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Murat Tekin; Çetin Toraman; Aysen Melek Aytug Kosan – International Journal of Assessment Tools in Education, 2024
In the present study, we examined the psychometric properties of the data obtained from the Commitment to Profession of Medicine Scale (CPMS) with 4-point, 5-point, 6-point, and 7-point response sets based on Item Response Theory (IRT). A total of 2150 medical students from 16 different universities participated in the study. The participants were…
Descriptors: Psychometrics, Medical Students, Likert Scales, Data Collection
Ferdinand Valentin Stoye; Claudia Tschammler; Oliver Kuss; Annika Hoyer – Research Synthesis Methods, 2024
The development of new statistical models for the meta-analysis of diagnostic test accuracy studies is still an ongoing field of research, especially with respect to summary receiver operating characteristic (ROC) curves. In the recently published updated version of the "Cochrane Handbook for Systematic Reviews of Diagnostic Test…
Descriptors: Diagnostic Tests, Accuracy, Barriers, Models
Leonard Taylor – Higher Education: The International Journal of Higher Education Research, 2024
The fullness of Black students' experiences in college has yet to be archived. The same can be said of Black people broadly, whose existence has long been reduced by and to what is observable, by systems of power and those at the helm. This is perhaps due to the structural and structural limitations of data collection efforts, or not of interest…
Descriptors: African American Students, College Students, Power Structure, Success
Wenchao Ma; Miguel A. Sorrel; Xiaoming Zhai; Yuan Ge – Journal of Educational Measurement, 2024
Most existing diagnostic models are developed to detect whether students have mastered a set of skills of interest, but few have focused on identifying what scientific misconceptions students possess. This article developed a general dual-purpose model for simultaneously estimating students' overall ability and the presence and absence of…
Descriptors: Models, Misconceptions, Diagnostic Tests, Ability
Alexey L. Voskov – International Journal of Mathematical Education in Science and Technology, 2024
QR decomposition is widely used for solving the least squares problem. However, existing materials about it may be too abstract for non-mathematicians, especially STEM students, and/or require serious background in linear algebra. The paper describes theoretical background and examples of GNU Octave compatible MATLAB scripts that give relatively…
Descriptors: Mathematics, Algorithms, Data Science, Mathematical Concepts
Fernando Prieto Ramos; Diego Guzmán – Interpreter and Translator Trainer, 2024
The relevance of translation and law degrees as pathways to professional legal translation is the subject of persistent debate, but there is limited research on the relationship between legal translators' backgrounds and competence levels in practice. This study compares the revision performance of several groups of institutional translators (44…
Descriptors: Translation, Laws, Quality Assurance, Revision (Written Composition)
Il Do Ha – Measurement: Interdisciplinary Research and Perspectives, 2024
Recently, deep learning has become a pervasive tool in prediction problems for structured and/or unstructured big data in various areas including science and engineering. In particular, deep neural network models (i.e. a basic core model of deep learning) can be viewed as an extension of statistical models by going through the incorporation of…
Descriptors: Artificial Intelligence, Statistical Analysis, Models, Algorithms
Fernando Rios-Avila; Michelle Lee Maroto – Sociological Methods & Research, 2024
Quantile regression (QR) provides an alternative to linear regression (LR) that allows for the estimation of relationships across the distribution of an outcome. However, as highlighted in recent research on the motherhood penalty across the wage distribution, different procedures for conditional and unconditional quantile regression (CQR, UQR)…
Descriptors: Regression (Statistics), Research Methodology, Alternative Assessment, Models
Tobias Kohn; Jacqueline Staub – Informatics in Education, 2024
The choice of programming language for education is an intensely debated topic. On the one hand, the programming language is supposed to be "relevant" in that its organisation, structures, and paradigms adhere to current standards and best practices in industry and academia. On the other hand, the programming language is expected to be…
Descriptors: Computer Science Education, Programming, Data Processing, Philosophy
Kaitlyn G. Fitzgerald; Elizabeth Tipton – Grantee Submission, 2024
This article presents methods for using extant data to improve the properties of estimators of the standardized mean difference (SMD) effect size. Because samples recruited into education research studies are often more homogeneous than the populations of policy interest, the variation in educational outcomes can be smaller in these samples than…
Descriptors: Data Use, Computation, Effect Size, Meta Analysis
Stefanie A. Wind; Benjamin Lugu – Applied Measurement in Education, 2024
Researchers who use measurement models for evaluation purposes often select models with stringent requirements, such as Rasch models, which are parametric. Mokken Scale Analysis (MSA) offers a theory-driven nonparametric modeling approach that may be more appropriate for some measurement applications. Researchers have discussed using MSA as a…
Descriptors: Item Response Theory, Data Analysis, Simulation, Nonparametric Statistics
Lubna Hakami; Davinia Hernández-Leo; Ishari Amarasinghe; Batuhan Sayis – British Journal of Educational Technology, 2024
Despite the growing interest in using multimodal data to analyse students' actions in Computers-Supported Collaborative Learning (CSCL) settings, studying teacher's orchestration load in such settings remains overlooked. The notion of classroom orchestration, and orchestration load, offer a lens to study the implications of increasingly complex…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Teacher Responsibility, Faculty Workload
Schachter, Rachel E.; Freeman, Donald; Parakkal, Naivedya – Review of Research in Education, 2020
Connecting teachers' perspectives with their practice is an enduring challenge shaping what and how we understand teaching. Researchers tend to bifurcate teachers' work between their private and their public lives. These "worlds" bring particular meanings that are rendered through the analyses of visual documentations of teaching and…
Descriptors: Classroom Research, Data Use, Data Collection, Data Analysis
Poling, Lisa; Weiland, Travis – Teaching Statistics: An International Journal for Teachers, 2020
With the creation of interactive tasks that allow students to explore spatial ways of knowing in conjunction with their other ways of knowing the world, we create a space where students can make sense of information as they organize these new ideas into their already existing schema. Through the use of a Common Online Data Analysis Platform…
Descriptors: Data Analysis, Data Collection, Spatial Ability, Statistics
Tanner, Richelle L.; Collins, Lisa E. – Journal of College Science Teaching, 2021
Understanding data analysis and interpreting data are key components of teaching interdisciplinary undergraduate students. We detail a semester-long research project that introduces students to long-term data sets, incorporates the use of widely available statistical analysis, and underscores an inquiry-based method of teaching climate change. Our…
Descriptors: Climate, Undergraduate Students, Interdisciplinary Approach, Research Projects