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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
Mayer, Benjamin; Kuemmel, Anja; Meule, Marianne; Muche, Rainer – Journal of Statistics and Data Science Education, 2023
Teaching practical skills is of particular interest in the study of human medicine. With regard to medical statistics this means the use of statistical software, which may be effectively taught by a flipped classroom approach. As a pilot study, we designed and implemented an elective course on medical statistics that focused on hands-on data…
Descriptors: Computer Software, Medicine, Statistics, Flipped Classroom
Langerbein, Janine; Massing, Till; Klenke, Jens; Striewe, Michael; Goedicke, Michael; Hanck, Christoph – International Educational Data Mining Society, 2023
Due to the precautionary measures during the COVID-19 pandemic many universities offered unproctored take-home exams. We propose methods to detect potential collusion between students and apply our approach on event log data from take-home exams during the pandemic. We find groups of students with suspiciously similar exams. In addition, we…
Descriptors: Information Retrieval, Pattern Recognition, Data Analysis, Information Technology
Wilbert, Jürgen; Bosch, Jannis; Lüke, Timo – International Journal for Research in Learning Disabilities, 2021
Analysis of data from single-case intervention studies commonly involves visual analysis. Previous research indicates that visual analysis may suffer from low reliability and unpromising error rates. We investigated the reliability and validity of visual analysis and explored to what extent data trends affect judgments. We administered a…
Descriptors: Data Analysis, Reliability, Validity, Visual Aids
Pham Van, Thuan; Tran, Trung; Trinh Thi Phuong, Thao; Hoang Ngoc, Anh; Nghiem Thi, Thanh; La Phuong, Thuy – Journal on Efficiency and Responsibility in Education and Science, 2022
The higher education efficiency evaluation model using the data envelopment analysis method has interested many researchers. This paper uses bibliometric analysis on publications extracted from the Scopus database to provide a comprehensive overview of research publications on the measurement of higher education efficiency based on data…
Descriptors: Higher Education, Efficiency, Measurement, Data Analysis
Markus Seyfried; Stefan Hollenberg; Judith Heße-Husain – Journal of Higher Education Policy and Management, 2024
Research on student selection mostly focuses on accepted applicants and the effects of selection procedures. In this sense, most samples seem to be biased, which is well-reflected in the literature. The present study investigates student selection regarding students who had been initially de-selected but finally succeeded in the admission process.…
Descriptors: Admission Criteria, Selective Admission, Stakeholders, Technology
Jones, Thomas J.; Ehlers, Todd A. – Journal of Geoscience Education, 2021
The need for geoscience students to develop a quantitative skillset is ever increasing. However, this can be difficult to implement in university-style lecture courses in a way that is both manageable for the instructor and does not involve lengthy, potentially repetitive, question sheets for the students. Here, a method for teaching dimensional…
Descriptors: Earth Science, Science Experiments, Graduate Students, College Science
Alturki, Sarah; Cohausz, Lea; Stuckenschmidt, Heiner – Smart Learning Environments, 2022
The tremendous growth in electronic educational data creates the need to have meaningful information extracted from it. Educational Data Mining (EDM) is an exciting research area that can reveal valuable knowledge from educational databases. This knowledge can be used for many purposes, including identifying dropouts or weak students who need…
Descriptors: Information Retrieval, Data Analysis, Data Use, Prediction
Agbo, Friday Joseph; Sanusi, Ismaila Temitayo; Oyelere, Solomon Sunday; Suhonen, Jarkko – Education Sciences, 2021
This study investigated the role of virtual reality (VR) in computer science (CS) education over the last 10 years by conducting a bibliometric and content analysis of articles related to the use of VR in CS education. A total of 971 articles published in peer-reviewed journals and conferences were collected from Web of Science and Scopus…
Descriptors: Computer Simulation, Computer Science Education, Educational Research, Research Methodology
Kubsch, Marcus; Stamer, Insa; Steiner, Mara; Neumann, Knut; Parchmann, Ilka – Practical Assessment, Research & Evaluation, 2021
In light of the replication crisis in psychology, null-hypothesis significance testing (NHST) and "p"-values have been heavily criticized and various alternatives have been proposed, ranging from slight modifications of the current paradigm to banning "p"-values from journals. Since the physics education research community…
Descriptors: Data Analysis, Bayesian Statistics, Educational Research, Science Education
Kemper, Lorenz; Vorhoff, Gerrit; Wigger, Berthold U. – European Journal of Higher Education, 2020
We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…
Descriptors: Foreign Countries, Predictor Variables, Potential Dropouts, School Holding Power
Berens, Johannes; Schneider, Kerstin; Gortz, Simon; Oster, Simon; Burghoff, Julian – Journal of Educational Data Mining, 2019
To successfully reduce student attrition, it is imperative to understand what the underlying determinants of attrition are and which students are at risk of dropping out. We develop an early detection system (EDS) using administrative student data from a state and private university to predict student dropout as a basis for a targeted…
Descriptors: Risk Management, At Risk Students, Dropout Prevention, College Students
Amaral, João Alberto Arantes do; Hess, Aurélio – Anatolian Journal of Education, 2017
In this article, we discuss the dynamics that led to viewing of 18 five-minute videos, created as part of a business dynamics course and made freely available on Internet. Over a period of five years, the videos were watched 2,740 times in 80 countries. The goal of our research was to understand what dynamics drove the viewership. We collected…
Descriptors: Online Courses, Video Technology, Lecture Method, Audiences
McEvoy, Eileen; Heikinaro-Johansson, Pilvikki; MacPhail, Ann – Sport, Education and Society, 2017
The aim of this paper was to gain an understanding of the views of a group of physical education teacher educators on the purpose(s) of school physical education and whether, how and why these views have changed over time. Semi-structured individual interviews were carried out with thirteen physical education teacher educators; a fourteenth…
Descriptors: Foreign Countries, Physical Education Teachers, Teacher Educators, Teacher Attitudes
Biehler, Rolf; Frischemeier, Daniel; Podworny, Susanne – ZDM: The International Journal on Mathematics Education, 2018
Elements of statistical modeling can be implemented already in primary school. A prerequisite for this approach is that teachers are well-educated in this domain. Content knowledge, pedagogical content knowledge and (pedagogical) content related technological knowledge are core components of teacher education. We designed a course for elementary…
Descriptors: Preservice Teachers, Elementary School Teachers, Pedagogical Content Knowledge, Civics