discusses the basic makeup of Jupyter notebooks and shows how these notebooks can be set up for students who have had little to no prior exposure to the Python…
Descriptors: Translation, Second Language Learning, Second Language Instruction, Natural Language Processing
Darmoroz, Halyna – Comparative Professional Pedagogy, 2017
The paper deals with the aspects of professional training of specialists in computational linguistics by the example of the University of Stuttgart. First of all, we have attempted to define the essence of the terms "applied linguistics" and "computational linguistics" based on the views of Ukrainian and foreign scholars. We…
Descriptors: Computational Linguistics, Universities, Curriculum Development, Foreign Countries